Search results for: real property

Authors: Bezhan Ghvaberidze

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A multiple criteria optimization approach for the solution of the Fuzzy Vehicle Routing Problem (FVRP) is proposed. For the possibility environment the levels of movements between customers are calculated by the constructed simulation interactive algorithm. The first criterion of the bi-criteria optimization problem - minimization of the expectation of total fuzzy travel time on closed routes is constructed for the FVRP. A new, second criterion – maximization of feasibility of movement on the closed routes is constructed by the Choquet finite averaging operator. The FVRP is reduced to the bi-criteria partitioning problem for the so called “promising” routes which were selected from the all admissible closed routes. The convenient selection of the “promising” routes allows us to solve the reduced problem in the real-time computing. For the numerical solution of the bi-criteria partitioning problem the -constraint approach is used. An exact algorithm is implemented based on D. Knuth’s Dancing Links technique and the algorithm DLX. The Main objective was to present the new approach for FVRP, when there are some difficulties while moving on the roads. This approach is called FVRP for extreme conditions (FVRP-EC) on the roads. Also, the aim of this paper was to construct the solving model of the constructed FVRP. Results are illustrated on the numerical example where all Pareto-optimal solutions are found. Also, an approach for more complex model FVRP with time windows was developed. A numerical example is presented in which optimal routes are constructed for extreme conditions on the roads.

Keywords: combinatorial optimization, Fuzzy Vehicle routing problem, multiple objective programming, possibility theory

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Authors: Paola Comella, Vincenzo Francani, Paola Gattinoni

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This paper presents the Colzate-Vertova landslide, a Deep Seated Gravitational Slope Deformation (DSGSD) located in the Seriana Valley, Northern Italy. The paper aims at describing the development as well as evaluating the factors that influence the evolution of the landslide. After defining the conceptual model of the landslide, numerical simulations were developed using a finite element numerical model, first with a two-dimensional domain, and later with a three-dimensional one. The results of the 2-D model showed a displacement field typical of a sackung, as a consequence of the erosion along the Seriana Valley. The analysis also showed that the groundwater flow could locally affect the slope stability, bringing about a reduction in the safety factor, but without reaching failure conditions. The sensitivity analysis carried out on the strength parameters pointed out that slope failures could be reached only for relevant reduction of the geotechnical characteristics. Such a result does not fit the real conditions observed on site, where a number of small failures often develop all along the hillslope. The 3-D model gave a more comprehensive analysis of the evolution of the DSGSD, also considering the border effects. The results showed that the convex profile of the slope favors the development of displacements along the lateral valley, with a relevant reduction in the safety factor, justifying the existing landslides.

Keywords: deep seated gravitational slope deformation, Italy, landslide, numerical modeling

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Authors: Lei Zhu, Nan Li

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Cold stamping has been widely applied in the automotive industry for the mass production of a great range of automotive panels. Predicting the springback to ensure the dimensional accuracy of the cold-stamped components is a critical step. The main approaches for the prediction and compensation of springback in cold stamping include running Finite Element (FE) simulations and conducting experiments, which require forming process expertise and can be time-consuming and expensive for the design of cold stamping tools. Machine learning technologies have been proven and successfully applied in learning complex system behaviours using presentative samples. These technologies exhibit the promising potential to be used as supporting design tools for metal forming technologies. This study, for the first time, presents a novel application of a Convolutional Neural Network (CNN) based surrogate model to predict the springback fields for variable U-shape cold bending geometries. A dataset is created based on the U-shape cold bending geometries and the corresponding FE simulations results. The dataset is then applied to train the CNN surrogate model. The result shows that the surrogate model can achieve near indistinguishable full-field predictions in real-time when compared with the FE simulation results. The application of CNN in efficient springback prediction can be adopted in industrial settings to aid both conceptual and final component designs for designers without having manufacturing knowledge.

Keywords: springback, cold stamping, convolutional neural networks, machine learning

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Authors: Ya L. V., Benjamin Ong Wei Lin, Wanli Niu, Benjamin Seah Chin Tat

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This article introduces a methodology that improves reliability and cyclability of 2nd-life Li-ion battery system repurposed as an energy storage system (ESS). Most of the 2nd-life retired battery systems in the market have module/pack-level state-of-health (SOH) indicator, which is utilized for guiding appropriate depth-of-discharge (DOD) in the application of ESS. Due to the lack of cell-level SOH indication, the different degrading behaviors among various cells cannot be identified upon reaching retired status; in the end, considering end-of-life (EOL) loss and pack-level DOD, the repurposed ESS has to be oversized by > 1.5 times to complement the application requirement of reliability and cyclability. This proposed battery grading algorithm, using non-invasive methodology, is able to detect outlier cells based on historical voltage data and calculate cell-level historical maximum temperature data using semi-analytic methodology. In this way, the individual battery cell in the 2nd-life battery system can be graded in terms of SOH on basis of the historical voltage fluctuation and estimated historical maximum temperature variation. These grades will have corresponding DOD grades in the application of the repurposed ESS to enhance system reliability and cyclability. In all, this introduced battery grading algorithm is non-invasive, compatible with all kinds of retired Li-ion battery systems which lack of cell-level SOH indication, as well as potentially being embedded into battery management software for preventive maintenance and real-time cyclability optimization.

Keywords: battery grading algorithm, 2nd-life repurposing battery system, semi-analytic methodology, reliability and cyclability

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Authors: Shivaram P. Arunachalam, Mustafa Y. Sir, Andy Boggust, David M. Nestler, Thomas R. Hellmich, Kalyan S. Pasupathy

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Emergency departments (EDs) provide urgent care to patients throughout the day in a complex and chaotic environment. Real-time location systems (RTLS) are increasingly being utilized in healthcare settings, and have shown to improve safety, reduce cost, and increase patient satisfaction. Radio Frequency Identification Device (RFID) data in an ED has been shown to compute variables such as patient-provider contact time, which is associated with patient outcomes such as 30-day hospitalization. These variables can provide avenues for improving ED operational efficiency. A major challenge with ED financial operations is under-coding of critical care services due to physicians’ difficulty reporting accurate times for critical care provided under Current Procedural Terminology (CPT) codes 99291 and 99292. In this work, the authors propose a framework to optimize ED critical care billing using RFID data. RFID estimated physician-patient contact times could accurately quantify direct critical care services which will help model a data-driven approach for ED critical care billing. This paper will describe the framework and provide insights into opportunities to prevent under coding as well as over coding to avoid insurance audits. Future work will focus on data analytics to demonstrate the feasibility of the framework described.

Keywords: critical care billing, CPT codes, emergency department, RFID

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Authors: V. Linfante

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Catwalks are one of the key moments in fashion: the first and most relevant display where brands stage their collections, products, ideas, and style. The garment is 'the star' of the catwalk and must show itself not just as a product but as a result of a design process endured for several months. All contents developed within this process become ingredients for connecting scenography, music, lights, and direction into a unique fashion narrative. According to the spirit of different ages, fashion shows have been transformed and shaped into peculiar formats: from Pandoras to presentations organized by Parisian couturiers, across the 'marathons' typical of the beginning of modern fashion system, coming up to the present structure of fashion weeks, with their complex organization and related creative and technical businesses. The paper intends to introduce the evolution of the fashion system through its unique process of seasonally staging and showing its production. The paper intends to analyse the evolution of the fashion shows from the intimacy of ballrooms at the beginning of the 20th century, passing through the enthusiasm attitude typical from the '70s and the '80s, to finally depict our present. In this last scenario, catwalks are not anymore a standard collections presentation but become one of the most exciting expression of contemporary culture (and sub-cultures), going from sophisticated performances (as Karl Lagerfeld's Chanel shows) to real artistic happenings (as the events of Victor&Rolf, Alexander McQueen, OFF_WHITE, Vetements, and Martin Margiela), often involving contemporary architecture, digital world, technology, social media, performing art and artists.

Keywords: branding, communication, fashion, new media, performing art

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Authors: Vemula Amalakrishna, S. Pushpavanam

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Change and motion characterize and persistently reshape the world around us, on scales from molecular to global. The subtle interplay between change (Reaction) and motion (Diffusion) gives rise to an astonishing intricate spatial or temporal pattern. These pattern formation in nature has been intellectually appealing for many scientists since antiquity. Periodic precipitation patterns, also known as Liesegang patterns (LP), are one of the stimulating examples of such self-assembling reaction-diffusion (RD) systems. LP formation has a great potential in micro and nanotechnology. So far, the research on LPs has been concentrated mostly on how these patterns are forming, retrieving information to build a universal mathematical model for them. Researchers have developed various theoretical models to comprehensively construct the geometrical diversity of LPs. To the best of our knowledge, simulation studies of LPs assume an arbitrary value of RD parameters to explain experimental observation qualitatively. In this work, existing models were studied to understand the mechanism behind this phenomenon and challenges pertaining to models were understood and explained. These models are not computationally effective due to the presence of discontinuous precipitation rate in RD equations. To overcome the computational challenges, smoothened Heaviside functions have been introduced, which downsizes the computational time as well. Experiments were performed using a conventional LP system (AgNO₃-K₂Cr₂O₇) to understand the effects of different gels and temperatures on formed LPs. The model is extended for real parameter values to compare the simulated results with experimental data for both 1-D (Cartesian test tubes) and 2-D(cylindrical and Petri dish).

Keywords: reaction-diffusion, spatio-temporal patterns, nucleation and growth, supersaturation

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Authors: Mi-Hyang Lee, Seung-Hoon Han

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Korean traditional residences have been built with deep design issues for various values such as social, cultural, and environmental influences to be started from a few thousand years ago, but its meaning is being vanished due to the different lifestyles these days. It is necessary, therefore, to grasp the meaning of the Korea traditional building called Hanok and to get Korean people understand its real advantages. The purpose of this study is to propose a standardization methodology for evaluating comfort features towards Korean traditional houses. This paper is also trying to build an official standard evaluation system and to integrate aesthetic and psychological values induced from Hanok. Its comfort performance values could be divided into two large categories that are physical and psychological, and fourteen methods have been defined as the Korean Standards (KS). For this research, field survey data from representative Hanok types were collected for each method. This study also contains a qualitative in-depth analysis of the Hanok comfort index by the professions using AHP (Analytical Hierarchy Process) and has examined the effect of the methods. As a result, this paper could define what methods can provide trustful outcomes and how to evaluate the own strengths in aspects of spatial comfort of Hanok using suggested procedures towards the spatial configuration of the traditional dwellings. This study has finally proposed an integrated development of a standardization methodology assessing the comfort performance for Korean traditional residences, and it is expected that they could evaluate inhabitants of the residents and interior environmental conditions especially structured by wood materials like Hanok.

Keywords: Hanok, comfort performance, human condition, analytical hierarchy process

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Authors: Jamal Gaber Abdalla

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In business promotion and advertising, language is used intentionally to create a powerful influence over people and their behavior. In commercial and marketing activities, the choice of language to convey specific messages with the intention of influencing people is pragmatically important. Design and visual content in promotional and advertising texts also have a great persuasive impact on consumers. It is the functional combination of design, language and visual content that helps people to identify a product or service and remember it. Translating promotional and advertising texts between structurally and culturally different languages, such as English and Arabic, usually involves pragmatic/functional shifts that decide the quality of translation. This study explores some of these shifts in translating promotional and advertising texts between English and Arabic and their implications for translation quality. The study is based on a contrastive analysis of data collected from real samples of English-Arabic translations of promotional and advertising texts. The samples cover different promotional and advertising text types and different business domains. The aim is to identify the most recurrent translation shifts and most used translation approaches/strategies that achieve quality in view of the functional nature of promotional and advertising texts and target language culture conventions. The study shows that linguistic shifts and visual shifts are recurrent in English-Arabic translations of promotional and advertising texts. The study also shows that the most commonly used translation approaches/strategies are functional translation, domestication, communicative translation.

Keywords: advertising, Arabic, English, functional translation, promotion

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Authors: Rita Fofai

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The aim of the study is to help peacebuilding by analyzing the symbolical level of fights in the war. Despite the sufferings, war heroism still represents such a noble value in war narratives (especially in literature and films, whether it is high- or popular culture) which can make warfare attractive for every age-group. The questions of the study will revolve around the events when heroism is not a necessary and unselfish act for a greater good, but when the primary aim is to express strength in order to build self-mythology. Since war is a scene where the mythological level can meet reality, and even modern narratives use the elements of rituals and sacral references in even secular contexts, understanding the connection between rites and modern battles will ground this study, and the analysis will follow the logic of the violent rites. From this aspect, war is not merely the fight for different countries and ideas, but the fight of mankind with superhuman and natural or supernatural phenomena, as well. In this context, enemy symbolizes the threat of the world which is unpredictable for mankind, and the fight becomes a ritual combat; therefore the winner’s symbolic reward is to redefine himself or herself not only in the human environment but in the context of the whole world. The analysis of the study reveals that this kind of violence does not represents real heroism and rarely results in recruitment, on the contrary, conserves fear and the feeling of weakness, which is the root cause of this kind of act. The result of this study is a way to reshape the attitude toward so-called heroic war violence which is often a part of war narratives even nowadays. Since stepping out of the war tradition is mainly a cultural question, redefining the connection between society and narratives which has an effect on mentality and emotions, giving a clear guide to making difference between heroism and useless violence is very important in peacebuilding.

Keywords: war, ritual, heroism, violence, narratives, culture

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Authors: Hilal Naimi, Amelbahahouda Adamou-Mitiche, Lahcene Mitiche

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The main problem in the area of medical imaging has been image denoising. The most defying for image denoising is to secure data carrying structures like surfaces and edges in order to achieve good visual quality. Different algorithms with different denoising performances have been proposed in previous decades. More recently, models focused on deep learning have shown a great promise to outperform all traditional approaches. However, these techniques are limited to the necessity of large sample size training and high computational costs. This research proposes a denoising approach basing on LDTCWT (Lifting Dual Tree Complex Wavelet Transform) using Hybrid Thresholding with Wiener filter to enhance the quality image. This research describes the LDTCWT as a type of lifting wavelets remodeling that produce complex coefficients by employing a dual tree of lifting wavelets filters to get its real part and imaginary part. Permits the remodel to produce approximate shift invariance, directionally selective filters and reduces the computation time (properties lacking within the classical wavelets transform). To develop this approach, a hybrid thresholding function is modeled by integrating the Wiener filter into the thresholding function.

Keywords: lifting wavelet transform, image denoising, dual tree complex wavelet transform, wavelet shrinkage, wiener filter

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Authors: Maria Amodeo, Pasquale Arpaia, Marco Buzio, Vincenzo Di Capua, Francesco Donnarumma

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Different deep neural network architectures have been compared and tested to predict magnetic hysteresis in the context of pulsed electromagnets for experimental physics applications. Modelling quasi-static or dynamic major and especially minor hysteresis loops is one of the most challenging topics for computational magnetism. Recent attempts at mathematical prediction in this context using Preisach models could not attain better than percent-level accuracy. Hence, this work explores neural network approaches and shows that the architecture that best fits the measured magnetic field behaviour, including the effects of hysteresis and eddy currents, is the nonlinear autoregressive exogenous neural network (NARX) model. This architecture aims to achieve a relative RMSE of the order of a few 100 ppm for complex magnetic field cycling, including arbitrary sequences of pseudo-random high field and low field cycles. The NARX-based architecture is compared with the state-of-the-art, showing better performance than the classical operator-based and differential models, and is tested on a reference quadrupole magnetic lens used for CERN particle beams, chosen as a case study. The training and test datasets are a representative example of real-world magnet operation; this makes the good result obtained very promising for future applications in this context.

Keywords: deep neural network, magnetic modelling, measurement and empirical software engineering, NARX

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Authors: Brian Marsh

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Nitrogen fertilizer is the most used and often the most mismanaged nutrient input. Nitrogen management has tremendous implications on crop productivity, quality and environmental stewardship. Sufficient nitrogen is needed to optimum yield and quality. Soil and in-season plant tissue testing for nitrogen status are a time consuming and expensive process. Real time sensing of plant nitrogen status can be a useful tool in managing nitrogen inputs. The objectives of this project were to assess the reliability of remotely sensed non-destructive plant nitrogen measurements compared to wet chemistry data from sampled plant tissue, develop in-season nitrogen recommendations based on remotely sensed data for improved nitrogen use efficiency and assess the potential for determining yield and quality from remotely sensed data. Very good correlations were observed between early-season remotely sensed crop nitrogen status and plant nitrogen concentrations and subsequent in-season fertilizer recommendations. The transmittance/absorbance type meters gave the most accurate readings. Early in-season fertilizer recommendation would be to apply 40 kg nitrogen per hectare plus 16 kg nitrogen per hectare for each unit difference measured with the SPAD meter between the crop and reference area or 25 kg plus 13 kg per hectare for each unit difference measured with the CCM 200. Once the crop was sufficiently fertilized meter readings became inconclusive and were of no benefit for determining nitrogen status, silage yield and quality and grain yield and protein.

Keywords: wheat, nitrogen fertilization, chlorophyll meter

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Authors: Mohamed Mohamed, Philip Bonello, Peter Russhard

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Blade Tip Timing (BTT) is a technology concerned with the estimation of both frequency and amplitude of rotating blades. A BTT system comprises two main parts: (a) the arrival time measurement system, and (b) the analysis algorithms. Simulators play an important role in the development of the analysis algorithms since they generate blade tip displacement data from the simulated blade vibration under controlled conditions. This enables an assessment of the performance of the different algorithms with respect to their ability to accurately reproduce the original simulated vibration. Such an assessment is usually not possible with real engine data since there is no practical alternative to BTT for blade vibration measurement. Most simulators used in the literature are based on a simple spring-mass-damper model to determine the vibration. In this work, a more realistic experimentally validated simulator based on the Finite Element (FE) model of a bladed disc (blisk) is first presented. It is then used to generate the necessary data for the assessment of different BTT algorithms. The FE modelling is validated using both a hammer test and two firewire cameras for the mode shapes. A number of autoregressive methods, fitting methods and state-of-the-art inverse methods (i.e. Russhard) are compared. All methods are compared with respect to both synchronous and asynchronous excitations with both single and simultaneous frequencies. The study assesses the applicability of each method for different conditions of vibration, amount of sampling data, and testing facilities, according to its performance and efficiency under these conditions.

Keywords: blade tip timing, blisk, finite element, vibration measurement

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Authors: Zhifei Hu, Feng Xia

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In recent years, Graph neural network has been widely used in knowledge graph recommendation. The existing recommendation methods based on graph neural network extract information from knowledge graph through entity and relation, which may not be efficient in the way of information extraction. In order to better propose useful entity information for the current recommendation task in the knowledge graph, we propose an end-to-end Neural network Model based on multi-stream graph attentional Mechanism (MSGAT), which can effectively integrate the knowledge graph into the recommendation system by evaluating the importance of entities from both users and items. Specifically, we use the attention mechanism from the user's perspective to distil the domain nodes information of the predicted item in the knowledge graph, to enhance the user's information on items, and generate the feature representation of the predicted item. Due to user history, click items can reflect the user's interest distribution, we propose a multi-stream attention mechanism, based on the user's preference for entities and relationships, and the similarity between items to be predicted and entities, aggregate user history click item's neighborhood entity information in the knowledge graph and generate the user's feature representation. We evaluate our model on three real recommendation datasets: Movielens-1M (ML-1M), LFM-1B 2015 (LFM-1B), and Amazon-Book (AZ-book). Experimental results show that compared with the most advanced models, our proposed model can better capture the entity information in the knowledge graph, which proves the validity and accuracy of the model.

Keywords: graph attention network, knowledge graph, recommendation, information propagation

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Authors: Sadaf Karkoodi, Hassan Karampour

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There is a growing interest in the construction industry towards hybrid systems. The hybrid systems use construction materials such as timber, steel, and concrete smartly, can be prefabricated, and are cost-effective and sustainable solutions to an industry targeting reduced carbon footprint. Moreover, in case of periodical shortage in timber resources, reusable and waste wood such as fibres can be used in the hybrid modules, which facilitates the circular economy. In this research, a hybrid frame is proposed and experimentally validated by introducing dried wood fibre products inside cold-formed steel square hollow sections without using any adhesives. As such, fibre-filled steel tubular (FFST) columns, beams, and 2D frames are manufactured and tested. The results show that the FFST columns have stiffness and strength 44% and 55% higher than cold-formed steel columns, respectively. The bearing strength of the FFST beams shows an increase of 39.5% compared to steel only. The flexural stiffness and strength of the FFST beams are 8.5% and 28% higher than the bare steel beams, respectively. The FFST frame depicted an 18.4% higher ultimate load capacity than the steel-only frame under a mid-point concentrated load. Moreover, the FFST beam-to-column bolted connection showed high ductile performance. The initial results and the proposed simple manufacturing process suggest that the proposed FFST concept can be upscaled and used in real structures.

Keywords: wood fibre, reusing wood, fibre-filled steel, hybrid construction

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Authors: Meenakshi Srivastava, A. K. Mishra

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This study characterizes the metabolic versatility of denitrifying bacterial communities residing in the paddy soil using the GC-MS based Phospholipid Fatty Acid (PLFA) analyses simultaneously with nosZ gene based PCR-DGGE (Polymerase Chain Reaction-Denaturing Gradient Gel Electrophoresis) and real time Q-PCR analysis. We have analyzed the abundance of nitrous oxide reductase (nosZ) genes, which was subsequently related to soil PLFA profile and DGGE based denitrifier community structure. Soil denitrifying bacterial community comprised majority or dominance of Ochrobactrum sp. following Cupriavidus and uncultured bacteria strains in paddy soil of selected sites. Initially, we have analyzed the abundance of the nitrous oxide reductase gene (nosZ), which was found to be related with PLFA based lipid profile. Chandauli of Eastern UP, India represented greater amount of lipid content (C18-C20) and denitrifier’s diversity. This study suggests the positive co-relation between soil PLFA profiles, DGGE, and Q-PCR data. Thus, a close networking among metabolic abilities and taxonomic composition of soil microbial communities existed, and subsequently, such work at greater extent could be helpful in managing nutrient dynamics as well as microbial dynamics of paddy soil ecosystem.

Keywords: denaturing gradient gel electrophoresis, DGGE, nitrifying and denitrifying bacteria, PLFA, Q-PCR

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Authors: Hend K. Moosa, Eman A. Rashwan, Ezzat M. Hassan, Amany A. Ghazy, Amel G. Sheredy

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The stability of microRNA (miR) in the circulation can show a great progress toward the discovery of non-invasive diagnostic and prognostic biomarkers in many diseases. In the present study, circulatory miR-122 and miR-130a were analysed in chronic hepatitis C Egyptian patients in predicting the clinical outcome of interferon treatment. In addition, their expression levels were correlated to viral RNA levels, necro-inflammatory markers (AST, ALT) and to each other. This study was conducted on 51 subjects where 36 were chronic HCV patients in which they were divided into naive and interferon treated HCV patients (responders and non-responders) and 15 matched healthy controls. Serum quantification of miR-122 and miR-130a were performed by quantitative Real-time Polymerase Chain Reaction (qRT-PCR). The results showed a significant upregulation of miR-122 in non-responder patients (P=0.049). By receiver operating characteristic analysis curve, miR-122 revealed 65% sensitivity and 92.3% specificity in predicting non-responsiveness of patients to IFN treatment, while miR-130a showed a sensitivity of 100% and specificity of 53.85%. Remarkably, there was a significant positive correlation between miR-122 and miR-130a in naive HCV patients (r=0.714, p=0.003). However, there was no significant correlation between serum miR-122, miR-130a expression levels and necro-inflammatory markers (AST, ALT). To conclude, miR-122 and miR-130a have a significant association with viral RNA levels and accordingly, they may have a synergistic power in promoting viral replication. Interestingly, miR-122 and miR-130a have a predictive power in predicting clinical outcome of IFN treatment which can be further studied in currently used drugs in order to reduce the socio-economic burden of potentially non-responders.

Keywords: hepatitis C, microRNA, miR-122, miR-130a

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Authors: Joanna Apps, Elena Markova

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Concepts of the ideal mother and ideal mothering are disseminated through familial experiences, religious and cultural depictions of mothers and the national media. In recent years social media can also be added to the channels by which mothers and motherhood are socially constructed. However, the gulf between these depictions, -or in the case of social media ‘self-curations’ - of motherhood and lived experience has never been wider, particularly for women in disadvantaged or difficult circumstances. We report on a study of four lone mothers who were living with one or more of the following: limiting long term illness, large families, in temporary accommodation and on low incomes. The mothers were interviewed 3 times and invited to take a series of photos reflecting their lives in between each of the interviews. These photographs were used to ground the interviews in lived experience and as stimuli to discuss how the images within them compared to portrayals of mothers and motherhood that participants were exposed to on social media. The objectives of the study were to explore how mothers construct their identity in challenging and disadvantaged circumstances; to consider what their photographs of everyday life tell us about their experiences and understand the impact idealised images of motherhood have on real mothers in difficult circumstances. The results suggested that the mothers both strived to adhere to certain ideals of motherhood and acknowledged elements of these as partially or wholly impossible to achieve. The lack of depictions, in both national and social media, of motherhood that corresponded with their lived experience inhibited the mothers’ use of social media. Other themes included: lack of control, frustration and strain; and parental pride, love, humour, resilience, and hope.

Keywords: motherhood, social media, photography, poverty

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Authors: Alireza Nikravanshallmani, Jamshid Dehmeshki, Mojtaba Ahmadi

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Modeling of business processes, based on BPMN (Business Process Modeling Notation), helps analysts and managers to understand business processes, and, identify their shortages. These models provide a context to make rational decision of organizing business processes activities in an understandable manner. The purpose of this paper is to provide a framework for better understanding of business processes and their problems by reducing the cognitive load of displayed information for their audience at different managerial levels while keeping the essential information which are needed by them. For this reason, we integrate business process diagrams across the different managerial levels to develop a framework to improve the performance of business process management (BPM) projects. The proposed framework is entitled ‘Business process improvement framework based on managerial levels (BPIML)’. This framework, determine a certain type of business process diagrams (BPD) based on BPMN with respect to the objectives and tasks of the various managerial levels of organizations and their roles in BPM projects. This framework will make us able to provide the necessary support for making decisions about business processes. The framework is evaluated with a case study in a real business process improvement project, to demonstrate its superiority over the conventional method. A questionnaire consisted of 10 questions using Likert scale was designed and given to the participants (managers of Bank Refah Kargaran three managerial levels). By examining the results of the questionnaire, it can be said that the proposed framework provide support for correct and timely decisions by increasing the clarity and transparency of the business processes which led to success in BPM projects.

Keywords: business process management (BPM), business process modeling, business process reengineering (BPR), business process optimizing, BPMN

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Authors: Ghoul Rachid Brahim

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Introduction: Back pain is a real public health problem with a significant socio-economic impact. It is the consequence of a degeneration of the lumbar intervertebral disc (IVD). This often asymptomatic pathology is compatible with an active life. As soon as it becomes symptomatic, conservative treatment is recommended in the majority of cases. The physical or functional disability is resistant to well-monitored conservative treatment, which justifies a surgical alternative which imposes a well-studied reflection on the objectives to be achieved. Objective: Evaluate the indication and short and medium term contribution of surgery in the management of painful degenerative lumbar disc disease. To prove the effectiveness of surgical treatment in the management of painful lumbar degenerative disc disease. Materials and methods: This is a prospective descriptive mono-centric study without comparison group, comprising a series of 104 patients suffering from lumbar painful degenerative disc disease treated surgically. Retrospective analysis of data collected prospectively. Comparison between pre and postoperative clinical status, by pain self-assessment scores and on the impact on pre and postoperative quality of life (3, 6 to 12 months). Results: This study showed that patients who received surgical treatment had great improvements in symptoms, function and several health-related quality of life in the first year after surgery. Conclusions: The surgery had a significantly positive impact on patients' pain, disability and quality of life. Overall, 97% of the patients were satisfied.

Keywords: degenerative disc disease, intervertebral disc, several health-related quality, lumbar painful

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Authors: Adam Jenkins

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The Maritime RobotX Challenge provides a platform for postgraduate students conducting research in autonomous robotic systems to participate in an international competition. Although targeted to postgraduate students, the problem domain lends itself to a wide range of different levels of student expertise. In 2022, undergraduate Information Technology students from the University of South Australia undertook the challenge, utilizing a System of the Systems approach to the project's architecture. Each student group produced an independent solution to an identified task, which was then implemented on a Single Board Computer (SBC). A Central Control System then engaged each solution when appropriate, allowing the encapsulated SBC systems to manage each task as it was encountered. This approach facilitated collaboration among the multiple independent student teams over an 18-month period, and the fundamental system-agnostic architecture allowed for both the variance in student solutions and the limitations caused by the global electronics shortage. By adopting this approach, Information Technology teams were able to work independently yet produce an effective solution, leveraging their expertise to develop and construct an autonomous catamaran capable of meeting the competition's demanding requirements while producing a high level of engagement. The System of Systems approach is recommended to other universities interested in competing at this level and engaging students in a real-world problem.

Keywords: case study, robotics, education, programming, system of systems, multi-disciplinary collaboration

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Authors: Abdessalam Hijab, Hafida Boulekbache, Eric Henry

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According to several research studies, the city as a whole is a complex, spatially organized system; its modeling must take into account several factors, socio-economic, and political, or geographical, acting at multiple scales of observation according to varied temporalities. Sustainable management and protection of the environment in this complex system require significant human and technical investment, particularly for monitoring and maintenance. The objective of this paper is to propose an intelligent approach based on the coupling of Geographic Information System (GIS) and Information and Communications Technology (ICT) tools in order to integrate the inhabitants in the processes of sustainable management and protection of the urban environment, specifically in the processes of household waste collection in urban areas. We are discussing a collaborative 'city/inhabitant' space. Indeed, it is a geo-collaborative approach, based on the spatialization and real-time geo-localization of topological and multimedia data taken by the 'active' inhabitant, in the form of geo-localized alerts related to household waste issues in their city. Our proposal provides a good understanding of the extent to which civil society (inhabitants) can help and contribute to the development of complementary solutions for the collection of household waste and the protection of the urban environment. Moreover, it allows the inhabitant to contribute to the enrichment of a data bank for future uses. Our geo-collaborative model will be tested in the Lamkansa sampling district of the city of Casablanca in Morocco.

Keywords: geographic information system, GIS, information and communications technology, ICT, geo-collaboration, inhabitants, city

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Authors: T. Nishido, S. Fukumoto

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The functions of movable bearings decline due to corrosion and sediments. As the result, they cannot move or rotate according to the behaviors of girders. Because of the constraints, the bending moments are generated by the horizontal reaction forces and the heights of girders. Under these conditions, the authors obtained the following results by analysis and experiment. Tensile stresses due to the moments occurred at temperature fluctuations. The large tensile stresses on concrete slabs around the bearings caused cracks. Even if concrete slabs are newly replaced, cracks will come out again with function declined bearings. The functional declines of bearings are generally found by using displacement gauges. However the method is not suitable for long-term measurements. We focused on the change in the strains at the bearings and the lower flanges near them at temperature fluctuations. It was found that their strains were particularly large when the movements of the bearings were constrained. Therefore, we developed a long-term health monitoring wireless system with FBG (Fiber Bragg Grating) sensors which were attached to bearings and lower flanges. The FBG sensors have the characteristics such as non-electrical influence, resistance to weather, and high strain sensitivity. Such characteristics are suitable for long-term measurements. The monitoring system was inexpensive because it was limited to the purpose of measuring strains and temperature. Engineers can monitor the behaviors of bearings in real time with the wireless system. If an office is away from bridge sites, the system will save traveling time and cost.

Keywords: bridge bearing, concrete slab, 　FBG sensor, health monitoring

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Authors: M. N. Khajavi, S. Nasiri, E. Farokhi, M. R. Bavir

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Alcohol fuels are renewable, have low pollution and have high octane number; therefore, they are important as fuel in internal combustion engines. Percentage detection of these alcoholic fuels with gasoline is a complicated, time consuming, and expensive process. Nowadays, these processes are done in equipped laboratories, based on international standards. The aim of this research is to determine percentage detection of different fuels based on vibration analysis of engine block signals. By doing, so considerable saving in time and cost can be achieved. Five different fuels consisted of pure gasoline (G) as base fuel and combination of this fuel with different percent of ethanol and methanol are prepared. For example, volumetric combination of pure gasoline with 10 percent ethanol is called E10. By this convention, we made M10 (10% methanol plus 90% pure gasoline), E30 (30% ethanol plus 70% pure gasoline), and M30 (30% Methanol plus 70% pure gasoline) were prepared. To simulate real working condition for this experiment, the vehicle was mounted on a chassis dynamometer and run under 1900 rpm and 30 KW load. To measure the engine block vibration, a three axis accelerometer was mounted between cylinder 2 and 3. After acquisition of vibration signal, eight time feature of these signals were used as inputs to an Adaptive Neuro Fuzzy Inference System (ANFIS). The designed ANFIS was trained for classifying these five different fuels. The results show suitable classification ability of the designed ANFIS network with 96.3 percent of correct classification.

Keywords: internal combustion engine, vibration signal, fuel composition, classification, ANFIS

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Authors: Sarina Zainab Shirazi

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Abstract— With the advent of globalization, different countries have liberalized their trade policies to enhance economic integration and developmental processes but the advantages accrued vary greatly from region to region. This study specifically examines European Union (EU) and Association for South East Asian Nations (ASEAN), two regions that show contrasting integration patterns. EU shows most successful integrations versus the slower paced integration in the ASEAN region. A comprehensive panel data empirical investigation of EU and ASEAN in the context of economy size, geographical distances, language, ethnicity, common border and regional trade agreements (RTA) is conducted for a period of 1985 – 2015. The empirical investigation through the augmented gravity equation shows that the real effectiveness for enhanced intra-regional trade is significant when specific examination of export and import components is conducted in the presence of non-tariff barriers. These barriers surface in the form of terms of trade openness, inflation, exchange rate, common borders, common language, ethnic similarity, and presence of a formal regional trade agreement (RTA). Thus, these factors can be utilized by the EU and ASEAN regions in order to formulate effective policy tools to enhance trade within their respective spheres of influence.

Keywords: Association for South East Asian Nations, European Union, Gravity Model, Regional Trade

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Authors: Hanna Poikonen, Petri Toiviainen, Mari Tervaniemi

Abstract:

Event-related potentials (ERPs) evoked by simple tones in the brain have been extensively studied. However, in reality the music surrounding us is spectrally and temporally complex and dynamic. Thus, the research using natural sounds is crucial in understanding the operation of the brain in its natural environment. Music is an excellent example of natural stimulation, which, in various forms, has always been an essential part of different cultures. In addition to sensory responses, music elicits vast cognitive and emotional processes in the brain. When compared to laymen, professional musicians have stronger ERP responses in processing individual musical features in simple tone sequences, such as changes in pitch, timbre and harmony. Here we show that the ERP responses evoked by rapid changes in individual musical features are more intense in musicians than in laymen, also while listening to long excerpts of the composition Carmen. Interestingly, for professional dancers, the amplitudes of the cognitive P300 response are weaker than for musicians but still stronger than for laymen. Also, the cognitive P300 latencies of musicians are significantly shorter whereas the latencies of laymen are significantly longer. In contrast, sensory N100 do not differ in amplitude or latency between musicians and laymen. These results, acquired from a novel ERP methodology for natural music, suggest that we can take the leap of studying the brain with long pieces of natural music also with the ERP method of electroencephalography (EEG), as has already been made with functional magnetic resonance (fMRI), as these two brain imaging devices complement each other.

Keywords: electroencephalography, expertise, musical features, real-life music

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Authors: Kamel A. Elshorbagy, Mohamed A. Hussein, Rola S. Afify

Abstract:

Natural gas pressure reduction is typically achieved using pressure reducing valves, where isenthalpic expansion takes place with considerable amount of wasted energy in an irreversible throttling process of the gas. Replacing gas-throttling process by an expansion process in a turbo expander (TE) converts the pressure of natural gas into mechanical energy transmitted to a loading device (i.e. an electric generator). This paper investigates the performance of a turboexpander system for power recovery at natural gas pressure reduction stations. There is a considerable temperature drop associated with the turboexpander process. Essential preheating is required, using gas fired boilers, to avoid undesirable effects of a low outlet temperature. Various system configurations were simulated by the general flow sheet simulator HYSYS and factors affecting the overall performance of the systems were investigated. Power outputs and fuel requirements were found using typical gas flow variation data. The simulation was performed for two case studies in which real input data are used. These case studies involve a domestic (commercial) and an industrial natural gas pressure reduction stations in Egypt. Economic studies of using the turboexpander system in both of the two natural gas pressure reduction stations are conducted using precise data obtained through communication with several companies working in this field. The results of economic analysis, for the two case studies, prove that using turboexpander systems in Egyptian natural gas reduction stations can be a successful project for energy conservation.

Keywords: natural gas, power recovery, reduction stations, turboexpander systems

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Authors: Hui Zhang, Ye Tian, Fang Ye, Ziming Guo

Abstract:

Communication signal modulation recognition technology is one of the key technologies in the field of modern information warfare. At present, communication signal automatic modulation recognition methods are mainly divided into two major categories. One is the maximum likelihood hypothesis testing method based on decision theory, the other is a statistical pattern recognition method based on feature extraction. Now, the most commonly used is a statistical pattern recognition method, which includes feature extraction and classifier design. With the increasingly complex electromagnetic environment of communications, how to effectively extract the features of various signals at low signal-to-noise ratio (SNR) is a hot topic for scholars in various countries. To solve this problem, this paper proposes a feature extraction algorithm for the communication signal based on the improved Holder cloud feature. And the extreme learning machine (ELM) is used which aims at the problem of the real-time in the modern warfare to classify the extracted features. The algorithm extracts the digital features of the improved cloud model without deterministic information in a low SNR environment, and uses the improved cloud model to obtain more stable Holder cloud features and the performance of the algorithm is improved. This algorithm addresses the problem that a simple feature extraction algorithm based on Holder coefficient feature is difficult to recognize at low SNR, and it also has a better recognition accuracy. The results of simulations show that the approach in this paper still has a good classification result at low SNR, even when the SNR is -15dB, the recognition accuracy still reaches 76%.

Keywords: communication signal, feature extraction, Holder coefficient, improved cloud model

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Authors: Ali Essam El Shazly

Abstract:

The slum survey of 'Sequina' area in Alexandria details the building rooms of twenty-building samples according to the integral measure of space syntax. The essence of room organization sets the most integrative 'visitor' domain between the 'inhabitant' wings of less integrated 'parent' than the 'children' structure with visual ring of 'balcony' space. Despite the collective real relative asymmetry of 'pheno-type' aggregation, the relative asymmetry of individual layouts reveals 'geno-type' structure of spatial diversity. The multifunction of rooms optimizes the integral structure of graph and visibility merge, which contrasts with the deep tailing structure of distinctive social domains. The most integrative layout inverts the geno-type into freed rooms of shallow 'inhabitant' domain against the off-centered 'visitor' space, while the most segregated layout further restricts the pheno-type through isolated 'visitor' from 'inhabitant' domains across the 'staircase' public domain. The catalyst 'kitchen & living' spaces demonstrate multi-structural dimensions among the various social domains. The former ranges from most exposed central integrity to the most hidden 'motherhood' territories. The latter, however, mostly integrates at centrality or at the further ringy 'childern' domain. The study concludes social structure of spatial integrity for redevelopment, which is determined through the micro-level survey of rooms with integral dimensions.

Keywords: Alexandria, Sequina slum, spatial integration, space syntax

Procedia PDF Downloads 439