Search results for: image rotation

Authors: Eduardo Ruiz-Corzo, Luis Rodrigo Valencia Perez, Jorge Francisco Barragan Lopez

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The article shows the pressing conditions of marginalization prevailing in the Sierra Gorda, in the northern state of Queretaro, so it is essential to identify business options that generate a complementary source of income in a sustainable manner, in accordance with the fact that the area is a Biosphere Reserve by UNESCO. In this sense, the study identifies the enormous scenic richness of the area, the growing demand for leisure activities of the urban centers and the multifunctionality that adds, in a complementary way, the traditional activities that up to now have achieved the quality of life levels. From the application of the 43 interviews and 183 surveys, confirms the fact that the post-visit perception exceeds the expectations of the visitors emerges and affirms that the image that has been projected is attractive and timely. In order to understand how the current model of tourism promoted in the region is working, there is a need to evaluate it in a theoretical-methodological framework considering sustainable development assumptions. In order to determine the degree of contribution to business development, strengthening of social capital, and enjoyment and appreciation of cultural and natural heritage in the region.

Keywords: marginalization, rural tourism, multifunctionality, sustainability, revenue

Procedia PDF Downloads 141

Authors: Hyun-Koo Kim, Yong-Hun Kim, Soo-Young Suk, Ju H. Park, Ho-Youl Jung

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This paper presents an effective speed hump detection process at the day-time. we focus only on round types of speed humps in the day-time dynamic road environment. The proposed speed hump detection scheme consists mainly of two process as stereo matching and speed hump detection process. Our proposed process focuses to speed hump detection process. Speed hump detection process consist of noise reduction step, data fusion step, and speed hemp detection step. The proposed system is tested on Intel Core CPU with 2.80 GHz and 4 GB RAM tested in the urban road environments. The frame rate of test videos is 30 frames per second and the size of each frame of grabbed image sequences is 1280 pixels by 670 pixels. Using object-marked sequences acquired with an on-vehicle camera, we recorded speed humps and non-speed humps samples. Result of the tests, our proposed method can be applied in real-time systems by computation time is 13 ms. For instance; our proposed method reaches 96.1 %.

Keywords: data fusion, round types speed hump, speed hump detection, surface filter

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Authors: Robin Becker, Maike Eilers, Nane Roetmann, Manfred Helmus

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The shortage of junior staff in the construction industry is a problem that will be further exacerbated in the coming years by the retirement of the baby-boom generations (1955-1969) from employment. In addition, the current working conditions in the field of construction management are not attractive for young professionals. A survey of students revealed a desire for an increase in flexibility and an improved work-life balance in everyday working life. Students of civil engineering and architecture are basically interested in a career in construction management but have reservations due to the image of the profession and the current working conditions. A survey among experts from the construction industry shows that the profession can become more attractive. This report provides recommendations for action in the form of working modules to improve the working conditions of employees. If these are taken into account, graduates can be attracted to the profession of construction management, and existing staff can be retained more effectively. The aim of this report is to show incentives for employers to respond to the wishes and needs of their current and future employees to the extent that can be implemented.

Keywords: modern construction management, construction industry, work modules, shortage of junior staff, sustainable personnel management, making construction management more attractive, working time model

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Authors: Alejandro Carrasco-Pena, Mahmoud Omer, Nina Orlovskaya

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The results of studies of microstructure, mechanical behavior, vibrational response, and flow field analysis of critically endangered staghorn coral (Acropora cervicornis) skeletons are reported. The CaCO₃ aragonite structure of a chemically-cleaned coral skeleton of A. cervicornis was studied by optical microscopy and computer tomography. The mechanical behavior was studied using uniaxial compression and Vickers hardness technique. The average maximum stress measured during skeleton uniaxial compression was 10.7 ± 2.24 MPa and Vickers hardness was 3.56 ± 0.31 GPa. The vibrational response of the aragonite structure was studied by micro-Raman spectroscopy, which showed a substantial dependence of the structure on applied compressive stress. The flow-field around a single coral skeleton forming vortices in the wake of the moving skeleton was measured using Particle Image Velocimetry (PIV). The results are important for further analysis of time-dependent mechanical fatigue behavior and predicting the lifetime of staghorn corals.

Keywords: failure, mechanical properties, microstructure, Raman spectroscopy

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Authors: Xulu Yao, Moi Hoon Yap, Yanlong Zhang

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As a branch of artificial neural network, deep learning is widely used in the field of image recognition, but the lack of its dataset leads to imperfect model learning. By analysing the data scale requirements of deep learning and aiming at the application in GUI generation, it is found that the collection of GUI dataset is a time-consuming and labor-consuming project, which is difficult to meet the needs of current deep learning network. To solve this problem, this paper proposes a semi-supervised deep learning model that relies on the original small-scale datasets to produce a large number of reliable data sets. By combining the cyclic neural network with the generated countermeasure network, the cyclic neural network can learn the sequence relationship and characteristics of data, make the generated countermeasure network generate reasonable data, and then expand the Rico dataset. Relying on the network structure, the characteristics of collected data can be well analysed, and a large number of reasonable data can be generated according to these characteristics. After data processing, a reliable dataset for model training can be formed, which alleviates the problem of dataset shortage in deep learning.

Keywords: GUI, deep learning, GAN, data augmentation

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Authors: A. Yazdanmehr, H. Jahed

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Being made with the lightest commercially available industrial metal, Magnesium (Mg) alloys are of interest for light-weighting. Expanding their application to different material processing methods requires Mg properties at large strains. Several room-temperature processes such as shot and laser peening and hole cold expansion need compressive large strain data. Two methods have been proposed in the literature to obtain the stress-strain curve at high strains: 1) anti-buckling guides and 2) small cubic samples. In this paper, an anti-buckling fixture is used with the help of digital image correlation (DIC) to obtain the compression-tension (C-T) of AZ31B-H24 rolled sheet at large strain values of up to 10.5%. The effect of the anti-bucking fixture on stress-strain curves is evaluated experimentally by comparing the results with those of the compression tests of cubic samples. For testing cubic samples, a new fixture has been designed to increase the accuracy of testing cubic samples with DIC strain measurements. Results show a negligible effect of anti-buckling on stress-strain curves, specifically at high strain values.

Keywords: large strain, compression-tension, loading-unloading, Mg alloys

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Authors: Odile Amoncou, Djedje-Kossu Zahui

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The increased demand for digital communications during the COVID-19 pandemic has seen an unprecedented surge in new telecom infrastructure around the world. The expansion has been more remarkable in countries with developing telecom infrastructures. Particularly, the three telecom operators in Cote d’Ivoire, Orange CI, MTN CI, and MOOV Africa, have considerably scaled up their exploitation technologies and capacities in terms of towers, fiber optic installation, and customer service hubs. The trend will likely continue upward while expanding the carbon footprint of the Ivorian telecom operators. Therefore, the corporate social and environmental responsibilities of these telecommunication companies can no longer be overlooked. This paper assesses the sustainability of the three Ivorian telecommunication network operators by applying a combination of commonly used sustainability management indexes. These tools are streamlined and adapted to the relatively young and developing digital network of Cote D’Ivoire. We trust that this article will push the respective CEOs to make sustainability a top strategic priority and understand the substantial potential returns in terms of saving, new products, and new clients while improving their corporate image. In addition, good sustainability management can increase their stakeholders.

Keywords: sustainability of telecom operators, sustainability management index, carbon footprint, digital communications

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Authors: E. Irankhah, M. Zarif, E. Mazrooei Rad, K. Ghandehari

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Alzheimer's prevalence is on the rise, and the disease comes with problems like cessation of treatment, high cost of treatment, and the lack of early detection methods. The pathology of this disease causes the formation of protein deposits in the brain of patients called plaque amyloid. Generally, the diagnosis of this disease is done by performing tests such as a cerebrospinal fluid, CT scan, MRI, and spinal cord fluid testing, or mental testing tests and eye tracing tests. In this paper, we tried to use the Medial Temporal Atrophy (MTA) method and the Leave One Out (LOO) cycle to extract the statistical properties of the three Fz, Pz, and Cz channels of ERP signals for early diagnosis of this disease. In the process of CT scan images, the accuracy of the results is 81% for the healthy person and 88% for the severe patient. After the process of ERP signaling, the accuracy of the results for a healthy person in the delta band in the Cz channel is 81% and in the alpha band the Pz channel is 90%. In the results obtained from the signal processing, the results of the severe patient in the delta band of the Cz channel were 89% and in the alpha band Pz channel 92%.

Keywords: Alzheimer's disease, image and signal processing, LOO cycle, medial temporal atrophy

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Authors: Yi-De Liu

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For many European cities, a key motivation in developing event strategies is to use event as a catalyst for urban regeneration. One type of event that is particularly used as a means of urban development is the European Capital of Culture (ECOC) initiative. Based on a case study of the 2008 ECOC Liverpool, this paper aims at conceptualising the significance of major event for a city’s economic, cultural and social regenerations. In terms of economic regeneration, the role of the ECOC is central in creating Liverpool’s visitor economy and reshaping city image. Liverpool planned different themes for eight consecutive years as a way to ensure economic sustainability. As far as cultural regeneration is concerned, the ECOC contributed to the cultural regeneration of Liverpool by stimulating cultural participation and interest from the demand side, as well as improving cultural provision and collaboration within the cultural sector from the supply side. So as to social regeneration, Liverpool treated access development as a policy guideline and considered the ECOC as an opportunity to enhance the sense of place. The most significant lesson learned from Liverpool is its long-term planning and efforts made to integrate the ECOC into the overall urban development strategy. As a result, a more balanced and long-term effect on urban regeneration could be achieved.

Keywords: cultural event, urban regeneration, european capital of culture, Liverpool

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Authors: M. Krishna

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The study was intended to identify if scalp cooling therapy is effective on preventing chemotherapy-induced hair loss among cancer patients. Critical literature of non-randomized controlled trials was used to investigate whether scalp cooling therapy is effective on preventing chemotherapy-induced alopecia. The review identified that scalp cooling therapy is effective on preventing chemotherapy-induced alopecia. Most of the patients receiving chemotherapy experience alopecia. It is also perceived as the worst effect of chemotherapy. This may be severe and lead the patients to withdraw the chemo treatment. The image disturbance caused by alopecia will make the patient depressed and will lead to declined immunity. With the knowledge on effectiveness of scalp cooling therapy on preventing chemotherapy-induced alopecia, patient undergoing chemotherapy will not be hesitant to undergo the treatment. Patients are recommended to go through scalp cooling therapy every chemo cycle and the proper therapy duration is 30 minutes before, during chemo. The suggested duration of the scalp cooling therapy is 45-90 minutes for an effective and positive outcome. This finding is excluding other factors of alopecia such as menopause, therapeutic drugs, poor hair density, liver function problems, and drug regimes.

Keywords: alopecia, cancer, chemotherapy, scalp cooling therapy

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Authors: T. Garba, T. O. Quddus, Y. Y. Babanyara, M. A. Modibbo

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Desertification is define as the changing of productive land into a desert as the result of ruination of land by man-induced soil erosion, which forces famers in the affected areas to move migrate or encourage into reserved areas in search of a fertile land for their farming activities. This study therefore used remote sensing imageries to determine the level of changes in the vegetative areas. To achieve that Normalized Difference of the Vegetative Index (NDVI), classified imageries and image slicing derived from landsat TM 1986, land sat ETM 1999 and Nigeria sat 1 2007 were used to determine changes in vegetations. From the Classified imageries it was discovered that there a more natural vegetation in classified images of 1986 than that of 1999 and 2007. This finding is also future in the three NDVI imageries, it was discovered that there is increased in high positive pixel value from 0.04 in 1986 to 0.22 in 1999 and to 0.32 in 2007. The figures in the three histogram also indicted that there is increased in vegetative areas from 29.15 Km2 in 1986, to 60.58 Km2 in 1999 and then to 109 Km2 in 2007. The study recommends among other things that there is need to restore natural vegetation through discouraging of farming activities in and around the natural vegetation in the study area.

Keywords: vegetative index, classified imageries, change detection, landsat, vegetation

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Authors: Liliia N. Butymova, Vladimir Ya Modorskii

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To ensure the gas transmittal GCU's efficient operation, leakages through the labyrinth packings (LP) should be minimized. Leakages can be minimized by decreasing the LP gap, which in turn depends on thermal processes and possible rotor vibrations and is designed to ensure absence of mechanical contact. Vibration mitigation allows to minimize the LP gap. It is advantageous to research influence of processes in the dynamic gas-structure system on LP vibrations. This paper considers influence of rotor vibrations on LP gas dynamics and influence of the latter on the rotor structure within the FSI unidirectional dynamical coupled problem. Dependences of nonstationary parameters of gas-dynamic process in LP on rotor vibrations under various gas speeds and pressures, shaft rotation speeds and vibration amplitudes, and working medium features were studied. The programmed multi-processor ANSYS CFX was chosen as a numerical computation tool. The problem was solved using PNRPU high-capacity computer complex. Deformed shaft vibrations are replaced with an unyielding profile that moves in the fixed annulus "up-and-down" according to set harmonic rule. This solves a nonstationary gas-dynamic problem and determines time dependence of total gas-dynamic force value influencing the shaft. Pressure increase from 0.1 to 10 MPa causes growth of gas-dynamic force oscillation amplitude and frequency. The phase shift angle between gas-dynamic force oscillations and those of shaft displacement decreases from 3π/4 to π/2. Damping constant has maximum value under 1 MPa pressure in the gap. Increase of shaft oscillation frequency from 50 to 150 Hz under P=10 MPa causes growth of gas-dynamic force oscillation amplitude. Damping constant has maximum value at 50 Hz equaling 1.012. Increase of shaft vibration amplitude from 20 to 80 µm under P=10 MPa causes the rise of gas-dynamic force amplitude up to 20 times. Damping constant increases from 0.092 to 0.251. Calculations for various working substances (methane, perfect gas, air at 25 ˚С) prove the minimum gas-dynamic force persistent oscillating amplitude under P=0.1 MPa being observed in methane, and maximum in the air. Frequency remains almost unchanged and the phase shift in the air changes from 3π/4 to π/2. Calculations for various working substances (methane, perfect gas, air at 25 ˚С) prove the maximum gas-dynamic force oscillating amplitude under P=10 MPa being observed in methane, and minimum in the air. Air demonstrates surging. Increase of leakage speed from 0 to 20 m/s through LP under P=0.1 MPa causes the gas-dynamic force oscillating amplitude to decrease by 3 orders and oscillation frequency and the phase shift to increase 2 times and stabilize. Increase of leakage speed from 0 to 20 m/s in LP under P=1 MPa causes gas-dynamic force oscillating amplitude to decrease by almost 4 orders. The phase shift angle increases from π/72 to π/2. Oscillations become persistent. Flow rate proved to influence greatly on pressure oscillations amplitude and a phase shift angle. Work medium influence depends on operation conditions. At pressure growth, vibrations are mostly affected in methane (of working substances list considered), and at pressure decrease, in the air at 25 ˚С.

Keywords: aeroelasticity, labyrinth packings, oscillation phase shift, vibration

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Authors: Yu-Chen Wei, Dan-Leng Wang

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This study examines whether the reputation from media press affect the financial performance and market abnormal returns around the announcement of corporate social responsibility (CSR) award in the Taiwan Stock Market. The differences between this study and prior literatures are that the media reputation of media coverage and net optimism are constructed by using content analyses. The empirical results show the corporation which won CSR awards could promote financial performance next year. The media coverage and net optimism related to CSR winner are higher than the non-CSR companies prior and after the CSR award is announced, and the differences are significant, but the difference would decrease when the day was closing to announcement. We propose that non-CSR companies may try to manipulate media press to increase the coverage and positive image received by investors compared to the CSR winners. The cumulative real returns and abnormal returns of CSR winners did not significantly higher than the non-CSR samples however the leading returns of CSR winners would higher after the award announcement two months. The comparisons of performances between CSR and non-CSR companies could be the consideration of portfolio management for mutual funds and investors.

Keywords: corporate social responsibility, financial performance, abnormal returns, media, reputation management

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Authors: Andi Syahputra, R. H. Jatmiko, D. R. Hizbaron

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Land surface temperature (LST) in an area is influenced by conditions of vegetation density, building density, and the number of inhabitants who live in the area. Medan City is one of the largest cities in Indonesia, with a high rate of change from vegetation to developed land. This study aims to identify the relationship between the percentage of building density and land surface temperature in Medan City. Pixel image analysis method is carried out to obtain the value of building density in pixel images of Landsat 8 images with the help of WorldView-2 satellite imagery. The results showed the highest land surface temperature in 2018 of 35, 4°C was found in Medan Perjuangan District, and the lowest was 22.5°C in Medan Belawan District. Building density samples with a density level of 889.17 m were also found in Medan Perjuangan District, while the lowest building density sample was found in Medan Timur District. Linear regression analysis of the effect of building density with land surface temperature obtained a correlation (R) was 0.64, and a coefficient of determination (R²) was 0.411 and modeling of building density based on the LST has a correlation (R), and a coefficient of determination (R²) was 0.72 with The RMSE obtained 0.853.

Keywords: land surface temperature, Landsat, imagery, building density, vegetation, density

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Authors: Benjamin O. Ehigie, Aderemi Alarape, Nyitor Shenge, Sylvester A. Okhakhume, Timileyin Fashola, Fiyinfunjah Dosumu

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Organisational citizenship behaviour (OCB) is a construct in industrial and organisational behaviour that explains a person's voluntary commitment within an organisation, which is outside the scope of his or her contractual tasks. To attain organisational effectiveness the human factor of production is inevitable, hence the importance of employee behaviour. While the concept of organisational citizenship behavior is mostly discussed in the context of the workplace, it is reasoned that the idea could be reflective in relation to national commitment. Many developing countries in Africa, including Nigeria, suffer economic hardship today not necessarily due to poor resources but bad management of the resources. The mangers of their economies are not committed to the tenets of economic growth but engrossed in fraud, corruption, bribery, and other economic vices. It is this backdrop that necessitated the development and validation of the Ibadan-Nigeria Citizenship Behaviour (I-NCB) Scale. The study adopted a cross-sectional survey (online) research design, using 2404 postgraduate students in the Premier University of the country, with 99.2% being Nigerians and 0.8% non-Nigerians. Gender composition was 1,439 (60%) males and 965 (40%) females, 1201 (50%) were employed while 1203 50% unemployed, 74.2% of the employed were in public paid employment, 19.5% in private sector, and 6.3% were self-employed. Through literature review, 78 items were generated. Using 10 lecturers and 21 students, content and face validity were established respectively. Data collected were subjected to reliability and factor analytic statistics at p < .05 level of significance. Results of the content and face validity at 80% level of item acceptance resulted to 60 items; this was further reduced to 50 after item-total correlation using r=.30 criterion. Divergent validity of r= -.28 and convergent validity of r= .44 were obtained by correlating the I-NCB scale with standardized Counterproductive work behaviour (CWB) scale and Organisational Citizenship Behaviour (OCB) scale among the workers. The reliability coefficients obtained were; Cronbach alpha of internal consistency (α = 0.941) and split-half reliability of r = 0.728. Factor analyses of the I-NCB scale with principal component and varimax rotation yielded five factors when Eigenvalue above 1 were extracted. The factors which accounted for larger proportions of the total variance were given factor names as; Altruistic, Attachment, Affective, Civic responsibility and Allegiance. As much as there are vast journals on citizenship behaviour in organisations, there exists no standardized tool to measure citizenship behaviour of a country. The Ibadan-Nigeria Citizenship Behaviour (I-NCB) scale was consequently developed. The scale could be used to select personnel into political positions and senior administrative positions among career workers in Nigeria, with the aim of determining national commitment to service.

Keywords: counterproductive work behaviour, CWB, Nigeria Citizenship Behaviour, organisational citizenship behaviour, OCB, Ibadan

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Authors: P. Jayashree, S. Rajkumar

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With social networks and smart devices generating a multitude of data, effective data management is the need of the hour for networks and cloud applications. Some applications need effective storage while some other applications need effective communication over networks and data reduction comes as a handy solution to meet out both requirements. Most of the data compression techniques are based on data statistics and may result in either lossy or lossless data reductions. Though lossy reductions produce better compression ratios compared to lossless methods, many applications require data accuracy and miniature details to be preserved. A variety of data compression algorithms does exist in the literature for different forms of data like text, image, and multimedia data. In the proposed work, a generic progressive compression algorithm, based on probabilistic encoding, called PEINS is projected as an enhancement over irrational number stored coding technique to cater to storage issues of increasing data volumes as a cost effective solution, which also offers data security as a secondary outcome to some extent. The proposed work reveals cost effectiveness in terms of better compression ratio with no deterioration in compression time.

Keywords: compression ratio, generic compression, irrational number storage, probabilistic encoding

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Authors: Nazmul Shahadat, Anthony S. Maida

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In recent years, hypercomplex inspired neural networks improved deep CNN architectures due to their ability to share weights across input channels and thus improve cohesiveness of representations within the layers. The work described herein studies the effect of replacing existing layers in an Axial Attention ResNet with their quaternion variants that use cross-channel weight sharing to assess the effect on image classification. We expect the quaternion enhancements to produce improved feature maps with more interlinked representations. We experiment with the stem of the network, the bottleneck layer, and the fully connected backend by replacing them with quaternion versions. These modifications lead to novel architectures which yield improved accuracy performance on the ImageNet300k classification dataset. Our baseline networks for comparison were the original real-valued ResNet, the original quaternion-valued ResNet, and the Axial Attention ResNet. Since improvement was observed regardless of which part of the network was modified, there is a promise that this technique may be generally useful in improving classification accuracy for a large class of networks.

Keywords: axial attention, representational networks, weight sharing, cross-channel correlations, quaternion-enhanced axial attention, deep networks

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Authors: Shinhao Yang, Hsiao-Chien Huang, Chin-Hsiang Luo

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The leakage of protective clothing is an important issue in the occupational health field. There is no quantitative method for measuring the leakage of personal protective equipment. This work aims to measure the quantitative leakage of the personal protective equipment by using the fluorochrome aerosol tracer. The fluorescent aerosols were employed as airborne particulates in a controlled chamber with ultraviolet (UV) light-detectable stickers. After an exposure-and-leakage test, the protective equipment was removed and photographed with UV-scanning to evaluate areas, color depth ratio, and aerosol deposition and shielding effects of the areas where fluorescent aerosols had adhered to the body through the protective equipment. Thus, this work built a calculation software for quantitative leakage ratio of protective clothing based on fluorescent illumination depth/aerosol concentration ratio, illumination/Fa ratio, aerosol deposition and shielding effects, and the leakage area ratio on the segmentation. The results indicated that the two-repetition total leakage rate of the X, Y, and Z type protective clothing for subject T were about 3.05, 4.21, and 3.52 (mg/m2). For five-repetition, the leakage rate of T were about 4.12, 4.52, and 5.11 (mg/m2).

Keywords: fluorochrome, deposition, shielding effects, digital image processing, leakage ratio, personal protective equipment

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Authors: Seda Yavuz, Anıl Çelebi, Aysun Taşyapı Çelebi, Oğuzhan Urhan

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Nowadays, demand for using real-time video transmission capable devices is ever-increasing. So, high resolution videos have made efficient video compression techniques an essential component for capturing and transmitting video data. Motion estimation has a critical role in encoding raw video. Hence, various motion estimation methods are introduced to efficiently compress the video. Low bit‑depth representation based motion estimation methods facilitate computation of matching criteria and thus, provide small hardware footprint. In this paper, a hardware implementation of a two-bit transformation based low-complexity motion estimation method using local binary pattern approach is proposed. Image frames are represented in two-bit depth instead of full-depth by making use of the local binary pattern as a binarization approach and the binarization part of the hardware architecture is explained in detail. Experimental results demonstrate the difference between the proposed hardware architecture and the architectures of well-known low-complexity motion estimation methods in terms of important aspects such as resource utilization, energy and power consumption.

Keywords: binarization, hardware architecture, local binary pattern, motion estimation, two-bit transform

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Authors: A. I. A. Rahman, Sh-Hussain Salleh, K. Ahmad, K. Anuar

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Analysis of vocal fold vibration is essential for understanding the mechanism of voice production and for improving clinical assessment of voice disorders. This paper presents a Dynamic Time Warping (DTW) based approach to analyze and objectively classify vocal fold vibration patterns. The proposed technique was designed and implemented on a Glottal Area Waveform (GAW) extracted from high-speed laryngeal images by delineating the glottal edges for each image frame. Feature extraction from the GAW was performed using Linear Predictive Coding (LPC). Several types of voice reference templates from simulations of clear, breathy, fry, pressed and hyperfunctional voice productions were used. The patterns of the reference templates were first verified using the analytical signal generated through Hilbert transformation of the GAW. Samples from normal speakers’ voice recordings were then used to evaluate and test the effectiveness of this approach. The classification of the voice patterns using the technique of LPC and DTW gave the accuracy of 81%.

Keywords: dynamic time warping, glottal area waveform, linear predictive coding, high-speed laryngeal images, Hilbert transform

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Authors: Yang Yang, Dan Liu

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Anomaly detection models for network flow based on machine learning have poor detection performance under extremely unbalanced training data conditions and also have slow detection speed and large resource consumption when deploying on network edge devices. Embedding multi-teacher knowledge distillation (mKD) in anomaly detection can transfer knowledge from multiple teacher models to a single model. Inspired by this, we proposed a state-of-the-art model, mKDNAD, to improve detection performance. mKDNAD mine and integrate the knowledge of one-dimensional sequence and two-dimensional image implicit in network flow to improve the detection accuracy of small sample classes. The multi-teacher knowledge distillation method guides the train of the student model, thus speeding up the model's detection speed and reducing the number of model parameters. Experiments in the CICIDS2017 dataset verify the improvements of our method in the detection speed and the detection accuracy in dealing with the small sample classes.

Keywords: network flow anomaly detection (NAD), multi-teacher knowledge distillation, machine learning, deep learning

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Authors: Eirini Oikonomopoulou

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Paper is dealing with gentrification of a poor central historic district of Fener and Balat in Istanbul, Turkey and propose ålans and principles of a neighborhood. Istanbul is located in a special geographic place, just in the meeting of Europe and Asia and it has a long and great history, facts that had affected the urban form of the city. Trough the time different civilizations inhabited in the city and they changed it by giving different character to its parts. The modernization of Istanbul brought western ideas into the historic organic urban fabric and put in the first priority the need for a clear and strong car-road/highway network in order to improve the car accessibility along the city. Following that model, transformation of public spaces was based on the driving experience. New public spaces was formulated to be the new symbol of Turkish Republic, to give a beautiful and clean image of the modern Turkish city, as well as work as landmarks across the highway network. Even if city is upgraded, bad quality neighborhoods still exist, far and near to the historic city center. One of them is Fener/Balat, which is located in Fatih district on the European side of Istanbul. This project aims to analyze the urban qualities of that neighborhood (mahalle) and propose a better, qualitative urban space towards a denser, greener and more inclusive neighborhood which could be an example for the whole city.

Keywords: urban design, upgrade neighborhood, Istanbul, sustanability

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Authors: Shi-Yu Xu

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The top three risk factors that have contributed to building collapses during past earthquake events in Taiwan are: "irregular floor plans or elevations," "insufficient columns in single-bay buildings," and the "weak-story problem." Fortunately, these unsound structural characteristics can be directly identified from the floor plans. However, due to the vast number of old buildings, conducting manual inspections to identify these compromised structural features in all existing structures would be time-consuming and prone to human errors. This study aims to develop an algorithm that utilizes artificial intelligence techniques to automatically pinpoint the structural components within a building's floor plans. The obtained spatial information will be utilized to construct a digital structural model of the building. This information, particularly regarding the distribution of columns in the floor plan, can then be used to conduct preliminary seismic assessments of the building. The study employs various image processing and pattern recognition techniques to enhance detection efficiency and accuracy. The study enables a large-scale evaluation of structural vulnerability for numerous old buildings, providing ample time to arrange for structural retrofitting in those buildings that are at risk of significant damage or collapse during earthquakes.

Keywords: structural vulnerability detection, object recognition, seismic capacity assessment, old buildings, artificial intelligence

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Authors: Hanady Al-Zagheer

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The purpose of this paper research is to introduce the role of the social media (face book) in growing small and medium enterprises in Jordan, Today’s developments of information technologies are dazzling. Using information technologies results in having advantages in competition, decreasing costs, gaining time, and getting and sharing information. Now it is possible to state that there are different types of usage within the information technologies. Small and medium enterprises have been grown rapidly in recent years and continue to grow. Jordanian females have played a large role in the growth of entrepreneurship and have made an impact on household economics. Virtual storefronts have allowed these women to balance roles assigned by tradition and culture while becoming successful providers. If you have a small business with a limited public relations and advertising budget, Facebook can be a cost effective way to promote your services because opening an account is free. However, this can work against you if you do not maintain the page. A Face book page without frequent updates can destroy your brand value and image. According to a 2009 Computerworld article by Lisa Hoover, having a Facebook page that looks abandoned is worse than having no page at all. You might need to hire someone or pay an employee to update your business’s Facebook page.

Keywords: social media, social media small, medium enterprises, Jordan

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Authors: Beruk Berhanu Desalegn, Gelana Mulu

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Adolescence, especially for females, is a period of an ongoing risk behavior that triggers development of adverse health outcomes during adulthood. This study aimed to investigate the weight control practice and its associated factors among high school female-adolescents in Hawassa town, Ethiopia. A school-based cross-sectional study was conducted on 552 female-adolescents in Hawassa town. The study was conducted between December, 2020 to January, 2021. SPSS version 26 was used to analyse the data from the pre-tested questionnaire of socio-demographic, economic, socio-cultural, and related information. Among the total female-adolescents, 38.6% [95% CI= 34.5-42.8%] took on weight control practices. The study further revealed the condition of the weight control practice to be healthy (20.5%), unhealthy(25.9%, and the rest to be both healthyand unhealthy(7.8%). The multivariate regression model, cutoff p < 0.05, disclosed that predicters like late adolescent age [AOR=1.98; 95% CI=1.33-2.95], middle wealth status [AOR=2.72; 95% CI=1.60-4.63], high wealth status [AOR=5.69; 95% CI=3.43-9.46], normal BMI [AOR=2.36; 95% CI=1.18-4.71], overweight [AOR=2.45; 95% CI=1.13-5.28], mild depression [AOR=1.72; 95% CI=1.12-2.66] and dissatisfied own mid-torso body image [AOR=2.68; 95% CI=1.52-4.73] were found to have significant association with weight control practice. Therefore, it may be benefiting to consider the findings of this study for interventions associated with female adolescents weight control practices.

Keywords: female-adolescents, highschool, weight control practice, Ethiopia

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Authors: Mohamed Ali Abdennadher

Abstract:

Digital rock physics, an emerging field leveraging advanced imaging and numerical techniques, offers a promising approach to investigating the mechanical properties of granular materials without extensive physical experiments. This study focuses on using X-Ray Computed Tomography (CT) to capture the three-dimensional (3D) structure of coarse-grained soil at the particle level, combined with finite element analysis (FEA) to simulate the soil's behavior under compression. The primary goal is to establish a reliable virtual testing framework that can replicate laboratory results and offer deeper insights into soil mechanics. The methodology involves acquiring high-resolution CT scans of coarse-grained soil samples to visualize internal particle morphology. These CT images undergo processing through noise reduction, thresholding, and watershed segmentation techniques to isolate individual particles, preparing the data for subsequent analysis. A custom Python script is employed to extract particle shapes and conduct a statistical analysis of particle size distribution. The processed particle data then serves as the basis for creating a finite element model comprising approximately 500 particles subjected to one-dimensional compression. The FEA simulations explore the effects of mesh refinement and friction coefficient on stress distribution at grain contacts. A multi-layer meshing strategy is applied, featuring finer meshes at inter-particle contacts to accurately capture mechanical interactions and coarser meshes within particle interiors to optimize computational efficiency. Despite the known challenges in parallelizing FEA to high core counts, this study demonstrates that an appropriate domain-level parallelization strategy can achieve significant scalability, allowing simulations to extend to very high core counts. The results show a strong correlation between the finite element simulations and laboratory compression test data, validating the effectiveness of the virtual experiment approach. Detailed stress distribution patterns reveal that soil compression behavior is significantly influenced by frictional interactions, with frictional sliding, rotation, and rolling at inter-particle contacts being the primary deformation modes under low to intermediate confining pressures. These findings highlight that CT data analysis combined with numerical simulations offers a robust method for approximating soil behavior, potentially reducing the need for physical laboratory experiments.

Keywords: X-Ray computed tomography, finite element analysis, soil compression behavior, particle morphology

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Authors: Ertuğrul Ferhat Yilmaz, Ali Riza Perçin

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In the business enterprises implemented modern business enterprise principles, the most important issues are increasing the performance of workers and getting maximum income. Through the twentieth century, rapid development of the sectors of data processing and communication and because of the free trade politics arising of multilateral business enterprises have canceled the economical borders and changed the local rivalry into the spherical rivalry. In this rivalry conditions, the business enterprises have to work active and productive in order to continue their existences. The employees worked at business enterprises have formed the most important factor of product. Therefore, the business enterprises inferring the importance of the human factors in order to increase the profit have used “the performance evolution system” to increase the success and development of the employees. The evolution of the performance is aimed to increase the manpower productive by using the employees in an active way. Furthermore, this system assists the wage politics implemented in business enterprise, determining the strategically plans in business enterprises through the short and long terms, being promoted and determining the educational needs of employees, making decisions as dismissing and work rotation. It requires a great deal of effort to catch the pace of change in the working realm and to keep up ourselves up-to-date. To get the quality in people,to have an effect in workplace depends largely on the knowledge and competence of managers and prospective managers. Therefore,managers need to use the performance evaluation systems in order to base their managerial decisions on sound data. This study aims at finding whether the organizations effectively use performance evaluation systms,how much importance is put on this issue and how much the results of the evaulations have an effect on employees. Whether the organizations have the advantage of competition and can keep on their activities depend to a large extent on how they effectively and efficiently use their employees.Therefore,it is of vital importance to evaluate employees' performance and to make them better according to the results of that evaluation. The performance evaluation system which evaluates the employees according to the criteria related to that organization has become one of the most important topics for management. By means of those important ends mentioned above,performance evaluation system seems to be a tool that can be used to improve the efficiency and effectiveness of organization. Because of its contribution to organizational success, thinking performance evaluation on the axis of efficiency shows the importance of this study on a different angle. In this study, we have explained performance evaluation system ,efficiency and the relation between those two concepts. We have also analyzed the results of questionnaires conducted on the textile workers in Edirne city.We have got positive answers from the questions about the effects of performance evaluation on efficiency.After factor analysis ,the efficiency and motivation which are determined as factors of performance evaluation system have the biggest variance (%19.703) in our sample. Thus, this study shows that objective performance evaluation increases the efficiency and motivation of employees.

Keywords: performance, performance evolution system, productivity, Edirne region

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Authors: Asma Ameur, Dhafer Malouche

Abstract:

Hotel competitiveness research is an essential phase of the marketing strategy for any hotel. Certainly, knowing the hotels' competitors helps the hotelier to grasp its position in the market and the citizen to make the right choice in picking a hotel. Thus, competitiveness is an important indicator that can be influenced by various factors. In fact, the issue of competitiveness, this ability to cope with competition, remains a difficult and complex concept to define and to exploit. Therefore, the purpose of this article is to make an exploratory study to calculate a competitiveness indicator for hotels. Further on, this paper makes it possible to determine the criteria of direct or indirect effect on the image and the perception of a hotel. The actual research is used to look into the right model for hotel ‘competitiveness. For this reason, we exploit different theoretical contributions in the field of machine learning. Thus, we use some statistical techniques such as the Principal Component Analysis (PCA) to reduce the dimensions, as well as other techniques of statistical modeling. This paper presents a survey covering of the techniques and methods in hotel competitiveness research. Furthermore, this study allows us to deduct the significant variables that influence the determination of hotel’s competitors. Lastly, the discussed experiences in this article found that the hotel competitors are influenced by several factors with different rates.

Keywords: competitiveness, e-reputation, hotels' competitors, online hotel’ review, principal component analysis, statistical modeling

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Authors: Ahmadali Tahmasebimoradi, Chetra Mang, Xavier Lorang

Abstract:

Thanks to the additive manufacturing process, lattice structures are replacing the traditional structures in aeronautical and automobile industries. In order to evaluate the mechanical response of the lattice structures, one has to resort to numerical techniques. Ansys is a globally well-known and trusted commercial software that allows us to model the lattice structures and analyze their mechanical responses using either solid or beam elements. In this software, a script may be used to systematically generate the lattice structures for any size. On the one hand, solid elements allow us to correctly model the contact between the substrates (the supports of the lattice structure) and the lattice structure, the local plasticity, and the junctions of the microbeams. However, their computational cost increases rapidly with the size of the lattice structure. On the other hand, although beam elements reduce the computational cost drastically, it doesn’t correctly model the contact between the lattice structures and the substrates nor the junctions of the microbeams. Also, the notion of local plasticity is not valid anymore. Moreover, the deformed shape of the lattice structure doesn’t correspond to the deformed shape of the lattice structure using 3D solid elements. In this work, motivated by the pros and cons of the 3D and beam models, a numerically hybrid model is presented for the lattice structures to reduce the computational cost of the simulations while avoiding the aforementioned drawbacks of the beam elements. This approach consists of the utilization of solid elements for the junctions and beam elements for the microbeams connecting the corresponding junctions to each other. When the global response of the structure is linear, the results from the hybrid models are in good agreement with the ones from the 3D models for body-centered cubic with z-struts (BCCZ) and body-centered cubic without z-struts (BCC) lattice structures. However, the hybrid models have difficulty to converge when the effect of large deformation and local plasticity are considerable in the BCCZ structures. Furthermore, the effect of the junction’s size of the hybrid models on the results is investigated. For BCCZ lattice structures, the results are not affected by the junction’s size. This is also valid for BCC lattice structures as long as the ratio of the junction’s size to the diameter of the microbeams is greater than 2. The hybrid model can take into account the geometric defects. As a demonstration, the point clouds of two lattice structures are parametrized in a platform called LATANA (LATtice ANAlysis) developed by IRT-SystemX. In this process, for each microbeam of the lattice structures, an ellipse is fitted to capture the effect of shape variation and roughness. Each ellipse is represented by three parameters; semi-major axis, semi-minor axis, and angle of rotation. Having the parameters of the ellipses, the lattice structures are constructed in Spaceclaim (ANSYS) using the geometrical hybrid approach. The results show a negligible discrepancy between the hybrid and 3D models, while the computational cost of the hybrid model is lower than the computational cost of the 3D model.

Keywords: additive manufacturing, Ansys, geometric defects, hybrid finite element model, lattice structure

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Authors: Zuraidasahana Zulkarnain, Mohd Shafry Mohd Rahim, Nor Anita Fairos Ismail, Mohd Azhar M. Arsad

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Handwritten signature is accepted widely as a biometric characteristic for personal authentication. The use of appropriate features plays an important role in determining accuracy of signature verification; therefore, this paper presents a feature based on the geometrical concept. To achieve the aim, triangle attributes are exploited to design a new feature since the triangle possesses orientation, angle and transformation that would improve accuracy. The proposed feature uses triangulation geometric set comprising of sides, angles and perimeter of a triangle which is derived from the center of gravity of a signature image. For classification purpose, Euclidean classifier along with Voting-based classifier is used to verify the tendency of forgery signature. This classification process is experimented using triangular geometric feature and selected global features. Based on an experiment that was validated using Grupo de Senales 960 (GPDS-960) signature database, the proposed triangular geometric feature achieves a lower Average Error Rates (AER) value with a percentage of 34% as compared to 43% of the selected global feature. As a conclusion, the proposed triangular geometric feature proves to be a more reliable feature for accurate signature verification.

Keywords: biometrics, euclidean classifier, features extraction, offline signature verification, voting-based classifier

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