4653 research outputs found
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On the nature of supply chain reliability: models, solution approaches and agenda for future research
No full textPurpose - This research aims to update the literature about the importance of reliability in supply chain (SC) and to find out the SC determinants. Design/methodology/approach - This research surveys while contributing to the academic grasp of supply chain reliability (SCR) concepts. The study found 45 peer-reviewed publications using a structured survey technique with a four-step filtering process. The filtering process includes data reduction processes such as an evaluation of abstract and conclusion. The filtered study focuses on SCR and its determinants. Findings - One of the major findings is that most of the study has focused on mathematical and conceptual studies. Also, this study provides the answer to a question like how can reliability be better accepted and evolved within the SC after finding the determinants of SCR. Originality/value - The observed methodological gap in understanding and development of SCR was identified and classified into three categories: mathematical, conceptual and empirical studies (case studies and survey's mainly). This research will aid academics in developing and understanding the determinants of SCR.Managemen
A Parallel Connected Hybrid Microstrip-Substrate Integrated Waveguide Bandstop Filter
No full textThis study presents an original parallel connected hybrid microstrip-substrate integrated waveguide (PCHMSIW) bandstop filter. A low-pass filter implemented on a microstrip structure and a SIW-based high-pass filter are connected in parallel to each other. In this way, the aim is to obtain a bandstop filter in the novel hybrid design. The parallel connected hybrid microstrip-substrate integrated waveguide (PCHM-SIW) bandstop filter is synthesised, simulated, and produced. The effects of connecting filters in parallel are discussed. It is seen from the results of CST Studio Suite simulation that PCHM-SIW bandstop filter has a bandwidth of 2.85 GHz and a center frequency of 4.26 GHz. The frequency change rate of the center frequency between simulation and measurement is 7.02 % where it is just 3.76 % for the deviation in bandwidth. The results of the simulation and those of the measurement are close to each other. These results converge to ideal analytical results.Engineering, Electrical & Electroni
Multidimensional intuitive-analytic thinking style and its relation to moral concerns, epistemically suspect beliefs, and ideology
No full textLiterature highlights the distinction between intuitive and analytic thinking as a prominent cognitive style distinction, leading to the proposal of various theories within the framework of the dual process model. However, it remains unclear whether individuals differ in their thinking styles along a single dimension, from intuitive to analytic, or if other dimensions are at play. Moreover, the presence of numerous thinking style measures, employing different terminology but conceptually overlapping, leads to confusion. To address these complexities, Newton et al. suggested the idea that individuals vary across multiple dimensions of intuitive-analytic thinking styles and distinguished thinking styles between 4 distinct types: Actively open-minded thinking, close-minded thinking, preference for effortful thinking, and preference for intuitive thinking. They proposed a new measure for this 4-factor disposition, The 4-Component Thinking Styles Questionnaire (4-CTSQ), to comprehensively capture the psychological outcomes related to thinking styles || however, no independent test exists. In the current pre-registered studies, we test the validity of 4-CTSQ for the first time beyond the original study and examine the association of the proposed measure with various factors, including morality, conspiracy beliefs, paranormal and religious beliefs, vaccine hesitancy, and ideology in an underrepresented culture, Turkiye. We found that the correlated 4-factor model of 4-CTSQ is an appropriate measure to capture individual differences based on cognitive style. The results endorse the notion that cognitive style differences are characterized by distinct structures rather than being confined to two ends of a single continuum.Psychology, Multidisciplinar
A Comprehensive Review of Feature Selection and Feature Selection Stability in Machine Learning
No full textFeature selection is a dimension reduction technique used to select features that are relevant to machine learning tasks. Reducing the dataset size by eliminating redundant and irrelevant features plays a pivotal role in increasing the performance of machine learning algorithms, speeding up the learning process, and building simple models. The apparent need for feature selection has aroused considerable interest amongst researchers and has caused feature selection to find a wide range of application domains including text mining, pattern recognition, cybersecurity, bioinformatics, and big data. As a result, over the years, a substantial amount of literature has been published on feature selection and a wide variety of feature selection methods have been proposed. The quality of feature selection algorithms is measured not only by evaluating the quality of the models built using the features they select, or by the clustering tendencies of the features they select, but also by their stability. Therefore, this study focused on feature selection and feature selection stability. In the pages that follow, general concepts and methods of feature selection, feature selection stability, stability measures, and reasons and solutions for instability are discussed.Multidisciplinary Science
Development of a New Robust Stable Walking Algorithm for a Humanoid Robot Using Deep Reinforcement Learning with Multi-Sensor Data Fusion
No full textThe difficult task of creating reliable mobility for humanoid robots has been studied for decades. Even though several different walking strategies have been put forth and walking performance has substantially increased, stability still needs to catch up to expectations. Applications for Reinforcement Learning (RL) techniques are constrained by low convergence and ineffective training. This paper develops a new robust and efficient framework based on the Robotis-OP2 humanoid robot combined with a typical trajectory-generating controller and Deep Reinforcement Learning (DRL) to overcome these limitations. This framework consists of optimizing the walking trajectory parameters and posture balancing system. Multi-sensors of the robot are used for parameter optimization. Walking parameters are optimized using the Dueling Double Deep Q Network (D3QN), one of the DRL algorithms, in the Webots simulator. The hip strategy is adopted for the posture balancing system. Experimental studies are carried out in both simulation and real environments with the proposed framework and Robotis-OP2's walking algorithm. Experimental results show that the robot performs more stable walking with the proposed framework than Robotis-OP2's walking algorithm. It is thought that the proposed framework will be beneficial for researchers studying in the field of humanoid robot locomotion.Computer Science, Information Systems || Engineering, Electrical & Electronic || Physics, Applie
Online sequential, outlier robust, and parallel layer perceptron extreme learning machine models for sediment transport in sewer pipes
No full textSediment transport is a noteworthy task in the design and operation of sewer pipes. Decreasing sewer pipe hydraulic capacity and transport of pollution are the main consequences of continuous sedimentation. Among different design approaches, the non-deposition with deposited bed (NDB) method can be used for the design of large sewer pipes || however, existing models are established on limited data ranges and mostly applied conventional regression methods. The current study improves the NDB sediment transport modeling by utilizing wide data ranges, and furthermore, applying robust machine learning techniques. In the present study, the conventional extreme learning machine (ELM) technique and its advanced versions, namely the online sequential-extreme learning machine (OS-ELM), outlier robust-extreme learning machine (OR-ELM), and parallel layer perceptron-extreme learning machine (PLP-ELM) are used for the modeling. In the studies conducted in the literature, sediment deposited bed thickness (t(s)) or deposited bed width (W-b) was used in the model structure as a deposited sediment variable, and therefore, different parameters in terms of t(s) and W-b can be incorporated into the model structure. However, an uncertainty arises in the selection of the appropriate parameter among W-b/Y, t(s)/Y, W-b/D, and t(s)/D (Y is flow depth and D circular pipe diameter). In order to define the most appropriate parameter to best describe the impact of deposited sediment at the channel bottom in the modeling procedure, four various scenarios using four different parameters that incorporate deposited sediment variables at their structures as W-b/Y, t(s)/Y, W/D, and t(s)/D are considered for model development. It is found that models that incorporate sediment bed thickness (t(s)) provide better results than those which use deposited bed width (W-b) in their structures. Among four different scenarios, models that utilized t(s)/D dimensionless parameter, give superior results in contrast to their alternatives. Based on the outcomes, the OR-ELM approach outperformed ELM, OS-ELM, and PLP-ELM techniques. The results obtained from applied methods are compared to their corresponding models in the literature, indicating the superiority of the OR-ELM model. It is figured out that the thickness of the deposited bed is an effective variable in modeling NDB sediment transport in sewer pipes.Environmental Science
Construction and Demolition Waste Management in Urban Transformation: A Case Study for Performance Evaluation
No full textDue to the decreasing resources in the world, different recycling applications in different sectors are gaining more importance. Urban transformations initiated especially for earthquake remnants and old buildings provide many advantages for the construction sector. Recycling of valuable materials from the wastes from each demolished construction site is very important in terms of costs. It is also important to analyse the effectiveness of both public and private companies to compare different approaches and illustrate best practices. From this point of view, this research has been carried out on the recycling of construction and demolition wastes in Turkey and the performance of companies dealing with this business. Analytical hierarchy process (AHP) and gray relations analysis (GRA) will be applied for the evaluation phase. The criteria will be analysed through AHP and the connection between companies will be determined with the GRA method. According to the results, potential improvement opportunities will be identified to increase the performance and competitiveness of construction excavation companies. This will also allow the findings to serve as a potential model for other construction companies operating under different contingency factors, as well as presenting the list of criteria that construction companies should pay attention for performance evaluation.Construction & Building Technolog
A dynamic connectedness analysis between rare earth prices and renewable energy
No full textCurrent world environmental challenges put pressure on clean energy produced mostly through renewables. There is an undeniably important role of rare earth minerals in renewable energy technologies. This study aims to infer the relationship between rare earth, clean energy, renewable energy technologies, and carbon emissions, focusing on daily stock price index data and applying the novel quantile time-frequency connectedness model, and the cross-quantilogram dependence approach during 2012-2022. Results show that spillovers among rare earth minerals and renewable energy are dependent on market conditions, time horizons, and analyzed quan-tiles. They also highlight the net receiver role of rare earth, especially in the short term. Findings might help investors understand diversification benefits and support policymakers in developing strategies for lessening import dependence on rare earth metals, as important as they are for renewable technology adoption to ensure green growth.Environmental Studie
Gender, Sustainability, and Urbanism: A Systematic Review of Literature and Cross-Cluster Analysis
No full textGender diversity and equality have a significant influence on policymaking regarding sustainable development, environmental issues, and urbanism. This study examines the general bibliometric outlook and research patterns of publications on gender equality, urbanism, and sustainability to provide a general perspective on the relevant literature and trends for institutions and scholars who wish to conduct research within the framework of gender, sustainability, and urbanism. The findings of this study show that there are a limited number of studies dealing with gender equality, sustainability, and urbanism. The study analyzed 308 papers in total, utilizing data mining and analytics techniques such as t-SNE and SNA for a systematic review process. The study utilized the PRISMA protocol as the research method. The results showed that research on the frame of gender, sustainability, and urbanism peaked in 2021, and the top countries for studying gender, sustainability, and urbanism are the USA, the UK, Spain, and China. The research fields that contributed the most were those dealing with environmental studies and green and sustainable technologies, followed by those dealing with business and women's studies. The following three thematically inclined clusters were revealed by the t-SNE analysis: (1) Gender Diversity, Corporate Sustainability, and Board Governance || (2) Gender, Environmental Sustainability, Sustainable Development, and Policy Agenda || and (3) Gender, Sustainable Urbanism, and Community Development. The findings of the study revealed that fostering gender equality with policies such as gender mainstreaming, as in SDG 5 and SDG 11, and gender equality strategies of the EU or UN will help to overcome discrimination against women in the urban space and empower sustainable development.Green & Sustainable Science & Technology || Environmental Sciences || Environmental Studie
Urban Open Therapy Gardens in EU Cities Mission: Izmir Union Park Proposal
No full textOne of the biggest problems of societies living in modern world cities is the stress brought by a fast lifestyle. Stress affects individuals psychologically, physically, and socially. With the increase in the factors that cause stress, the need for places that individuals can use as therapy areas has also increased. Especially in this period when the 2030 100 EU (European Union) Cities Mission is determined, it is very important to design urban green spaces where the environmental and social criteria of sustainability are met, as places where society can breathe and where the society gets away from stress. In this study, based on the experiential quality criteria in outdoor therapy gardens, and the results of the evaluations made by experts and users, suggestions are made to improve the conditions of Birlik Park, located in the Gaziemir district of Izmir, one of the cities selected for the 100 EU Cities Mission, and to use it as an open space therapy garden.Green & Sustainable Science & Technology || Environmental Sciences || Environmental Studie