Search results for: image transformation

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: Wafa Toumi, Alessandro Ripalti, Luigi Ricciardiello, Dalila Gargouri, Jamel Kharrat, Abderraouf Cherif, Ahmed Bouhafa, Slim Jarboui, Mohamed Zili, Ridha Khelifa

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Background & aims: Colorectal cancer (CRC) is one of the most common malignancies throughout the world. Several risk factors, both genetic and environmental, including viral infections, have been linked to colorectal carcinogenesis. A few studies report the detection of human polyomavirus JC (JCV) DNA and transformation antigen (T-Ag) in a fraction of the colorectal tumors studied and suggest an association of this virus with CRC. In order to investigate whether such an association of JCV with CRC will hold in a different epidemiological setting, we looked for the presence of JCV DNA and T-Ag expression in a group of Tunisian CRC patients. Methods: Fresh colorectal mucosa biopsies were obtained from 17 healthy volunteers and from both colorectal tumors and adjacent normal tissues of 47 CRC patients. DNA was extracted from fresh biopsies or from formalin-fixed, paraffin-embedded tissue sections using the Invitrogen Purelink Genomic DNA mini Kit. A simple PCR and a nested PCR were used to amplify a region of the T-Ag gene. The obtained PCR products revealed a 154 bp and a 98 bp bands, respectively. Specificity was confirmed by sequencing of the PCR products. T-Ag expression was determined by immunohistochemical staining using a mouse monoclonal antibody (clone PAb416) directed against SV40 T-Ag that cross reacts with JCV T-Ag. Results: JCV DNA was found in 12 (25%) and 22 (46%) of the CRC tumors by simple PCR and by nested PCR, respectively. All paired adjacent normal mucosa biopsies were negative for viral DNA. Sequencing of the DNA amplicons obtained confirmed the authenticity of T-Ag sequences. Immunohistochemical staining showed nuclear T-Ag expression in all 22 JCV DNA- positive samples and in 3 additional tumor samples which appeared DNA-negative by PCR. Conclusions: These results suggest an association of JCV with a subpopulation of Tunisian colorectal tumors.

Keywords: colorectal cancer, immunohistochemistry, Polyomavirus JC, PCR

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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: 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: 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: Svitlana Antonenko, Gennady Telegeev

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Introductive statement: The development of chronic myeloid leukemia (CML) is caused by Bcr-Abl oncoprotein. Modern treatments with tyrosine kinase inhibitors are greatly complicated by the mutational variability of the Bcr-Abl oncoprotein, which causes drug resistance. Therefore, there is an urgent need to develop new approaches to the treatment of the disease, which will allow modeling the level of Bcr-Abl oncoprotein in the cell. Promising in this direction is the identification of proteases that can selectively promote cellular proteolysis of oncoproteins. The aim of the study was to study the effect of the interaction of Bcr-Abl with deubiquitinase USP1 on the level of oncoprotein in CML cells. Methodology: K562 cells were selected for the experiment. Сells were incubated with ML323 inhibitor for 24 hours. Precipitation of endogenous proteins from K562 cell lysate was performed using anti-Bcr-Abl antibodies. Cell lysates and precipitation results were studied by Western blot. Subcellular localization of proteins was studied by immunofluorescence analysis followed by confocal microscopy. The results were analyzed quantitatively and statistically. Major findings: The Bcr-Abl/USP1 protein complex was detected in CML cells, and it was found that inhibition of USP1 deubiquitinating activity by the compound ML323 leads to disruption of this protein complex and a decrease in the level of Bcr-Abl oncoprotein in cells. The interaction of Bcr-Abl with USP1 may result in deubiquitination of the oncoprotein, which disrupts its proteasomal degradation and leads to the accumulation of CML in cells. Conclusion: We believe that the interaction of oncoprotein with USP1 may be one of the prerequisites that contribute to malignant cell transformation due to the deubiquitination of oncoprotein, which leads to its accumulation and disease progression. A correlation was found between the deubiquitinating activity of USP1 and the level of oncoprotein in CML cells. Thus, we identify deubiquitinase USP1 as a promising therapeutic target for the development of a new strategy for the treatment of CML by modulating the level of Bcr-Abl in the cell.

Keywords: chronic myeloid leukemia, Bcr-Abl, USP1, deubiquitination Bcr-Abl, K562 cell

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Authors: Ali Mohammed Yimer, Ayalew H. Assen, Youssef Belmabkhout

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This study delves into sustainable approaches for valorizing phosphatic wastes, specifically phosphate mining wastes and phosphogypsum, which are byproducts of phosphate industries and pose significant environmental challenges due to their accumulation. We propose a unified strategic synthesis method aimed at converting these wastes into hetero-functional porous materials. Our approach involves isolating the primary components of phosphatic wastes, such as CaO, SiO2 and Al2O3 to fabricate functional porous materials falling into two distinct classes. Firstly, alumina and silica components are extracted or isolated to produce zeolites (including CAN, GIS, SOD, FAU, and LTA), characterized by a Si/Al ratio of less than 5. Secondly, residual calcium is utilized to synthesize calcium-based metal–organic frameworks (Ca-MOFs) employing various organic linkers like Ca-BDC, Ca-BTC and Ca-TCPB (SBMOF-2), thereby providing flexibility in material design. Characterization techniques including XRD, SEM-EDX, FTIR, and TGA-MS affirm successful material assembly, while sorption analyses using N2, CO2, and H2O demonstrate the porosity of the materials. Particularly noteworthy is the water/alcohol separation potential exhibited by the Ca-BTC MOF, owing to its optimal pore aperture size (∼3.4 Å). To enhance replicability and scalability, detailed protocols for each synthesis step and specific conditions for each process are provided, ensuring that the methodology can be easily reproduced and scaled up for industrial applications. This synthetic transformation approach represents a valorization route for converting phosphatic wastes into extended porous structures, promising significant environmental and economic benefits.

Keywords: calcium-based metal-organic frameworks, low-silica zeolites, porous materials, sustainable synthesis, valorization

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Authors: Enrique Claver Cortés, Bartolomé Marco Lajara, Eduardo Sánchez García, Pedro Seva Larrosa, Encarnación Manresa Marhuenda, Lorena Ruiz Fernández, Esther Poveda Pareja

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In recent decades, the analysis of the effects of clustering as an essential factor for the development of innovations and the competitiveness of enterprises has raised great interest in different areas. Nowadays, companies have access to almost all tangible and intangible resources located and/or developed in any country in the world. However, despite the obvious advantages that this situation entails for companies, their geographical location has shown itself, increasingly clearly, to be a fundamental factor that positively influences their innovative performance and competitiveness. Industrial clusters could represent a unique level of analysis, positioned between the individual company and the industry, which makes them an ideal unit of analysis to determine the effects derived from company membership of a cluster. Also, the absorptive capacity (hereinafter 'AC') can mediate the process of innovation development by companies located in a cluster. The transformation and exploitation of knowledge could have a mediating effect between knowledge acquisition and innovative performance. The main objective of this work is to determine the key factors that affect the degree of generation and use of knowledge from the environment by companies and, consequently, their innovative performance and competitiveness. The elements analyzed are the companies' membership of a cluster and the AC. To this end, 30 most relevant papers published on this subject in the "Web of Science" database have been reviewed. Our findings show that, within a cluster, the knowledge coming from the companies' environment can significantly influence their innovative performance and competitiveness, although in this relationship, the degree of access and exploitation of the companies to this knowledge plays a fundamental role, which depends on a series of elements both internal and external to the company.

Keywords: absorptive capacity, clusters, innovation, knowledge

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Authors: Martin Hofmann, Diego Stutzer, Thomas Niederhauser, Juergen Burger

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Dental biofilm is the main etiologic factor for caries, periodontal and peri-implant infections. In addition to the risk of tooth loss, periodontitis is also associated with an increased risk of systemic diseases such as atherosclerotic cardiovascular disease and diabetes. For this reason, dental hygienists use ultrasonic scalers for prophylactic and periodontal care of the teeth. However, the current instruments are limited to their dimensions and operating frequencies. The innovative design of a planar ultrasonic transducer introduces a new type of dental scalers. The flat titanium-based design allows the mass to be significantly reduced compared to a conventional screw-mounted Langevin transducer, resulting in a more efficient and controllable scaler. For the development of the novel device, multi-physics finite element analysis was used to simulate and optimise various design concepts. This process was supported by prototyping and electromechanical characterisation. The feasibility and potential of a planar ultrasonic transducer have already been confirmed by our current prototypes, which achieve higher performance compared to commercial devices. Operating at the desired resonance frequency of 28 kHz with a driving voltage of 40 Vrms results in an in-plane tip oscillation with a displacement amplitude of up to 75 μm by having less than 8 % out-of-plane movement and an energy transformation factor of 1.07 μm/mA. In a further step, we will adapt the design to two additional resonance frequencies (20 and 40 kHz) to obtain information about the most suitable mode of operation. In addition to the already integrated characterization methods, we will evaluate the clinical efficiency of the different devices in an in vitro setup with an artificial biofilm pocket model.

Keywords: ultrasonic instrumentation, ultrasonic scaling, piezoelectric transducer, finite element simulation, dental biofilm, dental calculus

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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: Rebecca J. Hafner, Daniel Read, David Elmes

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The current research applies decision making theory in order to address the problem of increasing uptake of energy-efficient technologies in the market place, where uptake is currently slower than one might predict following rational choice models. Specifically, in two studies we apply the alignable/non-alignable features effect and explore the impact of varying information structure on the consumers’ preference for standard versus energy efficient technologies. As researchers in the Interdisciplinary centre for Storage, Transformation and Upgrading of Thermal Energy (i-STUTE) are currently developing energy efficient heating systems for homes and businesses, we focus on the context of home heating choice, and compare preference for a standard condensing boiler versus an energy efficient heat pump, according to experimental manipulations in the structure of prior information. In Study 1, we find that people prefer stronger alignable features when options are similar; an effect which is mediated by an increased tendency to infer missing information is the same. Yet, in contrast to previous research, we find no effects of alignability on option preference when options differ. The advanced methodological approach used here, which is the first study of its kind to randomly allocate features as either alignable or non-alignable, highlights potential design effects in previous work. Study 2 is designed to explore the interaction between alignability and construal level as an explanation for the shift in attentional focus when options differ. Theoretical and applied implications for promoting energy efficient technologies are discussed.

Keywords: energy-efficient technologies, decision-making, alignability effects, construal level theory, CO2 reduction

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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: Arwin Malabanan, Carl Chester Ragudo, Jerome Tadiosa, John Dee Mangoba, Eric Augustus Tingatinga, Romeo Eliezer Longalong

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Concrete hollow blocks (CHB) are the most commonly used masonry block for walls in residential houses, school buildings and public buildings in the Philippines. During the recent 2013 Bohol earthquake (Mw 7.2), it has been proven that CHB walls are very vulnerable to severe external action like strong ground motion. In this paper, a numerical model of CHB structures is proposed, and seismic behavior of CHB houses is presented. In modeling, the Rigid Body Spring-Discrete Element method (RBS-DEM)) is used wherein masonry blocks are discretized into rigid elements and connected by nonlinear springs at preselected contact points. The shear and normal stiffness of springs are derived from the material properties of CHB unit incorporating the grout and mortar fillings through the volumetric transformation of the dimension using material ratio. Numerical models of reinforced and unreinforced walls are first subjected to linearly-increasing in plane loading to observe the different failure mechanisms. These wall models are then assembled to form typical model masonry houses and then subjected to the El Centro and Pacoima earthquake records. Numerical simulations show that the elastic, failure and collapse behavior of the model houses agree well with shaking table tests results. The effectiveness of the method in replicating failure patterns will serve as a basis for the improvement of the design and provides a good basis of strengthening the structure.

Keywords: concrete hollow blocks, discrete element method, earthquake, rigid body spring model

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Authors: S. Ahmed John

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Marine forms-bacteria, actinobacteria, cynobacteria, fungi, microalgae, seaweeds mangroves and other halophytes an extremely important oceanic resources and constituting over 90% of the oceanic biomass. The marine natural products have lead to the discovery of many compounds considered worthy for clinical applications. The marine sources have the highest probability of yielding natural products. Natural derivatives play an important role to prevent the cancer incidences as synthetic drug transformation in mangrove. 28.12% of anticancer compound extracted from the mangroves. Exchocaria agollocha has the anti cancer compounds. The present investigation reveals the potential of the Exchocaria agollocha with biotechnological applications for anti cancer, antimicrobial drug discovery, environmental remediation, and developing new resources for the industrial process. The anti-cancer activity of Exchocaria agollocha was screened from 3.906 to 1000 µg/ml of concentration with the dilution leads to 1:1 to 1:128 following methanol and chloroform extracts. The cell viability in the Exchocaria agollocha was maximum at the lower concentration where as low at the higher concentration of methanol and chloroform extracts when compare to control. At 3.906 concentration, 85.32 and 81.96 of cell viability was found at 1:128 dilution of methanol and chloroform extracts respectively. At the concentration of 31.25 following 1:16 dilution, the cell viability was 65.55 in methanol and 45.55 in chloroform extracts. However, at the higher concentration, the cell viability 22.35 and 8.12 was recorded in the extracts of methanol and chloroform. The cell viability was more in methanol when compare to chloroform extracts at lower concentration. The present findings gives current trends in screening and the activity analysis of metabolites from mangrove resources and to expose the models to bring a new sustain for tackling cancer. Bioactive compounds of Exchocaria agollocha have extensive use in treatment of many diseases and serve as a compound and templates for synthetic modification.

Keywords: bio-active product, compounds, natural products and microalgae

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Authors: Asma Ameur, Dhafer Malouche

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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: Melis Inalpulat, Levent Genc

Abstract:

In the present study, an attempt was made to state the Land Use Land Cover (LULC) transformation over three decades around the urban regions of Balıkesir, Bursa, and Çanakkale provincial centers (PCs) in Turkey. Landsat imageries acquired in 1984, 1999 and 2014 were used to determine the LULC change. Images were classified using the supervised classification technique and five main LULC classes were considered including forest (F), agricultural land (A), residential area (urban) - bare soil (R-B), water surface (W), and other (O). Change detection analyses were conducted for 1984-1999 and 1999-2014, and the results were evaluated. Conversions of LULC types to R-B class were investigated. In addition, population changes (1985-2014) were assessed depending on census data, the relations between population and the urban areas were stated, and future populations and urban area needs were forecasted for 2030. The results of LULC analysis indicated that urban areas, which are covered under R-B class, were expanded in all PCs. During 1984-1999 R-B class within Balıkesir, Bursa and Çanakkale PCs were found to have increased by 7.1%, 8.4%, and 2.9%, respectively. The trend continued in the 1999-2014 term and the increment percentages reached to 15.7%, 15.5%, and 10.2% at the end of 30-year period (1984-2014). Furthermore, since A class in all provinces was found to be the principal contributor for the R-B class, urban sprawl lead to the loss of agricultural lands. Moreover, the areas of R-B classes were highly correlated with population within all PCs (R²>0.992). Depending on this situation, both future populations and R-B class areas were forecasted. The estimated values of increase in the R-B class areas for Balıkesir, Bursa, and Çanakkale PCs were 1,586 ha, 7,999 ha and 854 ha, respectively. Due to this fact, the forecasted values for 2,030 are 7,838 ha, 27,866, and 2,486 ha for Balıkesir, Bursa, and Çanakkale, and thus, 7.7%, 8.2%, and 9.7% more R-B class areas are expected to locate in PCs in respect to the same order.

Keywords: landsat, LULC change, population, urban sprawl

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Authors: Abe Degale D., Cheng Jian

Abstract:

When creating automated video surveillance systems, violent action recognition is crucial. In recent years, hand-crafted feature detectors have been the primary method for achieving violence detection, such as the recognition of fighting activity. Researchers have also looked into learning-based representational models. On benchmark datasets created especially for the detection of violent sequences in sports and movies, these methods produced good accuracy results. The Hockey dataset's videos with surveillance camera motion present challenges for these algorithms for learning discriminating features. Image recognition and human activity detection challenges have shown success with deep representation-based methods. For the purpose of detecting violent images and identifying aggressive human behaviours, this research suggested a deep representation-based model using the transfer learning idea. The results show that the suggested approach outperforms state-of-the-art accuracy levels by learning the most discriminating features, attaining 99.34% and 99.98% accuracy levels on the Hockey and Movies datasets, respectively.

Keywords: violence detection, faster RCNN, transfer learning and, surveillance video

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Authors: Kay Thinzar Phu, Lwin Lwin Oo

Abstract:

In an intelligent transport system and advanced driver assistance system, the developing of real-time traffic sign detection and recognition (TSDR) system plays an important part in recent research field. There are many challenges for developing real-time TSDR system due to motion artifacts, variable lighting and weather conditions and situations of traffic signs. Researchers have already proposed various methods to minimize the challenges problem. The aim of the proposed research is to develop an efficient and effective TSDR in real time. This system proposes an adaptive thresholding method based on RGB color for traffic signs detection and new features for traffic signs recognition. In this system, the RGB color thresholding is used to detect the blue and yellow color traffic signs regions. The system performs the shape identify to decide whether the output candidate region is traffic sign or not. Lastly, new features such as termination points, bifurcation points, and 90’ angles are extracted from validated image. This system uses Myanmar Traffic Sign dataset.

Keywords: adaptive thresholding based on RGB color, blue color detection, feature extraction, yellow color detection

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Authors: Xingmao Ma, Wenjie Sun

Abstract:

Rice paddies are frequently co-contaminated by arsenic (As) and cadmium (Cd), both of which demonstrate a high propensity for accumulation in rice grains and cause global food safety and public health concern. Even though different agricultural management strategies have been explored for their simultaneous control in rice grains, a viable solution is yet to be developed. Interestingly, several nanoagrichemicals, such as the zinc nanofertilizer and copper nanopesticide have displayed strong potential to reduce As or Cd accumulation in rice tissues. In order to determine whether these nanoagrichemicals can lower the accumulation of both As and Cd in rice, a series of bench studies were performed. Our results show that zinc oxide nanoparticles at 100 mg/Kg significantly lowered both As, and Cd in rice roots and shoots in flood irrigated rice seedlings, while equivalent amount of zinc ions only reduced As concentration in rice shoots. Zinc ions significantly increased Cd concentration in rice shoots by almost 30%. The results demonstrate a unique 'nano-effect' of zinc oxide nanoparticles, which is ascribed to the slow releasing of zinc ions from nanoparticles and the formation of different transformation products in these two treatments. We also evaluated the effect of nanoscale soil amendment, silicon oxide nanoparticles (SiO₂NPs) on the simultaneous reduction in both flooding and alternate wet and dry irrigation scheme. The effect of SiO₂NPs on As and Cd accumulation in rice tissues was strongly affected by the irrigation scheme. While 2000 mg/kg of SiO₂NPs significantly reduced As in rice roots and insignificantly reduced As in rice shoots in flooded rice, it increased As concentration in rice shoots in alternate wet and dry irrigation. In both irrigation scenarios, SiO₂NPs significantly reduced Cd concentration in rice roots, but only reduced Cd concentration in rice shoots in alternate wet and dry irrigation. Our results demonstrate a marked effect of nanoagrichemicals on the accumulation of As and Cd in rice and can be a potential solution to simultaneously control both in certain conditions.

Keywords: arsenic, cadmium, rice, nanoagrichemicals

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Authors: Sharda Kumari, Saiman Shetty

Abstract:

Autonomous trucking is just one of the numerous significant shifts impacting fleet management services. The Society of Automotive Engineers (SAE) has defined six levels of vehicle automation that have been adopted internationally, including by the United States Department of Transportation. On public highways in the United States, organizations are testing driverless vehicles with at least Level 4 automation which indicates that a human is present in the vehicle and can disable automation, which is usually done while the trucks are not engaged in highway driving. However, completely driverless vehicles are presently being tested in the state of California. While autonomous trucking can increase safety, decrease trucking costs, provide solutions to trucker shortages, and improve efficiencies, logistics, too, requires advancements to keep up with trucking innovations. Given that artificial intelligence, machine learning, and automated procedures enable people to do their duties in other sectors with fewer resources, CRM (Customer Relationship Management) can be applied to the autonomous trucking business to provide the same level of efficiency. In a society witnessing significant digital disruptions, fleet management is likewise being transformed by technology. Utilizing strategic alliances to enhance core services is an effective technique for capitalizing on innovations and delivering enhanced services. Utilizing analytics on CRM systems improves cost control of fuel strategy, fleet maintenance, driver behavior, route planning, road safety compliance, and capacity utilization. Integration of autonomous trucks with automated fleet management, yard/terminal management, and customer service is possible, thus having significant power to redraw the lines between the public and private spheres in autonomous trucking logistics.

Keywords: autonomous vehicles, customer relationship management, customer experience, autonomous trucking, digital transformation

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Authors: Abdesselem Dakhli, Wajdi Bellil, Chokri Ben Amar

Abstract:

DNA Barcode, a short mitochondrial DNA fragment, made up of three subunits; a phosphate group, sugar and nucleic bases (A, T, C, and G). They provide good sources of information needed to classify living species. Such intuition has been confirmed by many experimental results. Species classification with DNA Barcode sequences has been studied by several researchers. The classification problem assigns unknown species to known ones by analyzing their Barcode. This task has to be supported with reliable methods and algorithms. To analyze species regions or entire genomes, it becomes necessary to use similarity sequence methods. A large set of sequences can be simultaneously compared using Multiple Sequence Alignment which is known to be NP-complete. To make this type of analysis feasible, heuristics, like progressive alignment, have been developed. Another tool for similarity search against a database of sequences is BLAST, which outputs shorter regions of high similarity between a query sequence and matched sequences in the database. However, all these methods are still computationally very expensive and require significant computational infrastructure. Our goal is to build predictive models that are highly accurate and interpretable. This method permits to avoid the complex problem of form and structure in different classes of organisms. On empirical data and their classification performances are compared with other methods. Our system consists of three phases. The first is called transformation, which is composed of three steps; Electron-Ion Interaction Pseudopotential (EIIP) for the codification of DNA Barcodes, Fourier Transform and Power Spectrum Signal Processing. The second is called approximation, which is empowered by the use of Multi Llibrary Wavelet Neural Networks (MLWNN).The third is called the classification of DNA Barcodes, which is realized by applying the algorithm of hierarchical classification.

Keywords: DNA barcode, electron-ion interaction pseudopotential, Multi Library Wavelet Neural Networks (MLWNN)

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Authors: Zuoji Huang, Haiming Qian, Chunlin Wang, Jinyan Sun, Nan Xu

Abstract:

In this paper, the strategy to extract double road edge lines from acquired road stripe image was explored. The workflow is as follows: the road stripes are acquired by probabilistic boosting tree algorithm and morphological algorithm immediately, and road centerlines are detected by thinning algorithm, so the initial road edge lines can be acquired along the road centerlines. Then we refine the results with big variation of local curvature of centerlines. Specifically, the energy function of edge line is constructed by gradient feature and spectral information, and Dijkstra algorithm is used to optimize the initial road edge lines. The Snake model is constructed to solve the fracture problem of intersection, and the discrete dynamic programming algorithm is used to solve the model. After that, we could get the final road network. Experiment results show that the strategy proposed in this paper can be used to extract the continuous and smooth road edge lines from high-resolution remote sensing images with an accuracy of 88% in our study area.

Keywords: road edge lines extraction, energy function, intersection fracture, Snake model

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Authors: Lianzhong Zhang, Chao Huang

Abstract:

Sea-land segmentation is a basic step in many tasks such as sea surface monitoring and ship detection. The existing sea-land segmentation algorithms have poor segmentation accuracy, and the parameter adjustments are cumbersome and difficult to meet actual needs. Also, the current sea-land segmentation adopts traditional deep learning models that use Convolutional Neural Networks (CNN). At present, the transformer architecture has achieved great success in the field of natural images, but its application in the field of radar images is less studied. Therefore, this paper proposes a sea-land segmentation method based on the transformer architecture to strengthen edge supervision. It uses a self-attention mechanism with a gating strategy to better learn relative position bias. Meanwhile, an additional edge supervision branch is introduced. The decoder stage allows the feature information of the two branches to interact, thereby improving the edge precision of the sea-land segmentation. Based on the Gaofen-3 satellite image dataset, the experimental results show that the method proposed in this paper can effectively improve the accuracy of sea-land segmentation, especially the accuracy of sea-land edges. The mean IoU (Intersection over Union), edge precision, overall precision, and F1 scores respectively reach 96.36%, 84.54%, 99.74%, and 98.05%, which are superior to those of the mainstream segmentation models and have high practical application values.

Keywords: SAR, sea-land segmentation, deep learning, transformer

Procedia PDF Downloads 185