Search results for: graph representation of circuit networks

Authors: S. Shakibaei, P. Alpkokin

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The railway network is one of the major components of a transportation system in a country which may be an indicator of the country’s level of economic improvement. Since 2000s on, revival of national railways and development of High Speed Rail (HSR) lines are one of the most remarkable policies of Turkish government in railway sector. Within this trend, the railway age is to be revived and coming decades will be a golden opportunity. Indubitably, major infrastructures such as road and railway networks require sizeable investment capital, precise maintenance and reparation. Traditionally, governments are held responsible for funding, operating and maintaining these infrastructures. However, lack or shortage of financial resources, risk responsibilities (particularly cost and time overrun), and in some cases inefficacy in constructional, operational and management phases persuade governments to find alternative options. Financial power, efficient experiences and background of private sector are the factors convincing the governments to make a collaboration with private parties to develop infrastructures. Public-Private Partnerships (PPP or 3P or P3) and related regulatory issues are born considering these collaborations. In Turkey, PPP approaches have attracted attention particularly during last decade and these types of investments have been accelerated by government to overcome budget limitations and cope with inefficacy of public sector in improving transportation network and its operation. This study mainly tends to present a comprehensive overview of PPP concept, evaluate the regulatory procedure in Europe and propose a general framework for Turkish State Railways (TCDD) as an outlook on privatization, liberalization and deregulation of railway network.

Keywords: deregulation, high-speed railway, liberalization, privatization, public-private partnership

Procedia PDF Downloads 171

Authors: Elham Fariborzi, Hoda Anvari Kazemabad

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Today, ICT plays an important role in all matters and it affects the development of creative cities. According to virtual space in this technology, it use especially for expand terms like smart schools, Virtual University, web-based training and virtual classrooms that is in parallel with the traditional teaching. Nowadays, the educational systems in different countries such as Iran are changing and start increasing creativity in the learning environment. It will contribute to the development of innovative ideas and thinking of the people in this environment; such opportunities might be cause scientific discovery and development issues. The creativity means the ability to generate ideas and numerous, new and suitable solutions for solving the problems of real and virtual individuals and society, which can play a significant role in the development of creative current physical cities or virtual borders ones in the future. The purpose of this paper is to study strategies to increase creativity in a virtual learning to develop a creative city. In this paper, citation/ library study was used. The full description given in the text, including how to create and enhance learning creativity in a virtual classroom by reflecting on performance and progress; attention to self-directed learning guidelines, efficient use of social networks, systematic discussion groups and non-intuitive targeted controls them by involved factors and it may be effective in the teaching process regarding to creativity. Meanwhile, creating a virtual classroom the style of class recognizes formally the creativity. Also the use of a common model of creative thinking between student/teacher is effective to solve problems of virtual classroom. It is recommended to virtual education’ authorities in Iran to have a special review to the virtual curriculum for increasing creativity in educational content and such classes to be witnesses more creative in Iran's cities.

Keywords: virtual learning, creativity, e-learning, bioinformatics, biomedicine

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Authors: Daniel M. Muntean, Viorel Ungureanu

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More than half of the urban population in Romania lives today in residential buildings made out of large prefabricated reinforced concrete panels. Since their initial design was made in the 1960’s, these housing units are now being technically and morally outdated, consuming large amounts of energy for heating, cooling, ventilation and lighting, while failing to meet the needs of the contemporary life-style. Due to their widespread use, the design of a system that improves their energy efficiency would have a real impact, not only on the energy consumption of the residential sector, but also on the quality of life that it offers. Furthermore, with the transition of today’s existing power grid to a “smart grid”, buildings could become an active element for future electricity networks by contributing in micro-generation and energy storage. One of the most addressed issues today is to find locally adapted strategies that can be applied considering the 20-20-20 EU policy criteria and to offer sustainable and innovative solutions for the cost-optimal energy performance of buildings adapted on the existing local market. This paper presents a possible adaptive design scenario towards sustainable retrofitting of these housing units. The apartments are transformed in order to meet the current living requirements and additional extensions are placed on top of the building, replacing the unused roof space, acting not only as housing units, but as active solar energy collection systems. An adaptive building envelope is ensured in order to achieve overall air-tightness and an elevator system is introduced to facilitate access to the upper levels.

Keywords: adaptive building, energy efficiency, retrofitting, residential buildings, smart grid

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Authors: Jennifer De Paola

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Objectives: The literature is saturated with figures and hard data on happiness and its rates, causes and effects at a large scale, whereas very little is known about the way specific groups of people within societies understand and talk about happiness in their everyday life. The present study contributes to fill this gap in the happiness research by analyzing social representations of happiness among young women through the theoretical frame provided by Moscovici’s Social Representation Theory. Methods: Participants were (N= 351) female students (16-18 year olds) from Finnish, Swedish and English speaking high schools in the Helsinki region, Finland. Main source of data collection were word associations using the stimulus word ‘happiness’ and word associations using as stimulus the term that in the participants’ opinion represents the opposite of happiness. The allowed number of associations was five per stimulus word (10 associations per participant). In total, the 351 participants produced 6973 associations with the two stimulus words given: 3500 (50,19%) associations with ‘happiness’ and 3473 (49,81%) associations with ‘opposite of happiness’. The associations produced were analyzed qualitatively to identify associations with similar meaning and then coded combining similar associations in larger categories. Results: In total, 33 categories were identified respectively for the stimulus word ‘happiness’ and for the stimulus word ‘opposite of happiness’. In general terms, the 33 categories identified for ‘happiness’ included associations regarding relationships with key people considered important, such as ‘family’, abstract concepts such as meaningful life, success and moral values as well as more mundane and hedonic elements like food, pleasure and fun. Similarly, the 33 categories emerged for ‘opposite of happiness’ included relationship problems and arguments, negative feelings such as sadness, depression, stress as well as more concrete issues such as financial problems. Participants were also asked to rate their own level of happiness on a scale from 1 to 10. Results indicated the mean of the self-rated level of happiness was 7,93 (the range varied from 1 to 10; SD = 1, 50). Participants’ responses were further divided into three different groups according to the self-rated level of happiness: group 1 (level 10-9), group 2 (level 8-6), and group 3 (level 5 and lower) in order to investigate the way the categories mentioned above were distributed among the different groups. Preliminary results show that the category ‘family’ is associated with higher level of happiness, whereas its presence gradually decreases among the participants with a lower level of happiness. Moreover, the category ‘depression’ seems to be mainly present among participants in group 3, whereas the category ‘sadness’ is mainly present among participants with higher level of happiness. Conclusion: In conclusion, this study indicates the prevalent ways of thinking about happiness and its opposite among young female students, suggesting that representations varied to some extent depending on the happiness level of the participants. This study contributes to bringing new knowledge as it considers happiness as a holistic state, thus going beyond the literature that so far has too often viewed happiness as a mere unidimensional spectrum.

Keywords: female, happiness, social representations, unhappiness

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Authors: Rasha Ahmadi

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Glioblastoma is one of the most frequent brain malignancies, having a high mortality rate and limited survival in individuals with this malignancy. Despite different treatments and surgery, recurrence of glioblastoma cancer stem cells may arise as a subsequent tumor. For this reason, it is crucial to research the markers associated with glioblastoma stem cells and specifically their microenvironment. In this study, using bioinformatics analysis, we analyzed and nominated genes in the microenvironment pathways of glioblastoma stem cells. In this study, an appropriate database was selected for analysis by referring to the GEO database. This dataset comprised gene expression patterns in stem cells derived from glioblastoma patients. Gene clusters were divided as high and low expression. Enrichment databases such as Enrichr, STRING, and GEPIA were utilized to analyze the data appropriately. Finally, we extracted the potential genes 2700 high-expression and 1100 low-expression genes are implicated in the metabolic pathways of glioblastoma cancer progression. Cellular senescence, MAPK, TNF, hypoxia, zimosterol biosynthesis, and phosphatidylinositol metabolism pathways were substantially expressed and the metabolic pathways were downregulated. After assessing the association between protein networks, MSMP, SOX2, FGD4 ,and CNTNAP3 genes with high expression and DMKN and SBSN genes with low were selected. All of these genes were observed in the survival curve, with a survival of fewer than 10 percent over around 15 months. hsa-mir-192-5p, hsa-mir-129-5p, hsa-mir-215-5p, hsa-mir-335-5p, and hsa-mir-340-5p played key function in glioblastoma cancer stem cells microenviroments. We introduced critical genes through integrated and regular bioinformatics studies by assessing the amount of gene expression profile data that can play an important role in targeting genes involved in the energy and microenvironment of glioblastoma cancer stem cells. Have. This study indicated that hsa-mir-192-5p, and hsa-mir-129-5p are appropriate candidates for this.

Keywords: Glioblastoma, Cancer Stem Cells, Biomarker Discovery, Gene Expression Profiles, Bioinformatics Analysis, Tumor Microenvironment

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Authors: Jonathan K. Hill

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The transportation networks throughout Africa remain the only transportation infrastructure system in the world that is attacked by terrorists at a high frequency, so the international community can learn from each attack. The targeting of transportation should be recognized as a direct attack against a civilian population, so the international community should work to better understand the types of attacks utilized, the types of improvised explosive device designs adapted to transportation targets, and the ways the various modes of transportation have been attacked throughout the continent. Some countries have seen grenade attacks that have resulted in only injuries, while some countries have experienced large vehicle bombings that have resulted in hundreds of injuries and numerous deaths. With insurgencies, explosive devices have been small, complex, and generally target an enemy of the insurgency. With terrorist bombings, the explosive devices have been large, brazen, and targeted at civilian populations. And, these civilian populations are easily targeted within the transportation system. The presentation provided by Assess Africa LLC is titled ‘Evolution of Bombings Against Transportation Infrastructure’ and covers improvised explosive device characteristics, how improvised explosive devices have been adapted to transportation targets in Africa, analyses recent incidents, and provides some advice for effective protective measures. A main component of the improvised explosive device characteristics portion of the presentation focuses on the link between explosive device components, the intelligence network, and the bomb-builder’s network. By understanding the components, how the use of various components can be linked to a terrorist group’s capabilities, and how the bomb-builder acquires materials, the analysis of improvised explosive device attacks takes on a new direction – one that focuses on defeating the network instead of merely reviewing incidents of the past.

Keywords: Africa, bombings, critical infrastructure protection, transportation security

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Authors: Halonen

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Covid-19 pandemic and the succeeding crises have profoundly shaken the accustomed ways of interaction and thereby challenged the customary engagement patterns among entrepreneurs Consequently, this has led to the experience of lack of collegial interaction for some. Networks and relationships are a crucial factor to strengthening resilience, being especially significant in non-ordinary times. This study aims to shed light on entrepreneurs’ resilience development in and through entrepreneurs’ communal and training space. The context for research is a communal training space in a municipality in Finland of which goal is to help entrepreneurs to experience of peer support and community as part of the "tribe" is strengthened, the entrepreneurs' well-being at work, resilience, ability to change, innovativeness and general life management is strengthened. This communal space is regarded as an example of a physical community of practice (CoP) of entrepreneurs. The research aims to highlight the importance of rediscovering the “new normal” communality as itself but as a key building block of resilience. The initial research questions of the study are: RQ1: What is the role of entrepreneurs’ CoP and communal space in nurturing resilience development among them? RQ2: What positive entrepreneurial outcomes can be achieved through established CoP. The data will be gathered starting from the launch of the communality space in September 2023 onwards. It includes participatory observations of training gatherings, interviews with entrepreneurs and utilizes action research as the method. The author has an active role in participating and facilitating the development. The full paper will be finalized by the fall 2024. The idea of the new normal communality in a CoP among entrepreneurs is to be rediscovered due to its positive impact on entrepreneur’s resilience and business success. The other implications of study can extend to wider entrepreneurial ecosystem and other key stakeholders. Especially emphasizing the potential of communality in CoP for fostering entrepreneurs’ resilience and well-being ensuing business growth, community-driven entrepreneurship development and vitality of the case municipality.

Keywords: resilience, resilience development, communal space, community of practice (CoP)

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Authors: Faiza Belbachir, Thibault Schienhinski

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The massive development of online social networks allows users to post and share their opinions on various topics. With this huge volume of opinion, it is interesting to extract and interpret these information for different domains, e.g., product and service benchmarking, politic, system of recommendation. This is why opinion detection is one of the most important research tasks. It consists on differentiating between opinion data and factual data. The difficulty of this task is to determine an approach which returns opinionated document. Generally, there are two approaches used for opinion detection i.e. Lexical based approaches and Machine Learning based approaches. In Lexical based approaches, a dictionary of sentimental words is used, words are associated with weights. The opinion score of document is derived by the occurrence of words from this dictionary. In Machine learning approaches, usually a classifier is trained using a set of annotated document containing sentiment, and features such as n-grams of words, part-of-speech tags, and logical forms. Majority of these works are based on documents text to determine opinion score but dont take into account if these texts are really correct. Thus, it is interesting to exploit other information to improve opinion detection. In our work, we will develop a new way to consider the opinion score. We introduce the notion of trust score. We determine opinionated documents but also if these opinions are really trustable information in relation with topics. For that we use lexical SentiWordNet to calculate opinion and trust scores, we compute different features about users like (numbers of their comments, numbers of their useful comments, Average useful review). After that, we combine opinion score and trust score to obtain a final score. We applied our method to detect trust opinions in TRIPADVISOR collection. Our experimental results report that the combination between opinion score and trust score improves opinion detection.

Keywords: Tripadvisor, opinion detection, SentiWordNet, trust score

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Authors: Soheila Sadeghi

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In construction projects, predicting project performance metrics accurately is essential for effective management and successful delivery. However, conventional methods often depend on fixed baseline plans, disregarding the evolving nature of project progress and external influences. To address this issue, we introduce a distinct approach based on machine learning to forecast key performance indicators, such as cost variance and earned value, for each Work Breakdown Structure (WBS) category within an urban road reconstruction project. Our proposed model leverages time series forecasting techniques, namely Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) networks, to predict future performance by analyzing historical data and project progress. Additionally, the model incorporates external factors, including weather patterns and resource availability, as features to improve forecast accuracy. By harnessing the predictive capabilities of machine learning, our performance forecasting model enables project managers to proactively identify potential deviations from the baseline plan and take timely corrective measures. To validate the effectiveness of the proposed approach, we conduct a case study on an urban road reconstruction project, comparing the model's predictions with actual project performance data. The outcomes of this research contribute to the advancement of project management practices in the construction industry by providing a data-driven solution for enhancing project performance monitoring and control.

Keywords: project performance forecasting, machine learning, time series forecasting, cost variance, schedule variance, earned value management

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Authors: Shativel S., Chandana B. R., Kavya B. C., Obli B. Vikram, Suganthi J., Nagendra Rao G.

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Satellite communication plays a pivotal role in modern global communication networks, serving as a vital link between terrestrial infrastructure and remote regions. The demand for reliable satellite reception systems, especially in UHF (Ultra High Frequency) and VHF (Very High Frequency) bands, has grown significantly over the years. This research paper presents the design and optimization of a high-gain, dual-band crossed Yagi-Uda antenna in CST Studio Suite, specifically tailored for satellite reception. The proposed antenna system incorporates a circularly polarized (Right-Hand Circular Polarization - RHCP) design to reduce Faraday loss. Our aim was to use fewer elements and achieve gain, so the antenna is constructed using 6x2 elements arranged in cross dipole and supported with a boom. We have achieved 10.67dBi at 146MHz and 9.28dBi at 437.5MHz.The process includes parameter optimization and fine-tuning of the Yagi-Uda array’s elements, such as the length and spacing of directors and reflectors, to achieve high gain and desirable radiation patterns. Furthermore, the optimization process considers the requirements for UHF and VHF frequency bands, ensuring broad frequency coverage for satellite reception. The results of this research are anticipated to significantly contribute to the advancement of satellite reception systems, enhancing their capabilities to reliably connect remote and underserved areas to the global communication network. Through innovative antenna design and simulation techniques, this study seeks to provide a foundation for the development of next-generation satellite communication infrastructure.

Keywords: Yagi-Uda antenna, RHCP, gain, UHF antenna, VHF antenna, CST, radiation pattern.

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Authors: Abeer A. Aljohani

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COVID-19 virus spread has been one of the extreme pandemics across the globe. It is also referred to as coronavirus, which is a contagious disease that continuously mutates into numerous variants. Currently, the B.1.1.529 variant labeled as omicron is detected in South Africa. The huge spread of COVID-19 disease has affected several lives and has surged exceptional pressure on the healthcare systems worldwide. Also, everyday life and the global economy have been at stake. This research aims to predict COVID-19 disease in its initial stage to reduce the death count. Machine learning (ML) is nowadays used in almost every area. Numerous COVID-19 cases have produced a huge burden on the hospitals as well as health workers. To reduce this burden, this paper predicts COVID-19 disease is based on the symptoms and medical history of the patient. This research presents a unique architecture for COVID-19 detection using ML techniques integrated with feature dimensionality reduction. This paper uses a standard UCI dataset for predicting COVID-19 disease. This dataset comprises symptoms of 5434 patients. This paper also compares several supervised ML techniques to the presented architecture. The architecture has also utilized 10-fold cross validation process for generalization and the principal component analysis (PCA) technique for feature reduction. Standard parameters are used to evaluate the proposed architecture including F1-Score, precision, accuracy, recall, receiver operating characteristic (ROC), and area under curve (AUC). The results depict that decision tree, random forest, and neural networks outperform all other state-of-the-art ML techniques. This achieved result can help effectively in identifying COVID-19 infection cases.

Keywords: supervised machine learning, COVID-19 prediction, healthcare analytics, random forest, neural network

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Authors: Vipul M. Patel, Hemantkumar B. Mehta

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Technological innovations in electronic world demand novel, compact, simple in design, less costly and effective heat transfer devices. Closed Loop Pulsating Heat Pipe (CLPHP) is a passive phase change heat transfer device and has potential to transfer heat quickly and efficiently from source to sink. Thermal performance of a CLPHP is governed by various parameters such as number of U-turns, orientations, input heat, working fluids and filling ratio. The present paper is an attempt to predict the thermal performance of a CLPHP using Artificial Neural Network (ANN). Filling ratio and heat input are considered as input parameters while thermal resistance is set as target parameter. Types of neural networks considered in the present paper are radial basis, generalized regression, linear layer, cascade forward back propagation, feed forward back propagation; feed forward distributed time delay, layer recurrent and Elman back propagation. Linear, logistic sigmoid, tangent sigmoid and Radial Basis Gaussian Function are used as transfer functions. Prediction accuracy is measured based on the experimental data reported by the researchers in open literature as a function of Mean Absolute Relative Deviation (MARD). The prediction of a generalized regression ANN model with spread constant of 4.8 is found in agreement with the experimental data for MARD in the range of ±1.81%.

Keywords: ANN models, CLPHP, filling ratio, generalized regression, spread constant

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Authors: Patricia Girrbach

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Currently, our society is facing a new and incremental upheaval technological revolution named digitalization. In order to face the relating challenges organizations have to be prepared. They need appropriate circumstances in order to cope with current issues concerning digital transformation processes. Nowadays digitalization emerged as top issues for companies and business leaders. In this context, it is a pressure on companies to have a positive, productive digital culture. And indeed, Organizations realize that they need to address this important issue. In this context 87 percent of organizations quote culture and engagement as one of their top challenges in terms of any change process, but especially in terms of the digital turn. Executives can give their company a competitive advantage and attract top talent by having a strong workplace culture that supports digitalization. Many current studies attest that fact. Digital-oriented companies can hire more easily, they have the lowest voluntary turnover rates, deliver better customer service, and are more profitable over the long run. Based on this background it is important to provide companies starting points and practical measurements how to reach this goal. The major findings are that firms need to make sense out of digitalization. In this context, they should focus on internal but also on external stakeholders. Furthermore, they should create certain working conditions and they should support the qualification of employees, e.g. by Virtual Reality. These measurements can create positive experiences in terms of digitalization in order to ensure the support of stuff in terms of the digital turn. Based on several current studies and literature research this paper provides concrete measurements for companies in order to enable the digital turn. Therefore, the aim of this paper is providing possible practical starting points which support both the education of employees by digitalization as well as the digital turn itself within the organization.

Keywords: digitalization, industry 4.0, education 4.0, virtual reality

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Authors: Thilini M. Yatanwala

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CCTV (Closed-Circuit-Television) Surveillance System is being used in public places over decades and a large variety of data is being produced every moment. However, most of the CCTV data is stored in isolation without having integrity. As a result, identification of the behavior of suspicious people along with their location has become strenuous. This research was conducted to acquire more accurate and reliable timely information from the CCTV video records. The implemented system can identify human objects in public places based on outfit colors. Inter-process communication technologies were used to implement the CCTV camera network to track people in the premises. The research was conducted in three stages and in the first stage human objects were filtered from other movable objects available in public places. In the second stage people were uniquely identified based on their outfit colors and in the third stage an individual was continuously tracked in the CCTV network. A face detection algorithm was implemented using cascade classifier based on the training model to detect human objects. HAAR feature based two-dimensional convolution operator was introduced to identify features of the human face such as region of eyes, region of nose and bridge of the nose based on darkness and lightness of facial area. In the second stage outfit colors of human objects were analyzed by dividing the area into upper left, upper right, lower left, lower right of the body. Mean color, mod color and standard deviation of each area were extracted as crucial factors to uniquely identify human object using histogram based approach. Color based measurements were written in to XML files and separate directories were maintained to store XML files related to each camera according to time stamp. As the third stage of the approach, inter-process communication techniques were used to implement an acknowledgement based CCTV camera network to continuously track individuals in a network of cameras. Real time analysis of XML files generated in each camera can determine the path of individual to monitor full activity sequence. Higher efficiency was achieved by sending and receiving acknowledgments only among adjacent cameras. Suspicious incidents such as a person staying in a sensitive area for a longer period or a person disappeared from the camera coverage can be detected in this approach. The system was tested for 150 people with the accuracy level of 82%. However, this approach was unable to produce expected results in the presence of group of people wearing similar type of outfits. This approach can be applied to any existing camera network without changing the physical arrangement of CCTV cameras. The study of human identification and suspicious incident detection using outfit color analysis can achieve higher level of accuracy and the project will be continued by integrating motion and gait feature analysis techniques to derive more information from CCTV videos.

Keywords: CCTV surveillance, human detection and identification, image processing, inter-process communication, security, suspicious detection

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Authors: Nurulhuda A. Manaf, Nor Najihah Zainal Abidin, Nur Amalina Jamaludin

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Coordinating service interactions are a vital part of developing distributed applications that are built up as networks of autonomous participants, e.g., software components, web services, online resources, involve a collaboration between a diverse number of participant services on different providers. The complexity in coordinating service interactions reflects how important the techniques and approaches require for designing and coordinating the interaction between participant services to ensure the overall goal of a collaboration between participant services is achieved. The objective of this research is to develop capability of steering a complex service interaction towards a desired outcome. Therefore, an efficient technique for modelling, generating, and verifying the coordination of service interactions is developed. The developed model describes service interactions using service choreographies approach and focusing on a declarative approach, advocating an Object Management Group (OMG) standard, Semantics of Business Vocabulary and Rules (SBVR). This model, namely, SBVR model for service choreographies focuses on a declarative deontic rule expressing both obligation and prohibition, which can be more useful in working with coordinating service interactions. The generated SBVR model is then be formulated and be transformed into Alloy model using Alloy Analyzer for verifying the generated SBVR model. The transformation of SBVR into Alloy allows to automatically generate the corresponding coordination of service interactions (service choreography), hence producing an immediate instance of execution that satisfies the constraints of the specification and verifies whether a specific request can be realised in the given choreography in the generated choreography.

Keywords: service choreography, service coordination, behavioural modelling, complex interactions, declarative specification, verification, model transformation, semantics of business vocabulary and rules, SBVR

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Authors: Marco Ranzato, Maguelone Vignes

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The co-design process recently run by the trans-disciplinary urban laboratory Metrolab Brussels for outlining the architecture of a future integrated health centre in Brussels (Belgium) has highlighted that a buffer place open to the local community is the appropriate cornerstone around which organizing a space where diverse professionals and patients are together. In the context of the migrants 'crisis' in Europe, the growing number of vulnerable people in Brussels and the increasing complexity of the health and welfare systems, the NGO Doctors of the World (DoW) has launched a project funded by The European Regional Development Fund, and aiming to create a new community centre combining social and health services in a poor but changing neighborhood of Brussels. Willing not to make a 'ghetto' of this new integrated service, the NGO looks at hosting different publics in order to make the poorest, marginal and most vulnerable people access to a regular kind of service. As a trans-disciplinary urban research group, Metrolab has been involved in the process of co-designing the architecture of the future centre with a set of various health professionals, social workers, and patients’ representatives. Metrolab drawn on the participants’ practice experiences and knowledge of hosting different kinds of publics and professions in a same structure in order to imagine what rooms should fit into the centre, what atmosphere they should convey, how should they be interrelated and organized, and, concurrently, how the building should fit into the urban frame of its neighborhood. The result is that, in order for an integrated health centre framed in the landscape of a disadvantaged neighborhood to function, it has to work as social community centre offering accessibility and conviviality to diverse social groups. This paper outlines the methodology that Metrolab used to design and conduct, in close collaboration with DoW, a series of 3 workshops. Through sketching and paper modeling, the methodology made participants talk about their experience by projecting them into a situation. It included a combination of individual and collective work in order to sharp participants’ eyes on architectural forms, explicit their thoughts and experience through inter-subjectivity and imagine solutions to the challenges they raised. Such a collaborative method encompasses several challenges about patients’ participation and representation, replicability of the conditions of success and the plurality of the research findings communication formats. This paper underlines how this participatory process has contributed to build knowledge on the few-documented topic of the architecture of community health centres. More importantly, the contribution builds on this participatory process to discuss the importance of adapting the architecture of the new integrated health centre to the changing population of Brussels and to the issues of its specific neighborhood.

Keywords: co-design, health, social innovation, urban lab

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Authors: Anjan Hazra, Nirjhar Dasgupta, Chandan Sengupta, Sauren Das

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Tea (Camellia sinensis) has received substantial attention from the scientific world time to time, not only for its commercial importance, but also for its demand to the health-conscious people across the world for its extensive use as potential sources of antioxidant supplement. These health-benefit traits primarily rely on some regulatory networks of different metabolic pathways. Development of microsatellite markers from the conserved genomic regions is being worthwhile for studying the genetic diversity of closely related species or self-pollinated species. Although several SSR markers have been reported, in tea the trait-specific Simple Sequence Repeats (SSRs) are yet to be identified, which can be used for marker assisted breeding technique. MicroRNAs are endogenous, noncoding, short RNAs directly involved in regulating gene expressions at the post-transcriptional level. It has been found that diversity in miRNA gene interferes the formation of its characteristic hair pin structure and the subsequent function. In the present study, the precursors of small regulatory RNAs (microRNAs) has been fished out from tea Expressed Sequence Tag (EST) database. Furthermore, the simple sequence repeat motifs within the putative miRNA precursor genes are also identified in order to experimentally validate their existence and function. It is already known that genic-SSR markers are very adept and breeder-friendly source for genetic diversity analysis. So, the potential outcome of this in-silico study would provide some novel clues in understanding the miRNA-triggered polymorphic genic expression controlling specific metabolic pathways, accountable for tea quality.

Keywords: micro RNA, simple sequence repeats, tea quality, trait specific marker

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Authors: Henry Okechukwu Onyeiwu

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Nigeria, with its rich tapestry of ethnicities, cultures, and religions, serves as a critical case study in understanding how law influences and shapes collective identities. This abstract delves into the historical context of legal systems in Nigeria, examining the colonial legacies that have influenced contemporary laws and how these laws interact with traditional practices and beliefs. This study examines the critical role of law in shaping and transforming collective identities in Nigeria, a nation characterized by its rich tapestry of ethnicities, cultures, and religions. The legal framework in Nigeria has evolved in response to historical, social, and political dynamics, influencing the way communities perceive themselves and interact with one another. This research highlights the interplay between law and collective identity, exploring how legal instruments, such as constitutions, statutes, and judicial rulings, have contributed to the formation, negotiation, and reformation of group identities over time. Moreover, contemporary legal debates surrounding issues such as citizenship, resource allocation, and communal conflicts further illustrate the law's role in identity formation. The legal recognition of different ethnic groups fosters a sense of belonging and collective identity among these groups, yet it simultaneously raises questions about inclusivity and equality. Laws concerning indigenous rights and affirmative action are essential in this discourse, as they reflect the necessity of balancing majority rule with minority rights—a challenge that Nigeria continues to navigate. By employing a multidisciplinary approach that integrates legal studies, sociology, and anthropology, the study analyses key historical milestones, such as colonial legal legacies, post-independence constitutional developments, and ongoing debates surrounding federalism and ethnic rights. It also investigates how laws affect social cohesion and conflict among Nigeria's diverse ethnic groups, as well as the role of law in promoting inclusivity and recognizing minority rights. Case studies are utilized to illustrate practical examples of legal transformations and their impact on collective identities in various Nigerian contexts, including land rights, religious freedoms, and ethnic representation in government. The findings reveal that while the law has the potential to unify disparate groups under a national identity, it can also exacerbate divisions when applied inequitably or favouring particular groups over others. Ultimately, this study aims to shed light on the dual nature of law as both a tool for transformation and a potential source of conflict in the evolution of collective identities in Nigeria. By understanding these dynamics, policymakers and legal practitioners can develop strategies to foster unity and respect for diversity in a complex societal landscape.

Keywords: law, collective identity, Nigeria, ethnicity, conflict, inclusion, legal framework, transformation

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Authors: Ulysse Lecomte, Maryline Thenot

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For a long time, disabled people lived in isolation within the family environment, with little interaction with the outside world and a high risk of social exclusion. However, in a number of countries, progress has been made thanks to changes in legislation on the social integration of disabled people, a significant change in attitudes, and the development of CSR. But the problem of their social, economic, and professional exclusion persists and has been further exacerbated by the COVID-19 pandemic. This societal phenomenon is sufficiently important to be the subject of management science research. We have therefore focused our work on society's current perception of people with disabilities and their possible integration. Our aim is to find out what levers could be put in place to bring about positive change in the situation. We have chosen to focus on the perception of young people in France, who are the new generation responsible for the future of our society and from whom tomorrow's decisionmakers, future employers, and stakeholders who can influence the living conditions of disabled people will be drawn. Our study sample corresponds to the 18-30 age group, which is the population of young adults likely to have sufficient experience and maturity. The aim of this study is not only to find out how this population currently perceives disability but also to identify the factors influencing this perception and the most effective levers for action to act positively on this phenomenon and thus promote better social integration of people with disabilities in the future. The methodology is based on theoretical and empirical research. The literature review includes a historical and etymological approach to disability, a definition of the different concepts of disability, an approach to disability as a vector of social exclusion, and the role of perception and representations in defining the social image of disability. This literature review is followed by an empirical part carried out by means of a questionnaire administered to 110 young people aged 18 to 30. Analysis of our results suggests that, despite a recent improvement, disabled people are still perceived as vulnerable and socially marginalised. The following factors stand out as having a significant influence (positive or negative) on the perception of disability: the individual's familiarity with the 'world of disability', cultural factors, the degree of 'visibility' of the disability and the empathy level of the disabled person him/herself. Others, on the other hand, such as socio-political and economic factors, have little impact on this perception. In addition, it is possible to classify the various levers of action likely to improve the social perception of disability according to their degree of effectiveness. Our study population prioritised training initiatives for the various players and stakeholders (teachers, students, disabled people themselves, companies, sports clubs, etc.). This was followed by communication, ecommunication and media campaigns in favour of disability. Lastly, the sample was judged as 'less effective' positive discrimination actions such as setting a minimum percentage for the representation of disabled people in various fields (studies, employment, politics ...).

Keywords: disability, perception, social image, young people, influencing factors, levers for action

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Authors: Robert L. Fine, Zhiyong Yang, Christy Spivey, Bonnie Boardman, Maureen Courtney

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Importance: Barriers to traditional advance care planning (ACP) and advance directive (AD) creation have limited the promise of ACP/AD for individuals and families, the healthcare team, and society. Reengineering ACP by using a web-based, consumer-driven process has recently been suggested. We report early experience with such a process. Objective: Begin to analyze the potential of the creation and use of ACP/ADs as generated by a consumer-friendly, digital process by 1) assessing the likelihood that consumers would create ACP/ADs without structured intervention by medical or legal professionals, and 2) analyzing the responses to determine if the plans can help doctors better understand a person’s goals, preferences, and priorities for their medical treatments and the naming of healthcare agents. Design: The authors chose 900 users of MyDirectives.com, a digital ACP/AD tool, solely based on their state of residence in order to achieve proportional representation of all 50 states by population size and then reviewed their responses, summarizing these through descriptive statistics including treatment preferences, demographics, and revision of preferences. Setting: General United States population. Participants: The 900 participants had an average age of 50.8 years (SD = 16.6); 84.3% of the men and 91% of the women were in self-reported good health when signing their ADs. Main measures: Preferences regarding the use of life-sustaining treatments, where to spend final days, consulting a supportive and palliative care team, attempted cardiopulmonary resuscitation (CPR), autopsy, and organ and tissue donation. Results: Nearly 85% of respondents prefer cessation of life-sustaining treatments during their final days whenever those may be, 76% prefer to spend their final days at home or in a hospice facility, and 94% wanted their future doctors to consult a supportive and palliative care team. 70% would accept attempted CPR in certain limited circumstances. Most respondents would want an autopsy under certain conditions, and 62% would like to donate their organs. Conclusions and relevance: Analysis of early experience with an all-digital web-based ACP/AD platform demonstrates that individuals from a wide range of ages and conditions can engage in an interrogatory process about values, goals, preferences, and priorities for their medical treatments by developing advance directives and easily make changes to the AD created. Online creation, storage, and retrieval of advance directives has the potential to remove barriers to ACP/AD and, thus, to further improve patient-centered end-of-life care.

Keywords: Advance Care Plan, Advance Decisions, Advance Directives, Consumer; Digital, End of Life Care, Goals, Living Wills, Prefences, Universal Advance Directive, Statements

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Authors: K. Sathishkumar, V. Thiagarasu

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Due to recent advances in DNA microarray technology, it is now feasible to obtain gene expression profiles of tissue samples at relatively low costs. Many scientists around the world use the advantage of this gene profiling to characterize complex biological circumstances and diseases. Microarray techniques that are used in genome-wide gene expression and genome mutation analysis help scientists and physicians in understanding of the pathophysiological mechanisms, in diagnoses and prognoses, and choosing treatment plans. DNA microarray technology has now made it possible to simultaneously monitor the expression levels of thousands of genes during important biological processes and across collections of related samples. Elucidating the patterns hidden in gene expression data offers a tremendous opportunity for an enhanced understanding of functional genomics. However, the large number of genes and the complexity of biological networks greatly increase the challenges of comprehending and interpreting the resulting mass of data, which often consists of millions of measurements. A first step toward addressing this challenge is the use of clustering techniques, which is essential in the data mining process to reveal natural structures and identify interesting patterns in the underlying data. This work presents an analysis of several clustering algorithms proposed to deals with the gene expression data effectively. The existing clustering algorithms like Support Vector Machine (SVM), K-means algorithm and evolutionary algorithm etc. are analyzed thoroughly to identify the advantages and limitations. The performance evaluation of the existing algorithms is carried out to determine the best approach. In order to improve the classification performance of the best approach in terms of Accuracy, Convergence Behavior and processing time, a hybrid clustering based optimization approach has been proposed.

Keywords: microarray technology, gene expression data, clustering, gene Selection

Procedia PDF Downloads 323

Authors: Debatosh Das, Moxian Chen, Jianhua Zhang, Caroline Gutjahr

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Arbuscular mycorrhiza (AM) is a mutualistic symbiosis between plant roots and Glomeromycotina fungi, which is activated under low but inhibited by high phosphate. The effect of phosphate on AM development has been observed for many years, but mechanisms regulating it under contrasting phosphate levels remain unknown. Based on previous observations that promoters of several AM functional genes contain PHR binding motifs, we hypothesized that PHR2, a master regulator of phosphate starvation response in rice, was recruited to regulate AM symbiosis development. We observed a drastic reduction in root colonization and significant AM transcriptome modulation in phr2. PHR2 targets genes required for root colonization and AM signaling. The role of PHR2 in improving root colonization, mycorrhizal phosphate uptake, and growth response was confirmed in field soil. In conclusion, rice PHR2, which is considered a master regulator of phosphate starvation responses, acts as a positive regulator of AM symbiosis between Glomeromycotina fungi and rice roots. PHR2 directly targets the transcription of plant strigolactone and AM genes involved in the establishment of this symbiosis. Our work facilitates an understanding of ways to enhance AMF propagule populations introduced in field soils (as a biofertilizer) in order to restore the natural plant-AMF networks disrupted by modern agricultural practices. We show that PHR2 is required for AM-mediated improvement of rice yield in low phosphate paddy field soil. Thus, our work contributes knowledge for rational application of AM in sustainable agriculture. Our data provide important insights into the regulation of AM by the plant phosphate status, which has a broad significance in agriculture and terrestrial ecosystems.

Keywords: biofertilizer, phosphate, mycorrhiza, rice, sustainable, symbiosis

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Authors: Roman Kulikov, Svetlana Kolesnikova

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Last decade Cloud Computing technologies have been rapidly becoming ubiquitous. Each year more and more organizations, corporations, internet services and social networks trust their business sensitive information to Public Cloud. The data storage in Public Cloud is protected by security mechanisms such as firewalls, cryptography algorithms, backups, etc.. In this way, however, only outsider attacks can be prevented, whereas virtualization tools can be easily compromised by insider. The protection of Public Cloud’s critical elements from internal intruder remains extremely challenging. A hypervisor, also called a virtual machine manager, is a program that allows multiple operating systems (OS) to share a single hardware processor in Cloud Computing. One of the hypervisor's functions is to enforce access control policies. Furthermore, it prevents guest OS from disrupting each other and from accessing each other's memory or disk space. Hypervisor is the one of the most critical and vulnerable elements in Cloud Computing infrastructure. Nevertheless, it has been poorly protected from being compromised by insider. By exploiting certain vulnerabilities, privilege escalation can be easily achieved in insider attacks on hypervisor. In this way, an internal intruder, who has compromised one process, is able to gain control of the entire virtual machine. Thereafter, the consequences of insider attacks in Public Cloud might be more catastrophic and significant to virtual tools and sensitive data than of outsider attacks. So far, almost no preventive security countermeasures have been developed. There has been little attention paid for developing models to assist risks mitigation strategies. In this paper formal model of insider attacks on hypervisor is designed. Our analysis identifies critical hypervisor`s vulnerabilities that can be easily compromised by internal intruder. Consequently, possible conditions for successful attacks implementation are uncovered. Hence, development of preventive security countermeasures can be improved on the basis of the proposed model.

Keywords: insider attack, public cloud, cloud computing, hypervisor

Procedia PDF Downloads 361

Authors: Kasra Majbouri Yazdi, Adel Majbouri Yazdi, Saeid Khodayi, Jingyu Hou, Wanlei Zhou, Saeed Saedy

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Fake news and false information are big challenges of all types of media, especially social media. There is a lot of false information, fake likes, views and duplicated accounts as big social networks such as Facebook and Twitter admitted. Most information appearing on social media is doubtful and in some cases misleading. They need to be detected as soon as possible to avoid a negative impact on society. The dimensions of the fake news datasets are growing rapidly, so to obtain a better result of detecting false information with less computation time and complexity, the dimensions need to be reduced. One of the best techniques of reducing data size is using feature selection method. The aim of this technique is to choose a feature subset from the original set to improve the classification performance. In this paper, a feature selection method is proposed with the integration of K-means clustering and Support Vector Machine (SVM) approaches which work in four steps. First, the similarities between all features are calculated. Then, features are divided into several clusters. Next, the final feature set is selected from all clusters, and finally, fake news is classified based on the final feature subset using the SVM method. The proposed method was evaluated by comparing its performance with other state-of-the-art methods on several specific benchmark datasets and the outcome showed a better classification of false information for our work. The detection performance was improved in two aspects. On the one hand, the detection runtime process decreased, and on the other hand, the classification accuracy increased because of the elimination of redundant features and the reduction of datasets dimensions.

Keywords: clustering, fake news detection, feature selection, machine learning, social media, support vector machine

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Authors: Elucir Gir, Laelson Rochelle Milanês Sousa, Pedro Henrique Tertuliano Leoni, Carla Aparecida Arena Ventura, Ana Cristina de Oliveira e Silva, Renata Karina Reis

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Context and significance: Resilience is a protective agent for the physical and mental well-being of nursing professionals. Team members are constantly subjected to high levels of work stress that can negatively impact care performance and users of health services. Stress levels have been exacerbated with the COVID-19 pandemic. Objective: The aim of this study was to analyze the resilience of nursing professionals in Brazil during the COVID-19 pandemic. Method: Cross-sectional study with a quantitative approach carried out with professionals from nursing teams from all regions of Brazil. Data collection took place in the first year of the pandemic between October and December 2020. Data were obtained through an online questionnaire posted on social networks. The information collected included the sociodemographic characterization of the nursing professionals and the Brief Resilient Coping Scale was applied. Student's t-test for independent samples and analysis of variance (ANOVA) were used to compare resilience scores with sociodemographic variables. Results: 8,792 nursing professionals participated in the study, 5,767 (65.6%) were nurses, 7,437 (84.6%) were female and 2,643 (30.1%) were from the Northeast region of Brazil, 5,124 (58.8% ) had low levels of resilience. The results showed a statistically significant difference between the resilience score and the variables: professional category (p<0.001); sex (p = 0.003); age range (p<0.001); region of Brazil (p<0.001); marital status (p=0.029) and providing assistance in a field hospital (p<0.001). Conclusion: Participants in this study had, in general, low levels of resilience. There is an urgent need for actions aimed at promoting the psychological health of nursing professionals inserted in pandemic contexts. Descriptors: Psychological Resilience; Nursing professionals; COVID-19; SARSCoV-2.

Keywords: psychological resilience, nursing professionals, COVID-19, SARS-CoV-2

Procedia PDF Downloads 87

Authors: H. Parveen Begam, M. A. Maluk Mohamed

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Mobile Grid Computing is an environment that allows sharing and coordinated use of diverse resources in dynamic, heterogeneous and distributed environment using different types of electronic portable devices. In a grid environment the security issues are like authentication, authorization, message protection and delegation handled by GSI (Grid Security Infrastructure). Proving better security between mobile devices and grid infrastructure is a major issue, because of the open nature of wireless networks, heterogeneous and distributed environments. In a mobile grid environment, the individual computing devices may be resource-limited in isolation, as an aggregated sum, they have the potential to play a vital role within the mobile grid environment. Some adaptive methodology or solution is needed to solve the issues like authentication of a base station, security of information flowing between a mobile user and a base station, prevention of attacks within a base station, hand-over of authentication information, communication cost of establishing a session key between mobile user and base station, computing complexity of achieving authenticity and security. The sharing of resources of the devices can be achieved only through the trusted relationships between the mobile hosts (MHs). Before accessing the grid service, the mobile devices should be proven authentic. This paper proposes the dynamic certificate based mutual authentication protocol between two mobile hosts in a mobile grid environment. The certificate generation process is done by CA (Certificate Authority) for all the authenticated MHs. Security (because of validity period of the certificate) and dynamicity (transmission time) can be achieved through the secure service certificates. Authentication protocol is built on communication services to provide cryptographically secured mechanisms for verifying the identity of users and resources.

Keywords: mobile grid computing, certificate authority (CA), SSL/TLS protocol, secured service certificates

Procedia PDF Downloads 305

Authors: Nina Sankat, Gerd Wilsch, Cassian Gottlieb, Steven Millar, Tobias Guenther

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Laser-Induced Breakdown Spectroscopy (LIBS) is a combination of laser ablation and optical emission spectroscopy, which in principle can simultaneously analyze all elements on the periodic table. Materials can be analyzed in terms of chemical composition in a two-dimensional, time efficient and minor destructive manner. These advantages predestine LIBS as a monitoring technique in the field of civil engineering. The decreasing service life of concrete infrastructures is a continuously growing problematic. A variety of intruding, harmful substances can damage the reinforcement or the concrete itself. To insure a sufficient service life a regular monitoring of the structure is necessary. LIBS offers many applications to accomplish a successful examination of the conditions of concrete structures. A selection of those applications are the 2D-evaluation of chlorine-, sodium- and sulfur-concentration, the identification of carbonation depths and the representation of the heterogeneity of concrete. LIBS obtains this information by using a pulsed laser with a short pulse length (some mJ), which is focused on the surfaces of the analyzed specimen, for this only an optical access is needed. Because of the high power density (some GW/cm²) a minimal amount of material is vaporized and transformed into a plasma. This plasma emits light depending on the chemical composition of the vaporized material. By analyzing the emitted light, information for every measurement point is gained. The chemical composition of the scanned area is visualized in a 2D-map with spatial resolutions up to 0.1 mm x 0.1 mm. Those 2D-maps can be converted into classic depth profiles, as typically seen for the results of chloride concentration provided by chemical analysis like potentiometric titration. However, the 2D-visualization offers many advantages like illustrating chlorine carrying cracks, direct imaging of the carbonation depth and in general allowing the separation of the aggregates from the cement paste. By calibrating the LIBS-System, not only qualitative but quantitative results can be obtained. Those quantitative results can also be based on the cement paste, while excluding the aggregates. An additional advantage of LIBS is its mobility. By using the mobile system, located at BAM, onsite measurements are feasible. The mobile LIBS-system was already used to obtain chloride, sodium and sulfur concentrations onsite of parking decks, bridges and sewage treatment plants even under hard conditions like ongoing construction work or rough weather. All those prospects make LIBS a promising method to secure the integrity of infrastructures in a sustainable manner.

Keywords: concrete, damage assessment, harmful substances, LIBS

Procedia PDF Downloads 176

Authors: Bamikole J. Adeyemi, Prashant Jadhawar, Lateef Akanji

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Liquid-liquid interfacial flow is an important process that has applications across many spheres. One such applications are residual oil mobilization, where crude oil and low salinity water are emulsified due to lowered interfacial tension under the condition of low shear rates. The amphiphilic components (asphaltenes and resins) in crude oil are considered to assemble at the interface between the two immiscible liquids. To justify emulsification, drag and snap-off suppression as the main effects of low salinity water, mobilization of residual oil is visualized as thickening and slip of the wetting phase at the brine/crude oil interface which results in the squeezing and drag of the non-wetting phase to the pressure sinks. Meanwhile, defining the boundary conditions for such a system can be very challenging since the interfacial dynamics do not only depend on interfacial tension but also the flow rate. Hence, understanding the flow boundary condition at the brine/crude oil interface is an important step towards defining the influence of low salinity water composition on residual oil mobilization. This work presents a numerical evaluation of three slip boundary conditions that may apply at liquid-liquid interfaces. A mathematical model was developed to describe the evolution of a viscoelastic interfacial thin liquid film. The base model is developed by the asymptotic expansion of the full Navier-Stokes equations for fluid motion due to gradients of surface tension. This model was upscaled to describe the dynamics of the film surface deformation. Subsequently, Jeffrey’s model was integrated into the formulations to account for viscoelastic stress within a long wave approximation of the Navier-Stokes equations. To study the fluid response to a prescribed disturbance, a linear stability analysis (LSA) was performed. The dispersion relation and the corresponding characteristic equation for the growth rate were obtained. Three slip (slip, 1; locking, -1; and no-slip, 0) boundary conditions were examined using the resulted characteristic equation. Also, the dynamics of the evolved interfacial thin liquid film were numerically evaluated by considering the influence of the boundary conditions. The linear stability analysis shows that the boundary conditions of such systems are greatly impacted by the presence of amphiphilic molecules when three different values of interfacial tension were tested. The results for slip and locking conditions are consistent with the fundamental solution representation of the diffusion equation where there is film decay. The interfacial films at both boundary conditions respond to exposure time in a similar manner with increasing growth rate which resulted in the formation of more droplets with time. Contrarily, no-slip boundary condition yielded an unbounded growth and it is not affected by interfacial tension.

Keywords: boundary conditions, liquid-liquid interfaces, low salinity water, residual oil mobilization

Procedia PDF Downloads 129

Authors: Merve Uzuner Sahin, Kumru D. Atalay, Berna Dengiz

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In today’s competitive market, there are many alternative products that can be used in similar manner and purpose. Therefore, the utility of the product is an important issue for the preferability of the brand. This utility could be measured in terms of its functionality, durability, reliability. These all are affected by the system capabilities. Reliability is an important system design criteria for the manufacturers to be able to have high availability. Availability is the probability that a system (or a component) is operating properly to its function at a specific point in time or a specific period of times. System availability provides valuable input to estimate the production rate for the company to realize the production plan. When considering only the corrective maintenance downtime of the system, mean time between failure (MTBF) and mean time to repair (MTTR) are used to obtain system availability. Also, the MTBF and MTTR values are important measures to improve system performance by adopting suitable maintenance strategies for reliability engineers and practitioners working in a system. Failure and repair time probability distributions of each component in the system should be known for the conventional availability analysis. However, generally, companies do not have statistics or quality control departments to store such a large amount of data. Real events or situations are defined deterministically instead of using stochastic data for the complete description of real systems. A fuzzy set is an alternative theory which is used to analyze the uncertainty and vagueness in real systems. The aim of this study is to present a novel approach to compute system availability using representation of MTBF and MTTR in fuzzy numbers. Based on the experience in the system, it is decided to choose 3 different spread of MTBF and MTTR such as 15%, 20% and 25% to obtain lower and upper limits of the fuzzy numbers. To the best of our knowledge, the proposed method is the first application that is used fuzzy MTBF and fuzzy MTTR for fuzzy system availability estimation. This method is easy to apply in any repairable production system by practitioners working in industry. It is provided that the reliability engineers/managers/practitioners could analyze the system performance in a more consistent and logical manner based on fuzzy availability. This paper presents a real case study of a repairable multi-stage production line in lead-acid battery production factory in Turkey. The following is focusing on the considered wet-charging battery process which has a higher production level than the other types of battery. In this system, system components could exist only in two states, working or failed, and it is assumed that when a component in the system fails, it becomes as good as new after repair. Instead of classical methods, using fuzzy set theory and obtaining intervals for these measures would be very useful for system managers, practitioners to analyze system qualifications to find better results for their working conditions. Thus, much more detailed information about system characteristics is obtained.

Keywords: availability analysis, battery production system, fuzzy sets, triangular fuzzy numbers (TFNs)

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Authors: Irene Yi

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Machine learning, natural language processing, and neural network models of language are becoming more and more prevalent in the fields of technology and linguistics today. Training data for machines are at best, large corpora of human literature and at worst, a reflection of the ugliness in society. Machines have been trained on millions of human books, only to find that in the course of human history, derogatory and sexist adjectives are used significantly more frequently when describing females in history and literature than when describing males. This is extremely problematic, both as training data, and as the outcome of natural language processing. As machines start to handle more responsibilities, it is crucial to ensure that they do not take with them historical sexist and misogynistic notions. This paper gathers data and algorithms from neural network models of language having to deal with syntax, semantics, sociolinguistics, and text classification. Results are significant in showing the existing intentional and unintentional misogynistic notions used to train machines, as well as in developing better technologies that take into account the semantics and syntax of text to be more mindful and reflect gender equality. Further, this paper deals with the idea of non-binary gender pronouns and how machines can process these pronouns correctly, given its semantic and syntactic context. This paper also delves into the implications of gendered grammar and its effect, cross-linguistically, on natural language processing. Languages such as French or Spanish not only have rigid gendered grammar rules, but also historically patriarchal societies. The progression of society comes hand in hand with not only its language, but how machines process those natural languages. These ideas are all extremely vital to the development of natural language models in technology, and they must be taken into account immediately.

Keywords: gendered grammar, misogynistic language, natural language processing, neural networks

Procedia PDF Downloads 120