5916 research outputs found
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Multi-climate zone approach to sustainable retrofitting for optimizing energy efficiency and CO2 reduction in Australian detached houses
No full textPurposeThis research proposes an innovative approach to enhancing the energy efficiency of detached houses in Australia by providing retrofit solutions based on the specific energy demands of several cities across various climatic zones. This study investigates the effectiveness of building envelope retrofits for detached houses in achieving energy efficiency and CO2 emission reduction across different climatic zones within Australia.Design/methodology/approachDesignBuilder and PVSOL (R) were used to simulate a typical detached house for Canberra, Brisbane and Adelaide. 12 retrofit scenarios, including thermal wall insulation for the walls and roof and the implementation of photovoltaic panels on the roof, were implemented to analyze their impact on the case study building's energy consumption and reduction in greenhouse gas emissions.FindingsThe results show that the provided retrofitting solutions considerably reduced the energy consumption of the case study by 58% (Canberra), 54% (Brisbane) and 63% (Adelaide), highlighting the substantial benefits of this combined approach. Annual CO2 emissions are reduced by 28%, 26%, and 30% in Canberra, Brisbane and Adelaide.Originality/valueThis research presents the importance of retrofitting detached home envelopes in Australia by considering different climatic zones to achieve significant improvements in energy efficiency and CO2 emission reduction. This approach contributes by providing a robust and replicable methodology for future energy performance assessments, providing a valuable framework for policymakers, building professionals and researchers seeking to improve energy efficiency in residential buildings under various climate conditions. The scenarios and results provide the foundation to establish evidence-based policies to reduce energy consumption and CO2 emissions in similar climates
ALNS algorithm for load handling and agv routing with trolleys
No full textThis study addresses a multi-load automated guided vehicle (AGV) routing problem, motivated by an industrial collaboration with Vestel Electronics, a global leader in consumer electronics and white goods manufacturing. The problem involves optimizing the routing and load handling of a homogeneous AGV fleet equipped with modular trolley attachments. While trolleys enhance load capacity, they also increase travel time proportionally to the number of attachments. Distinct from existing literature, this study integrates key complexities, including the impact of trolley attachments on travel time, time windows for transport requests, and penalties for deviations from these time windows, alongside minimizing total travel distance. To solve this problem, we develop a mixed-integer linear programming (MILP) model and propose an adaptive large neighborhood search (ALNS) heuristic, incorporating fourteen destroy-and-repair operators. The ALNS algorithm significantly outperforms both the MILP model and the rule-of-thumb approach currently used in practice. Through extensive computational experiments, including a real-life case study, we show that the ALNS algorithm is robust to the size of the instances and performs efficiently. Moreover, the contextual bandit-enhanced ALNS achieves superior solution quality, particularly when given sufficient iterations, and contributes to a more intelligent and adaptive search process. We also conduct a real-life case study on Vestel Electronics and conclude that Vestel Electronics can reduce its cost to 1/48th of its current value
[COMP24] The Automated Negotiating Agents Competition (ANAC) 2024 challenges and results
No full textThis paper introduces the main research challenges and results of the 15th International Automated Negotiating Agents Competition (ANAC 2024). The main challenges addressed are learning the reservation value in bilateral negotiation and designing a factory agent employing concurrent negotiation in supply chain management. Additionally, it outlines the future directions for the competition.Netherlands Organization for Scientific Research (NWO) ; Springer AI ; AI Journal ; NEC-AIST AI Cooperative Research Laborator
A cross-validation study of Turkish sentiment analysis datasets and tools
No full textIn recent years, sentiment analysis has gained increasing significance, prompting researchers to explore datasets in various languages, including Turkish. However, the limited availability and reuse of Turkish datasets across studies has yielded highly diverse outcomes. To address this, we conducted a systematic review of sentiment analysis studies on Turkish text. Our search identified 78 relevant studies, from which we extracted over 80 datasets. These studies were labeled using a comprehensive sentiment analysis taxonomy, and the dataset details were compiled into a structured repository. Furthermore, we evaluated the performance of four stateof-the-art models-XLM-T, BERTurk (fine-tuned with the BounTi dataset), TSAM, and TurkishBERTweet-on four widely-used Turkish datasets. Among the models, XLM-T achieved the highest performance with an accuracy of 0.92 and F1 score of 0.95 on the Twt dataset, while TSAM reached 0.97 accuracy and F1 score on the Humir dataset. Our empirical results demonstrate that model performance varies significantly based on dataset characteristics such as domain, balance, and linguistic structure. Our review revealed key research gaps, including the limited application of emotion-based and concept-based sentiment analysis techniques and the lack of domain diversity in Turkish sentiment datasets. By highlighting such gaps and compiling a centralized repository, this study provides a comprehensive and publicly accessible resource to guide future research in Turkish sentiment analysis.Publisher versio
Multiple item economic lot sizing problem with inventory dependent demand
No full textWe consider a multiple item Economic Lot Sizing problem where the demands for items depend on their stock quantities. The objective is to find a production plan such that the resulting stock levels (and hence demands) maximize total profit over a finite planning horizon. The single item version of this problem has been studied in the literature, and a polynomial time algorithm has been proposed when there are no bounds on production. It has also been proven that the single item version is NP-hard even when there are constant (i.e., time-invariant) finite capacities on production. We extend this single item model by considering multiple items and production capacities. We propose a Lagrangian relaxation method to find an initial solution to the problem. This solution is a hybrid solution obtained by combining two distinct solutions generated in the process of solving the Lagrangian dual problem. Starting with this initial solution, we then implement a Tabu Search algorithm to find better solutions. The performance of the proposed solution method is compared with the performance of a standard commercial software that works on a mixed integer programming formulation of the problem. We show that our solution approach finds better solutions within a predetermined time limit in general.TÜBİTAKPublisher versio
Correlates of young children's screen time: Child-, parent-, and home-related factors
No full textOkul öncesi çocukların günlerinin önemli bir kısmını ekran karşısında geçirdikleri bilinmektedir. Önceki çalışmalarda, çocukların ekran başında geçirdikleri sürenin çeşitli demografik, ailevi ve ev içi unsurlarla ilişkili olduğu gösterilmiştir. Bu bulguların çoğu, yüksek gelirli ve erken çocukluk eğitiminin yaygın olduğu gelişmiş ülkelerden gelmektedir. Farklı ülkelerdeki bulguların kıyaslanması ve çocukların ekran süresini belirleyebilecek yeni değişkenlerin alanyazına kazandırılması açısından ülkemizde yaşayan okul öncesi çocukların ekran süresi ile ilişkili unsurları tespit etmek önemlidir. Bu çalışmanın ilk amacı, çevrimiçi bir anket aracılığıyla okul öncesi çocukların ekran süresi ile ilişkili olabilecek çocuk (örn., yaş), ebeveyn (örn., stres seviyesi) ve ev ortamı (örn., arka plan televizyon sıklığı) ile ilgili unsurları incelemektir. Çalışmanın ikinci amacı, çocukların ekran süresi ile ebeveynin algıladığı sosyal destek arasın7 daki ilişkiyi alanyazında ilk kez incelemektir. Çalışmaya altı yaşından küçük çocuğu bulunan (Ort. = 41.5 ay, SS = 17.9) 647 ebeveyn katılmıştır. Çocukların ekran süresinin, ebeveynlerin çocukların teknoloji kullanımına yönelik olumlu tutumları, ebeveynlerin ekran süresi, çocuğun yaşı ve ebeveyn tarafından algılanan dikkat dağınıklığı ve arka plan televizyon sıklığı ile olumlu yönde ilişkili olduğu görülmüştür. Çocukların ekran süresinin, anne7baba eğitim seviyesi, hane geliri ve ebeveynin algıladığı sosyal destek ile olumsuz yönde ilişkili olduğu bulunmuştur. Hiyerarşik regresyon analizinde, arka plan televizyon sıklığı, ebeveynlerin çocukların teknoloji kullanımına yönelik olumlu tutumları ve çocuğun yaşı ekran süresinin en güçlü yordayıcıları olarak öne çıkmıştır. Ebeveynin algıladığı sosyal destek miktarının çocukların ekran süresi ile ilişkili bir değişken olduğu ilk kez mevcut çalışmada gösterilmiştir. Bulguların ülkemizdeki okul öncesi çocukların ekran süresini azaltmaya yönelik geliştirilecek girişimlere bilgi sağlayacağı düşünülmektedir.Young children spend a significant part of their day in front of screens. Existing literature has shown associationsbetween children's screen time and various demographic, parent7related, and home7related factors. Most evidencecomes from high7income, developed countries with access to early childcare options. Investigating these factors inT & uuml;rkiye is crucial to compare findings across countries and identify new variables that might influence children'sscreen time. The first goal of this study was to examine child7related factors (e.g., age), parent7related factors (e.g.,parental stress), and home7related factors (e.g., background television) that may be associated with young children'sscreen time through an online survey. The second goal was to investigate the relationship between children's screentime and parents' perceived social support for the first time in the literature. A total of 647 parents with children younger than six (M = 41.5, SD = 17.9) months) participated. Results revealed that children's screen time was positivelycorrelated with parents' positive attitudes toward children's use of technology, parents' own screen time, child ageand distractibility as perceived by the parents, and the frequency of background television at home. Conversely,children's screen time was negatively related to parental education, household income, and parents' perceived social support. Hierarchical regression analysis indicated that the frequency of background television at home, parents' positive attitudes toward children's use of technology, and child age emerged as the strongest predictors of children's screen time. This study is the first to propose and demonstrate the role of social support in determining children's screen time. Our findings may provide valuable insights for designing intervention strategies to reduce screen time among preschoolers.Publisher versio
Enhanced nearest centroid model tree classifier
No full textIn this study, first, we improved an existing variant of the Nearest Centroid algorithm. In this new version, the predictive power of features and within-class variances are used as weights in distance calculation. This version is called the Enhanced Nearest Centroid (ENC). Second, we proposed a new model tree algorithm for binary classification. It is named as the Enhanced Nearest Centroid Model Tree (ENCMT). The model tree is built using ENC at each leaf node of the decision tree. To evaluate the performance of the new model tree, we used an independent test platform and ran the algorithm on 30 binary datasets available therein. Results showed that ENCMT improves the performance of the decision tree algorithm. We also compared ENCMT with the Logistic Model Tree (LMT) algorithm and showed that it outperforms LMT as well. We also designed a bagging algorithm where ENCMT is used to build a random forest. Our comparison results show that its performance is significantly better than the Random Forest (RF) algorithm.Publisher versio
Populist securitization of migration: The anti-immigrant zafer party example in Türkiye
No full textAlthough T & uuml;rkiye is the largest refugee-hosting country in the world, the Zafer Party's (ZP) (English: Victory Party) discourse on migration as the pioneer representative of the European-style anti-immigrant right party example has been under-studied. To address this gap, this research examines the discursive practices of the ZP through the lens of populist securitization. It focuses on revealing how the ZP employs a people-centred appeal to securitization, explaining how the people are located within its populist discourse as a threatened object of reference and actor. In this way, it empirically contributes to the burgeoning literature bridging between populism and securitization theory. To this end, it conducts an extensive qualitative frame analysis of the party's manifesto, programme, press releases, public speeches uttered by party leader & Uuml;mit & Ouml;zda & gbreve;. The time frame of the research is designated as starting from the establishment of the ZP, i.e. 26 August 2021, to the Presidential and Parliamentary Elections in T & uuml;rkiye, i.e. 14 May 2023. The paper finds out that ZP combines populist and nationalist appeals by creating vertical (down/up) and horizontal (in/out) antagonisms, exhibiting parallels with similar tendencies in its European counterparts
Dyadic examination of children's emotion regulation in family context: Contributions of coparenting and parents' self-compassion
No full textThe purpose of the current study was to examine the dyadic association between parents' self-compassion and children's emotion regulation in early childhood, with a specific focus on the mediating role of the coparenting relationship (cooperation, conflict, and triangulation). The sample of this study consisted of 333 parental dyads (333 mothers and 333 fathers) who had at least one child between 36 and 96 months (M = 68.89, SD = 15.03). Both mothers and fathers reported their level of self-compassion, the coparenting quality, and their child's emotion regulation. The Actor-Partner Interdependence Model (APIM) and Actor- Partner Interdependence Mediation Model (APIMeM) were used to investigate the effects of the actor and partner on the study variables. The results from the Actor-Partner Interdependence Model (APIM) revealed a significant and positive association between parents' self-compassion and their respective reports of child emotion regulation. Notably, fathers' self-compassion was significantly associated with mothers' reports of child emotion regulation, but mothers' self-compassion did not show a significant association with fathers' reports of child emotion regulation. Results also demonstrated that fathers' coparenting cooperation mediated the relationship between mothers' self-compassion and fathers' reports of child emotion regulation, as well as the relationship between fathers' self-compassion and their own reports of child emotion regulation. However, conflict and triangulation within the coparenting relationship did not mediate the association between parents' self-compassion and children's emotion regulation.TÜBİTAKPublisher versio