Search results for: adjusted network

Authors: Veronica Botero, Karen Ortiz

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The Faculty of Mines, of the National University of Colombia, Medellín Campus, is a faculty that has 136 years of history and represents one of the most important study centers in the country in the field of engineering and scientific research, as well as a reference at a global, national, and Latin American level in this matter. Despite being a faculty with so many years of history and having trained a large number of graduates under the traditional mechanistic and androcentric paradigm, which reproduces the logic of the traditional scientific method and the differentiated and severe look between subject-object of research among other binarisms, has also been the place where professors and students have become aware of the need to transform this paradigm into engineering, and focus on the sustainability of diversity and the well-being of the natural and social systems that inhabit the territories and has opened possibilities for the implementation of classes that address feminist pedagogical theories and practices. The class: The return of the witches, is an initiative that constitutes an important training exercise that provides students with the study of feminisms, the importance of closing gender gaps and critical readings on the traditional paradigm of engineering. The objective of this article is to present a systematization of the experience of design, implementation and development of this elective class, describing the tensions that arose at the time when a subject of this style was created and proposed in the Department of Geosciences and Environment, from the Faculty of Mines in 2022; the reactions of the groups of students who have taken it and their perceptions and opinions about ecofeminism as proposals for critical analysis and practices in relation to the environment and, above all, how their readings of the world have changed after having studied this subject for a semester. The pedagogical journey and the feminist methodologies that have been designed and adjusted over two years of work will be explained based on the sharing of situated knowledge of the students and the two teachers who teach the course, who pose challenges to the dominant ideology in engineering since one of them is trained in human sciences and feminist studies and the other, although trained in civil engineering and geosciences, is a woman with diverse sexual orientation and is the first professor to have assumed the position of dean in the 135 years of history of the Faculty. The transformations in the life experience of the students are revealing since they affirm that the training process is forceful and powerful to outline a much more qualified and critical professional profile that contributes to the transformation of gender gaps in the country. This class is therefore a challenge in this Faculty of Engineering that still presents a dominant ideology on gender that has not been questioned or challenged before.

Keywords: feminisms, gender equality, gender bias, engineering for life Manifiesto.

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Authors: Kimuel Suyat, Francis Aldrine Uy, John Paul Carreon

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The Philippines, composed of many islands, is connected with approximately 8030 bridges. Continuous evaluation of the structural condition of these bridges is needed to safeguard the safety of the general public. With most bridges reaching its design life, retrofitting and replacement may be needed. Concerned government agencies allocate huge costs for periodic monitoring and maintenance of these structures. The rising volume of traffic and aging of these infrastructures is challenging structural engineers to give rise for structural health monitoring techniques. Numerous techniques are already proposed and some are now being employed in other countries. Vibration Analysis is one way. The natural frequency and vibration of a bridge are design criteria in ensuring the stability, safety and economy of the structure. Its natural frequency must not be so high so as not to cause discomfort and not so low that the structure is so stiff causing it to be both costly and heavy. It is well known that the stiffer the member is, the more load it attracts. The frequency must not also match the vibration caused by the traffic loads. If this happens, a resonance occurs. Vibration that matches a systems frequency will generate excitation and when this exceeds the member’s limit, a structural failure will happen. This study presents a method for calculating dynamic fragility through the use of vibration-based monitoring system. Dynamic fragility is the probability that a structural system exceeds a limit state when subjected to dynamic loads. The bridge is modeled in SAP2000 based from the available construction drawings provided by the Department of Public Works and Highways. It was verified and adjusted based from the actual condition of the bridge. The bridge design specifications are also checked using nondestructive tests. The approach used in this method properly accounts the uncertainty of observed values and code-based structural assumptions. The vibration response of the structure due to actual loads is monitored using installed sensors on the bridge. From the determinacy of these dynamic characteristic of a system, threshold criteria can be established and fragility curves can be estimated. This study conducted in relation with the research project between Department of Science and Technology, Mapúa Institute of Technology, and the Department of Public Works and Highways also known as Mapúa-DOST Smart Bridge Project deploys Structural Health Monitoring Sensors at Zamora Bridge. The bridge is selected in coordination with the Department of Public Works and Highways. The structural plans for the bridge are also readily available.

Keywords: structural health monitoring, dynamic characteristic, threshold criteria, traffic loads

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Authors: Mohanaad Talal Shakir, Saad AJAJ Khalaf, Nawar Ahmed Aljumaily, Mustafa Talal Shakere

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Cloud computing is a model for enabling convenient, on demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. Objectives of this paper are to investigate the role of the Enterprise System and Cloud Computing Services to assist and guide him to ensure the initiative become successful. The cloud computing technology offers great potential for Enterprise such as the speed of dealing with data and product introductions, innovations and speed of response. The use of cloud computing technology leads to the rapid development and competitiveness of enterprises in various fields.

Keywords: cloud computing, information management, marketing, enterprise systems

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Authors: P. Shrivastava, A. Shukla, K. Verma, S. Rungta

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Parkinson's disease is a chronic neurological disorder that directly affects human gait. It leads to slowness of movement, causes muscle rigidity and tremors. Gait serve as a primary outcome measure for studies aiming at early recognition of disease. Using gait techniques, this paper implements efficient binary bat algorithm for an early detection of Parkinson's disease by selecting optimal features required for classification of affected patients from others. The data of 166 people, both fit and affected is collected and optimal feature selection is done using PSO and Bat algorithm. The reduced dataset is then classified using neural network. The experiments indicate that binary bat algorithm outperforms traditional PSO and genetic algorithm and gives a fairly good recognition rate even with the reduced dataset.

Keywords: parkinson, gait, feature selection, bat algorithm

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Authors: M. Pilgun

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The report presents the results of a study of the specifics of speech perception by actors of video hosting services on the material of urban planning conflicts. To analyze the content, the multimodal approach using neural network technologies is employed. Analysis of word associations and associative networks of relevant stimulus revealed the evaluative reactions of the actors. Analysis of the data identified key topics that generated negative and positive perceptions from the participants. The calculation of social stress and social well-being indices based on user-generated content made it possible to build a rating of road transport construction objects according to the degree of negative and positive perception by actors.

Keywords: social media, speech perception, video hosting, networks

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Authors: Benalia Nadia, Bensiali Nadia, Zezouri Noura

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This paper studies the effects of voltage sags, both symmetrical and unsymmetrical, on the three-phase Synchronous Machine (SM) when powering an isolate load or infinite bus bar. The vast majority of the electrical power generation systems in the world is consist of synchronous generators coupled to the electrical network though a transformer. Voltage sags on SM cause speed variations, current and torque peaks and hence may cause tripping and equipment damage. The consequences of voltage sags in the machine behavior depends on different factors such as its magnitude (or depth), duration , the parameters of the machine and also the size of load. In this study, we consider the machine feeds an infinite bus bar in the first and the isolate load using symmetric and asymmetric defaults to see the behavior of the machine in both case the simulation have been used on SIMULINK MATLAB.

Keywords: power quality, voltage sag, synchronous generator, infinite system

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Authors: Zoltan Theisz, Gergely Mezei

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Modern industrial automation relies on service oriented concepts of Internet of Things (IoT) device modeling in order to provide a flexible and extendable environment for service meta-repository. However, state-of-the-art meta-modeling techniques prefer design-time modeling, which results in a heavy usage of class sometimes unnecessary static subtyping. Although this approach benefits from clear-cut object-oriented design principles, it also seals the model repository for further dynamic extensions. In this paper, a dynamic multi-level modeling approach is introduced that enables dynamic subtyping through a more relaxed partial instantiation mechanism. The approach is demonstrated on a simple sensor network example.

Keywords: meta-modeling, dynamic subtyping, DMLA, industrial automation, arrowhead

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Authors: Shazia Ali, Yves Mard, Éric Severin

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To the best of our knowledge, this is the first study to have analyzed the impact of a) firm-specific product-market power and b) industry competition on earnings management behavior of European firms in distress versus healthy years while controlling for firm-level characteristics. We predicted a significant relationship between firms’ product market power and earnings management tools and their trade-off under the moderation effect of financial distress. We found that the firm-level market power hereinafter referred to as MP (proxied by the industry-adjusted Lerner Index) is positively associated with both real and accrual earnings management. However, MP is associated with a higher level of real earnings management compared to accrual earnings management in distress years compared to healthy years. On the other hand, industry product market power (representing low competition and proxied by the inverse of the total number of firms in an industry hereinafter referred to as NUMB) and firms product market power (proxied by firm market share hereinafter referred to as MS) are associated with lower inflationary accruals and higher deflationary accruals respectively. On the other hand, they are found to be linked with higher real earnings management in distress versus healthy years. When we divided the sample into small and big firms based on their respective industry-year median total assets, we found that all three measures of industry competition (Industry Median Lerner Index (hereinafter referred to as IMLI), NUMB, and Herfindahl–Hirschman Index (hereinafter referred to as HHI) indicate that small firms in low-competitive industries in financial distress are more likely to inflate their earnings through discretionary accruals. While big firms in this situation are more likely to lower the use of both inflationary and deflationary discretionary accruals as indicated by IMLI and HHI and trade-off accruals earnings management for real earnings management as indicated by NUMB. Moreover, IMLI and HHI did not show any interesting results when we divided the sample based on the firm Lerner Index/Market Power. However, the distressed firms with high market power (MP>industry median) are found to engage in income-decreasing discretionary accruals in low-competitive industries (high NUMB). Whereas firms with low market power in the same industry use downward discretionary accruals but inflate income using real activities (abnCFO). Our findings are robust across alternate measures of discretionary accruals and financial distress, such as the Altman Z-Score. The finding of the study is valuable for accounting standard setters, competition authorities, policymakers, and investors alike to help in informed decision-making.

Keywords: financial distress, earnings management, market competition

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Authors: Reza Bazargan lari, Mohammad H. Fattahi

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Natural resources management including water resources requires reliable estimations of time variant environmental parameters. Small improvements in the estimation of environmental parameters would result in grate effects on managing decisions. Noise reduction using wavelet techniques is an effective approach for pre-processing of practical data sets. Predictability enhancement of the river flow time series are assessed using fractal approaches before and after applying wavelet based pre-processing. Time series correlation and persistency, the minimum sufficient length for training the predicting model and the maximum valid length of predictions were also investigated through a fractal assessment.

Keywords: wavelet, de-noising, predictability, time series fractal analysis, valid length, ANN

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Authors: Gaurav Shinde, Sai Charan Gongiguntla, Prajwal Shirur, Ahmed Hambaba

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Health issues are significantly increasing, putting a substantial strain on healthcare services. This has accelerated the integration of machine learning in healthcare, particularly following the COVID-19 pandemic. The utilization of machine learning in healthcare has grown significantly. We introduce DeClEx, a pipeline that ensures that data mirrors real-world settings by incorporating Gaussian noise and blur and employing autoencoders to learn intermediate feature representations. Subsequently, our convolutional neural network, paired with spatial attention, provides comparable accuracy to state-of-the-art pre-trained models while achieving a threefold improvement in training speed. Furthermore, we provide interpretable results using explainable AI techniques. We integrate denoising and deblurring, classification, and explainability in a single pipeline called DeClEx.

Keywords: machine learning, healthcare, classification, explainability

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Authors: André Pasti

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Historically, the communication sector in Argentina is characterized by intense monopolization and geographical concentration in the city of Buenos Aires. In 2000, the four major media conglomerates in operation – Clarín, Telefónica, America and Hadad – controlled 84% of the national media market. By 2009, new policies were implemented as a result of civil society organizations demands. Legally, a new regulatory framework was approved: the law 26,522 of Audiovisual Communications Services. Supposedly, these policies intend to create new conditions for the development of the audiovisual economy in the territory of Argentina. The regionalization of audiovisual production and the democratization of channels and access to media were among the priorities. This paper analyses the main changes and continuities in the organization of the spatial circuit of the audiovisual industry in Argentina provoked by these new policies. These new policies aim at increasing the diversity of audiovisual producers and promoting regional audiovisual industries. For this purpose, a national program for the development of audiovisual centers within the country was created. This program fostered a federalized production network, based on nine audiovisual regions and 40 nodes. Each node has created technical, financial and organizational conditions to gather different actors in audiovisual production – such as SMEs, social movements and local associations. The expansion of access to technical networks was also a concern of other policies, such as ‘Argentina connected’, whose objective was to expand access to broadband Internet. The Open Digital Television network also received considerable investments. Furthermore, measures have been carried out in order to impose limits on the concentration of ownership as well as to eliminate the oligopolies and to ensure more competition in the sector. These actions intended to force a divide of the media conglomerates into smaller groups. Nevertheless, the corporations that compose these conglomerates resist strongly, making full use of their economic and judiciary power. Indeed, the absence of effective impact of such measures can be testified by the fact that the audiovisual industry remains strongly concentrated in Argentina. Overall, these new policies were designed properly to decentralize audiovisual production and expand the regional diversity of the audiovisual industry. However, the effective transformation of the organization of the audiovisual circuit in the territory faced several resistances. This can be explained firstly and foremost by the ideological and economic power of the media conglomerates. In the second place, there is an inherited inertia from the unequal distribution of the objects needed for the audiovisual production and consumption. Lastly, the resistance also relies on financial needs and in the excessive dependence of the state for the promotion of regional audiovisual production.

Keywords: Argentina, audiovisual industry, communication policies, geographic concentration, regionalization, spatial circuit

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Authors: Khalid Salhi, El Miloud Jaara, Mohammed Talibi Alaoui

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In this paper, we present a neural approach for unsupervised natural color-texture image segmentation, which is based on both Kohonen maps and mathematical morphology, using a combination of the texture and the image color information of the image, namely, the fractal features based on fractal dimension are selected to present the information texture, and the color features presented in RGB color space. These features are then used to train the network Kohonen, which will be represented by the underlying probability density function, the segmentation of this map is made by morphological watershed transformation. The performance of our color-texture segmentation approach is compared first, to color-based methods or texture-based methods only, and then to k-means method.

Keywords: segmentation, color-texture, neural networks, fractal, watershed

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Authors: Amdy Moustapha Drame, Ilya V. Germashev, E. A. Markushevskaya

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Among the main problems of medicine is breast cancer, from which a significant number of women around the world are constantly dying. Therefore, the detection of malignant breast tumors is an urgent task. For many years, various technologies for detecting these tumors have been used, in particular, in thermal imaging in order to determine different levels of breast cancer development. These periodic screening methods are a diagnostic tool for women and may have become an alternative to older methods such as mammography. This article proposes a model for the identification of malignant neoplasms of the mammary glands by the asymmetry of internal and external thermal imaging fields.

Keywords: asymmetry, breast cancer, tumors, deep learning, thermogram, convolutional transformation, classification

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Authors: Muazzam A. Khan

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In order to avoid dangerous environmental disasters, robots are being recognized as good entrants to step in as human rescuers. Robots has been gaining interest of many researchers in rescue matters especially which are furnished with advanced sensors. In distributed wireless robot system main objective for a rescue system is to track the location of the object continuously. This paper provides a novel idea to track and locate human in disaster area using stereo vision system and ZigBee technology. This system recursively predict and updates 3D coordinates in a robot coordinate camera system of a human which makes the system cost effective. This system is comprised of ZigBee network which has many advantages such as low power consumption, self-healing low data rates and low cost.

Keywords: stereo vision, segmentation, classification, human tracking, ZigBee module

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Authors: Salman Ali Nisar, Koshi Suzuki

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Precedence Diagram Method (PDM) with its additional relationships i.e., start-to-start, finish-to-finish, and start-to-finish, between activities provides more flexible schedule than traditional Critical Path Method (CPM). But, changing the duration of critical activities in PDM network will have anomalous effect on critical path. Researchers have proposed some classification of critical activity effects. In this paper, we do further study on classifications of critical activity effect and provide more information in detailed. Furthermore, we determine the maximum amount of time for each class of critical activity effect by which the project managers can control the dynamic feature (shortening/lengthening) of critical activities and project duration more efficiently.

Keywords: construction project management, critical path method, project scheduling, precedence diagram method

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Authors: P. K. Guha Thakurta, Shouvik Roy, Bhawana Raj

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A congestion control scheme in mobile networks is proposed in this paper through a verification based model. The model proposed in this work is represented through performance metric like buffer Occupancy, latency and packet loss rate. Based on pre-defined values, each of the metric is introduced in terms of three different states. A Markov chain based model for the proposed work is introduced to monitor the occurrence of the corresponding state transitions. Thus, the estimation of the network status is obtained in terms of performance metric. In addition, the improved performance of our proposed model over existing works is shown with experimental results.

Keywords: congestion, mobile networks, buffer, delay, call drop, markov chain

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Authors: Olga Santesteban, Glorisa Canino, Hector R. Bird, Cristiane S. Duarte

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Objective: To address whether harsh discipline is associated with disruptive behavior disorders (DBD) in Puerto Rican children over time. Background: Both cross-sectional and longitudinal studies report that rates of DBD vary by gender, age and other demographics, being more frequent among boys, later in life and among those who live in urban areas. Also, the literature supports the direct, positive association between harsh discipline and externalizing behaviors. Nevertheless, scholars have underscored the important role of race and ethnicity in understanding discipline effects on children. The impact of harsh discipline in a Puerto Rican population remains to be studied. Methods: Sample: This is a secondary analysis of the Boricua Youth Study which assessed yearly (3 times) Puerto Rican children aged 5-15 in two different sites: San Juan (Puerto Rico) and the South Bronx (NY), N=2951. Participants that did not have scores of harsh discipline in the 3 waves were excluded for this analysis (N=2091). Main Measures: a) Harsh Discipline (Parent report) was measured using 6 items from the “Parental Discipline Scale” that measures various forms of punishment, including physical and verbal abuse, and withholding affection; b) Disruptive Behavior Disorder (Parent report): Parent version of the Diagnostic Interview Schedule for Children-IV (DISC-IV) was used to asses children’s conduct disorders; c) Demographic factors: Child gender, child age, family income, marital status; d) Parental factors: parental psychopathology, parental monitoring, familism, parent support; e) Children characteristics: Controlling for any diagnostic at wave 1 (internalizing or externalizing). Data Analysis: Logistic regression was carried out relating the likelihood of DBD to harsh discipline along waves controlling for potential confounders as demographics, child and parent characteristics. Results: There were no significant differences in harsh discipline by site in wave 1 and wave 2 but there was a significant difference in wave 3. Also, there were no significant differences in DBD by site in wave 1 and wave 2 but there was a significant difference in wave 3. There was a significant difference of discipline by gender and age in all the waves. We calculated unadjusted (OR) and adjusted (AOD) and 95% confidence intervals (95%CI) showing the relation between harsh discipline at wave 1 and the presence of child disruptive behavior disorder at wave 3 for both South Bronx and Puerto Rico. There was an association between harsh discipline and the likelihood of having DBD in The Bronx (AOR=1.76; 95%CI=1.13-2.74, p.013) and in Puerto Rico (AOR=2.17; 95%CI=1.28-3.67, p.004) having controlled for demographic, parental and individual factors. Conclusions: Context may be an important differential factor shaping the potential risk of harsh discipline toward DBD for Puerto Rican children.

Keywords: disruptive behavior disorders, harsh discipline, puerto rican, psychological education

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

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

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

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Authors: Yasser F. Hassan

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The reduction or removal of noise in a color image is an essential part of image processing, whether the final information is used for human perception or for an automatic inspection and analysis. This paper describes the modeling system based on the rough neural network model to adaptive cellular automata for various image processing tasks and noise remover. In this paper, we consider the problem of object processing in colored image using rough neural networks to help deriving the rules which will be used in cellular automata for noise image. The proposed method is compared with some classical and recent methods. The results demonstrate that the new model is capable of being trained to perform many different tasks, and that the quality of these results is comparable or better than established specialized algorithms.

Keywords: rough sets, rough neural networks, cellular automata, image processing

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Authors: Gaokai Liu

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Automatic defect detection for nanomaterial images is widely required in industrial scenarios. Deep learning approaches are considered as the most effective solutions for the great majority of image-based tasks. In this paper, an edge guidance network for defect segmentation is proposed. First, the encoder path with multiple convolution and downsampling operations is applied to the acquisition of shared features. Then two decoder paths both are connected to the last convolution layer of the encoder and supervised by the edge and segmentation labels, respectively, to guide the whole training process. Meanwhile, the edge and encoder outputs from the same stage are concatenated to the segmentation corresponding part to further tune the segmentation result. Finally, the effectiveness of the proposed method is verified via the experiments on open nanofibrous datasets.

Keywords: deep learning, defect detection, image segmentation, nanomaterials

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Authors: Megan Burfoot, Ali GhaffarianHoseini, Nicola Naismith, Amirhosein GhaffarianHoseini

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Intelligent Acoustic Technology (IAT) is a novel architectural device used in buildings to automatically vary the acoustic conditions of space. IAT is realized by integrating two components: Variable Acoustic Technology (VAT) and an intelligent system. The VAT passively alters the RT by changing the total sound absorption in a room. In doing so, the Reverberation Time (RT) is changed and thus, the sound strength and clarity are altered. The intelligent system detects sound waves in real-time to identify the aural situation, and the RT is adjusted accordingly based on pre-programmed algorithms. IAT - the synthesis of these two components - can dramatically improve acoustic comfort, as the acoustic condition is automatically optimized for any detected aural situation. This paper presents an evaluation of the improvements of acoustic comfort in an existing tertiary classroom located at Auckland University of Technology in New Zealand. This is a pilot case study, the first of its’ kind attempting to quantify the benefits of IAT. Naturally, the potential acoustic improvements from IAT can be actualized by only installing the VAT component of IAT and by manually adjusting it rather than utilizing an intelligent system. Such a simplified methodology is adopted for this case study to understand the potential significance of IAT without adopting a time and cost-intensive strategy. For this study, the VAT is built by overlaying reflective, rotating louvers over sound absorption panels. RT's are measured according to international standards before and after installing VAT in the classroom. The louvers are manually rotated in increments by the experimenter and further RT measurements are recorded. The results are compared with recommended guidelines and reference values from national standards for spaces intended for speech and communication. The results obtained from the measurements are used to quantify the potential improvements in classroom acoustic comfort, where IAT to be used. This evaluation reveals the current existence of poor acoustic conditions in the classroom caused by high RT's. The poor acoustics are also largely attributed to the classrooms’ inability to vary acoustic parameters for changing aural situations. The classroom experiences one static acoustic state, neglecting to recognize the nature of classrooms as flexible, dynamic spaces. Evidently, when using VAT the classroom is prescribed with a wide range of RTs it can achieve. Namely, acoustic requirements for varying teaching approaches are satisfied, and acoustic comfort is improved. By quantifying the benefits of using VAT, it can confidently suggest these same benefits are achieved with IAT. Nevertheless, it is encouraged that future studies continue this line of research toward the eventual development of IAT and its’ acceptance into mainstream architecture.

Keywords: acoustic comfort, classroom acoustics, intelligent acoustics, variable acoustics

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Authors: Salah Hamri, Tewfik Bouchaour, Ulrich Maschke

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The aim of this works is the study of swelling ratio of cross-linked polymer networks poly (2-hydroxyethyl methacrylate) (PHEMA). The system composed of erythrosine and Triethanolamine, in aqueous medium, is used as photo-initiator and 1,6-Hexanediol diacrylate as cross-linker. The analysis of UV-visible and infrared spectra, which were taken at different times during polymerization/cross linking, makes it possible to obtain useful information on the reaction mechanism. The swelling behavior was study by changing the nature of solvent, dye sensitizer (erythrosine, rose Bengal and eosin), and pH of the medium. The exploitation of experimental results using Fick diffusion model is also expected and shows a good correlation between theoretical and experimental results.

Keywords: cross-linker, photo-sensitizer, polymer network, swelling ratio

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Authors: Nova Grail S. Luminang, Gwyneth B. Gortiza, Alvin E. Haboc, Marinol K. Hate, Rhean Mitchel N. Joven, Kara Kate D. Lammao, Rosemarie M. Lambayung, Elmo Carl D. Lardizabal, Zyra B. Linggayo, Rizza Mae G. Liwag, Ronalyn O. Songcuan

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Breast cancer survivorship represents a complex and continuous journey extending beyond the completion of treatment, involving coping with physical, emotional, and psychological aspects of life post-treatment. This study aimed to explore the lived experiences of breast cancer survivors after successful treatment in Tabuk City, focusing on their post-treatment experiences, coping mechanisms, and necessary lifestyle changes. Researchers have selected Tabuk City as their research locale. Utilizing Martin Heidegger’s descriptive phenomenological design, this qualitative research included six participants, allowing for data saturation. Purposive sampling was employed to select participants. Researchers used Colaizzi’s Phenomenological Method in analyzing the data in order to achieve a reliable understanding of the participants’ experiences. The findings revealed three main themes: going through post-treatment hurdles, building resilience, and transformative wellness adjustments. Breast cancer survivors faced significant challenges, including physical adversities, emotional turmoil, limited social life, memory lapses, decreased sexual intimacy, and economic constraints. To cope, survivors adjusted their thoughts and attitudes, accepted their situation, relied on religious beliefs, and joined the support group Kalinga Cancer Care Ministry INC. Additionally, they strived to return to a normal life and embraced gratitude. Survivors made essential changes to their daily routines, modifying their diets, exploring herbal remedies, and incorporating physical activities such as walking and household chores. These adjustments helped improve their overall well-being and prevent cancer recurrence. The researchers concluded that the journey of breast cancer survivors is marked by significant challenges and inspiring resilience. The impact of breast cancer treatment extends beyond physical recovery, encompassing profound emotional and social dimensions. Despite these difficulties, survivors demonstrate remarkable strength and adaptability, making positive lifestyle changes that offer a hopeful and inspiring narrative of recovery and perseverance.

Keywords: breast cancer, lived experiences, breast cancer survivor, post-treatment hurdles, emotional turmoil

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Authors: M. Benbouzid, Q. Bresson, A. Duclos, K. Longo, Q. Morel

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Currently, electricity suppliers must predict the consumption of their customers in order to deduce the power they need to produce. It is, then, important in a first step to optimize household consumption to obtain more constant curves by limiting peaks in energy consumption. Here centralized real time scheduling is proposed to manage the equipment's starting in parallel. The aim is not to exceed a certain limit while optimizing the power consumption across a habitat. The Raspberry Pi is used as a box; this scheduler interacts with the various sensors in 6LoWPAN. At the scale of a single dwelling, household consumption decreases, particularly at times corresponding to the peaks. However, it would be wiser to consider the use of a residential complex so that the result would be more significant. So, the ceiling would no longer be fixed. The scheduling would be done on two scales, firstly, per dwelling, and secondly, at the level of a residential complex.

Keywords: smart grid, energy box, scheduling, Gang Model, energy consumption, energy management system, wireless sensor network

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Authors: Bilal Tebboub, AmelLabbani

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This article introduces a compact sensor based on high-transmission, high-sensitivity two-dimensional photonic crystals. The photonic crystal consists of a square network of silicon rods in the air. The sensor is composed of two waveguide couplers and a microcavity designed for monitoring the percentage of hydrogen in the air and identifying gas types. Through the Finite-Difference Time-Domain (FDTD) method, we demonstrate that the sensor's resonance wavelength is contingent upon changes in the gas refractive index. We analyze transmission spectra, quality factors, and sensor sensitivity. The sensor exhibits a notable quality factor and a sensitivity value of 1374 nm/RIU. Notably, the sensor's compact structure occupies an area of 74.5 μm2, rendering it suitable for integrated optical circuits.

Keywords: 2-D photonic crystal, sensitivity, F.D.T.D method, label-free biosensing

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Authors: F. Louati, H. Trabelsi, M. Jamei

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Desiccation cracks following drainage-humidification cycles. With water loss, mainly due to evaporation, suction in the soil increases, producing volumetric shrinkage and tensile stress. When the tensile stress reaches tensile strength, the soil cracks. Desiccation cracks networks can directly control soil hydraulic properties. The aim of this study was for quantifying the hydraulic properties for examples the water retention curve, the saturated hydraulic conductivity, the unsaturated hydraulic conductivity function, the shrinkage dynamics in Tibar soil- clay soil in the Northern of Tunisia. Then a numerical simulation of unsaturated hydraulic properties for a crack network has been attempted. The finite elements code ‘CODE_BRIGHT’ can be used to follow the hydraulic distribution in cracked porous media.

Keywords: desiccation, cracks, permeability, unsaturated hydraulic flow, simulation

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Authors: Görkem Cemali̇, Avram Aruh, Gamze Torun Köse, Erde Can ŞAfak

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In order to heal bone disorders, the conventional methods which involve the use of autologous and allogenous bone grafts or permanent implants have certain disadvantages such as limited supply, disease transmission, or adverse immune response. A biodegradable material that acts as structural support to the damaged bone area and serves as a scaffold that enhances bone regeneration and guides bone formation is one desirable solution. Poly(propylene fumarate) (PPF) which is an unsaturated polyester that can be copolymerized with appropriate vinyl monomers to give biodegradable network structures, is a promising candidate polymer to prepare bone tissue engineering scaffolds. In this study, hydroxyl-terminated PPF was synthesized and thermally cured with vinyl phosphonic acid (VPA) and diethyl vinyl phosphonate (VPES) in the presence of radical initiator benzoyl peroxide (BP), with changing co-monomer weight ratios (10-40wt%). In addition, the synthesized PPF was cured with VPES comonomer at body temperature (37oC) in the presence of BP initiator, N, N-Dimethyl para-toluidine catalyst and varying amounts of Beta-tricalcium phosphate (0-20 wt% ß-TCP) as filler via radical polymerization to prepare composite materials that can be used in injectable forms. Thermomechanical properties, compressive properties, hydrophilicity and biodegradability of the PPF/VPA and PPF/VPES copolymers were determined and analyzed with respect to the copolymer composition. Biocompatibility of the resulting polymers and their composites was determined by the MTS assay and osteoblast activity was explored with von kossa, alkaline phosphatase and osteocalcin activity analysis and the effects of VPA and VPES comonomer composition on these properties were investigated. Thermally cured PPF/VPA and PPF/VPES copolymers with different compositions exhibited compressive modulus and strength values in the wide range of 10–836 MPa and 14–119 MPa, respectively. MTS assay studies showed that the majority of the tested compositions were biocompatible and the overall results indicated that PPF/VPA and PPF/VPES network polymers show significant potential for applications as bone tissue engineering scaffolds where varying PPF and co-monomer ratio provides adjustable and controllable properties of the end product. The body temperature cured PPF/VPES/ß-TCP composites exhibited significantly lower compressive modulus and strength values than the thermal cured PPF/VPES copolymers and were therefore found to be useful as scaffolds for cartilage tissue engineering applications.

Keywords: biodegradable, bone tissue, copolymer, poly(propylene fumarate), scaffold

Procedia PDF Downloads 166

Authors: Nidhal K. Azawi, John M. Gauch

Abstract:

Colorectal cancer is one of the leading causes of cancer death in the US and the world, which is why millions of colonoscopy examinations are performed annually. Unfortunately, noise, specular highlights, and motion artifacts corrupt many images in a typical colonoscopy exam. The goal of our research is to produce automated techniques to detect and correct or remove these noninformative images from colonoscopy videos, so physicians can focus their attention on informative images. In this research, we first automatically extract features from images. Then we use machine learning and deep neural network to classify colonoscopy images as either informative or noninformative. Our results show that we achieve image classification accuracy between 92-98%. We also show how the removal of noninformative images together with image alignment can aid in the creation of image panoramas and other visualizations of colonoscopy images.

Keywords: colonoscopy classification, feature extraction, image alignment, machine learning

Procedia PDF Downloads 253

Authors: Charles Davidson

Abstract:

This paper presents the Stoplight Analysis System of Partnering Organizations Readiness, offering a structured framework to evaluate conflict resolution collaboration feasibility, especially crucial in conflict areas, employing a colour-coded approach and specific assessment points, with implications for more informed decision-making and improved outcomes in peacebuilding initiatives. Derived from at total of 40 years of practical peacebuilding experience from the project’s two researchers as well as interviews of various other peacebuilding actors, this paper introduces the Stoplight Analysis System of Partnering Organizations Readiness, a comprehensive framework designed to facilitate effective collaboration in international/local peacebuilding partnerships by evaluating the readiness of both potential partner organisations and the location of the proposed project. ^The system employs a colour-coded approach, categorising potential partnerships into three distinct indicators: Red (no-go), Yellow (requires further research), and Green (promising, go ahead). Within each category, specific points are identified for assessment, guiding decision-makers in evaluating the feasibility and potential success of collaboration. The Red category signals significant barriers, prompting an immediate stoppage in the consideration of partnership. The Yellow category encourages deeper investigation to determine whether potential issues can be mitigated, while the Green category signifies organisations deemed ready for collaboration. This systematic and structured approach empowers decision-makers to make informed choices, enhancing the likelihood of successful and mutually beneficial partnerships. Methodologically, this paper utilised interviews from peacebuilders from around the globe, scholarly research of extant strategies, and a collaborative review of programming from the project’s two authors from their own time in the field. This method as a formalised model has been employed for the past two years across a litany of partnership considerations, and has been adjusted according to its field experimentation. This research holds significant importance in the field of conflict resolution as it provides a systematic and structured approach to peacebuilding partnership evaluation. In conflict-affected regions, where the dynamics are complex and challenging, the Stoplight Analysis System offers decision-makers a practical tool to assess the readiness of partnering organisations. This approach can enhance the efficiency of conflict resolution efforts by ensuring that resources are directed towards partnerships with a higher likelihood of success, ultimately contributing to more effective and sustainable peacebuilding outcomes.

Keywords: collaboration, conflict resolution, partnerships, peacebuilding

Procedia PDF Downloads 64

Authors: Mohamed Shaban, Ali Alfallah

Abstract:

This paper describes an application for testing of a fault indicator but it could be used for other network protection testing. The application is created in the LabVIEW environment and consists of three parts. The first part of the application is determined for transient phenomenon generation and imitates voltage and current transient signal at ground fault originate. The second part allows to set sequences of trend for each current and voltage output signal, up to six trends for each phase. The last part of the application generates harmonic signal with continuously controllable amplitude of current or voltage output signal and phase shift of each signal can be changed there. Further any sub-harmonics and upper harmonics can be added to selected current output signal

Keywords: signal generator-fault indicator, harmonic signal generator, voltage output

Procedia PDF Downloads 495