Search results for: intelligent memory structures
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6014

Search results for: intelligent memory structures

4034 Elasto-Plastic Analysis of Structures Using Adaptive Gaussian Springs Based Applied Element Method

Authors: Mai Abdul Latif, Yuntian Feng

Abstract:

Applied Element Method (AEM) is a method that was developed to aid in the analysis of the collapse of structures. Current available methods cannot deal with structural collapse accurately; however, AEM can simulate the behavior of a structure from an initial state of no loading until collapse of the structure. The elements in AEM are connected with sets of normal and shear springs along the edges of the elements, that represent the stresses and strains of the element in that region. The elements are rigid, and the material properties are introduced through the spring stiffness. Nonlinear dynamic analysis has been widely modelled using the finite element method for analysis of progressive collapse of structures; however, difficulties in the analysis were found at the presence of excessively deformed elements with cracking or crushing, as well as having a high computational cost, and difficulties on choosing the appropriate material models for analysis. The Applied Element method is developed and coded to significantly improve the accuracy and also reduce the computational costs of the method. The scheme works for both linear elastic, and nonlinear cases, including elasto-plastic materials. This paper will focus on elastic and elasto-plastic material behaviour, where the number of springs required for an accurate analysis is tested. A steel cantilever beam is used as the structural element for the analysis. The first modification of the method is based on the Gaussian Quadrature to distribute the springs. Usually, the springs are equally distributed along the face of the element, but it was found that using Gaussian springs, only up to 2 springs were required for perfectly elastic cases, while with equal springs at least 5 springs were required. The method runs on a Newton-Raphson iteration scheme, and quadratic convergence was obtained. The second modification is based on adapting the number of springs required depending on the elasticity of the material. After the first Newton Raphson iteration, Von Mises stress conditions were used to calculate the stresses in the springs, and the springs are classified as elastic or plastic. Then transition springs, springs located exactly between the elastic and plastic region, are interpolated between regions to strictly identify the elastic and plastic regions in the cross section. Since a rectangular cross-section was analyzed, there were two plastic regions (top and bottom), and one elastic region (middle). The results of the present study show that elasto-plastic cases require only 2 springs for the elastic region, and 2 springs for the plastic region. This showed to improve the computational cost, reducing the minimum number of springs in elasto-plastic cases to only 6 springs. All the work is done using MATLAB and the results will be compared to models of structural elements using the finite element method in ANSYS.

Keywords: applied element method, elasto-plastic, Gaussian springs, nonlinear

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4033 Simulation and Fabrication of Plasmonic Lens for Bacteria Detection

Authors: Sangwoo Oh, Jaewoo Kim, Dongmin Seo, Jaewon Park, Yongha Hwang, Sungkyu Seo

Abstract:

Plasmonics has been regarded one of the most powerful bio-sensing modalities to evaluate bio-molecular interactions in real-time. However, most of the plasmonic sensing methods are based on labeling metallic nanoparticles, e.g. gold or silver, as optical modulation markers, which are non-recyclable and expensive. This plasmonic modulation can be usually achieved through various nano structures, e.g., nano-hole arrays. Among those structures, plasmonic lens has been regarded as a unique plasmonic structure due to its light focusing characteristics. In this study, we introduce a custom designed plasmonic lens array for bio-sensing, which was simulated by finite-difference-time-domain (FDTD) approach and fabricated by top-down approach. In our work, we performed the FDTD simulations of various plasmonic lens designs for bacteria sensor, i.e., Samonella and Hominis. We optimized the design parameters, i.e., radius, shape, and material, of the plasmonic lens. The simulation results showed the change in the peak intensity value with the introduction of each bacteria and antigen i.e., peak intensity 1.8711 a.u. with the introduction of antibody layer of thickness of 15nm. For Salmonella, the peak intensity changed from 1.8711 a.u. to 2.3654 a.u. and for Hominis, the peak intensity changed from 1.8711 a.u. to 3.2355 a.u. This significant shift in the intensity due to the interaction between bacteria and antigen showed a promising sensing capability of the plasmonic lens. With the batch processing and bulk production of this nano scale design, the cost of biological sensing can be significantly reduced, holding great promise in the fields of clinical diagnostics and bio-defense.

Keywords: plasmonic lens, FDTD, fabrication, bacteria sensor, salmonella, hominis

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4032 Fabrication of Drug-Loaded Halloysite Nanotubes Containing Sodium Alginate/Gelatin Composite Scaffolds

Authors: Masoumeh Haghbin Nazarpak, Hamidreza Tolabi, Aryan Ekhlasi

Abstract:

Bone defects are mentioned as one of the most challenging clinical conditions, affecting millions of people each year. A fracture, osteoporosis, tumor, or infection usually causes these defects. At present, autologous and allogeneic grafts are used to correct bone defects, but these grafts have some difficulties, such as limited access, infection, disease transmission, and immune rejection. Bone tissue engineering is considered a new strategy for repairing bone defects. However, problems with scaffolds’ design with unique structures limit their clinical applications. In addition, numerous in-vitro studies have been performed on the behavior of bone cells in two-dimensional environments. Still, cells grow in physiological situations in the human body in a three-dimensional environment. As a result, the controlled design of porous structures with high structural complexity and providing the necessary flexibility to meet specific needs in bone tissue repair is beneficial. For this purpose, a three-dimensional composite scaffold based on gelatin and sodium alginate hydrogels is used in this research. In addition, the antibacterial drug-loaded halloysite nanotubes were introduced into the hydrogel scaffold structure to provide a suitable substrate for controlled drug release. The presence of halloysite nanotubes improved hydrogel’s properties, while the drug eliminated infection and disease transmission. Finally, it can be acknowledged that the composite scaffold prepared in this study for bone tissue engineering seems promising.

Keywords: halloysite nanotubes, bone tissue engineering, composite scaffold, controlled drug release

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4031 Perceived Structural Empowerment and Work Commitment among Intensive Care nurses in SMC

Authors: Ridha Abdulla Al Hammam

Abstract:

Purpose: to measure the extent of perceived structural empowerment and work commitment the intensive care unit in SMC have in their work place. Background: nurses’ access to power structures (information, recourses, opportunity, and support) directly influences their productivity, retention, and job satisfaction. Exploring nurses’ level and sources of work commitment (affective, normative, and continuance) is very essential to guide nursing leaders making decisions to improve work environment to facilitate effective nursing care. Both concepts (Structural Empowerment and Work Commitment) were never investigated in our critical care unit. Methods: a sample of 50 nurses attained from the Intensive Care Unit (Adult). Conditions for Workplace Effectiveness Questionnaire and Three-Component Model Employee Commitment Survey were used to measure the two concepts respectively. The study is quantitative, descriptive, and correlational in design. Results: the participants reported moderate structural empowerment provided by their work place (M=15 out of 20). The sample perceived high access to opportunity mainly through gaining more skills (M=4.45 out of 5) where the rest power structures were perceived with moderate accessibility. The participants’ affective commitment (M=5.6 out of 7) to work in the ICU overweighed their normative and continuance commitment (M=5.1, M=4.9 out of 7) implying a stronger emotional connection with their unit. Strong positive and significant correlations were observed between the participants’ structural empowerment scores and all work commitment sources. Conclusion: these results provided an insight on aspects of work environment that need to be fostered and improved in our intensive care unit which have a direct linkage to nurses’ work commitment and potentially to their quality of care they provide.

Keywords: structural empowerment, commitment, intensive care, nurses

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4030 A Context-Centric Chatbot for Cryptocurrency Using the Bidirectional Encoder Representations from Transformers Neural Networks

Authors: Qitao Xie, Qingquan Zhang, Xiaofei Zhang, Di Tian, Ruixuan Wen, Ting Zhu, Ping Yi, Xin Li

Abstract:

Inspired by the recent movement of digital currency, we are building a question answering system concerning the subject of cryptocurrency using Bidirectional Encoder Representations from Transformers (BERT). The motivation behind this work is to properly assist digital currency investors by directing them to the corresponding knowledge bases that can offer them help and increase the querying speed. BERT, one of newest language models in natural language processing, was investigated to improve the quality of generated responses. We studied different combinations of hyperparameters of the BERT model to obtain the best fit responses. Further, we created an intelligent chatbot for cryptocurrency using BERT. A chatbot using BERT shows great potential for the further advancement of a cryptocurrency market tool. We show that the BERT neural networks generalize well to other tasks by applying it successfully to cryptocurrency.

Keywords: bidirectional encoder representations from transformers, BERT, chatbot, cryptocurrency, deep learning

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4029 Design of the Intelligent Virtual Learning Coach. A Contextual Learning Approach to Digital Literacy of Senior Learners in the Context of Electronic Health Record (EHR)

Authors: Ilona Buchem, Carolin Gellner

Abstract:

The call for the support of senior learners in the development of digital literacy has become prevalent in recent years, especially in view of the aging societies paired with advances in digitalization in all spheres of life, including e-health. The goal has been to create opportunities for learning that incorporate the use of context in a reflective and dialogical way. Contextual learning has focused on developing skills through the application of authentic problems. While major research efforts in supporting senior learners in developing digital literacy have been invested so far in e-learning, focusing on knowledge acquisition and cognitive tasks, little research exists in reflective mentoring and coaching with the help of pedagogical agents and addressing the contextual dimensions of learning. This paper describes an approach to creating opportunities for senior learners to improve their digital literacy in the authentic context of the electronic health record (EHR) with the support of an intelligent virtual learning coach. The paper focuses on the design of the virtual coach as part of an e-learning system, which was developed in the EPA-Coach project founded by the German Ministry of Education and Research. The paper starts with the theoretical underpinnings of contextual learning and the related design considerations for a virtual learning coach based on previous studies. Since previous research in the area was mostly designed to cater to the needs of younger audiences, the results had to be adapted to the specific needs of senior learners. Next, the paper outlines the stages in the design of the virtual coach, which included the adaptation of the design requirements, the iterative development of the prototypes, the results of the two evaluation studies and how these results were used to improve the design of the virtual coach. The paper then presents the four prototypes of a senior-friendly virtual learning coach, which were designed to represent different preferences related to the visual appearance, the communication and social interaction styles, and the pedagogical roles. The first evaluation of the virtual coach design was an exploratory, qualitative study, which was carried out in October 2020 with eight seniors aged 64 to 78 and included a range of questions about the preferences of senior learners related to the visual design, gender, age, communication and role. Based on the results of the first evaluation, the design was adapted to the preferences of the senior learners and the new versions of prototypes were created to represent two male and two female options of the virtual coach. The second evaluation followed a quantitative approach with an online questionnaire and was conducted in May 2021 with 41 seniors aged 66 to 93 years. Following three research questions, the survey asked about (1) the intention to use, (2) the perceived characteristics, and (3) the preferred communication/interaction style of the virtual coach, i. e. task-oriented, relationship-oriented, or a mix. This paper follows with the discussion of the results of the design process and ends with conclusions and next steps in the development of the virtual coach including recommendations for further research.

Keywords: virtual learning coach, virtual mentor, pedagogical agent, senior learners, digital literacy, electronic health records

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4028 Making Unorganized Social Groups Responsible for Climate Change: Structural Analysis

Authors: Vojtěch Svěrák

Abstract:

Climate change ethics have recently shifted away from individualistic paradigms towards concepts of shared or collective responsibility. Despite this evolving trend, a noticeable gap remains: a lack of research exclusively addressing the moral responsibility of specific unorganized social groups. The primary objective of the article is to fill this gap. The article employs the structuralist methodological approach proposed by some feminist philosophers, utilizing structural analysis to explain the existence of social groups. The argument is made for the integration of this framework with the so-called forward-looking Social Connection Model (SCM) of responsibility, which ascribes responsibilities to individuals based on their participation in social structures. The article offers an extension of this model to justify the responsibility of unorganized social groups. The major finding of the study is that although members of unorganized groups are loosely connected, collectively they instantiate specific external social structures, share social positioning, and the notion of responsibility could be based on that. Specifically, if the structure produces harm or perpetuates injustices, and the group both benefits from and possesses the capacity to significantly influence the structure, a greater degree of responsibility should be attributed to the group as a whole. This thesis is applied and justified within the context of climate change, based on the asymmetrical positioning of different social groups. Climate change creates a triple inequality: in contribution, vulnerability, and mitigation. The study posits that different degrees of group responsibility could be drawn from these inequalities. Two social groups serve as a case study for the article: first, the Pakistan lower class, consisting of people living below the national poverty line, with a low greenhouse gas emissions rate, severe climate change-related vulnerability due to the lack of adaptation measures, and with very limited options to participate in the mitigation of climate change. Second, the so-called polluter elite, defined by members' investments in polluting companies and high-carbon lifestyles, thus with an interest in the continuation of structures leading to climate change. The first identified group cannot be held responsible for climate change, but their group interest lies in structural change and should be collectively maintained. On the other hand, the responsibility of the second identified group is significant and can be fulfilled by a justified demand for some political changes. The proposed approach of group responsibility is suggested to help navigate climate justice discourse and environmental policies, thus helping with the sustainability transition.

Keywords: collective responsibility, climate justice, climate change ethics, group responsibility, social ontology, structural analysis

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4027 Series Network-Structured Inverse Models of Data Envelopment Analysis: Pitfalls and Solutions

Authors: Zohreh Moghaddas, Morteza Yazdani, Farhad Hosseinzadeh

Abstract:

Nowadays, data envelopment analysis (DEA) models featuring network structures have gained widespread usage for evaluating the performance of production systems and activities (Decision-Making Units (DMUs)) across diverse fields. By examining the relationships between the internal stages of the network, these models offer valuable insights to managers and decision-makers regarding the performance of each stage and its impact on the overall network. To further empower system decision-makers, the inverse data envelopment analysis (IDEA) model has been introduced. This model allows the estimation of crucial information for estimating parameters while keeping the efficiency score unchanged or improved, enabling analysis of the sensitivity of system inputs or outputs according to managers' preferences. This empowers managers to apply their preferences and policies on resources, such as inputs and outputs, and analyze various aspects like production, resource allocation processes, and resource efficiency enhancement within the system. The results obtained can be instrumental in making informed decisions in the future. The top result of this study is an analysis of infeasibility and incorrect estimation that may arise in the theory and application of the inverse model of data envelopment analysis with network structures. By addressing these pitfalls, novel protocols are proposed to circumvent these shortcomings effectively. Subsequently, several theoretical and applied problems are examined and resolved through insightful case studies.

Keywords: inverse models of data envelopment analysis, series network, estimation of inputs and outputs, efficiency, resource allocation, sensitivity analysis, infeasibility

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4026 Development and Characterization of Ceramic-Filled Composite Filaments and Functional Structures for Fused Deposition Modeling

Authors: B. Khatri, K. Lappe, M. Habedank, T. Müller, C. Megnin, T. Hanemann

Abstract:

We present a process flow for the development of ceramic-filled polymer composite filaments compatible with the fused deposition modeling (FDM) 3D printing process. Thermoplastic-ceramic composites were developed using acrylonitrile butadiene styrene (ABS) and 10- and 20 vol.% barium titanate (BaTiO3) powder (corresponding to 39.47- and 58.23 wt.% respectively) and characterized for their flow properties. To make them compatible with the existing FDM process, the composites were extruded into filaments. These composite filaments were subsequently structured into tensile stress specimens using a commercially available FDM 3D printer and characterized for their mechanical properties. Rheometric characterization of the material composites revealed non-Newtonian behavior with the viscosity logarithmically decreasing over increasing shear rates, as well as higher viscosities for samples with higher BaTiO3 filler content for a given shear rate (with the ABS+20vol.% BaTiO3 composite being over 50% more viscous compared to pure ABS at a shear rate of 1x〖10〗^3 s^(-1)). Mechanical characterization of the tensile stress specimens exhibited increasingly brittle behavior as well as a linearly decreasing ultimate tensile strength of the material composites with increasing volumetric ratio of BaTiO3 (from σ_max=32.4MPa for pure ABS to σ_max=21.3MPa for ABS+20vol.% BaTiO3). Further studies being undertaken include the development of composites with higher filler concentrations, sintering of the printed composites to yield pure dielectric structures and the determination of the dielectric characteristics of the composites.

Keywords: ceramic composites, fused deposition modeling, material characterization, rapid prototyping

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4025 Retrofitting Adaptive Reuse into Palaces of Northern India

Authors: Shefali Nayak

Abstract:

The architectural appeal, familiarity, and idiom of culturally significant structures are due to societal attachment to various movements, historical association or deviation. Generally, the urge to preserve a building in the northern part of India is driven either by emotional dogma or rational thinking, but, it is also influenced by traditional affinity. The northern region of India has an assortment of palaces and Havelis belonging to various time periods and families with vernacular yet signature style of architecture. Many of them are either successfully conserved by being put into adaptive reuse and some of them have been midst controversies and continued to remain in ruins. The research focuses on comparing successful examples of adaptive reuse such as Neemrana, Mehrangargh Fort palace with a few other merchant havelis converted into heritage hotels. Furthermore, evaluates the architectural aspects of structure, materials, plumbing and electrical installations, as well as specific challenges faced by heritage professionals practicing sustainability, while respecting traditional feelings of various stakeholders. This paper concludes through the analysis of the case study that, its highly unlikely for sustainable design cannot be used as a stand-alone application for heritage structures or cities, it needs the support of architecture conservation to be put into practice. However, it is often demanding to fit a new use of a building into an aged structure. This paper records modern-day generic requirements that reflect challenges faced by different architects, while conserving a heritage structure and retrofitting it into today's requisites. The research objective is to establish how conservation, restoration, and urban regeneration are closely related to sustainable architecture in historical cities.

Keywords: architecture conservation, architecture heritage, adaptive reuse, retrofitting, sustainability, urban regeneration

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4024 Evaluating Probable Bending of Frames for Near-Field and Far-Field Records

Authors: Majid Saaly, Shahriar Tavousi Tafreshi, Mehdi Nazari Afshar

Abstract:

Most reinforced concrete structures are designed only under heavy loads have large transverse reinforcement spacing values, and therefore suffer severe failure after intense ground movements. The main goal of this paper is to compare the shear- and axial failure of concrete bending frames available in Tehran using incremental dynamic analysis under near- and far-field records. For this purpose, IDA analyses of 5, 10, and 15-story concrete structures were done under seven far-fault records and five near-faults records. The results show that in two-dimensional models of short-rise, mid-rise and high-rise reinforced concrete frames located on Type-3 soil, increasing the distance of the transverse reinforcement can increase the maximum inter-story drift ratio values up to 37%. According to the existing results on 5, 10, and 15-story reinforced concrete models located on Type-3 soil, records with characteristics such as fling-step and directivity create maximum drift values between floors more than far-fault earthquakes. The results indicated that in the case of seismic excitation modes under earthquake encompassing directivity or fling-step, the probability values of failure and failure possibility increasing rate values are much smaller than the corresponding values of far-fault earthquakes. However, in near-fault frame records, the probability of exceedance occurs at lower seismic intensities compared to far-fault records.

Keywords: IDA, failure curve, directivity, maximum floor drift, fling step, evaluating probable bending of frames, near-field and far-field earthquake records

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4023 Through-Bolt Moment Connection in HSS Column

Authors: Bardia Khafaf, Mehrdad Ghaffari, Amir Hussein Samakar

Abstract:

It is currently desirable to use Hollow Square Sections (HSS) in moment resistant structures in construction of building because they offer fewer restrictions for designing and more useful space while adhering to build design codes. This paper present a through bolt connection in HSS column. This connection meets building code standards that require the moment resistant connections to deflect and absorb energy resulting from gravity and seismic loads. Connection through bolts is installed and pretension to provide the connection strength needed to make a beam–column moment rigid zone. A rigid joint is typically used to resist lateral forces by holding columns and beams fixed in relation to one another. With bolted moment frames using HSS columns, a through–bolt connection could be used to secure the beam and end plate to the column. However, when multiple columns and beams are used to span a length of building, the use of through-bolts would necessities aligning multiple beams simultaneously to the columns. In the case of a linear span, the assembly process requires the holes of a first beam end plate to be aligned with through bolt holes in a column and aligning the holes of a second, opposing beam plate with the column through bolt, then inserting the through bolts in each hole for tightening with nuts and washers. In moment resistant building, a problem arises when assembling beams to columns where multiple beams and columns are required. Through bolt, moment connections are among the economical, practical and not difficult rigid steel connection for HSS column building. In this paper, the results of numerous analytical studies performed for moment structures with HSS columns with through bolt based on AISC standard codes are shown.

Keywords: through bolt, moment resistant connection, HSS columns section, construction engineering

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4022 A Case Study of Alkali-Silica Reaction Induced Consistent Damage and Strength Degradation Evaluation in a Textile Mill Building Due to Slow-Reactive Aggregates

Authors: Ahsan R. Khokhar, Fizza Hassan

Abstract:

Alkali-Silica Reaction (ASR) has been recognized as a potential cause of concrete degradation in the world since the 1940s. In Pakistan, mega hydropower structures like dams, weirs constructed from aggregates extracted from a local riverbed exhibited different levels of alkali-silica reactivity over an extended service period. The concrete expansion potential due to such aggregates has been categorized as slow-reactive. Apart from hydropower structures, ASR existence has been identified in the concrete structural elements of a Textile Mill building which used aggregates extracted from the nearby riverbed. The original structure of the Textile Mill was erected in the 80s with the addition of a textile ‘sizing and wrapping’ hall constructed in the 90s. In the years to follow, intensive spalling was observed in the structural members of the subject hall; enough to threat to the overall stability of the building. Limitations such as incomplete building data posed hurdles during the detailed structural investigation. The paper lists observations made while assessing the extent of damage and its effect on the building hall structure. Core testing and Petrographic tests were carried out as per the ASTM standards for strength degradation analysis followed by the identifying its root cause. Results confirmed significant structural strength reduction because of ASR which necessitated the formulation of an immediate re-strengthening solution. The paper also discusses the possible tracks of rehabilitative measures which are being adapted to stabilize the structure and seize further concrete expansion.

Keywords: Alkali-Silica Reaction (ASR), concrete strength degradation, damage assessment, damage evaluation

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4021 Experimental Investigation on the Fire Performance of Corrugated Sandwich Panels made from Renewable Material

Authors: Avishek Chanda, Nam Kyeun Kim, Debes Bhattacharyya

Abstract:

The use of renewable substitutes in various semi-structural and structural applications has experienced an increase since the last few decades. Sandwich panels have been used for many decades, although research on understanding the effects of the core structures on the panels’ fire-reaction properties is limited. The current work investigates the fire-performance of a corrugated sandwich panel made from renewable, biodegradable, and sustainable material, plywood. The bench-scale fire testing apparatus, cone-calorimeter, was employed to evaluate the required fire-reaction properties of the sandwich core in a panel configuration, with three corrugated layers glued together with face-sheets under a heat irradiance of 50 kW/m2. The study helped in documenting a unique heat release trend associated with the fire performance of the 3-layered corrugated sandwich panels and in understanding the structural stability of the samples in the event of a fire. Furthermore, the total peak heat release rate was observed to be around 421 kW/m2, which is significantly low compared to many polymeric materials in the literature. The total smoke production was also perceived to be very limited compared to other structural materials, and the total heat release was also nominal. The time to ignition of 21.7 s further outlined the advantages of using the plywood component since polymeric composites, even with flame-retardant additives, tend to ignite faster. Overall, the corrugated plywood sandwich panels had significant fire-reaction properties and could have important structural applications. The possible use of structural panels made from bio-degradable material opens a new avenue for the use of similar structures in sandwich panel preparation.

Keywords: corrugated sandwich panel, fire-reaction properties, plywood, renewable material

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4020 The Meaning Structures of Political Participation of Young Women: Preliminary Findings in a Practical Phenomenology Study

Authors: Amanda Aliende da Matta, Maria del Pilar Fogueiras Bertomeu, Valeria de Ormaechea Otalora, Maria Paz Sandin Esteban, Miriam Comet Donoso

Abstract:

This communication presents the preliminary emerging themes in a research on political participation of young women. The study follows a qualitative methodology; in particular, the applied hermeneutic phenomenological method, and the general objective of the research is to give an account of the experience of political participation as young women. The study participants are women aged 18 to 35 who have experience in political participation. The techniques of data collection are the descriptive story and the phenomenological interview. With respect to the first methodological steps, these have been: 1) collect and select stories of lived experience in political participation, 2) select descriptions of lived experience (DLEs) in political participation of the chosen stories, 3) to prepare phenomenological interviews from the selected DLEs, 4) to conduct phenomenological thematic analysis (PTA) of the DLEs. We have so far initiated the PTA on 5 vignettes. Hermeneutic phenomenology as a research approach is based on phenomenological philosophy and applied hermeneutics. Phenomenology is a descriptive philosophy of pure experience and essences, through which we seek to capture an experience at its origins without categorizing, interpreting or theorizing it. Hermeneutics, on the other hand, may be defined as a philosophical current that can be applied to data analysis. Max Van Manen wrote that hermeneutic phenomenology is a method of abstemious reflection on the basic structures of the lived experience of human existence. In hermeneutic phenomenology we focus, then, on the way we experience “things” in the first person, seeking to capture the world exactly as we experience it, not as we categorize or conceptualize it. In this study, the empirical methods used were: Lived experience description (written) and conversational interview. For these short stories, participants were asked: “What was your lived experience of participation in politics as a young woman? Can you tell me any stories or anecdotes that you think exemplify or typify your experience?”. The questions were accompanied by a list of guidelines for writing descriptive vignettes. And the analytical method was PTA. Among the provisional results, we found preliminary emerging themes, which could in the advance of the investigation result in meaning structures of political participation of young women. They are the following: - Complicity may be inherent/essential in political participation as a young woman; - Feelings may be essential/inherent in political participation as a young woman; - Hope may be essential in authentic political participation as a young woman; - Frustration may be essential in authentic political participation as a young woman; - Satisfaction may be essential in authentic political participation as a young woman; - There may be tension between individual/collective inherent/essential in political participation as a young woman; - Political participation as a young woman may include moments of public demonstration.

Keywords: applied hermeneutic phenomenology, hermeneutics, phenomenology, political participation

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4019 Trigonelline: A Promising Compound for The Treatment of Alzheimer's Disease

Authors: Mai M. Farid, Ximeng Yang, Tomoharu Kuboyama, Chihiro Tohda

Abstract:

Trigonelline is a major alkaloid component derived from Trigonella foenum-graecum L. (fenugreek) and has been reported before as a potential neuroprotective agent, especially in Alzheimer’s disease (AD). However, the previous data were unclear and used model mice were not well established. In the present study, the effect of trigonelline on memory function was investigated in Alzheimer’s disease transgenic model mouse, 5XFAD which overexpresses the mutated APP and PS1 genes. Oral administration of trigonelline for 14 days significantly enhanced object recognition and object location memories. Plasma and cerebral cortex were isolated at 30 min, 1h, 3h, and 6 h after oral administration of trigonelline. LC-MS/MS analysis indicated that trigonelline was detected in both plasma and cortex from 30 min after, suggesting good penetration of trigonelline into the brain. In addition, trigonelline significantly ameliorated axonal and dendrite atrophy in Amyloid β-treated cortical neurons. These results suggest that trigonelline could be a promising therapeutic candidate for AD.

Keywords: alzheimer’s disease, cortical neurons, LC-MS/MS analysis, trigonelline

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4018 IT and Security Experts' Innovation and Investment Front for IT-Entrepreneurship in Pakistan

Authors: Ahmed Mateen, Zhu Qingsheng, Muhammad Awais, Muhammad Yahya Saeed

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This paper targets the rising factor of entrepreneurship innovation, which lacks in Pakistan as compared to the other countries or the regions like China, India, and Malaysia, etc. This is an exploratory and explanatory study. Major aspects have identified as the direction for the policymakers while highlighting the issues in true spirit. IT needs to be considered not only as a technology but also as itself growing as a new community. IT management processes are complex and broad, so generally requires extensive attention to the collective aspects of human variables, capital and technology. In addition, projects tend to have a special set of critical success factors, and if these are processed and given attention, it will improve the chances of successful implementation. This is only possible with state of the art intelligent decision support systems and accumulating IT staff to some extent in decision processes. This paper explores this issue carefully and discusses six issues to observe the implemented strength and possible enhancement.

Keywords: security and defense forces, IT-incentives, big IT-players, IT-entrepreneurial-culture

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4017 Organizational Learning Strategies for Building Organizational Resilience

Authors: Stephanie K. Douglas, Gordon R. Haley

Abstract:

Organizations face increasing disruptions, changes, and uncertainties through the rapid shifts in the economy and business environment. A capacity for resilience is necessary for organizations to survive and thrive in such adverse conditions. Learning is an essential component of an organization's capability for building resilience. Strategic human resource management is a principal component of learning and organizational resilience. To achieve organizational resilience, human resource management strategies must support individual knowledge, skills, and ability development through organizational learning. This study aimed to contribute to the comprehensive knowledge of the relationship between strategic human resource management and organizational learning to build organizational resilience. The organizational learning dimensions of knowledge acquisition, knowledge distribution, knowledge interpretation, and organizational memory can be fostered through human resource management strategies and then aggregated to the organizational level to build resilience.

Keywords: human resource development, human resource management, organizational learning, organizational resilience

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4016 Parallel Genetic Algorithms Clustering for Handling Recruitment Problem

Authors: Walid Moudani, Ahmad Shahin

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This research presents a study to handle the recruitment services system. It aims to enhance a business intelligence system by embedding data mining in its core engine and to facilitate the link between job searchers and recruiters companies. The purpose of this study is to present an intelligent management system for supporting recruitment services based on data mining methods. It consists to apply segmentation on the extracted job postings offered by the different recruiters. The details of the job postings are associated to a set of relevant features that are extracted from the web and which are based on critical criterion in order to define consistent clusters. Thereafter, we assign the job searchers to the best cluster while providing a ranking according to the job postings of the selected cluster. The performance of the proposed model used is analyzed, based on a real case study, with the clustered job postings dataset and classified job searchers dataset by using some metrics.

Keywords: job postings, job searchers, clustering, genetic algorithms, business intelligence

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4015 Forecasting Thermal Energy Demand in District Heating and Cooling Systems Using Long Short-Term Memory Neural Networks

Authors: Kostas Kouvaris, Anastasia Eleftheriou, Georgios A. Sarantitis, Apostolos Chondronasios

Abstract:

To achieve the objective of almost zero carbon energy solutions by 2050, the EU needs to accelerate the development of integrated, highly efficient and environmentally friendly solutions. In this direction, district heating and cooling (DHC) emerges as a viable and more efficient alternative to conventional, decentralized heating and cooling systems, enabling a combination of more efficient renewable and competitive energy supplies. In this paper, we develop a forecasting tool for near real-time local weather and thermal energy demand predictions for an entire DHC network. In this fashion, we are able to extend the functionality and to improve the energy efficiency of the DHC network by predicting and adjusting the heat load that is distributed from the heat generation plant to the connected buildings by the heat pipe network. Two case-studies are considered; one for Vransko, Slovenia and one for Montpellier, France. The data consists of i) local weather data, such as humidity, temperature, and precipitation, ii) weather forecast data, such as the outdoor temperature and iii) DHC operational parameters, such as the mass flow rate, supply and return temperature. The external temperature is found to be the most important energy-related variable for space conditioning, and thus it is used as an external parameter for the energy demand models. For the development of the forecasting tool, we use state-of-the-art deep neural networks and more specifically, recurrent networks with long-short-term memory cells, which are able to capture complex non-linear relations among temporal variables. Firstly, we develop models to forecast outdoor temperatures for the next 24 hours using local weather data for each case-study. Subsequently, we develop models to forecast thermal demand for the same period, taking under consideration past energy demand values as well as the predicted temperature values from the weather forecasting models. The contributions to the scientific and industrial community are three-fold, and the empirical results are highly encouraging. First, we are able to predict future thermal demand levels for the two locations under consideration with minimal errors. Second, we examine the impact of the outdoor temperature on the predictive ability of the models and how the accuracy of the energy demand forecasts decreases with the forecast horizon. Third, we extend the relevant literature with a new dataset of thermal demand and examine the performance and applicability of machine learning techniques to solve real-world problems. Overall, the solution proposed in this paper is in accordance with EU targets, providing an automated smart energy management system, decreasing human errors and reducing excessive energy production.

Keywords: machine learning, LSTMs, district heating and cooling system, thermal demand

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4014 Secure Intelligent Information Management by Using a Framework of Virtual Phones-On Cloud Computation

Authors: Mohammad Hadi Khorashadi Zadeh

Abstract:

Many new applications and internet services have been emerged since the innovation of mobile networks and devices. However, these applications have problems of security, management, and performance in business environments. Cloud systems provide information transfer, management facilities, and security for virtual environments. Therefore, an innovative internet service and a business model are proposed in the present study for creating a secure and consolidated environment for managing the mobile information of organizations based on cloud virtual phones (CVP) infrastructures. Using this method, users can run Android and web applications in the cloud which enhance performance by connecting to other CVP users and increases privacy. It is possible to combine the CVP with distributed protocols and central control which mimics the behavior of human societies. This mix helps in dealing with sensitive data in mobile devices and facilitates data management with less application overhead.

Keywords: BYOD, mobile cloud computing, mobile security, information management

Procedia PDF Downloads 317
4013 Modular Robotics and Terrain Detection Using Inertial Measurement Unit Sensor

Authors: Shubhakar Gupta, Dhruv Prakash, Apoorv Mehta

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In this project, we design a modular robot capable of using and switching between multiple methods of propulsion and classifying terrain, based on an Inertial Measurement Unit (IMU) input. We wanted to make a robot that is not only intelligent in its functioning but also versatile in its physical design. The advantage of a modular robot is that it can be designed to hold several movement-apparatuses, such as wheels, legs for a hexapod or a quadpod setup, propellers for underwater locomotion, and any other solution that may be needed. The robot takes roughness input from a gyroscope and an accelerometer in the IMU, and based on the terrain classification from an artificial neural network; it decides which method of propulsion would best optimize its movement. This provides the bot with adaptability over a set of terrains, which means it can optimize its locomotion on a terrain based on its roughness. A feature like this would be a great asset to have in autonomous exploration or research drones.

Keywords: modular robotics, terrain detection, terrain classification, neural network

Procedia PDF Downloads 145
4012 The Budget Impact of the DISCERN™ Diagnostic Test for Alzheimer’s Disease in the United States

Authors: Frederick Huie, Lauren Fusfeld, William Burchenal, Scott Howell, Alyssa McVey, Thomas F. Goss

Abstract:

Alzheimer’s Disease (AD) is a degenerative brain disease characterized by memory loss and cognitive decline that presents a substantial economic burden for patients and health insurers in the US. This study evaluates the payer budget impact of the DISCERN™ test in the diagnosis and management of patients with symptoms of dementia evaluated for AD. DISCERN™ comprises three assays that assess critical factors related to AD that regulate memory, formation of synaptic connections among neurons, and levels of amyloid plaques and neurofibrillary tangles in the brain and can provide a quicker, more accurate diagnosis than tests in the current diagnostic pathway (CDP). An Excel-based model with a three-year horizon was developed to assess the budget impact of DISCERN™ compared with CDP in a Medicare Advantage plan with 1M beneficiaries. Model parameters were identified through a literature review and were verified through consultation with clinicians experienced in diagnosis and management of AD. The model assesses direct medical costs/savings for patients based on the following categories: •Diagnosis: costs of diagnosis using DISCERN™ and CDP. •False Negative (FN) diagnosis: incremental cost of care avoidable with a correct AD diagnosis and appropriately directed medication. •True Positive (TP) diagnosis: AD medication costs; cost from a later TP diagnosis with the CDP versus DISCERN™ in the year of diagnosis, and savings from the delay in AD progression due to appropriate AD medication in patients who are correctly diagnosed after a FN diagnosis.•False Positive (FP) diagnosis: cost of AD medication for patients who do not have AD. A one-way sensitivity analysis was conducted to assess the effect of varying key clinical and cost parameters ±10%. An additional scenario analysis was developed to evaluate the impact of individual inputs. In the base scenario, DISCERN™ is estimated to decrease costs by $4.75M over three years, equating to approximately $63.11 saved per test per year for a cohort followed over three years. While the diagnosis cost is higher with DISCERN™ than with CDP modalities, this cost is offset by the higher overall costs associated with CDP due to the longer time needed to receive a TP diagnosis and the larger number of patients who receive a FN diagnosis and progress more rapidly than if they had received appropriate AD medication. The sensitivity analysis shows that the three parameters with the greatest impact on savings are: reduced sensitivity of DISCERN™, improved sensitivity of the CDP, and a reduction in the percentage of disease progression that is avoided with appropriate AD medication. A scenario analysis in which DISCERN™ reduces the utilization for patients of computed tomography from 21% in the base case to 16%, magnetic resonance imaging from 37% to 27% and cerebrospinal fluid biomarker testing, positive emission tomography, electroencephalograms, and polysomnography testing from 4%, 5%, 10%, and 8%, respectively, in the base case to 0%, results in an overall three-year net savings of $14.5M. DISCERN™ improves the rate of accurate, definitive diagnosis of AD earlier in the disease and may generate savings for Medicare Advantage plans.

Keywords: Alzheimer’s disease, budget, dementia, diagnosis.

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4011 Coupling Large Language Models with Disaster Knowledge Graphs for Intelligent Construction

Authors: Zhengrong Wu, Haibo Yang

Abstract:

In the context of escalating global climate change and environmental degradation, the complexity and frequency of natural disasters are continually increasing. Confronted with an abundance of information regarding natural disasters, traditional knowledge graph construction methods, which heavily rely on grammatical rules and prior knowledge, demonstrate suboptimal performance in processing complex, multi-source disaster information. This study, drawing upon past natural disaster reports, disaster-related literature in both English and Chinese, and data from various disaster monitoring stations, constructs question-answer templates based on large language models. Utilizing the P-Tune method, the ChatGLM2-6B model is fine-tuned, leading to the development of a disaster knowledge graph based on large language models. This serves as a knowledge database support for disaster emergency response.

Keywords: large language model, knowledge graph, disaster, deep learning

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4010 Comparison of the Existing Damage Indices in Steel Moment-Resisting Frame Structures

Authors: Hamid Kazemi, Abbasali Sadeghi

Abstract:

Assessment of seismic behavior of frame structures is just done for evaluating life and financial damages or lost. The new structural seismic behavior assessment methods have been proposed, so it is necessary to define a formulation as a damage index, which the damage amount has been quantified and qualified. In this paper, four new steel moment-resisting frames with intermediate ductility and different height (2, 5, 8, and 12-story) with regular geometry and simple rectangular plan were supposed and designed. The three existing groups’ damage indices were studied, each group consisting of local index (Drift, Maximum Roof Displacement, Banon Failure, Kinematic, Banon Normalized Cumulative Rotation, Cumulative Plastic Rotation and Ductility), global index (Roufaiel and Meyer, Papadopoulos, Sozen, Rosenblueth, Ductility and Base Shear), and story (Banon Failure and Inter-story Rotation). The necessary parameters for these damage indices have been calculated under the effect of far-fault ground motion records by Non-linear Dynamic Time History Analysis. Finally, prioritization of damage indices is defined based on more conservative values in terms of more damageability rate. The results show that the selected damage index has an important effect on estimation of the damage state. Also, failure, drift, and Rosenblueth damage indices are more conservative indices respectively for local, story and global damage indices.

Keywords: damage index, far-fault ground motion records, non-linear time history analysis, SeismoStruct software, steel moment-resisting frame

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4009 Free Raducal Scavenging Activity of Fractionated Extract and Structural Elucidation of Isolated Compounds from Hydrocotyl Bonariensis Comm. Ex Lam Leaves

Authors: Emmanuel O Ajani, Sabiu S, Mariam Zakari, Fisayo A Bamisaye

Abstract:

Hydrocotyl bonariensis is a plant which anticataractogenic potentials have been reported. In the present study an attempt was made to evaluate the in vitro antioxidant activity of the fractionates of the leaves extract and also characterize some of its chemical constituents. DPPH, H₂O₂, OH and NO free radical scavenging, metal chelating and reducing power activity was used to evaluate the antioxidant activity of the crude extract fractionates. Fresh leaves of Hydrocotyl bonariensis leaves were extracted in 70% methanol. The extract was partitioned with different solvent system of increasing polarity (n-hexane, chloroform, ethyl acetate methanol and water). Compounds were isolated from the aqueous practitionate using accelerated gradient chromatography, vacuum liquid chromatography, preparative TLC and conventional column chromatography. The presence of the chemical groups was established with HPLC and Fourier Transform Infra Red. The structures of isolated compounds were elucidated by spectroscopic study and chemical shifts. Data from the study indicates that all the fractionates contain compounds with free radical scavenging activity. This activity was more pronounced in the aqueous fractionate (DPPH IC₅₀, 0025 ± 0.011 mg/ml, metal chelating capacity 27.5%, OH- scavenging IC₅₀, 0.846 ± 0.037 mg/ml, H₂O₂ scavenging IC₅₀ 0.521 ± 0.015 mg/ml, reducing power IC₅₀ 0.248 ± 0.025 mg/ml and NO scavenging IC₅₀ 0.537 ± 0.038 mg/ml). Two compounds were isolated and when compared with data from the literature; the structures were suggestive of polyphenolic flavonoid, quercetin and 3-O-β-D-glucopyranosyl-sitosterol. The result indicates that H. bonariensis leaves contain bioactive compounds with antioxidant activity.

Keywords: antioxidant, cataract, free radical, flavonoids, hydrocotyl bonariensis

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4008 Application of Electrochemical Impedance Spectroscopy to Monitor the Steel/Soil Interface During Cathodic Protection of Steel in Simulated Soil Solution

Authors: Mandlenkosi George Robert Mahlobo, Tumelo Seadira, Major Melusi Mabuza, Peter Apata Olubambi

Abstract:

Cathodic protection (CP) has been widely considered a suitable technique for mitigating corrosion of buried metal structures. Plenty of efforts have been made in developing techniques, in particular non-destructive techniques, for monitoring and quantifying the effectiveness of CP to ensure the sustainability and performance of buried steel structures. The aim of this study was to investigate the evolution of the electrochemical processes at the steel/soil interface during the application of CP on steel in simulated soil. Carbon steel was subjected to electrochemical tests with NS4 solution used as simulated soil conditions for 4 days before applying CP for a further 11 days. A previously modified non-destructive voltammetry technique was applied before and after the application of CP to measure the corrosion rate. Electrochemical impedance spectroscopy (EIS), in combination with mathematical modeling through equivalent electric circuits, was applied to determine the electrochemical behavior at the steel/soil interface. The measured corrosion rate was found to have decreased from 410 µm/yr to 8 µm/yr between days 5 and 14 because of the applied CP. Equivalent electrical circuits were successfully constructed and used to adequately model the EIS results. The modeling of the obtained EIS results revealed the formation of corrosion products via a mixed activation-diffusion mechanism during the first 4 days, while the activation mechanism prevailed in the presence of CP, resulting in a protective film. The x-ray diffraction analysis confirmed the presence of corrosion products and the predominant protective film corresponding to the calcareous deposit.

Keywords: carbon steel, cathodic protection, NS4 solution, voltammetry, EIS

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4007 The Effect of Corporate Governance to Islamic Banking Performance Using Maqasid Index Approach in Indonesia

Authors: Audia Syafa'atur Rahman, Rozali Haron

Abstract:

The practices of Islamic banking are more attuned to the goals of profit maximization rather than obtaining ethical profit. Ethical profit is obtained from interest-free earnings and to give an impact which benefits to the growth of society and economy. Good corporate governance practices are needed to assure the sustainability of Islamic banks in order to achieve Maqasid Shariah with the main purpose of boosting the well-being of people. The Maqasid Shariah performance measurement is used to measure the duties and responsibilities expected to be performed by Islamic banks. It covers not only unification dimension like financial measurement, but also many dimensions covered to reflect the main purpose of Islamic banks. The implementation of good corporate governance is essential because it covers the interests of the stakeholders and facilitates effective monitoring to encourage Islamic banks to utilize resources more efficiently in order to achieve the Maqasid Shariah. This study aims to provide the empirical evidence on the Maqasid performance of Islamic banks in relation to the Maqasid performance evaluation model, to examine the influence of SSB characteristics and board structures to Islamic Banks performance as measured by Maqasid performance evaluation model. By employing the simple additive weighting method, Maqasid index for all the Islamic Banks in Indonesia within 2012 to 2016 ranged from above 11% to 28%. The Maqasid Syariah performance index where results reached above 20% are obtained by Islamic Banks such as Bank Muamalat Indonesia, Bank Panin Syariah, and Bank BRI Syariah. The consistent achievement above 23% is achieved by BMI. Other Islamic Banks such as Bank Victoria Syariah, Bank Jabar Banten Syariah, Bank BNI Syariah, Bank Mega Syariah, BCA Syariah, and Maybank Syariah Indonesia shows a fluctuating value of the Maqasid performance index every year. The impact of SSB characteristics and board structures are tested using random-effects generalized least square. The findings indicate that SSB characteristics (Shariah Supervisory Board size, Shariah Supervisory Board cross membership, Shariah Supervisory Board Education, and Shariah Supervisory Board reputation) and board structures (Board size and Board independence) have an essential role in improving the performance of Islamic Banks. The findings denote Shariah Supervisory Board with smaller size, higher portion of Shariah Supervisory Board cross membership; lesser Shariah Supervisory Board holds doctorate degree, lesser reputable scholar, more members on board of directors, and less independence non-executive directors will enhance the performance of Islamic Banks.

Keywords: Maqasid Shariah, corporate governance, Islamic banks, Shariah supervisory board

Procedia PDF Downloads 240
4006 A Deep Learning Based Integrated Model For Spatial Flood Prediction

Authors: Vinayaka Gude Divya Sampath

Abstract:

The research introduces an integrated prediction model to assess the susceptibility of roads in a future flooding event. The model consists of deep learning algorithm for forecasting gauge height data and Flood Inundation Mapper (FIM) for spatial flooding. An optimal architecture for Long short-term memory network (LSTM) was identified for the gauge located on Tangipahoa River at Robert, LA. Dropout was applied to the model to evaluate the uncertainty associated with the predictions. The estimates are then used along with FIM to identify the spatial flooding. Further geoprocessing in ArcGIS provides the susceptibility values for different roads. The model was validated based on the devastating flood of August 2016. The paper discusses the challenges for generalization the methodology for other locations and also for various types of flooding. The developed model can be used by the transportation department and other emergency response organizations for effective disaster management.

Keywords: deep learning, disaster management, flood prediction, urban flooding

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4005 Imagology: The Study of Multicultural Imagery Reflected in the Heart of Elif Shafak’s 'The Bastard of Istanbul'

Authors: Mohammad Reza Haji Babai, Sepideh Ahmadkhan Beigi

Abstract:

Internationalization and modernization of the globe have played their roles in the process of cultural interaction between globalized societies and, consequently, found their way to the world of literature under the name of ‘imagology’. Imagology has made it possible for the reader to understand the author’s thoughts and judgments of others. The present research focuses on the intercultural images portrayed in the novel of a popular Turkish-French writer, Elif Shafak, about the lifestyle, traditions, habits, and social norms of Turkish, Americans, and Armenians. The novel seeks to articulate a more intricate multicultural memory of Turkishness by grieving over the Armenian massacre. This study finds that, as a mixture of multiple lifestyles and discourses, The Bastard of Istanbul reflects not only images of oriental culture but also occidental cultures. This means that the author has attempted to maintain selfhood through historical and cultural recollection, which resulted in constructing the self and another identity.

Keywords: imagology, Elif Shafak, The Bastard of Istanbul, self-image, other-image

Procedia PDF Downloads 141