Search results for: virtual machine migration

Authors: Andres M. Tuates Jr., Ofero A. Caparino

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Plastics have achieved a dominant position in agriculture because of their transparency, lightness in weight, impermeability to water and their resistance to microbial attack. However, this generates a higher quantity of wastes that are difficult to dispose of by farmers. To address these problems, the project aim to develop and evaluate the biodegradable film for mango fruit bag during development. The PBS and starch were melt-blended in a twin-screw extruder and then blown into film extrusion machine. The physic-chemical-mechanical properties of biodegradable fruit bag were done following standard methods of test. Field testing of fruit bag was also conducted to evaluate its durability and efficiency field condition. The PHilMech-FiC fruit bag is made of biodegradable material measuring 6 x 8 inches with a thickness of 150 microns. The tensile strength is within the range of LDPE while the elongation is within the range of HDPE. It is projected that after thirty-six (36) weeks, the film will be totally degraded. Results of field testing show that the quality of harvested fruits using PHilMech-FiC biodegradable fruit bag in terms of percent marketable, non-marketable and export, peel color at the ripe stage, flesh color, TSS, oBrix, percent edible portion is comparable with the existing bagging materials such as Chinese brown paper bag and old newspaper.

Keywords: cassava starch, PBS, biodegradable, chemical, mechanical properties

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Authors: Xinghui Wu, Chun Yang

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Inertial microfluidics is a competitive fluidic method with applications in separation of particles, cells and bacteria. In contrast to traditional microfluidic devices with low Reynolds number, inertial microfluidics works in the intermediate Re number range which brings about several intriguing inertial effects on particle separation/focusing to meet the throughput requirement in the real-world. Geometric modifications to make channels become irregular shapes can leverage fluid inertia to create complex secondary flow for adjusting the particle equilibrium positions and thus enhance the separation resolution and throughput. Although inertial microfluidics has been extensively studied by experiments, our current understanding of its mechanisms is poor, making it extremely difficult to build rational-design guidelines for the particle focusing locations, especially for irregularly shaped microfluidic channels. Inertial particle microfluidics in irregularly shaped channels were investigated in our group. There are several fundamental issues that require us to address. One of them is about the balance between the inertial lift forces and the secondary drag forces. Also, it is critical to quantitatively describe the dependence of the life forces on particle-particle interactions in irregularly shaped channels, such as a rectangular one. To provide physical insights into the inertial microfluidics in channels of irregular shapes, in this work the immersed boundary-lattice Boltzmann method (IB-LBM) was introduced and validated to explore the transport characteristics and the underlying mechanisms of an inertial focusing single particle in a rectangular microchannel. The transport dynamics of a finitesized particle were investigated over wide ranges of Reynolds number (20 < Re < 500) and particle size. The results show that the inner equilibrium positions are more difficult to occur in the rectangular channel, which can be explained by the secondary flow caused by the presence of a finite-sized particle. Furthermore, force decoupling analysis was utilized to study the effect of each type of lift force on the inertia migration, and a theoretical model for the lateral lift force of a finite-sized particle in the rectangular channel was established. Such theoretical model can be used to provide theoretical guidance for the design and operation of inertial microfluidics.

Keywords: inertial microfluidics, particle focuse, life force, IB-LBM

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Authors: Junkyeong Kim, Jooyoung Park, Aoqi Zhang, Seunghee Park

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The tensile force of Pre-Stressed Concrete (PSC) girder is the most important factor for evaluating the performance of PSC girder bridges. To measure the tensile force of PSC girder, several NDT methods were studied. However, conventional NDT method cannot be applied to the real-size PSC girder because the PS tendons could not be approached. To measure the tensile force of real-size PSC girder, this study proposed embedded EM sensor based tensile force estimation method. The embedded EM sensor could be installed inside of PSC girder as a sheath joint before the concrete casting. After curing process, the PS tendons were installed, and the tensile force was induced step by step using hydraulic jacking machine. The B-H loop was measured using embedded EM sensor at each tensile force steps and to compare with actual tensile force, the load cell was installed at each end of girder. The magnetization energy loss, that is the closed area of B-H loop, was decreased according to the increase of tensile force with regular pattern. Thus, the tensile force could be estimated by the tracking the change of magnetization energy loss of PS tendons. Through the experimental result, the proposed method can be used to estimate the tensile force of the in-situ real-size PSC girder bridge.

Keywords: tensile force estimation, embedded EM sensor, magnetization energy loss, PSC girder

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Authors: Anum Javed

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This study identifies the dynamical image of human body that continues its metamorphosis in the virtual field of reality. It calls attention to the ways where humans start co-evolving with other life forms; technology in particular and are striving to establish a realm outside the physical framework of matter. The problem exceeds the area of technological ethics by explicably and explanatorily entering the space of literary texts and criticism. Textual analysis of Geek Love (1989) by Katherine Dunn is adjoined with posthumanist perspectives of Pramod K. Nayar to beget psycho-somatic changes in man’s nature of being. It uncovers the meaning people give to their experiences in this budding social and cultural phenomena of material representation tied up with personal practices and technological innovations. It also observes an ethical, physical and psychological reassessment of man within the context of technological evolutions. The study indicates the elements that have rendered morphological freedom and new materialism in man’s consciousness. Moreover this work is inquisitive of what it means to be a human in this time of accelerating change where surgeries, implants, extensions, cloning and robotics have shaped a new sense of being. It attempts to go beyond individual’s body image and explores how objectifying media and culture have influenced people’s judgement of others on new material grounds. It further argues a decentring of the glorified image of man as an independent entity because of his energetic partnership with intelligent machines and external agents. The history of the future progress of technology is also mentioned. The methodology adopted is posthumanist techno-ethical textual analysis. This work necessitates a negotiating relationship between man and technology in order to achieve harmonic and balanced interconnected existence. The study concludes by recommending a call for an ethical set of codes to be cultivated for the techno-human habituation. Posthumanism ushers a strong need of adopting new ethics within the terminology of neo-materialist humanism.

Keywords: corporeality, dematerialism, human ethos, posthumanism

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Authors: Cindy Davis

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Higher education is changing globally and there is increasing pressure from professional social work accreditation bodies for academic programs to demonstrate how students have successfully met mandatory graduate competencies. As professional accreditation organizations increase their demand for evidence of graduate competencies, strategies to document and recording learning outcomes becomes increasingly challenging for academics and students. Studies in higher education have found support for the pedagogical value of ePortfolios, a flexible personal learning space that is owned by the student and include opportunity for assessment, feedback and reflection as well as a virtual space to store evidence of demonstration of professional competencies and graduate attributes. Examples of institutional uses of ePortfolios include e-administration of a diverse student population, assessment of student learning, and the demonstration of graduate attributes attained and future student career preparation. The current paper presents a case study on the introduction of ePortfolios for social work graduates in Australia as part of an institutional approach to technology-enhanced learning and e-learning. Social work graduates were required to submit an ePortfolio hosted on PebblePad. The PebblePad platform was selected because it places the student at the center of their learning whilst providing powerful tools for staff to structure, guide and assess that learning. The ePortofolio included documentation and evidence of how the student met each graduate competency as set out by the social work accreditation body in Australia (AASW). This digital resource played a key role in the process of external professional accreditation by clearly documenting and evidencing how students met required graduate competencies. In addition, student feedback revealed a positive outcome on how this resource provided them with a consolidation of their learning experiences and assisted them in obtaining employment post-graduation. There were also significant institutional factors that were key to successful implementation such as investment in the digital technology, capacity building amongst academics, and technical support for staff and students.

Keywords: accreditation, social work, teaching, technology

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Authors: Felix Boehnisch, Alexander Lutz

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Based on the number of users and the amount of content posted daily, Facebook is considered the largest social network in the world. This content includes images or text posts from companies but also private persons, which are also commented on by other users. However, it can sometimes be difficult for companies to keep track of all the posts and the reactions to them, especially when there are several posts a day that contain hundreds to thousands of comments. To facilitate this, the following paper deals with the possible applications of sentiment analysis to social media comments in order to be able to support the work in social media marketing. In a first step, post comments were divided into positive and negative by a subjective rating, then the same comments were checked for their polarity value by the two german python libraries TextBlobDE and SentiWS and also grouped into positive, negative, or even neutral. As a control, the subjective classifications were compared with the machine-generated ones by a confusion matrix, and relevant quality criteria were determined. The accuracy of both libraries was not really meaningful, with 60% to 66%. However, many words or sentences were not evaluated at all, so there seems to be room for optimization to possibly get more accurate results. In future studies, the use of these specific German libraries can be optimized to gain better insights by either applying them to stricter cleaned data or by adding a sentiment value to emojis, which have been removed from the comments in advance, as they are not contained in the libraries.

Keywords: Facebook, German libraries, polarity, sentiment analysis, social media comments

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Authors: Darshini Mahadevia, Kanika Gounder, Saumya Lathia

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Cities, an outcome of natural growth and migration, are ever-expanding due to urban sprawl. In the Global South, urban areas are experiencing a switch from public transport to private vehicles, coupled with intensified urban agglomeration, leading to frequent longer commutes by automobiles. This increase in travel distance and motorized vehicle kilometres lead to unsustainable cities. To achieve the nationally pledged GHG emission mitigation goal, the government is prioritizing a modal shift to low-carbon transport modes like mass transit and paratransit. Mixed land-use and urban densification are crucial for the economic viability of these projects. Informed by desktop assessment of mobility plans and in-person primary surveys, the paper explores the challenges around urban densification and travel patterns in two Indian cities of contrasting nature- Surat, a metropolitan industrial city with a 5.9 million population and a very compact urban form, and Udaipur, a heritage city attracting large international tourists’ footfall, with limited scope for further densification. Dense, mixed-use urban areas often improve access to basic services and economic opportunities by reducing distances and enabling people who don't own personal vehicles to reach them on foot/ cycle. But residents travelling on different modes end up contributing to similar trip lengths, highlighting the non-uniform distribution of land-uses and lack of planned transport infrastructure in the city and the urban-peri urban networks. Additionally, it is imperative to manage these densities to reduce negative externalities like congestion, air/noise pollution, lack of public spaces, loss of livelihood, etc. The study presents a comparison of the relationship between transport systems with the built form in both cities. The paper concludes with recommendations for managing densities in urban areas along with promoting low-carbon transport choices like improved non-motorized transport and public transport infrastructure and minimizing personal vehicle usage in the Global South.

Keywords: India, low-carbon transport, travel behaviour, trip length, urban densification

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Authors: Agbortoko Manyigbe Ayuk Nkem, Eno Cynthia Osuh

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This paper sets to examine the relationship between climate change and urban livelihood through a vulnerability assessment of the urban poor in Douala. Urban development in Douala places priority towards industrial and city-centre development with little focus on the urban poor in terms of housing units and areas of sustenance. With the high rate of urbanisation and increased land prices, the urban poor are forced to occupy marginal lands which are mainly wetlands, wastelands and along abandoned neighbourhoods prone to natural hazards. Due to climate change and its effects, these wetlands are constantly flooded thereby destroying homes, properties, and crops. Also, most of these urban dwellers have found solace in urban agriculture as a means for survival. However, since agriculture in tropical regions like Cameroon depends largely on seasonal rainfall, the changes in rainfall pattern has led to misplaced periods for crop planting and a huge wastage of resources as rainfall becomes very unreliable with increased temperature levels. Data for the study was obtained from both primary and secondary sources. Secondary sources included published materials related to climate change and vulnerability. Primary data was obtained through focus-group discussions with some urban farmers while a stratified sampling of residents within marginal lands was done. Each stratum was randomly sampled to obtain information on different stressors related to climate change and their effect on livelihood. Findings proved that the high rate of rural-urban migration into Douala has led to increased prevalence of the urban poor and their vulnerability to climate change as evident in their constant fight against flood from unexpected sea level rise and irregular rainfall pattern for urban agriculture. The study also proved that women were most vulnerable as they depended solely on urban agriculture and its related activities like retailing agricultural products in different urban markets which to them serves as a main source of income in the attainment of basic needs for the family. Adaptation measures include the constant use of sand bags, raised makeshifts as well as cultivation along streams, planting after evidence of constant rainfall has become paramount for sustainability.

Keywords: adaptation, Douala, Cameroon, climate change, development, livelihood, vulnerability

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Authors: Hamidreza Ghazvinian, Khosro Ghazvinian, Touba Khodaiean

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The importance of evaporation estimation in water resources and agricultural studies is undeniable. Pan evaporation are used as an indicator to determine the evaporation of lakes and reservoirs around the world due to the ease of interpreting its data. In this research, intelligent models were investigated in estimating pan evaporation on a daily basis. Shahroud and Mayamey were considered as the studied cities. These two cities are located in Semnan province in Iran. The mentioned cities have dry weather conditions that are susceptible to high evaporation potential. Meteorological data of 11 years of synoptic stations of Shahrood and Mayamey cities were used. The intelligent models used in this study are Artificial Neural Network (ANN), Least Squares Support Vector Machine (LSSVM), and M5 tree models. Meteorological parameters of minimum and maximum air temperature (Tmax, Tmin), wind speed (WS), sunshine hours (SH), air pressure (PA), relative humidity (RH) as selected input data and evaporation data from pan (EP) to The output data was considered. 70% of data is used at the education level, and 30 % of the data is used at the test level. Models used with explanation coefficient evaluation (R2) Root of Mean Squares Error (RMSE) and Mean Absolute Error (MAE). The results for the two Shahroud and Mayamey stations showed that the above three models' operations are rather appropriate.

Keywords: pan evaporation, intelligent methods, shahroud, mayamey

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Authors: Amin Nezarat, Naeime Seifadini

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Trip mode selection is a behavioral characteristic of passengers with immense importance for travel demand analysis, transportation planning, and traffic management. Identification of trip mode distribution will allow transportation authorities to adopt appropriate strategies to reduce travel time, traffic and air pollution. The majority of existing trip mode inference models operate based on human selected features and traditional machine learning algorithms. However, human selected features are sensitive to changes in traffic and environmental conditions and susceptible to personal biases, which can make them inefficient. One way to overcome these problems is to use neural networks capable of extracting high-level features from raw input. In this study, the convolutional neural network (CNN) architecture is used to predict the trip mode distribution based on raw GPS trajectory data. The key innovation of this paper is the design of the layout of the input layer of CNN as well as normalization operation, in a way that is not only compatible with the CNN architecture but can also represent the fundamental features of motion including speed, acceleration, jerk, and Bearing rate. The highest prediction accuracy achieved with the proposed configuration for the convolutional neural network with batch normalization is 85.26%.

Keywords: predicting, deep learning, neural network, urban trip

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Authors: Clare Maxwell, Lorna Porcellato, Valerie Fleming, Kate Fleming

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A review of global online forums and social media reveals large numbers of mothers experiencing bottle refusal by their breastfed baby. It is difficult to determine precise numbers due to a lack of data, however, established virtual communities illustrate thousands of posts in relation to the issue. Mothers report various negative consequences of bottle refusal including delaying their return to work, time and financial outlay spent on methods to overcome it and experiencing stress, anxiety, and resentment of breastfeeding. A search of the literature revealed no studies being identified, and due to a lack of epidemiological data, a study investigating mother’s experiences of bottle refusal by their breastfed baby was undertaken. The aim of the study was to investigate UK mothers’ experiences of bottle refusal by their breastfed baby. Data were collected using an online questionnaire collecting quantitative and qualitative data. 841 UK mothers who had experienced or were experiencing bottle refusal by their breastfed baby completed the questionnaire. Data were analyzed using descriptive statistics and non-parametric testing. The results showed 61% (516/840) of mothers reported their breastfed baby was still refusing/had never accepted a bottle, with 39% (324/840) reporting their baby had eventually accepted. The most frequently reported reason to introduce a bottle was so partner/family could feed the baby 59% (499/839). 75% (634/841) of mothers intended their baby to feed on a bottle ‘occasionally’. Babies who accepted a bottle were more likely to be older at 1st attempt to introduce one than those babies who refused (Mdn = 12 weeks v 8 weeks, n = 286) (p = <0.001). Length of time taken to acceptance was 9 weeks (Mdn = 9, IQR = 18, R = 103.9, n = 306) with the older the baby was at 1st attempt to introduce a bottle being associated with a shorter length of time to acceptance (p = < 0.002). 60% (500/841) of mothers stated that none of the methods they used had worked. 26% (222/841) of mothers reported bottle refusal had had a negative impact upon their overall breastfeeding experience. 47% (303/604) reported they would have tried to introduce a bottle earlier to prevent refusal. This study provides a unique insight into the scenario of bottle refusal by breastfed babies. It highlights that bottle refusal by breastfed babies is a significant issue, which requires recognition from those communicating breastfeeding information to mothers.

Keywords: bottle feeding, bottle refusal, breastfeeding, infant feeding

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Authors: Tayyibah Khanam, Mohammad Saad Alam, Sanchari Deb, Yasser Rafat

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Electric vehicles are considered as viable replacements to gasoline cars since they help in reducing harmful emissions and stimulate power generation through renewable energy sources, hence contributing to sustainability. However, one of the significant obstacles in the mass deployment of electric vehicles is the charging time anxiety among users and, thus, the subsequent large waiting times for available chargers at charging stations. Data analytics, on the other hand, has revolutionized the decision-making tasks of management and operating systems since its arrival. In this paper, we attempt to optimize the choice of EV charging stations for users in their vicinity by minimizing the time taken to reach the charging stations and the waiting times for available chargers. Time taken to travel to the charging station is calculated by the Google Maps API and the waiting times are predicted by polynomial regression of the historical data stored. The proposed framework utilizes real-time data and historical data from all operating charging stations in the city and assists the user in finding the best suitable charging station for their current situation and can be implemented in a mobile phone application. The algorithm successfully predicts the most optimal choice of a charging station and the minimum required time for various sample data sets.

Keywords: charging data, electric vehicles, machine learning, waiting times

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Authors: Vidhu Mitha Goutham, Ruma Mukherjee

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The low availability of well-trained, unlimited, dynamic-access models for specific languages makes it hard for corporate users to adopt quick translation techniques and incorporate them into product solutions. As translation tasks increasingly require a dynamic sequence learning curve; stable, cost-free opensource models are scarce. We survey and compare current translation techniques and propose a modified sequence to sequence model repurposed with attention techniques. Sequence learning using an encoder-decoder model is now paving the path for higher precision levels in translation. Using a Convolutional Neural Network (CNN) encoder and a Recurrent Neural Network (RNN) decoder background, we use Fairseq tools to produce an end-to-end bilingually trained Spanish-English machine translation model including source language detection. We acquire competitive results using a duo-lingo-corpus trained model to provide for prospective, ready-made plug-in use for compound sentences and document translations. Our model serves a decent system for large, organizational data translation needs. While acknowledging its shortcomings and future scope, it also identifies itself as a well-optimized deep neural network model and solution.

Keywords: attention, encoder-decoder, Fairseq, Seq2Seq, Spanish, translation

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Authors: Ntaganda J.M., Maniraguha J.D., Mukeshimana S., Harelimana D, Bizimungu T., Ruataganda E.

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This paper presents the design of Graphic User Interface (GUI) in Matlab as interaction tool between human and machine. The designed GUI can be used by medical doctors and other experts particularly the physiologists. Matlab packages and estimated parameters of the mathematical model of cardiovascular-respiratory system developed in Rwandan context are used in GUI. The ordinary differential equations (ODE’s) govern a mathematical model in designing GUI in Matlab and a window that sets model estimated parameters and the measured parameters by any user. For healthy subject, these measured parameters include heart rate, systolic blood and diastolic blood pressure, partial pressure of oxygen in arterial blood, partial pressure of carbon dioxide in arterial blood, concentration of bound and dissolved oxygen in the mixed venous blood entering the lungs, and concentration of bound and dissolved carbon dioxide in the mixed venous blood entering the lungs. The results of numerical test give a consistent appearance as empirically known results.

Keywords: Graphic User Interface, mathematical model, cardiovascur-respiratory system, walking physical activity, blood pressure, oxygen

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Authors: Adrian-Gabriel Chifu, Sebastien Fournier

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One of the challenges of natural language understanding is to deal with the subjectivity of sentences, which may express opinions and emotions that add layers of complexity and nuance. Sentiment analysis is a field that aims to extract and analyze these subjective elements from text, and it can be applied at different levels of granularity, such as document, paragraph, sentence, or aspect. Aspect-based sentiment analysis is a well-studied topic with many available data sets and models. However, there is no clear definition of what makes a sentence difficult for aspect-based sentiment analysis. In this paper, we explore this question by conducting an experiment with three data sets: ”Laptops”, ”Restaurants”, and ”MTSC” (Multi-Target-dependent Sentiment Classification), and a merged version of these three datasets. We study the impact of domain diversity and syntactic diversity on difficulty. We use a combination of classifiers to identify the most difficult sentences and analyze their characteristics. We employ two ways of defining sentence difficulty. The first one is binary and labels a sentence as difficult if the classifiers fail to correctly predict the sentiment polarity. The second one is a six-level scale based on how many of the top five best-performing classifiers can correctly predict the sentiment polarity. We also define 9 linguistic features that, combined, aim at estimating the difficulty at sentence level.

Keywords: sentiment analysis, difficulty, classification, machine learning

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Authors: Carolina Arriagada, Yasna Contreras

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Since mid-2000, the migratory flows of Latin American migrants to Chile have been increasing constantly. There are two reasons that would explain why Chile is presented as an attractive country for the migrants. On the one hand, traditional centres of migrants’ attraction such as the United States and Europe have begun to close their borders. On the other hand, Chile exhibits relative economic and political stability, which offers greater job opportunities and better standard of living when compared to the migrants’ origin country. At the same time, the neoliberal economic model of Chile, developed under an extractive production of the natural resources, has privatized the urban space. The market regulates the growth of the fragmented and segregated cities. Then, the vulnerable population, most of the time, is located in the periphery and in the marginal areas of the urban space. In this aspect, the migrants have begun to occupy those degraded and depressed areas of the city. The problem raised is that the increase of the social spatial segregation could be also attributed to the migrants´ occupation of the marginal urban places of the city. The aim of this investigation is to carry out an analysis of the migrants’ housing strategies, which are transforming the marginal areas of the city. The methodology focused on the urban experience of the migrants, through the observation of spatial practices, ways of living and networks configuration in order to transform the marginal territory. The techniques applied in this study are semi–structured interviews in-depth interviews. The study reveals that the migrants housing strategies for living in the marginal areas of the city are built on a paradox way. On the one hand, the migrants choose proximity to their place of origin, maintaining their identity and customs. On the other hand, the migrants choose proximity to their social and familiar places, generating sense of belonging. In conclusion, the migration as international displacements under a globalized economic model increasing socio spatial segregation in cities is evidenced, but the transformation of the marginal areas is a fundamental resource of their integration migratory process. The importance of this research is that it is everybody´s responsibility not only the right to live in a city without any discrimination but also to integrate the citizens within the social urban space of a city.

Keywords: migrations, marginal space, resignification, visibility

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Authors: Masaumi Nakahara, Sou Watanabe, Hiromichi Ogi, Atsuhiro Shibata, Kazunori Nomura

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In the Japan Atomic Energy Agency, three types of experimental research, advanced reactor fuel reprocessing, radioactive waste disposal, and nuclear fuel cycle technology, have been carried out at the Chemical Processing Facility. The facility has generated high level radioactive liquid and solid wastes in hot cells. The high level radioactive solid waste is divided into three main categories, a flammable waste, a non-flammable waste, and a solid reagent waste. A plastic product is categorized into the flammable waste and molten with a heating mantle. The non-flammable waste is cut with a band saw machine for reducing the volume. Among the solid reagent waste, a used adsorbent after the experiments is heated, and an extractant is decomposed for its stabilization. All high level radioactive solid wastes in the hot cells are packed in a high level radioactive solid waste can. The high level radioactive solid waste can is transported to the 2nd High Active Solid Waste Storage in the Tokai Reprocessing Plant in the Japan Atomic Energy Agency.

Keywords: high level radioactive solid waste, advanced reactor fuel reprocessing, radioactive waste disposal, nuclear fuel cycle technology

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Authors: Wafaa Salah, Mostafa A. Salama, Jane Doe

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Recently, the corporate social performance (CSP) is not less important than the corporate financial performance (CFP). Debate still exists about the nature of the relationship between the CSP and CFP, whether it is a positive, negative or a neutral correlation. The objective of this study is to explore the relationship between corporate social responsibility (CSR) reports and CFP. The study uses the accounting-based and market-based quantitative measures to quantify the financial performance of seven organizations listed on the Egyptian Stock Exchange in 2007-2014. Then uses the information retrieval technologies to quantify the contribution of each of the three dimensions of the corporate social responsibility report (environmental, social and economic). Finally, the correlation between these two sets of variables is viewed together in a model to detect the correlations between them. This model is applied on seven firms that generate social responsibility reports. The results show a positive correlation between the Earnings per share (market based measure) and the economical dimension in the CSR report. On the other hand, total assets and property, plant and equipment (accounting-based measure) are positively correlated to the environmental and social dimensions of the CSR reports. While there is not any significant relationship between ROA, ROE, Operating income and corporate social responsibility. This study contributes to the literature by providing more clarification of the relationship between CFP and the isolated CSR activities in a developing country.

Keywords: financial, social, machine learning, corporate social performance, corporate social responsibility

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Authors: Rafi Ullah, Shah Muhammad Emaduddin, Taha Jilani

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Vehicle Adhoc Networks (VANET) belongs to a special class of Mobile Adhoc Network (MANET) with high mobility. Network is created by road side vehicles equipped with communication devices like GPS and Wifi etc. Since the environment is highly dynamic due to difference in speed and high mobility of vehicles and weak stability of the network connection, it is a challenging task to design an efficient routing protocol for such an unstable environment. Our proposed algorithm uses heuristic for the calculation of optimal path for routing the packet efficiently in collaboration with several other parameters like geographical location, speed, priority, the distance among the vehicles, communication range, and networks congestion. We have incorporated probabilistic, heuristic and machine learning based approach inconsistency with the relay function of the memory buffer to keep the packet moving towards the destination. These parameters when used in collaboration provide us a very strong and admissible heuristics. We have mathematically proved that the proposed technique is efficient for the routing of packets, especially in a medical emergency situation. These networks can be used for medical emergency, security, entertainment and routing purposes.

Keywords: heuristics routing, intelligent routing, VANET, route optimization

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Authors: Vimala Rani P, Narasimha Malikarjunan, Mercy Shalinie S

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Data Networking was brought forth as an instantiation of information-centric networking. The attackers can send a colossal number of spoofs to take hold of the Pending Interest Table (PIT) named an Interest Flooding attack (IFA) since the in- interests are recorded in the PITs of the intermediate routers until they receive corresponding Data Packets are go beyond the time limit. These attacks can be detrimental to network performance. PIT expiration rate or the Interest satisfaction rate, which cannot differentiate the IFA from attacks, is the criterion Traditional IFA detection techniques are concerned with. Threshold values can casually affect Threshold-based traditional methods. This article proposes an accurate IFA detection mechanism based on a Multiple Feature-based Extreme Learning Machine (MF-ELM). Accuracy of the attack detection can be increased by presenting the entropy of Internet names, Interest satisfaction rate and PIT usage as features extracted in the MF-ELM classifier. Furthermore, we deploy a queue-based hostile Interest prefix mitigation mechanism. The inference of this real-time test bed is that the mechanism can help the network to resist IFA with higher accuracy and efficiency.

Keywords: information-centric network, pending interest table, interest flooding attack, MF-ELM classifier, queue-based mitigation strategy

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Authors: Swati Swati, Yuhang Chen, Robert Reuben

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Coronary stents are devices resembling the shape of a tube which are placed in coronary arteries, to keep the arteries open in the treatment of coronary arterial diseases. Coronary stents are routinely deployed to clear atheromatous plaque. The stent essentially applies an internal pressure to the artery because its structure is cylindrically symmetrical and this may introduce some abnormalities in final arterial shape. The goal of the project is to develop segmented circumferential arterial compliance measuring devices which can be deployed (eventually) in vivo. The segmentation of the device will allow the mechanical asymmetry of any stenosis to be assessed. The purpose will be to assess the quality of arterial tissue for applications in tailored stents and in the assessment of aortic aneurism. Arterial distensibility measurement is of utmost importance to diagnose cardiovascular diseases and for prediction of future cardiac events or coronary artery diseases. In order to arrive at some generic outcomes, a preliminary experimental set-up has been devised to establish the measurement principles for the device at macro-scale. The measurement methodology consists of a strain gauge system monitored by LABVIEW software in a real-time fashion. This virtual instrument employs a balloon within a gelatine model contained in a split cylinder with strain gauges fixed on it. The instrument allows automated measurement of the effect of air-pressure on gelatine and measurement of strain with respect to time and pressure during inflation. Compliance simple creep model has been applied to the results for the purpose of extracting some measures of arterial compliance. The results obtained from the experiments have been used to study the effect of air pressure on strain at varying time intervals. The results clearly demonstrate that with decrease in arterial volume and increase in arterial pressure, arterial strain increases thereby decreasing the arterial compliance. The measurement system could lead to development of portable, inexpensive and small equipment and could prove to be an efficient automated compliance measurement device.

Keywords: arterial compliance, atheromatous plaque, mechanical symmetry, strain measurement

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Authors: Chrysoula Karathanasi, Senad Karavdic, Angela Odero, Michèle Baumann

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It is not only the economic determinants that impact on life conditions, but maintaining a good level of life satisfaction (LS) may also be an important challenge currently. In Luxembourg, university students receive financial aid from the government. They are then registered at the Centre for Documentation and Information on Higher Education (CEDIES). Luxembourg is built on migration with almost half its population consisting of foreigners. It is upon this basis that our research aims to analyze the associations with mental health factors (health satisfaction, psychological quality of life, worry), perceived financial situation, career attitudes (adaptability, optimism, knowledge, planning) and LS, for non-Luxembourgish and native postgraduate students. Between 2012 and 2013, postgraduates registered at CEDIES were contacted by post and asked to participate in an online survey with either the option of English or French. The study population comprised of 644 respondents. Our statistical analysis excluded: those born abroad who had Luxembourgish citizenship, or those born in Luxembourg who did not have citizenship. Two groups were formed one consisting 147 non-Luxembourgish and the other 284 natives. A single item measured LS (1=not at all satisfied to 10=very satisfied). Bivariate tests, correlations and multiple linear regression models were used in which only significant relationships (p<0.05) were integrated. Among the two groups no differences were found between LS indicators (7.8/10 non-Luxembourgish; 8.0/10 natives) as both were higher than the European indicator of 7.2/10 (for 25-34 years). In the case of non-Luxembourgish students, they were older than natives (29.3 years vs. 26.3 years) perceived their financial situation as more difficult, and a higher percentage of their parents had an education level higher than a Bachelor's degree (father 59.2% vs 44.6% for natives; mother 51.4% vs 33.7% for natives). In addition, the father’s education was related to the LS of postgraduates and the higher was the score, the greater was the contribution to LS. Whereas for native students, when their scores of health satisfaction and career optimism were higher, their LS’ score was higher. For both groups their LS was linked to mental health-related factors, perception of their financial situation, career optimism, adaptability and planning. The higher the psychological quality of life score was, the greater the LS of postgraduates’ was. Good health and positive attitudes related to the job market enhanced their LS indicator.

Keywords: career attributes, father's education level, life satisfaction, mental health

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Authors: Aikaterini Tavoulari, Michael Proulx, Karin Petrini

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Objective: This study aims to explore the unique challenges faced by young individuals with vision impairment (VI) during key life transitions, utilizing a community-based participatory research (CBPR) approach to identify limitations and positive aspects of existing support systems, with a focus on accessibility and diversity. Design: The study employs a qualitative CBPR design, engaging young participants with VI through online and in-person working groups over six months, prioritizing their active involvement and diverse perspectives. Methods: Twenty-one young individuals with VI from across the UK and with different VI conditions were recruited to participate in the study via a climbing and virtual reality event and stakeholders’ support. Data collection methods included open discussions, forum exchanges, and qualitative questionnaires. The data were analyzed with NVivo using inductive thematic analysis to identify key themes and patterns related to the challenges and experiences of life transitions for this diverse population. Results: The analysis revealed barriers to accessibility, such as assumptions about what a person with VI can do, inaccessibility to material, noisy environments, and insufficient training with assistive technologies. Enablers included guidance from diverse professionals and peers, multisensory approaches (beyond tactile), and peer collaborations. This study underscores the need for developing accessible and tailored strategies together with these young people to address the specific needs of this diverse population during critical life transitions (e.g., to independent living, employment and higher education). Conclusion: Engaging and co-designing effective approaches and tools with young people with VI is key to tackling the specific accessibility barriers they encounter. These approaches should be targeted at different transitional periods of their life journey, promoting diversity and inclusion.

Keywords: vision impairement, life transitions, qualitative research, community-based participatory design, accessibility

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Authors: Frederico Fialho Teixeira, Islam Mashaly, Maryam Shafiei, Jurij Karlovsek

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The ubiquity of data gathering and smart technologies, advancements in virtual technologies, and the development of the internet of things (IoT) have created urgent demands for the development of frameworks and efficient workflows for data collection, visualisation, and analysis. Digital twin, in different scales of the city into the building, allows for bringing together data from different sources to generate fundamental and illuminating insights for the management of current facilities and the lifecycle of amenities as well as improvement of the performance of current and future designs. Over the past two decades, there has been growing interest in the topic of digital twin and their applications in city and building scales. Most such studies look at the urban environment through a homogeneous or generalist lens and lack specificity in particular characteristics or identities, which define an urban university campus. Bridging this knowledge gap, this paper offers a framework for developing a digital twin for a university campus that, with some modifications, could provide insights for any large-scale digital twin settings like towns and cities. It showcases how currently unused data could be purposefully combined, interpolated and visualised for producing analysis-ready data (such as flood or energy simulations or functional and occupancy maps), highlighting the potential applications of such a framework for campus planning and policymaking. The research integrates campus-level data layers into one spatial information repository and casts light on critical data clusters for the digital twin at the campus level. The paper also seeks to raise insightful and directive questions on how digital twin for campus can be extrapolated to city-scale digital twin. The outcomes of the paper, thus, inform future projects for the development of large-scale digital twin as well as urban and architectural researchers on potential applications of digital twin in future design, management, and sustainable planning, to predict problems, calculate risks, decrease management costs, and improve performance.

Keywords: digital twin, smart campus, framework, data collection, point cloud

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Authors: Taylor Kolody, Farkhund Iqbal, Rabia Batool, Benjamin Fung, Mohammed Hussaeni, Saiqa Aleem

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The rising threat of climate change has led to an increase in public awareness and care about our collective and individual environmental impact. A key component of this impact is our use of cars and other polluting forms of transportation, but it is often difficult for an individual to know how severe this impact is. While there are applications that offer this feedback, they require manual entry of what transportation mode was used for a given trip, which can be burdensome. In order to alleviate this shortcoming, a data from the 2016 TRIPlab datasets has been used to train a variety of machine learning models to automatically recognize the mode of transportation. The accuracy of 89.6% is achieved using single deep neural network model with Gated Recurrent Unit (GRU) architecture applied directly to trip data points over 4 primary classes, namely walking, public transit, car, and bike. These results are comparable in accuracy to results achieved by others using ensemble methods and require far less computation when classifying new trips. The lack of trip context data, e.g., bus routes, bike paths, etc., and the need for only a single set of weights make this an appropriate methodology for applications hoping to reach a broad demographic and have responsive feedback.

Keywords: classification, gated recurrent unit, recurrent neural network, transportation

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Authors: Carolina S. Monteiro, Eugénia Pinto, Miguel A. Faria, Sara C. Cunha

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Rice (Oryza sativa) production plays a vital role in reducing hunger and poverty and assumes particular importance in low-income and developing countries. Rice is a sensitive plant, and production occurs strictly where suitable temperature and water conditions are found. Climatic changes are likely to affect worldwide, and some models have predicted increased temperatures, variations in atmospheric CO₂ concentrations and modification in precipitation patterns. Therefore, the ongoing climatic changes threaten rice production by increasing biotic and abiotic stress factors, and crops will grow in different environmental conditions in the following years. Around the world, the effects will be regional and can be detrimental or advantageous depending on the region. Mediterranean zones have been identified as possible hot spots, where dramatic temperature changes, modifications of CO₂ levels, and rainfall patterns are predicted. The actual estimated atmospheric CO₂ concentration is around 400 ppm, and it is predicted that it can reach up to 1000–1200 ppm, which can lead to a temperature increase of 2–4 °C. Alongside, rainfall patterns are also expected to change, with more extreme wet/dry episodes taking place. As a result, it could increase the migration of pathogens, and a shift in the occurrence of mycotoxins, concerning their types and concentrations, is expected. Mycotoxigenic spoilage fungi can colonize the crops and be present in all rice food chain supplies, especially Penicillium species, mainly resulting in ochratoxin A (OTA) contamination. In this scenario, the objectives of the present study are evaluating the effect of temperature (20 vs. 25 °C), CO₂ (400 vs. 1000 ppm), and water stress (0.93 vs 0.95 water activity) on growth and OTA production by a Penicillium nordicum strain in vitro on rice-based media and when colonizing layers of raw rice. Results demonstrate the effect of temperature, CO₂ and drought on the OTA production in a rice-based environment, thus contributing to the development of mycotoxins predictive models in climate change scenarios. As a result, improving mycotoxins' surveillance and monitoring systems, whose occurrence can be more frequent due to climatic changes, seems relevant and necessary. The development of prediction models for hazard contaminants presents in foods highly sensitive to climatic changes, such as mycotoxins, in the highly probable new agricultural scenarios is of paramount importance.

Keywords: climate changes, ochratoxin A, penicillium, rice

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Authors: Zhou Xiong, Kang Shao Bo, Yang Bo

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To date, high-performance structural steel has been widely used for columns in construction practices due to its significant advantages over conventional steel. However, the same design approach with conventional steel columns is still adopted in the design of high-performance steel columns. As a result, its superior properties cannot be fully considered in design. This paper conducts a test and finite element analysis on the overall stability behaviour of welded Q460GJ steel box columns. In the test, four steel columns with different slenderness and width-to-thickness ratio were compressed under an axial compression testing machine. And finite element models were established in which material nonlinearity and residual stress distributions of test columns were included. Then, comparisons were made between test results and finite element result, it showed that finite element analysis results are agree well with the test result. It means that the test and finite element model are reliable. Then, we compared the test result with the design value calculated by current code, the result showed that Q460GJ steel box columns have the higher overall buckling capacity than the design value. It is necessary to update the design curves for Q460GJ steel columns so that the overall stability capacity of Q460GJ box columns can be designed appropriately.

Keywords: axial compression, box columns, global buckling, numerical simulations, Q460GJ steel

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Authors: Xilu Liu, Ameen Farooq

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Beijing has several compact residential housing settings in many of its urban districts. The study in this paper reveals that urban compactness, as predictor of density, may carry an altogether different meaning in the developing world when compared to the U.S for achieving objectives of urban sustainability. Recent urban design studies in the U.S are debating for compact and mixed-use higher density housing to achieve sustainable and energy efficient living environments. While the concept of urban compactness is widely accepted as an approach in modern architectural and urban design fields, this belief may not directly carry well into all areas within cities of developing countries. Beijing’s technology-driven economy, with its historic and rich cultural heritage and a highly speculated real-estate market, extends its urban boundaries into multiple compact urban settings of varying scales and densities. The accelerated pace of migration from the countryside for better opportunities has led to unsustainable and uncontrolled buildups in order to meet the growing population demand within and outside of the urban center. This unwarranted compactness in certain urban zones has produced an unhealthy physical density with serious environmental and ecological challenging basic living conditions. In addition, crowding, traffic congestion, pollution and limited housing surrounding this compactness is a threat to public health. Several residential blocks in close proximity to each other were found quite compacted, or ill-planned, with residential sites due to lack of proper planning in Beijing. Most of them at first sight appear to be compact and dense but further analytical studies revealed that what appear to be dense actually are not as dense as to make a good case that could serve as the corner stone of sustainability and energy efficiency. This study considered several factors including floor area ratio (FAR), ground coverage (GSI), open space ratio (OSR) as indicators in analyzing urban compactness as a predictor of density. The findings suggest that these measures, influencing the density of residential sites under study, were much smaller in density than expected given their compact adjacencies. Further analysis revealed that several residential housing appear to support the notion of density in its compact layout but are actually compacted due to unregulated planning marred by lack of proper urban design standards, policies and guidelines specific to their urban context and condition.

Keywords: Beijing, density, sustainability, urban compactness

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Authors: B. Soni, S. Biswas

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Metal foams of Al find diverse applications in several industrial sectors such as in automotive and sports equipment industry as impact, acoustic and vibration absorbers, the aerospace industry as structural components in turbines and spatial cones, in the naval industry as low frequency vibration absorbers, and in construction industry as sound barriers inside tunnels, as fire proof materials and structure protection systems against explosions and even in heat exchangers, orthopedic components, and decorative items. Here, we report on the development of Al foams by a low cost and convenient technique of salt replication method with efficient control over size, geometry and distribution of the pores. Sodium bicarbonate was used as the foaming agent to form the porous refractory salt pattern. The mixed refractory salt slurry was microwave dried followed by sintering for selected time periods. Molten Al was infiltrated into the salt pattern in an inert atmosphere at a pressure of 2 bars. The final products were obtained by leaching out the refractory salt pattern. Mechanical properties of the derived samples were studied with a universal testing machine. The results were analyzed in correlation with their microstructural features evaluated with a scanning electron microscope (SEM).

Keywords: metal foam, Al, salt replication method, mechanical properties, SEM

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Authors: Samuel Owoade, Zainab Idowu, Idris Ajibade, Abel Uzoka

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Cloud computing adoption continues to soar, with 83% of enterprise workloads estimated to be in the cloud by 2022. However, this rapid migration raises security concerns, needing strong security management solutions to safeguard sensitive data and essential applications. This paper investigates the critical role of technical project managers in orchestrating security management initiatives for cloud environments, evaluating their responsibilities, challenges, and best practices for assuring the resilience and integrity of cloud infrastructures. Drawing from a comprehensive review of industry reports and interviews with cloud security experts, this research highlights the multifaceted landscape of security management in cloud environments. Despite the rapid adoption of cloud services, only 25% of organizations have matured their cloud security practices, indicating a pressing need for effective management strategies. This paper proposes a strategy framework adapted to the demands of technical project managers, outlining the important components of effective cloud security management. Notably, 76% of firms identify misconfiguration as a major source of cloud security incidents, underlining the significance of proactive risk assessment and constant monitoring. Furthermore, the study emphasizes the importance of technical project managers in facilitating cross-functional collaboration, bridging the gap between cybersecurity professionals, cloud architects, compliance officers, and IT operations teams. With 68% of firms seeing difficulties integrating security policies into their cloud systems, effective communication and collaboration are critical to success. Case studies from industry leaders illustrate the practical use of security management projects in cloud settings. These examples demonstrate the importance of technical project managers in using their expertise to address obstacles and generate meaningful outcomes, with 92% of firms reporting improved security practices after implementing proactive security management tactics. In conclusion, this research underscores the critical role of technical project managers in safeguarding cloud environments against evolving threats. By embracing their role as guardians of the cloud realm, project managers can mitigate risks, optimize resource utilization, and uphold the trust and integrity of cloud infrastructures in an era of digital transformation.

Keywords: cloud security, security management, technical project management, cybersecurity, cloud infrastructure, risk management, compliance

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