Search results for: quality metrics framework

Authors: Smita Krishnan, Krittika Chandran, Chandra Mohan Sinnathambi

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Produced water and its treatment and management are growing challenges in all producing regions. This water is generally considered as a nonrevenue product, but it can have significant value in enhanced oil recovery techniques if it meets the required quality standards. There is also an interest in the beneficial uses of produced water for agricultural and industrial applications. Advanced Oxidation Process is a chemical technology that has been growing recently in the wastewater treatment industry, and it is highly recommended for non-easily removal of organic compounds. The efficiency of AOPs is compound specific, therefore, the optimization of each process should be done based on different aspects.

Keywords: advanced oxidation process, photochemical processes, degradation, organic contaminants

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Authors: Juha Kettunen

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This study presents a project that tests and adjusts active European learning and teaching methods in Indonesian universities to increase their external impact on enterprises and other organizations; it also assesses the implementation of the Erasmus+ projects funded by the European Union. The project is based on the approach of innovation pedagogy that responds to regional development needs and integrates applied research and development projects into education to create capabilities for students to participate in development work after graduation. The assessment of the Erasmus+ project resulted in many improvements that can be made to achieve higher quality and innovativeness. The results of this study are useful for those who want to improve the applied research and development projects of higher education institutions.

Keywords: higher education, innovations, social network, project management

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Authors: Joachim Monkelbaan, Marcia Hale

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Now that global frameworks for sustainability governance (e.g. the Sustainable Development Goals, Paris Climate Agreement and Sendai Framework for Disaster Risk Reduction) are in place, the question is how these aspirations that represent major transitions can be put into practice. Water ‘infrasystems’ can play an especially significant role in strengthening regional sustainability. Infrasystems include both hard and soft infrastructure, such as pipes and technology for delivering water, as well as the institutions and governance models that direct its delivery. As such, an integrated infrasystems view is crucial for Integrative Water Management (IWM). Due to frequently contested ownership of and responsibility for water resources, these infrasystems can also play an important role in facilitating conflict and catalysing community empowerment, especially through participatory approaches to governance. In this paper, we analyze the water infrasystem of the Los Angeles region through the lens of global frameworks for sustainability governance. By complementing a solid overview of governance theories with empirical data from interviews with water actors in the LA metropolitan region (including NGOs, water managers, scientists and elected officials), this paper elucidates ways for this infrasystem to be better aligned with global sustainability frameworks. In addition, it opens up the opportunity to scrutinize the appropriateness of global frameworks when it comes to fostering sustainability action at the local level.

Keywords: governance, transitions, global frameworks, infrasystems

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Authors: Ana L. Gonzalez-Celis, Edgardo Ruiz-Carrillo, Karina Reyes-Jarquin, Margarita Chavez-Becerra

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Since recent decades, the aging has been viewed from a more positive perspective, where is not only about losses and damage, but also about being on a stage where you can enjoy life and live with well-being and quality of life. The challenge to feel better is to find those resources that seniors have. For that reason, psychological well-being has shown interest in the study of the affect and life satisfaction (hedonic well-being), while from a more recent tradition, focus on the development of capabilities and the personal growth, considering both as the main indicators of the quality of life. A resource that can be used in the later age is generativity, which refers to the ability of older people to develop and grow through activities that contribute with the improvement of the context in which they live and participate. In this way the generative interest is understood as a favourable attitude that contribute to the common benefit while strengthening and enriching the social institutions, to ensure continuity between generations and social development. On the other hand, generative behavior, differentiating from generative interest, is the expression of that attitude reflected in activities that make a social contribution and a benefit for generations to come. Hence the purpose of the research was to test if there is an association between the generative behaviour type and the psychological well-being with their dimensions. For this reason 188 Mexican adults from 60 to 94 years old (M = 69.78), 67% women, 33% men, completed two instruments: The Ryff’s Well-Being Scales to measure psychological well-being with 39 items with two dimensions (Hedonic and Eudaimonic well-being), and the Loyola’s Generative Behaviors Scale, grouped in five categories: Knowledge transmitted to the next generation, things to be remember, creativity, be productive, contribution to the community, and responsibility of other people. In addition, the socio-demographic data sheet was tested, and self-reported health status. The results indicated that the psychological well-being and its dimensions were significantly associated with the presence of generative behavior, where the level of well-being was higher when the frequency of some generative behaviour excelled; finding that the behavior with greater psychological well-being (M = 81.04, SD = 8.18) was "things to be remembered"; while with greater hedonic well-being (M = 73.39, SD = 12.19) was the behavior "responsibility of other people"; and with greater Eudaimonic well-being (M = 84.61, SD = 6.63), was the behavior "things to be remembered”. The most important findings highlight the importance of generative behaviors in adulthood, finding empirical evidence that the generativity in the last stage of life is associated with well-being. However, by finding differences in the types of generative behaviors at the level of well-being, is proposed the idea that generativity is not situated as an isolated construct, but needs other contextualized and related constructs that can simultaneously operate at different levels, taking into account the relationship between the environment and the individual, encompassing both the social and psychological dimension.

Keywords: eudaimonic well-being, generativity, hedonic well-being, Mexican elders, psychological well-being

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Authors: Marco F. Benaglia, Mei H. Chen, Kune M. Tsai, Chia H. Hung

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As societal and family structures, consumer dietary habits, and awareness about food safety and quality continue to evolve in most developed countries, the demand for refrigerated and frozen foods has been growing, and the issues related to their preservation have gained increasing attention. A well-established cold chain logistics system is essential to avoid any temperature abuse; therefore, assessing potential disruptions in the operational processes of cold chain logistics centers becomes pivotal. This study preliminarily employs HACCP to find disruption factors in cold chain logistics centers that may cause temperature abuse. Then, concept mapping is applied: selected experts engage in brainstorming sessions to identify any further factors. The panel consists of ten experts, including four from logistics and home delivery, two from retail distribution, one from the food industry, two from low-temperature logistics centers, and one from the freight industry. Disruptions include equipment-related aspects, human factors, management aspects, and process-related considerations. The areas of observation encompass freezer rooms, refrigerated storage areas, loading docks, sorting areas, and vehicle parking zones. The experts also categorize the disruption factors based on perceived similarities and build a similarity matrix. Each factor is evaluated for its impact, frequency, and investment importance. Next, multiple scale analysis, cluster analysis, and other methods are used to analyze these factors. Simultaneously, key disruption factors are identified based on their impact and frequency, and, subsequently, the factors that companies prioritize and are willing to invest in are determined by assessing investors’ risk aversion behavior. Finally, Cumulative Prospect Theory (CPT) is applied to verify the risk patterns. 66 disruption factors are found and categorized into six clusters: (1) "Inappropriate Use and Maintenance of Hardware and Software Facilities", (2) "Inadequate Management and Operational Negligence", (3) "Product Characteristics Affecting Quality and Inappropriate Packaging", (4) "Poor Control of Operation Timing and Missing Distribution Processing", (5) "Inadequate Planning for Peak Periods and Poor Process Planning", and (6) "Insufficient Cold Chain Awareness and Inadequate Training of Personnel". This study also identifies five critical factors in the operational processes of cold chain logistics centers: "Lack of Personnel’s Awareness Regarding Cold Chain Quality", "Personnel Not Following Standard Operating Procedures", "Personnel’s Operational Negligence", "Management’s Inadequacy", and "Lack of Personnel’s Knowledge About Cold Chain". The findings show that cold chain operators prioritize prevention and improvement efforts in the "Inappropriate Use and Maintenance of Hardware and Software Facilities" cluster, particularly focusing on the factors of "Temperature Setting Errors" and "Management’s Inadequacy". However, through the application of CPT theory, this study reveals that companies are not usually willing to invest in the improvement of factors related to the "Inappropriate Use and Maintenance of Hardware and Software Facilities" cluster due to its low occurrence likelihood, but they acknowledge the severity of the consequences if it does occur. Hence, the main implication is that the key disruption factors in cold chain logistics centers’ processes are associated with personnel issues; therefore, comprehensive training, periodic audits, and the establishment of reasonable incentives and penalties for both new employees and managers may significantly reduce disruption issues.

Keywords: concept mapping, cold chain, HACCP, cumulative prospect theory

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Authors: Jiang-Bei Qin, Rui-Xia Miao, Wei Ren

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In this study, high crystalline gallium oxide microstructures (wires, belts, and sheets) were synthesized by catalyst-free thermal oxidation. Structural studies such as X-ray diffraction, Raman and transmission electron microscope (TEM) investigations on the microstructures showed monoclinic phase of gallium oxide and single crystalline structure. The scanning electron microscopy (SEM) observations revealed that a huge super microsheet even grows up to 450 µm in length and 206 µm in width. Gallium oxide microstructures exhibit high crystallinity along (002) and (401), respectively. The PL spectrum of these microstructures excites a blue light band centered at 441 and 489nm. The growth mechanism of gallium oxide microstructures is discussed. These gallium oxide microstructures have great potential in functional devices.

Keywords: catalyst-free, gallium oxide, microstructures, thermal oxide

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Authors: Praveen Priyadarshi

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What is the nature of the 'political subjects' in the new urban spaces of the Indian cities? How do they become a 'public'? The paper explores these questions by studying the National Capital Region's gated communities in India. Even as the 'gated-ness' of these neighborhoods constantly underlines the definitive spatial boundary of the 'public' that it is constituted within the walls of a particular gated community, the making of this 'public' occurs as much in the digital spaces—in the digital space of online messaging apps and platforms—populated by unique digital identities. It is through constant exchanges of the digital identities that the 'public' is created. However, the institutional framework and the formal rules governing the making of the public are still analogue because they presume and privilege traditional modes of participation for people to constitute a 'public'. The institutions are designed as rules and norms governing people's behavior when they participate in traditional, physical mode, whereas rules and norms designed in the algorithms regulate people's social and political behavior in the digital domain. In exploring this disjuncture between the analogue institutions and the digital public, the paper analytically evaluates the nature of everyday politics in gates neighborhoods in India.

Keywords: gated communities, everyday politics, new urban spaces, digital publics

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Authors: Robnier Reyes, Andrew J. P. Marques, Joel Ramjist, Chris R. Pasarikovski, Victor X. D. Yang

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Over the past three decades, surgical robotic systems have demonstrated their ability to improve surgical outcomes. The LBR Med is a collaborative robotic arm that is meant to work with a surgeon to streamline surgical workflow. It has 7 degrees of freedom and thus can be easily oriented. Position and torque sensors at each joint allow it to maintain a position accuracy of 150 µm with real-time force and torque feedback, making it ideal for complex surgical procedures. Spinal fusion procedures involve the placement of as many as 20 pedicle screws, requiring a great deal of accuracy due to proximity to the spinal canal and surrounding vessels. Any deviation from intended path can lead to major surgical complications. Assistive surgical robotic systems are meant to serve as collaborative devices easing the workload of the surgeon, thereby improving pedicle screw placement by mitigating fatigue related inaccuracies. Moreover, robotic spinal systems have shown marked improvements over conventional freehanded techniques in both screw placement accuracy and fusion quality and have greatly reduced the need for screw revision, intraoperatively and post-operatively. However, current assistive spinal fusion robots, such as the ROSA Spine, are limited in functionality to positioning surgical instruments. While they offer a small degree of improvement in pedicle screw placement accuracy, they do not alleviate surgeon fatigue, nor do they provide real-time force and torque feedback during screw insertion. We propose a semi-autonomous surgical robot workflow for spinal fusion where the surgeon guides the robot to its initial position and orientation, and the robot drives the pedicle screw accurately into the vertebra. Here, we demonstrate feasibility by inserting pedicle screws into ex-vivo bovine rib bone. The robot monitors position, force and torque with respect to predefined values selected by the surgeon to ensure the highest possible spinal fusion quality. The workflow alleviates the strain on the surgeon by having the robot perform the screw placement while the ability to monitor the process in real-time keeps the surgeon in the system loop. The approach we have taken in terms of level autonomy for the robot reflects its ability to safely collaborate with the surgeon in the operating room without external navigation systems.

Keywords: ex vivo bovine bone, pedicle screw, surgical robot, surgical workflow

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Authors: A. Nazilah

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Floods are classified among sudden onset phenomenon and the highest natural disasters happen in Malaysia. Floods have a negative impact on mental health. Measuring the psychopathology symptoms among flood victims is an important step for intervention and treatment. However, there is a gap of a valid, reliable and an efficient instrument to measure flood victims' mental health, especially in Malaysia. This study aims to replicate the earlier studies of developing e-Psychological Instrument for Flood Victims (e-PIFV). The e-PIFV is a digital self-report inventory that has 84 items with 4 dimension scales namely stress, anxiety, depression, and trauma. Two replicated studies have been done to validate the instrument using expert judgment method. Results showed that content coefficient validity for each sub-scale of the instrument ranging from moderate to very strong validity. In study I, coefficient values of stress was 0.7, anxiety was 0.9, depression was 1.0, trauma was 0.6 and overall was 0.8. In study II, the coefficient values for two subscales and overall scale were increased. The coefficient value of stress was 0.8, anxiety was 0.9, depression was 1.0, trauma was 0.8 and overall was 0.9. This study supports the theoretical framework and provides practical implication in the field of clinical psychology and flood management.

Keywords: developing e-psychological instrument, content validity, instrument, mental health management, flood victims, psychopathology, validity

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Authors: Julinda Keçi

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In many countries, governments have been promoting the involvement of private sector entities to enter into long-term agreements for the development and delivery of large infrastructure projects, with a focus on overcoming the limitations upon public fund of the traditional approach. The involvement of private sector through public-private partnerships (PPP) brings in new capital investments, value for money and additional risks to handle. Worldwide research studies have shown that an objective, systematic, reliable and user-oriented risk assessment process and an optimal allocation mechanism among different stakeholders is crucial to the successful completion. In this framework this paper, which is the first stage of a research study, aims to identify the main risks for the delivery of PPP projects. A review of cross-countries research projects and case studies was performed to map the key risks affecting PPP infrastructure delivery. The matrix of mapping offers a summary of the frequency of factors, clustered in eleven categories: Construction, Design, Economic, Legal, Market, Natural, Operation, Political, Project finance, Project selection and Relationship. Results will highlight the most critical risk factors, and will hopefully assist the project managers in directing the managerial attention in the further stages of risk allocation.

Keywords: construction, infrastructure, public private partnerships, risks

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Authors: Osa D Egonwa

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In the 21^st century, the disciplinary boundaries of past centuries that we often create through mainstream art historical classification, techniques and sources may have been eroded by visual culture, which seems to provide a more inclusive umbrella for the new ways artists go about the creative process and its resultant commodities. Over the past four decades, artists in Africa have resorted to new materials, techniques and themes which have affected our ways of research on these artists and their art. Frontline artists such as El Anatsui, Yinka Shonibare, Erasmus Onyishi are demonstrating that any material is just suitable for artistic expression. Most of times, these materials come with their own techniques/effects and visual syntax: a combination of materials compounds techniques, formal aesthetic indexes, halo effects, and iconography. This tends to challenge the categories and we lean on to view, think and talk about them. This renders our main stream art historical research methods inadequate, thus suggesting new discursive concepts, terms and theories. This paper proposed the Africanist eclectic methods derived from the dual framework of Masquerade Theory and What Comes Behind Six is More Than Seven. This paper shares thoughts/research on art historical methods, terminological re-alignments on classification/source data, presentational format and interpretation arising from the emergent trends in our subject. The outcome provides useful tools to mediate new thoughts and experiences in recent African art and visual culture.

Keywords: art historical methods, classifications, concepts, re-alignment

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Authors: Panisa Panyalert

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This research presents the tourism industry at Nakhon Sawan province in an aspect of developing points of attractions and destinations. The author attempts to empirically analyze the tourist destination, Nakhon Sawan, by using components of the tourism inventory include: attraction, accessibility, accommodation and amenity. An understanding of existing tourism product is very important in order to find out strength and weakness by comparing with the nearby well-known tourist destination, Phitsanulok province. Moreover, the hypothetical evolution of a tourist area will be utilized as a framework for indicating stages of the destination in relation to number of tourists. The study uses secondary data of number of tourist arrivals in Nakhon Sawan from 2008 to 2013 receiving from National Statistical Office and Nakhon Sawan Provincial Administration Organization (NPAO) in order to find the stage of destination development, and an in-depth interview with several open-ended questions would be preferred in order to get deep details of necessary data by video recording with ten respondents. The findings are concentrated on potential places and sites, existing tourism product, strength and weakness, and positioning to assist the province to be the destination of tourists’ mind.

Keywords: destination development, destination management, tourism inventory, tourism product

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Authors: Xiaohua Zou, Yongxin Su

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The reasonable operation of heating, ventilation, and air conditioning (HVAC) is of great significance in improving the security, stability, and economy of power system operation. However, the uncertainty of the operating environment, thermal comfort varies by users and rapid decision-making pose challenges for HVAC demand response optimization. In this regard, this paper proposes a reinforcement learning-based method for HVAC demand response optimization considering few-shot personalized thermal comfort (PTC). First, an HVAC DR optimization framework based on few-shot PTC model and DRL is designed, in which the output of few-shot PTC model is regarded as the input of DRL. Then, a few-shot PTC model that distinguishes between awake and asleep states is established, which has excellent engineering usability. Next, based on soft actor criticism, an HVAC DR optimization algorithm considering the user’s PTC is designed to deal with uncertainty and make decisions rapidly. Experiment results show that the proposed method can efficiently obtain use’s PTC temperature, reduce energy cost while ensuring user’s PTC, and achieve rapid decision-making under uncertainty.

Keywords: HVAC, few-shot personalized thermal comfort, deep reinforcement learning, demand response

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Authors: O. A. Lawal, O. A Ojesanmi

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The demand for wireless cellular services continues to increase while the radio resources remain limited. Thus, network operators have to continuously manage the scarce radio resources in order to have an improved quality of service for mobile users. This paper proposes how to handle the problem of congestion in the mobile network by prioritizing handoff call, using the guard channel allocation scheme. The research uses specific threshold value for the time of allocation of the channel in the algorithm. The scheme would be simulated by generating various data for different traffics in the network as it would be in the real life. The result would be used to determine the probability of handoff call dropping and the probability of the new call blocking as a way of measuring the network performance.

Keywords: call block, channel, handoff, mobile cellular network

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Authors: Areej R. Banjar, Abraham G. Campbell

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The use of Mixed Reality (MR) in teaching and training is growing popular and can improve students’ ability to perform technical procedures. This short paper outlines the creation of an interactive educational MR 3D application that aims to improve the quality of instruction for dentistry students. This application is called MRImplantology and aims to teach the fundamentals and preoperative planning of dental implant placement. MRImplantology uses cone-beam computed tomography (CBCT) images as the source for 3D dental models that dentistry students will be able to freely manipulate within a 3D MR world to aid their learning process.

Keywords: augmented reality, education, dentistry, cone-beam computed tomography CBCT, head mounted display HMD, mixed reality

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Authors: Asmae Chraibi, Rachid Lghoul, Nabil Rhiati

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In the era of Industry 4.0, enterprises are increasingly employing digital technologies in order to improve their product development processes. This research focuses on the strategic deployment of Product Lifecycle Management (PLM) solutions during production as a key tracker of traceability and digital transformation activities. The study explores the integration of PLM within a larger organizational framework, examining its impact on product lifecycle efficiency, corporation, and innovation. Through a comprehensive analysis of a real case study from the automotive industry, this project evaluates the critical success factors and challenges associated with implementing PLM solutions for digital transformation. Moreover, it explores the synergic relationship between PLM and emerging technologies such as 3D experience and SOLIDWORKS, elucidating their combined potential in optimizing production workflows and enabling data-driven decision-making. The study's findings provide global approaches for firms looking to embark on a digital transformation journey by implementing PLM technologies. This research contributes to a better understanding of how PLM can be effectively used to foster innovation and competitiveness in the changing landscape of modern industry by shining light on best practices, critical considerations, and potential obstacles.

Keywords: product lifecyle management (PLM), industry 4.0, traceability, digital transformation, solution, innovation, 3D experience, SOLIDWORKS

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Authors: Md. Shafiullah, M. Shafiul Alam, Bandar Suliman Alsharif

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Electrical quantities such as frequency, voltage, current are being fluctuated due to abnormalities in power system. Most of the abnormalities cause fluctuation in system frequency and sometimes extreme abnormalities lead to system blackout. To protect the system from complete blackout planned and proper islanding plays a very important role even in case of extreme abnormalities. Islanding operation not only helps stabilizing a faulted system but also supports power supplies to critical and important loads, in extreme emergency. But the islanding systems are weaker than integrated system so the stability of islands is the prime concern when an integrated system is disintegrated. In this paper, different impacts on a load rich island have been studied and a frequency based auto-load shedding scheme has been developed for sudden load addition, generation outage and combined effect of both to the island. The developed scheme has been applied to Khulna-Barisal Island to validate the effectiveness of the developed technique. Various types of abnormalities to the test system have been simulated and for the simulation purpose CYME PSAF (Power System Analysis Framework) has been used.

Keywords: auto load shedding, FS&FD relay, impact study, island, PSAF, ROCOF

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Authors: Flavia Smarrazzo

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Initial-boundary value problems for nonlinear parabolic equations having a Radon measure as initial data have been widely investigated, looking for solutions which for positive times take values in some function space. On the other hand, if the diffusivity degenerates too fast at infinity, it is well known that function-valued solutions may not exist, singularities may persist, and it looks very natural to consider solutions which, roughly speaking, for positive times describe an orbit in the space of the finite Radon measures. In this general framework, our purpose is to introduce a concept of measure-valued solution which is consistent with respect to regularizing and smoothing approximations, in order to develop an existence theory which does not depend neither on the level of degeneracy of diffusivity at infinity nor on the choice of the initial measures. In more detail, we prove existence of suitably defined measure-valued solutions to the homogeneous Dirichlet initial-boundary value problem for a class of nonlinear parabolic equations without strong coerciveness. Moreover, we also discuss some qualitative properties of the constructed solutions concerning the evolution of their singular part, including conditions (depending both on the initial data and on the strength of degeneracy) under which the constructed solutions are in fact unction-valued or not.

Keywords: degenerate parabolic equations, measure-valued solutions, Radon measures, young measures

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Authors: Massimo Imparato

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The study aims to identify the background of the contemporary trends in the design of commercial outdoors, and the reasons for the radical change in the traditional relationship between architecture and interior design, where the latter is taking over the construction of the visual narrative framing the users’ experience, which was ruled in the past by the architectural discourse. The design of commercial interiors, in fact, influences the way in which their outdoor spaces are organized and used more than ever before, and reflects the multi-faceted changes in the consumers’ behaviors and their interaction with the built environment. The study starts with the analysis of the evolution of sheltered outdoor spaces to achieve a broader understanding of the shift of meaning of subjects such as private and public domains, and to consider the varied ways of interaction/integration between the building and its exterior space. The study identifies the major social, physical and cultural aspects influencing the design of contemporary commercial outdoor spaces, suggests a new framework for their understanding and draws the methodological guidelines for the development of a structured approach to the design of commercial outdoors. The purpose of the paper is to stress the influence of the design of interiors into the public realm, to indicate new directions in this field of research, and to provide new methodological tools for interior design professionals.

Keywords: interior design, landscape design, visual narrative, outdoor design

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Authors: Tayo P. Ogundunmade, Adedayo A. Adepoju

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Terrorist attacks in liberal democracies bring about a few pessimistic results, for example, sabotaged public support in the governments they target, disturbing the peace of a protected environment underwritten by the state, and a limitation of individuals from adding to the advancement of the country, among others. Hence, seeking for techniques to understand the different factors involved in terrorism and how to deal with those factors in order to completely stop or reduce terrorist activities is the topmost priority of the government in every country. This research aim is to develop an efficient deep learning-based predictive model for the prediction of future terrorist activities in Nigeria, addressing low-quality prediction accuracy problems associated with the existing solution methods. The proposed predictive AI-based model as a counterterrorism tool will be useful by governments and law enforcement agencies to protect the lives of individuals in society and to improve the quality of life in general. A Heterogeneous Bayesian Neural Network (HETBNN) model was derived with Gaussian error normal distribution. Three primary transfer functions (HOTTFs), as well as two derived transfer functions (HETTFs) arising from the convolution of the HOTTFs, are namely; Symmetric Saturated Linear transfer function (SATLINS ), Hyperbolic Tangent transfer function (TANH), Hyperbolic Tangent sigmoid transfer function (TANSIG), Symmetric Saturated Linear and Hyperbolic Tangent transfer function (SATLINS-TANH) and Symmetric Saturated Linear and Hyperbolic Tangent Sigmoid transfer function (SATLINS-TANSIG). Data on the Terrorist activities in Nigeria gathered through questionnaires for the purpose of this study were used. Mean Square Error (MSE), Mean Absolute Error (MAE) and Test Error are the forecast prediction criteria. The results showed that the HETFs performed better in terms of prediction and factors associated with terrorist activities in Nigeria were determined. The proposed predictive deep learning-based model will be useful to governments and law enforcement agencies as an effective counterterrorism mechanism to understand the parameters of terrorism and to design strategies to deal with terrorism before an incident actually happens and potentially causes the loss of precious lives. The proposed predictive AI-based model will reduce the chances of terrorist activities and is particularly helpful for security agencies to predict future terrorist activities.

Keywords: activation functions, Bayesian neural network, mean square error, test error, terrorism

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Authors: S. Sathiyamoorthi, P. Srinivasan, K. Suganya Devi

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Arylidene derivatives are the subclass of chalcone derivatives. Chalcone derivatives are studied widely for the past decade because of its nonlinearity. To seek new organic group of crystals which suit for fabrication of optical devices, three-member organic arylidene crystals were synthesized by using Claisen–Schmidt condensation reaction. Good quality crystals were grown by slow evaporation method. Functional groups were identified by FT-IR and FT-Raman spectrum. Optical transparency and optical band gap were determined by UV-Vis-IR studies. Thermal stability and melting point were calculated using TGA and DSC. Variation of dielectric loss and dielectric constant with frequency were calculated by dielectric measurement.

Keywords: DSC and TGA studies, nonlinear optic studies, Fourier Transform Infrared Spectroscopy, UV-vis-NIR spectra

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Authors: Yongsheng Guo, Mengyu Lu

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This study investigates how Chinese SMEs manage financial risks in financing from customers from the perspectives of ethics and national culture. A grounded theory approach is adopted to identify the causal conditions, actions/interactions, and consequences. 32 interviews were conducted, and systematic coding methods were used to identify themes and categories. This study found that Chinese ethical principles, including integrity, friendship, and reciprocity, and cultural traits, including collectivism, acquaintance society, and long-term orientation, provide conditions for financing from customers. The SMEs establish trust-based relationships with customers through personal communications and social networks and reduce financial risk through diversification, frequent operations, and enterprise reputations. Both customers and SMEs can get benefits like financial resources and customer experiences. This study creates a theoretical framework that connects the causal conditions, processes, and outcomes, providing a deeper understanding of financing from customers. A resource and process capability theory of SMEs and a customer capital and customer value model are proposed to connect accounting and finance concepts. Suggestions are proposed for the authorities as more guidance and regulations are needed for this informal finance.

Keywords: CRM, culture, ethics, SME, risk management

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Authors: Yaxin Tang, Mingao Hou, Qian He, Guangfu Luo

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Bimetallic nanoparticles serve as a promising class of catalysts with tunable properties suitable for diverse catalytic reactions, yet a comprehensive understanding of their actual structures under operating conditions and the optimal design principles remains largely elusive. In this study, we unveil a prevalent surface segregation phenomenon in nearly 100 platinum-group-element-based bimetallic nanoparticles through first principles-based molecular dynamics simulations. Our findings highlight that two components in a nanoparticle with relatively lower surface energy tend to segregate to the surface. Motivated by this discovery, we propose a deliberate exploitation of surface segregation in designing bimetallic nanoparticle catalysts, aiming for heightened stability and reduced consumption of precious metals. To validate this strategy, we further investigate 36 platinum-based bimetallic nanoparticles for propane dehydrogenation catalysis. Through a systematic examination of catalytic sites on nanoparticles, we identify several systems as top candidates with Pt-enriched surfaces, remarkable thermal stability, and superior catalytic activity for propane dehydrogenation. The insights gained garnered from this study are anticipated to provide a valuable framework for the optimal design of other bimetallic nanoparticles.

Keywords: bimetallic nanoparticles, platinum-group element, catalysis, surface segregation, first-principles calculations

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Authors: Nilki Upathissa, Torin Wirasinghe

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This solution addresses the challenges faced by traditional bookstores and the limitations of digital media, striking a balance between the tactile experience of printed books and the convenience of modern technology. The book exchange system offers a sustainable alternative, empowering users to access a diverse range of books while promoting community engagement. The user-friendly interfaces incorporated into the book exchange system ensure a seamless and enjoyable experience for users. Intuitive features for book management, search, and messaging facilitate effortless exchanges and interactions between users. By streamlining the process, the system encourages readers to explore new books aligned with their interests, enhancing the overall reading experience. Central to the system's success is the hybrid recommendation engine, which leverages advanced technologies such as Long Short-Term Memory (LSTM) models. By analyzing user input, the engine accurately predicts genre preferences, enabling personalized book recommendations. The hybrid approach integrates multiple technologies, including user interfaces, machine learning models, and recommendation algorithms, to ensure the accuracy and diversity of the recommendations. The evaluation of the book exchange system with the hybrid recommendation engine demonstrated exceptional performance across key metrics. The high accuracy score of 0.97 highlights the system's ability to provide relevant recommendations, enhancing users' chances of discovering books that resonate with their interests. The commendable precision, recall, and F1score scores further validate the system's efficacy in offering appropriate book suggestions. Additionally, the curve classifications substantiate the system's effectiveness in distinguishing positive and negative recommendations. This metric provides confidence in the system's ability to navigate the vast landscape of book choices and deliver recommendations that align with users' preferences. Furthermore, the implementation of this book exchange system with a hybrid recommendation engine has the potential to revolutionize the way readers interact with printed books. By facilitating book exchanges and providing personalized recommendations, the system encourages a sense of community and exploration within the reading community. Moreover, the emphasis on sustainability aligns with the growing global consciousness towards eco-friendly practices. With its robust technical approach and promising evaluation results, this solution paves the way for a more inclusive, accessible, and enjoyable reading experience for book lovers worldwide. In conclusion, the developed book exchange system with a hybrid recommendation engine represents a progressive solution to the challenges faced by traditional bookstores and the limitations of digital media. By promoting sustainability, widening access to printed books, and fostering engagement with reading, this system addresses the evolving needs of book enthusiasts. The integration of user-friendly interfaces, advanced machine learning models, and recommendation algorithms ensure accurate and diverse book recommendations, enriching the reading experience for users.

Keywords: recommendation systems, hybrid recommendation systems, machine learning, data science, long short-term memory, recurrent neural network

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Authors: Ho-Won Jung, Donghun Lee, Hyung-Jin Kim

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Predictive analytics (data analysis) uses a subset of measurements (the features, predictor, or independent variable) to predict another measurement (the outcome, target, or dependent variable) on a single person or unit. It applies empirical methods in statistics, operations research, and machine learning to predict the future, or otherwise unknown events or outcome on a single or person or unit, based on patterns in data. Most analyses of metabolic syndrome are not predictive analytics but statistical explanatory studies that build a proposed model (theory building) and then validate metabolic syndrome predictors hypothesized (theory testing). A proposed theoretical model forms with causal hypotheses that specify how and why certain empirical phenomena occur. Predictive analytics and explanatory modeling have their own territories in analysis. However, predictive analytics can perform vital roles in explanatory studies, i.e., scientific activities such as theory building, theory testing, and relevance assessment. In the context, this study is to demonstrate how to use our predictive analytics to support theory building (i.e., hypothesis generation). For the purpose, this study utilized a big data predictive analytics platform TM based on a co-occurrence graph. The co-occurrence graph is depicted with nodes (e.g., items in a basket) and arcs (direct connections between two nodes), where items in a basket are fully connected. A cluster is a collection of fully connected items, where the specific group of items has co-occurred in several rows in a data set. Clusters can be ranked using importance metrics, such as node size (number of items), frequency, surprise (observed frequency vs. expected), among others. The size of a graph can be represented by the numbers of nodes and arcs. Since the size of a co-occurrence graph does not depend directly on the number of observations (transactions), huge amounts of transactions can be represented and processed efficiently. For a demonstration, a total of 13,254 metabolic syndrome training data is plugged into the analytics platform to generate rules (potential hypotheses). Each observation includes 31 predictors, for example, associated with sociodemographic, habits, and activities. Some are intentionally included to get predictive analytics insights on variable selection such as cancer examination, house type, and vaccination. The platform automatically generates plausible hypotheses (rules) without statistical modeling. Then the rules are validated with an external testing dataset including 4,090 observations. Results as a kind of inductive reasoning show potential hypotheses extracted as a set of association rules. Most statistical models generate just one estimated equation. On the other hand, a set of rules (many estimated equations from a statistical perspective) in this study may imply heterogeneity in a population (i.e., different subpopulations with unique features are aggregated). Next step of theory development, i.e., theory testing, statistically tests whether a proposed theoretical model is a plausible explanation of a phenomenon interested in. If hypotheses generated are tested statistically with several thousand observations, most of the variables will become significant as the p-values approach zero. Thus, theory validation needs statistical methods utilizing a part of observations such as bootstrap resampling with an appropriate sample size.

Keywords: explanatory modeling, metabolic syndrome, predictive analytics, theory building

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Authors: Madhat Abu Al-Naeem, Ismail Yusoff, Ng Tham Fatt, Yatimah Alias

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Groundwater in Gaza strip is increasingly being exposed to anthropic and natural factors that seriously impacted the groundwater quality. Physiochemical data of groundwater can offer important information on changes in groundwater quality that can be useful in improving water management tactics. An integrative hydrochemical and statistical techniques (Hierarchical cluster analysis (HCA) and factor analysis (FA)) have been applied on the existence ten physiochemical data of 84 samples collected in (2000/2001) using STATA, AquaChem, and Surfer softwares to: 1) Provide valuable insight into the salinization sources and the hydrochemical processes controlling the chemistry of groundwater. 2) Differentiate the influence of natural processes and man-made activities. The recorded large diversity in water facies with dominance Na-Cl type that reveals a highly saline aquifer impacted by multiple complex hydrochemical processes. Based on WHO standards, only (15.5%) of the wells were suitable for drinking. HCA yielded three clusters. Cluster 1 is the highest in salinity, mainly due to the impact of Eocene saline water invasion mixed with human inputs. Cluster 2 is the lowest in salinity also due to Eocene saline water invasion but mixed with recent rainfall recharge and limited carbonate dissolution and nitrate pollution. Cluster 3 is similar in salinity to Cluster 2, but with a high diversity of facies due to the impact of many sources of salinity as sea water invasion, carbonate dissolution and human inputs. Factor analysis yielded two factors accounting for 88% of the total variance. Factor 1 (59%) is a salinization factor demonstrating the mixing contribution of natural saline water with human inputs. Factor 2 measure the hardness and pollution which explained 29% of the total variance. The negative relationship between the NO3- and pH may reveal a denitrification process in a heavy polluted aquifer recharged by a limited oxygenated rainfall. Multivariate statistical analysis combined with hydrochemical analysis indicate that the main factors controlling groundwater chemistry were Eocene saline invasion, seawater invasion, sewage invasion and rainfall recharge and the main hydrochemical processes were base ion and reverse ion exchange processes with clay minerals (water rock interactions), nitrification, carbonate dissolution and a limited denitrification process.

Keywords: dendrogram and cluster analysis, water facies, Eocene saline invasion and sea water invasion, nitrification and denitrification

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Authors: Maciej Dudek, Robert Kruszewski, Janusz Kudla, Konrad Walczyk

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In this paper, we study how taxation of bequests affects human capital formation in the long term and short term horizon. Our underlying model is an overlapping generation model (OLG) with some degree of altruism on the part of the ancestors' generation towards their descendants. We ask the question in three separate frameworks. First, we study a simple one-sector model where a proxy of human capital is wage income. It the steady-state -for CRRA utility function and human capital produced with non-decreasing returns -the taxation of bequests is neutral to the accumulation of human capital. In the second framework, neutrality applies to the growth rates of human capital, physical capital, and consumption. In this case, taxation increases the level of bequests, leading to a lower value of current consumption. Finally in we consider two periods model instead of infinite horizon model as long as the tax revenue is at least partially rebated back to the public, the fraction of human capital engaged in the process of formation of human capital increases with the tax rate on bequests. In other words, taxation of bequests is partially offset by an increase in human capital formation. Higher human capital allows the future generation to earn higher wages, and today's generation can find it optimal to endow the future generation with more human capital when taxation is imposed on physical capital transferred to the next generation.

Keywords: taxation, bequests, policy, human capital

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Authors: Leila Momenzadeh, Alexander V. Evteev, Elena V. Levchenko, Tanvir Ahmed, Irina Belova, Graeme Murch

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In this work, the phonon thermal conductivity of f.c.c. Al is investigated in detail in the temperature range 100 – 900 K within the framework of equilibrium molecular dynamics simulations making use of the Green-Kubo formalism and one of the most reliable embedded-atom method potentials. It is found that the heat current auto-correlation function of the f.c.c. Al model demonstrates a two-stage temporal decay similar to the previously observed for f.c.c Cu model. After the first stage of decay, the heat current auto-correlation function of the f.c.c. Al model demonstrates a peak in the temperature range 100-800 K. The intensity of the peak decreases as the temperature increases. At 900 K, it transforms to a shoulder. To describe the observed two-stage decay of the heat current auto-correlation function of the f.c.c. Al model, we employ decomposition model recently developed for phonon-mediated thermal transport in a monoatomic lattice. We found that the electronic contribution to the total thermal conductivity of f.c.c. Al dominates over the whole studied temperature range. However, the phonon contribution to the total thermal conductivity of f.c.c. Al increases as temperature decreases. It is about 1.05% at 900 K and about 12.5% at 100 K.

Keywords: aluminum, gGreen-Kubo formalism, molecular dynamics, phonon thermal conductivity

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Authors: Yen Yi Huang

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This paper aims to explore the application of strategies in applied drama to the social work education arena in order to enhance students' creativity, curiosity, and aesthetic sensitivity. Also, applied drama is used as a means to facilitate students' reflection-in-action and improve their understanding of issues on creative aging, gender equality, human rights, bullying, and prejudice. This paper mainly uses the perspective of Homi K. Bhabha's third space to explore the impact of applied drama and social work training on students. First, it focuses on how students create new understandings and insights in the third space of multidisciplinary training studies. Second, it analyzes how the hybridity and negotiation of ideas between applied drama and social work were created. Finally, it discusses the follow-up effects of the training and the factors that promote or hinder the hybridity and generation of the third space. This paper uses students' reflection papers for analysis. It is not focused on a discussion of the effectiveness of the teaching but attempts to bring new insights into the applications of applied drama to the social work education arena. The hybridity and generation of the third space require handling power strategically and looking after the emotional space of the students. Taking part in the training allows students in the third space of multidisciplinary training to reexamine the traditional framework of social work knowledge to create new ideas and possibilities.

Keywords: multidisciplinary, applied drama, social work education, third space

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Authors: Christodoulou Christos, Politis Anastasios

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A large majority of users favoured to wireless LAN connection since it was so simple to use. A wireless network can be the target of numerous attacks. Class hijacking is a well-known attack that is fairly simple to execute and has significant repercussions on users. The statistical flow analysis based on machine learning (ML) techniques is a promising categorization methodology. In a given dataset, which in the context of this paper is a collection of components representing frames belonging to various flows, machine learning (ML) can offer a technique for identifying and characterizing structural patterns. It is possible to classify individual packets using these patterns. It is possible to identify fraudulent conduct, such as class hijacking, and take necessary action as a result. In this study, we explore a way to use machine learning approaches to thwart this attack.

Keywords: wireless lan, quality of service, machine learning, class hijacking, EDCA remapping

Procedia PDF Downloads 49