Search results for: Mutare urban timber processing factories
Commenced in January 2007
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Edition: International
Paper Count: 7679

Search results for: Mutare urban timber processing factories

3539 The Development of Home-Based Long Term Care Model among Thai Elderly Dependent

Authors: N. Uaphongsathorn, C. Worawong, S. Thaewpia

Abstract:

Background and significance: The population is aging in Thai society, the elderly dependent is at great risk of various functional, psychological, and socio-economic problems as well as less access to health care. They may require long term care at home to maximize their functional abilities and activities of daily living and to improve their quality of life during their own age. Therefore, there is a need to develop a home-based long term care to meet the long term care needs of elders dependent. Methods: The research purpose was to develop long term care model among the elderly dependent in Chaiyaphum province in Northeast region of Thailand. Action Research which is composing of planning, action, observation, and reflection phases was used. Research was carried out for 12 months in all sub-districts of 6 districts in Chaiyaphum province. Participants (N = 1,010) participating in the processes of model development were comprised of 3 groups: a) a total of 110 health care professionals, b) a total of 600 health volunteers and family caregivers and c) a total of 300 the elderly dependent with chronically medical illnesses or disabilities. Descriptive statistics and content analysis were used to analyze data. Findings: Results have shown that the most common health problems among elders dependent with physical disabilities to function independently were cardiovascular disease, dementia, and traffic injuries. The development of home-based long term care model among elders dependent in Chaiyaphum province was composed of six key steps. They are: a) initiating policies supporting formal and informal caregivers for the elder dependent in all sub-districts, b) building network and multidisciplinary team, c) developing 3-day care manager training program and 3-day care provider training program d) training case managers and care providers for the elderly dependent through team and action learning, e) assessing, planning and providing care based on care individual’s needs of the elderly dependent, and f) sharing experiences for good practice and innovation for long term care at homes in district urban and rural areas. Among all care managers and care providers, the satisfaction level for training programs was high with a mean score of 3.98 out of 5. The elders dependent and family caregivers addressed that long term care at home could contribute to improving life’s daily activities, family relationship, health status, and quality of life. Family caregivers and volunteers have feeling a sense of personal satisfaction and experiencing providing meaningful care and support for elders dependent. Conclusion: In conclusion, a home-based long term care is important to Thai elders dependent. Care managers and care providers play a large role and responsibility to provide appropriate care to meet the elders’ needs in both urban and rural areas in Thai society. Further research could be rigorously studied with a larger group of populations in similar socio-economic and cultural contexts.

Keywords: elderly people, care manager, care provider, long term care

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3538 Mathematical Modelling of Bacterial Growth in Products of Animal Origin in Storage and Transport: Effects of Temperature, Use of Bacteriocins and pH Level

Authors: Benjamin Castillo, Luis Pastenes, Fernando Cordova

Abstract:

The pathogen growth in animal source foods is a common problem in the food industry, causing monetary losses due to the spoiling of products or food intoxication outbreaks in the community. In this sense, the quality of the product is reflected by the population of deteriorating agents present in it, which are mainly bacteria. The factors which are likely associated with freshness in animal source foods are temperature and processing, storage, and transport times. However, the level of deterioration of products depends, in turn, on the characteristics of the bacterial population, causing the decomposition or spoiling, such as pH level and toxins. Knowing the growth dynamics of the agents that are involved in product contamination allows the monitoring for more efficient processing. This means better quality and reasonable costs, along with a better estimation of necessary time and temperature intervals for transport and storage in order to preserve product quality. The objective of this project is to design a secondary model that allows measuring the impact on temperature bacterial growth and the competition for pH adequacy and release of bacteriocins in order to describe such phenomenon and, thus, estimate food product half-life with the least possible risk of deterioration or spoiling. In order to achieve this objective, the authors propose an analysis of a three-dimensional ordinary differential which includes; logistic bacterial growth extended by the inhibitory action of bacteriocins including the effect of the medium pH; change in the medium pH levels through an adaptation of the Luedeking-Piret kinetic model; Bacteriocin concentration modeled similarly to pH levels. These three dimensions are being influenced by the temperature at all times. Then, this differential system is expanded, taking into consideration the variable temperature and the concentration of pulsed bacteriocins, which represent characteristics inherent of the modeling, such as transport and storage, as well as the incorporation of substances that inhibit bacterial growth. The main results lead to the fact that temperature changes in an early stage of transport increased the bacterial population significantly more than if it had increased during the final stage. On the other hand, the incorporation of bacteriocins, as in other investigations, proved to be efficient in the short and medium-term since, although the population of bacteria decreased, once the bacteriocins were depleted or degraded over time, the bacteria eventually returned to their regular growth rate. The efficacy of the bacteriocins at low temperatures decreased slightly, which equates with the fact that their natural degradation rate also decreased. In summary, the implementation of the mathematical model allowed the simulation of a set of possible bacteria present in animal based products, along with their properties, in various transport and storage situations, which led us to state that for inhibiting bacterial growth, the optimum is complementary low constant temperatures and the initial use of bacteriocins.

Keywords: bacterial growth, bacteriocins, mathematical modelling, temperature

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3537 Analysis of Economic Development Challenges of Rapid Population Growth in Nigeria: Way Forward

Authors: Sabiu Abdullahi Yau

Abstract:

Nigeria is a high fertility country that experiences eye-popping population growth, with no end in sight. However, there is evidence that its large population inhibits government’s efforts in meeting the basic needs of the people. Moreover, past and present governments of Nigeria have been committing huge amount of financial resources to meet the basic infrastructural requirements capable of propelling growth and development. Despite the country’s large population and abundant natural resources, poverty, unemployment, rural-urban migration, deforestation and inadequate infrastructural facilities have been persistently on the increase resulting in consistent failure of government policies to impact positively on the economy. This paper, however, identifies and critically analyses the major development challenges caused by population growth in Nigeria using secondary data. The paper concludes that for the Nigeria’s economy to develop, all the identified challenges posed by rapid population growth must be promptly and squarely addressed.

Keywords: economic development, population, growth, Nigeria

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3536 Development and Evaluation of Economical Self-cleaning Cement

Authors: Anil Saini, Jatinder Kumar Ratan

Abstract:

Now a day, the key issue for the scientific community is to devise the innovative technologies for sustainable control of urban pollution. In urban cities, a large surface area of the masonry structures, buildings, and pavements is exposed to the open environment, which may be utilized for the control of air pollution, if it is built from the photocatalytically active cement-based constructional materials such as concrete, mortars, paints, and blocks, etc. The photocatalytically active cement is formulated by incorporating a photocatalyst in the cement matrix, and such cement is generally known as self-cleaning cement In the literature, self-cleaning cement has been synthesized by incorporating nanosized-TiO₂ (n-TiO₂) as a photocatalyst in the formulation of the cement. However, the utilization of n-TiO₂ for the formulation of self-cleaning cement has the drawbacks of nano-toxicity, higher cost, and agglomeration as far as the commercial production and applications are concerned. The use of microsized-TiO₂ (m-TiO₂) in place of n-TiO₂ for the commercial manufacture of self-cleaning cement could avoid the above-mentioned problems. However, m-TiO₂ is less photocatalytically active as compared to n- TiO₂ due to smaller surface area, higher band gap, and increased recombination rate. As such, the use of m-TiO₂ in the formulation of self-cleaning cement may lead to a reduction in photocatalytic activity, thus, reducing the self-cleaning, depolluting, and antimicrobial abilities of the resultant cement material. So improvement in the photoactivity of m-TiO₂ based self-cleaning cement is the key issue for its practical applications in the present scenario. The current work proposes the use of surface-fluorinated m-TiO₂ for the formulation of self-cleaning cement to enhance its photocatalytic activity. The calcined dolomite, a constructional material, has also been utilized as co-adsorbent along with the surface-fluorinated m-TiO₂ in the formulation of self-cleaning cement to enhance the photocatalytic performance. The surface-fluorinated m-TiO₂, calcined dolomite, and the formulated self-cleaning cement were characterized using diffuse reflectance spectroscopy (DRS), X-ray diffraction analysis (XRD), field emission-scanning electron microscopy (FE-SEM), energy dispersive x-ray spectroscopy (EDS), X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), BET (Brunauer–Emmett–Teller) surface area, and energy dispersive X-ray fluorescence spectrometry (EDXRF). The self-cleaning property of the as-prepared self-cleaning cement was evaluated using the methylene blue (MB) test. The depolluting ability of the formulated self-cleaning cement was assessed through a continuous NOX removal test. The antimicrobial activity of the self-cleaning cement was appraised using the method of the zone of inhibition. The as-prepared self-cleaning cement obtained by uniform mixing of 87% clinker, 10% calcined dolomite, and 3% surface-fluorinated m-TiO₂ showed a remarkable self-cleaning property by providing 53.9% degradation of the coated MB dye. The self-cleaning cement also depicted a noteworthy depolluting ability by removing 5.5% of NOx from the air. The inactivation of B. subtiltis bacteria in the presence of light confirmed the significant antimicrobial property of the formulated self-cleaning cement. The self-cleaning, depolluting, and antimicrobial results are attributed to the synergetic effect of surface-fluorinated m-TiO₂ and calcined dolomite in the cement matrix. The present study opens an idea and route for further research for acile and economical formulation of self-cleaning cement.

Keywords: microsized-titanium dioxide (m-TiO₂), self-cleaning cement, photocatalysis, surface-fluorination

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3535 Suburbia Beyond Housing: Supporting Community Through Social Connection, Identity, and Adaptability in the Modern Suburb

Authors: Alex Lundy

Abstract:

As the suburban landscape has evolved over time, it has been slowly stripped down to the absolute bare essentials of housing. This has resulted in the loss of core elements of the built environment which previously supported community no longer being present in most neighborhoods. As a result, this work will explore how current and past designers have successfully introduced these concepts in similar settings, in an effort to re-implement them into the contemporary subdivision. Ultimately, this will result in a reimagining suburban design through elements like identity, adaptability, place, and social spaces to improve community interaction and cohesion. Overall, this thesis asserts that contemporary subdivisions don’t support the growing need for community in daily life and should be improved through the implementation of historical neighborhood design and select modern urban concepts to better suit living needs.

Keywords: suburbia, community, social connection, identity, adaptability, neighborhood, place, unity, leasure, social ties, third place, learning from history

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3534 Continuous-Time and Discrete-Time Singular Value Decomposition of an Impulse Response Function

Authors: Rogelio Luck, Yucheng Liu

Abstract:

This paper proposes the continuous-time singular value decomposition (SVD) for the impulse response function, a special kind of Green’s functions e⁻⁽ᵗ⁻ ᵀ⁾, in order to find a set of singular functions and singular values so that the convolutions of such function with the set of singular functions on a specified domain are the solutions to the inhomogeneous differential equations for those singular functions. A numerical example was illustrated to verify the proposed method. Besides the continuous-time SVD, a discrete-time SVD is also presented for the impulse response function, which is modeled using a Toeplitz matrix in the discrete system. The proposed method has broad applications in signal processing, dynamic system analysis, acoustic analysis, thermal analysis, as well as macroeconomic modeling.

Keywords: singular value decomposition, impulse response function, Green’s function , Toeplitz matrix , Hankel matrix

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3533 Welfare State and Income Distribution to School-Age Children

Authors: Kanyarat Bussaban, Siriporn Poolsuwan

Abstract:

This study is conducted with the objective to prove how the distorted distribution of welfare affects the quality of school-age children lives differently in the case of an urban community in Bangkok. 334 samples are households from Suan Oi and Ratchapatubtim communities. The study of sample communities found the difference between two community areas that are close. The people of Suan Oi community are economically better off people than the people of the Ratchapatubtim community. They share the benefits of using most services except the welfare of a child’s education. The resulting analysis of the variability in quality of life of the school age children indicate that heads of the households are women looking for quality of life benefits when the compulsory school age is less. A study of the two communities suggests that the inequality in income distribution currently affects the quality of life of school-age children.

Keywords: inequality, income distribution, quality of school-age children lives, welfare state

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3532 Statistical Physics Model of Seismic Activation Preceding a Major Earthquake

Authors: Daniel S. Brox

Abstract:

Starting from earthquake fault dynamic equations, a correspondence between earthquake occurrence statistics in a seismic region before a major earthquake and eigenvalue statistics of a differential operator whose bound state eigenfunctions characterize the distribution of stress in the seismic region is derived. Modeling these eigenvalue statistics with a 2D Coulomb gas statistical physics model, previously reported deviation of seismic activation earthquake occurrence statistics from Gutenberg-Richter statistics in time intervals preceding the major earthquake is derived. It also explains how statistical physics modeling predicts a finite-dimensional nonlinear dynamic system that describes real-time velocity model evolution in the region undergoing seismic activation and how this prediction can be tested experimentally.

Keywords: seismic activation, statistical physics, geodynamics, signal processing

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3531 Premarital Sex, HIV and Use of Condom among Youths in Nigeria

Authors: Okechukwu Odinaka Ajaegbu

Abstract:

In the recent past, discussing about sex among children and youths was frowned at by traditional norms and as such sexual discussions and behavior were approached with great respect. Things are actually falling apart with the increasing number of young people that engage in premarital sex. Due to lack of experience and sex education, many young people are becoming increasingly exposed to the risk of HIV infection. In the light of the above, this study discussed premarital sex, HIV and use of condom among youths in Nigeria. Data for this study came from 2013 Nigeria Demographic and Health Survey and other secondary data. The survey revealed that only 18.5 percent of young women that had sex in the 12 months preceding the survey used condom. Out of 3306 never-married sexually active men and women, 1728 representing 52 percent live in urban areas and 43 percent of them did not use condom during sexual intercourse in the 12 months preceding the survey. This study concludes that for there to be reduction in prevalence of HIV/AIDS among Nigerian youths, there is need for concerted effort to be made towards educating youths on the expedient of the use of condom during sexual intercourse.

Keywords: condom, HIV, Nigeria, premarital sex, youths

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3530 Contrast Enhancement of Masses in Mammograms Using Multiscale Morphology

Authors: Amit Kamra, V. K. Jain, Pragya

Abstract:

Mammography is widely used technique for breast cancer screening. There are various other techniques for breast cancer screening but mammography is the most reliable and effective technique. The images obtained through mammography are of low contrast which causes problem for the radiologists to interpret. Hence, a high quality image is mandatory for the processing of the image for extracting any kind of information from it. Many contrast enhancement algorithms have been developed over the years. In the present work, an efficient morphology based technique is proposed for contrast enhancement of masses in mammographic images. The proposed method is based on Multiscale Morphology and it takes into consideration the scale of the structuring element. The proposed method is compared with other state-of-the-art techniques. The experimental results show that the proposed method is better both qualitatively and quantitatively than the other standard contrast enhancement techniques.

Keywords: enhancement, mammography, multi-scale, mathematical morphology

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3529 Searching Linguistic Synonyms through Parts of Speech Tagging

Authors: Faiza Hussain, Usman Qamar

Abstract:

Synonym-based searching is recognized to be a complicated problem as text mining from unstructured data of web is challenging. Finding useful information which matches user need from bulk of web pages is a cumbersome task. In this paper, a novel and practical synonym retrieval technique is proposed for addressing this problem. For replacement of semantics, user intent is taken into consideration to realize the technique. Parts-of-Speech tagging is applied for pattern generation of the query and a thesaurus for this experiment was formed and used. Comparison with Non-Context Based Searching, Context Based searching proved to be a more efficient approach while dealing with linguistic semantics. This approach is very beneficial in doing intent based searching. Finally, results and future dimensions are presented.

Keywords: natural language processing, text mining, information retrieval, parts-of-speech tagging, grammar, semantics

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3528 Mathematical Modeling of Carotenoids and Polyphenols Content of Faba Beans (Vicia faba L.) during Microwave Treatments

Authors: Ridha Fethi Mechlouch, Ahlem Ayadi, Ammar Ben Brahim

Abstract:

Given the importance of the preservation of polyphenols and carotenoids during thermal processing, we attempted in this study to investigate the variation of these two parameters in faba beans during microwave treatment using different power densities (1; 2; and 3W/g), then to perform a mathematical modeling by using non-linear regression analysis to evaluate the models constants. The variation of the carotenoids and polyphenols ratio of faba beans and the models are tested to validate the experimental results. Exponential models were found to be suitable to describe the variation of caratenoid ratio (R²= 0.945, 0.927 and 0.946) for power densities (1; 2; and 3W/g) respectively, and polyphenol ratio (R²= 0.931, 0.989 and 0.982) for power densities (1; 2; and 3W/g) respectively. The effect of microwave power density Pd(W/g) on the coefficient k of models were also investigated. The coefficient is highly correlated (R² = 1) and can be expressed as a polynomial function.

Keywords: microwave treatment, power density, carotenoid, polyphenol, modeling

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3527 Development of Ferrous-Aluminum Alloys from Recyclable Material by High Energy Milling

Authors: Arnold S. Freitas Neto, Rodrigo E. Coelho, Erick S. Mendonça

Abstract:

This study aimed to obtain an alloy of Iron and Aluminum in the proportion of 50% of atomicity for each constituent. Alloys were obtained by processing recycled aluminum and chips of 1200 series carbon steel in a high-energy mill. For the experiment, raw materials were processed thorough high energy milling before mixing the substances. Subsequently, the mixture of 1200 series carbon steel and Aluminum powder was carried out a milling process. Thereafter, hot compression was performed in a closed die in order to obtain the samples. The pieces underwent heat treatments, sintering and aging. Lastly, the composition and the mechanical properties of their hardness were analyzed. In this paper, results are compared with previous studies, which used iron powder of high purity instead of Carbon steel in the composition.

Keywords: Fe-Al alloys, high energy milling, metallography characterization, powder metallurgy

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3526 Hit-Or-Miss Transform as a Tool for Similar Shape Detection

Authors: Osama Mohamed Elrajubi, Idris El-Feghi, Mohamed Abu Baker Saghayer

Abstract:

This paper describes an identification of specific shapes within binary images using the morphological Hit-or-Miss Transform (HMT). Hit-or-Miss transform is a general binary morphological operation that can be used in searching of particular patterns of foreground and background pixels in an image. It is actually a basic operation of binary morphology since almost all other binary morphological operators are derived from it. The input of this method is a binary image and a structuring element (a template which will be searched in a binary image) while the output is another binary image. In this paper a modification of Hit-or-Miss transform has been proposed. The accuracy of algorithm is adjusted according to the similarity of the template and the sought template. The implementation of this method has been done by C language. The algorithm has been tested on several images and the results have shown that this new method can be used for similar shape detection.

Keywords: hit-or-miss operator transform, HMT, binary morphological operation, shape detection, binary images processing

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3525 A Custom Convolutional Neural Network with Hue, Saturation, Value Color for Malaria Classification

Authors: Ghazala Hcini, Imen Jdey, Hela Ltifi

Abstract:

Malaria disease should be considered and handled as a potential restorative catastrophe. One of the most challenging tasks in the field of microscopy image processing is due to differences in test design and vulnerability of cell classifications. In this article, we focused on applying deep learning to classify patients by identifying images of infected and uninfected cells. We performed multiple forms, counting a classification approach using the Hue, Saturation, Value (HSV) color space. HSV is used since of its superior ability to speak to image brightness; at long last, for classification, a convolutional neural network (CNN) architecture is created. Clusters of focus were used to deliver the classification. The highlights got to be forbidden, and a few more clamor sorts are included in the information. The suggested method has a precision of 99.79%, a recall value of 99.55%, and provides 99.96% accuracy.

Keywords: deep learning, convolutional neural network, image classification, color transformation, HSV color, malaria diagnosis, malaria cells images

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3524 Human Posture Estimation Based on Multiple Viewpoints

Authors: Jiahe Liu, HongyangYu, Feng Qian, Miao Luo

Abstract:

This study aimed to address the problem of improving the confidence of key points by fusing multi-view information, thereby estimating human posture more accurately. We first obtained multi-view image information and then used the MvP algorithm to fuse this multi-view information together to obtain a set of high-confidence human key points. We used these as the input for the Spatio-Temporal Graph Convolution (ST-GCN). ST-GCN is a deep learning model used for processing spatio-temporal data, which can effectively capture spatio-temporal relationships in video sequences. By using the MvP algorithm to fuse multi-view information and inputting it into the spatio-temporal graph convolution model, this study provides an effective method to improve the accuracy of human posture estimation and provides strong support for further research and application in related fields.

Keywords: multi-view, pose estimation, ST-GCN, joint fusion

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3523 Computational Analysis on Thermal Performance of Chip Package in Electro-Optical Device

Authors: Long Kim Vu

Abstract:

The central processing unit in Electro-Optical devices is a Field-programmable gate array (FPGA) chip package allowing flexible, reconfigurable computing but energy consumption. Because chip package is placed in isolated devices based on IP67 waterproof standard, there is no air circulation and the heat dissipation is a challenge. In this paper, the author successfully modeled a chip package which various interposer materials such as silicon, glass and organics. Computational fluid dynamics (CFD) was utilized to analyze the thermal performance of chip package in the case of considering comprehensive heat transfer modes: conduction, convection and radiation, which proposes equivalent heat dissipation. The logic chip temperature varying with time is compared between the simulation and experiment results showing the excellent correlation, proving the reasonable chip modeling and simulation method.

Keywords: CFD, FPGA, heat transfer, thermal analysis

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3522 Post Growth Annealing Effect on Deep Level Emission and Raman Spectra of Hydrothermally Grown ZnO Nanorods Assisted by KMnO4

Authors: Ashish Kumar, Tejendra Dixit, I. A. Palani, Vipul Singh

Abstract:

Zinc oxide, with its interesting properties such as large band gap (3.37eV), high exciton binding energy (60 meV) and intense UV absorption has been studied in literature for various applications viz. optoelectronics, biosensors, UV-photodetectors etc. The performance of ZnO devices is highly influenced by morphologies, size, crystallinity of the ZnO active layer and processing conditions. Recently, our group has shown the influence of the in situ addition of KMnO4 in the precursor solution during the hydrothermal growth of ZnO nanorods (NRs) on their near band edge (NBE) emission. In this paper, we have investigated the effect of post-growth annealing on the variations in NBE and deep level (DL) emissions of as grown ZnO nanorods. These observed results have been explained on the basis of X-ray Diffraction (XRD) and Raman spectroscopic analysis, which clearly show that improved crystalinity and quantum confinement in ZnO nanorods.

Keywords: ZnO, nanorods, hydrothermal, KMnO4

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3521 Precise Determination of the Residual Stress Gradient in Composite Laminates Using a Configurable Numerical-Experimental Coupling Based on the Incremental Hole Drilling Method

Authors: A. S. Ibrahim Mamane, S. Giljean, M.-J. Pac, G. L’Hostis

Abstract:

Fiber reinforced composite laminates are particularly subject to residual stresses due to their heterogeneity and the complex chemical, mechanical and thermal mechanisms that occur during their processing. Residual stresses are now well known to cause damage accumulation, shape instability, and behavior disturbance in composite parts. Many works exist in the literature on techniques for minimizing residual stresses in thermosetting and thermoplastic composites mainly. To study in-depth the influence of processing mechanisms on the formation of residual stresses and to minimize them by establishing a reliable correlation, it is essential to be able to measure very precisely the profile of residual stresses in the composite. Residual stresses are important data to consider when sizing composite parts and predicting their behavior. The incremental hole drilling is very effective in measuring the gradient of residual stresses in composite laminates. This method is semi-destructive and consists of drilling incrementally a hole through the thickness of the material and measuring relaxation strains around the hole for each increment using three strain gauges. These strains are then converted into residual stresses using a matrix of coefficients. These coefficients, called calibration coefficients, depending on the diameter of the hole and the dimensions of the gauges used. The reliability of the incremental hole drilling depends on the accuracy with which the calibration coefficients are determined. These coefficients are calculated using a finite element model. The samples’ features and the experimental conditions must be considered in the simulation. Any mismatch can lead to inadequate calibration coefficients, thus introducing errors on residual stresses. Several calibration coefficient correction methods exist for isotropic material, but there is a lack of information on this subject concerning composite laminates. In this work, a Python program was developed to automatically generate the adequate finite element model. This model allowed us to perform a parametric study to assess the influence of experimental errors on the calibration coefficients. The results highlighted the sensitivity of the calibration coefficients to the considered errors and gave an order of magnitude of the precisions required on the experimental device to have reliable measurements. On the basis of these results, improvements were proposed on the experimental device. Furthermore, a numerical method was proposed to correct the calibration coefficients for different types of materials, including thick composite parts for which the analytical approach is too complex. This method consists of taking into account the experimental errors in the simulation. Accurate measurement of the experimental errors (such as eccentricity of the hole, angular deviation of the gauges from their theoretical position, or errors on increment depth) is therefore necessary. The aim is to determine more precisely the residual stresses and to expand the validity domain of the incremental hole drilling technique.

Keywords: fiber reinforced composites, finite element simulation, incremental hole drilling method, numerical correction of the calibration coefficients, residual stresses

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3520 Municipal Solid Waste Management in Ethiopia: Systematic Review of Physical and Chemical Compositions and Generation Rate

Authors: Tsegay Kahsay Gebrekidan, Gebremariam Gebrezgabher Gebremedhin, Abraha Kahsay Weldemariam, Meaza Kidane Teferi

Abstract:

Municipal solid waste management (MSWM) in Ethiopia is a complex issue with institutional, social, political, environmental, and economic dimensions, impacting sustainable development. Effective MSWM planning necessitates understanding the generation rate and composition of waste. This systematic review synthesizes qualitative and quantitative data from various sources to aggregate current knowledge, identify gaps, and provide a comprehensive understanding of municipal solid waste management in Ethiopia. The findings reveal that the generation rate of municipal solid waste in Ethiopia is 0.38 kg/ca/day, with the waste composition being predominantly food waste, followed by ash, dust, and sand, and yard waste. Over 85% of this MSW is either reusable or recyclable, with a significant portion being organic matter (73.13% biodegradable) and 11.78% recyclable materials. Physicochemical analyses reveal that Ethiopian MSW is suitable for composting and biogas production, offering opportunities to reduce environmental pollution, and GHGs, support urban agriculture, and create job opportunities. However; challenges persist, including a lack of political will, weak municipal planning, limited community awareness, and inadequate waste management infrastructure, and only 31.8% of MSW is collected legally, leading to inefficient and harmful disposal practices. To improve MSWM, Ethiopia should focus on public awareness; increased funding, infrastructure investment, private sector partnerships, and implementing the 4 R principles (reduce, reuse, and recycle). An integrated approach involving government, industry, and civil society is essential. Further research on the physicochemical properties and strategic uses of MSW is needed to enhance management practices. Implications: The comprehensive study of municipal solid waste management (MSWM) in Ethiopia reveals the intricate interplay of institutional, social, political, environmental, and economic factors that influence the nation’s sustainable development. The findings underscore the urgent need for tailored, integrated waste management strategies that are informed by a thorough understanding of MSW generation rates, composition, and current management practices. Ethiopia’s lower per capita MSW generation compared to developed countries and the predominantly organic composition of its waste present significant opportunities for sustainable waste management practices such as composting and recycling. These practices can not only minimize the environmental impact but also support urban greening, agriculture, and renewable energy production. The high organic content, suitable physicochemical properties of MSW for composting, and potential for biogas and briquette production highlight pathways for creating employment, reducing waste, and enhancing soil fertility. Despite these opportunities, Ethiopia faces substantial challenges due to inadequate political will, weak municipal planning, limited community awareness, insufficient waste management infrastructure, and poor policy implementation. The high rate of illegal waste disposal further exacerbates environmental and health issues, emphasizing the need for a more effective and integrated MSWM approach. To address these challenges and harness the potential of MSW, Ethiopia must prioritize increasing public awareness; investing in infrastructure, fostering private sector partnerships, and implementing the principles of reduce, reuse, and recycle (3 R). Developing strategies that involve all stakeholders and turning waste into valuable resources is crucial. Government, industry, and civil society must collaborate to implement integrated MSWM systems that focus on waste reduction at the source, alternative material use, and advanced recycling technologies. Further research at both federal and regional levels is essential to optimize the physicochemical analysis and strategic use of MSW. Prompt action is required to transform waste management into a pillar of sustainable urban development, ultimately improving environmental quality and human health in Ethiopia.

Keywords: biodegradable, healthy environment, integrated solid waste management, municipal

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3519 Level Set and Morphological Operation Techniques in Application of Dental Image Segmentation

Authors: Abdolvahab Ehsani Rad, Mohd Shafry Mohd Rahim, Alireza Norouzi

Abstract:

Medical image analysis is one of the great effects of computer image processing. There are several processes to analysis the medical images which the segmentation process is one of the challenging and most important step. In this paper the segmentation method proposed in order to segment the dental radiograph images. Thresholding method has been applied to simplify the images and to morphologically open binary image technique performed to eliminate the unnecessary regions on images. Furthermore, horizontal and vertical integral projection techniques used to extract the each individual tooth from radiograph images. Segmentation process has been done by applying the level set method on each extracted images. Nevertheless, the experiments results by 90% accuracy demonstrate that proposed method achieves high accuracy and promising result.

Keywords: integral production, level set method, morphological operation, segmentation

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3518 Research on Energy-Related Occupant Behavior of Residential Air Conditioning Based on Zigbee Intelligent Electronic Equipment

Authors: Dawei Xia, Benyan Jiang, Yong Li

Abstract:

Split-type air conditioners is widely used for indoor temperature regulation in urban residential buildings in summer in China. The energy-related occupant behavior has a great impact on building energy consumption. Obtaining the energy-related occupant behavior data of air conditioners is the research basis for the energy consumption prediction and simulation. Relying on the development of sensing and control technology, this paper selects Zigbee intelligent electronic equipment to monitor the energy-related occupant behavior of 20 households for 3 months in summer. Through analysis of data, it is found that people of different ages in the region have significant difference in the time, duration, frequency, and energy consumption of air conditioners, and form a data model of three basic energy-related occupant behavior patterns to provide an accurate simulation of energy.

Keywords: occupant behavior, Zigbee, split air conditioner, energy simulation

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3517 Long Memory and ARFIMA Modelling: The Case of CPI Inflation for Ghana and South Africa

Authors: A. Boateng, La Gil-Alana, M. Lesaoana; Hj. Siweya, A. Belete

Abstract:

This study examines long memory or long-range dependence in the CPI inflation rates of Ghana and South Africa using Whittle methods and autoregressive fractionally integrated moving average (ARFIMA) models. Standard I(0)/I(1) methods such as Augmented Dickey-Fuller (ADF), Philips-Perron (PP) and Kwiatkowski–Phillips–Schmidt–Shin (KPSS) tests were also employed. Our findings indicate that long memory exists in the CPI inflation rates of both countries. After processing fractional differencing and determining the short memory components, the models were specified as ARFIMA (4,0.35,2) and ARFIMA (3,0.49,3) respectively for Ghana and South Africa. Consequently, the CPI inflation rates of both countries are fractionally integrated and mean reverting. The implication of this result will assist in policy formulation and identification of inflationary pressures in an economy.

Keywords: Consumer Price Index (CPI) inflation rates, Whittle method, long memory, ARFIMA model

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3516 Estimating City-Level Rooftop Rainwater Harvesting Potential with a Focus on Sustainability

Authors: Priya Madhuri P., Kamini J., Jayanthi S. C.

Abstract:

Rooftop rainwater harvesting is a crucial practice to address water scarcity, pollution, and flooding. This study aims to estimate the rooftop rainwater harvesting potential (RRWHP) for Suryapet, India, using building footprint data and average rainfall data. The study uses rainfall grids from the India Meteorological Department and Very High Resolution Satellite data to capture building footprints and calculate the RRWHP for a five-year period (2015-2020). Buildings with an area of more than 20 square meters are considered. A conservative figure of 60% efficiency for the catchment area is considered. The study chose 31,770 buildings with an effective rooftop area of around 1.56 sq. km. The city experiences annual rainfall values ranging from 791 mm to 987 mm, with August being the wettest month. The projected annual rooftop rainwater harvesting potential is 1.3 billion litres.

Keywords: buildings, rooftop rainwater harvesting, sustainable water management, urban

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3515 Tamper Resistance Evaluation Tests with Noise Resources

Authors: Masaya Yoshikawa, Toshiya Asai, Ryoma Matsuhisa, Yusuke Nozaki, Kensaku Asahi

Abstract:

Recently, side-channel attacks, which estimate secret keys using side-channel information such as power consumption and compromising emanations of cryptography circuits embedded in hardware, have become a serious problem. In particular, electromagnetic analysis attacks against cryptographic circuits between information processing and electromagnetic fields, which are related to secret keys in cryptography circuits, are the most threatening side-channel attacks. Therefore, it is important to evaluate tamper resistance against electromagnetic analysis attacks for cryptography circuits. The present study performs basic examination of the tamper resistance of cryptography circuits using electromagnetic analysis attacks with noise resources.

Keywords: tamper resistance, cryptographic circuit, hardware security evaluation, noise resources

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3514 Contextual Toxicity Detection with Data Augmentation

Authors: Julia Ive, Lucia Specia

Abstract:

Understanding and detecting toxicity is an important problem to support safer human interactions online. Our work focuses on the important problem of contextual toxicity detection, where automated classifiers are tasked with determining whether a short textual segment (usually a sentence) is toxic within its conversational context. We use “toxicity” as an umbrella term to denote a number of variants commonly named in the literature, including hate, abuse, offence, among others. Detecting toxicity in context is a non-trivial problem and has been addressed by very few previous studies. These previous studies have analysed the influence of conversational context in human perception of toxicity in controlled experiments and concluded that humans rarely change their judgements in the presence of context. They have also evaluated contextual detection models based on state-of-the-art Deep Learning and Natural Language Processing (NLP) techniques. Counterintuitively, they reached the general conclusion that computational models tend to suffer performance degradation in the presence of context. We challenge these empirical observations by devising better contextual predictive models that also rely on NLP data augmentation techniques to create larger and better data. In our study, we start by further analysing the human perception of toxicity in conversational data (i.e., tweets), in the absence versus presence of context, in this case, previous tweets in the same conversational thread. We observed that the conclusions of previous work on human perception are mainly due to data issues: The contextual data available does not provide sufficient evidence that context is indeed important (even for humans). The data problem is common in current toxicity datasets: cases labelled as toxic are either obviously toxic (i.e., overt toxicity with swear, racist, etc. words), and thus context does is not needed for a decision, or are ambiguous, vague or unclear even in the presence of context; in addition, the data contains labeling inconsistencies. To address this problem, we propose to automatically generate contextual samples where toxicity is not obvious (i.e., covert cases) without context or where different contexts can lead to different toxicity judgements for the same tweet. We generate toxic and non-toxic utterances conditioned on the context or on target tweets using a range of techniques for controlled text generation(e.g., Generative Adversarial Networks and steering techniques). On the contextual detection models, we posit that their poor performance is due to limitations on both of the data they are trained on (same problems stated above) and the architectures they use, which are not able to leverage context in effective ways. To improve on that, we propose text classification architectures that take the hierarchy of conversational utterances into account. In experiments benchmarking ours against previous models on existing and automatically generated data, we show that both data and architectural choices are very important. Our model achieves substantial performance improvements as compared to the baselines that are non-contextual or contextual but agnostic of the conversation structure.

Keywords: contextual toxicity detection, data augmentation, hierarchical text classification models, natural language processing

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3513 Natural Hazards and Their Costs in Albanian Part of Ohrid Graben

Authors: Mentor Sulollari

Abstract:

Albania, according to (UNU-EHS) United Nations University, Institute for Environment and Human Security studies for 2015, is listed as the number one country in Europe for the possibility to be caught by natural catastrophes. This is conditioned by unstudied human activity, which has seriously damaged the environment. Albanian part of Ohrid graben that lies in Southeast of Albania, is endangered by landslides and floods, as a result of uncontrolled urban development and low level of investment in infrastructure, rugged terrain in its western part and capricious climate caused by global warming. To be dealt with natural disasters, which cause casualties and material damage, it is important to study them in order to anticipate and reduce damages in future. As part of this study is the construction of natural hazards map, which show us where they are distributed, and which are the vulnerable areas. This article will also be dealing with socio-economic and environmental costs of those events and what are the measures to be taken to reduce them.

Keywords: flooding, landslides, natural catastrophes mapping, Pogradec, lake Ohrid, Albanian part of Ohrid graben

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3512 Land Use Change Modeling Using Cellular Automata, Case Study: Karawang City, West Java Province, Indonesia

Authors: Bagus Indrawan Hardi

Abstract:

Cellular Automata are widely used in land use modeling, it has been proven powerful to simulate land use change for small scale in many large cities in the world. In this paper, we try to implement CA for land use modeling in unique city in Indonesia, Karawang. Instead the complex numerical implementation, CA are simple, and it is accurate and also highly dependable on the on the rules (rule based). The most important to do in CA is how we form and calculate the neighborhood effect. The neighborhood effect represents the environment and relationship situation between the occupied cell and others. We adopted 196 cells of circular neighborhood with 8 cells of radius. For the results, CA works well in this study, we exhibit several analyzed and proceed of zoomed part in Karawang region. The rule set can handle the complexity in land use modeling. However, we cannot strictly believe of the result, many non-technical parameters, such as politics, natural disaster activities, etc. may change the results dramatically.

Keywords: cellular automata (CA), land use change, spatial dynamics, urban sprawl

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3511 Removal of Iron (II) from Wastewater in Oil Field Using 3-(P-Methyl) Phenyl-5-Thionyl-1,2,4-Triazoline Assembled on Silver Nanoparticles

Authors: E. M. S. Azzam, S. A. Ahmed, H. H. Mohamed, M. A. Adly, E. A. M. Gad

Abstract:

In this work we prepared 3-(p-methyl) phenyl-5-thionyl-1,2,4-triazoline (C1). The nanostructure of the prepared C1 compound was fabricated by assembling on silver nanoparticles. The UV and TEM analyses confirm the assembling of C1 compound on silver nanoparticles. The effect of C1 compound on the removal of Iron (II) from Iron contaminated samples and industrial wastewater samples (produced water from oil processing facility) were studied before and after their assembling on silver nanoparticles. The removal of Iron was studied at different concentrations of FeSO4 solution (5, 14 and 39 mg/l) and field sample concentration (661 mg/l). In addition, the removal of Iron (II) was investigated at different times. The Prepared compound and its nanostructure with AgNPs show highly efficient in removing the Iron ions. Quantum chemical descriptors using DFT was discussed. The output of the study pronounces that the C1 molecule can act as chelating agent for Iron (II).

Keywords: triazole derivatives, silver nanoparticles, iron (II), oil field

Procedia PDF Downloads 658
3510 Learning Grammars for Detection of Disaster-Related Micro Events

Authors: Josef Steinberger, Vanni Zavarella, Hristo Tanev

Abstract:

Natural disasters cause tens of thousands of victims and massive material damages. We refer to all those events caused by natural disasters, such as damage on people, infrastructure, vehicles, services and resource supply, as micro events. This paper addresses the problem of micro - event detection in online media sources. We present a natural language grammar learning algorithm and apply it to online news. The algorithm in question is based on distributional clustering and detection of word collocations. We also explore the extraction of micro-events from social media and describe a Twitter mining robot, who uses combinations of keywords to detect tweets which talk about effects of disasters.

Keywords: online news, natural language processing, machine learning, event extraction, crisis computing, disaster effects, Twitter

Procedia PDF Downloads 478