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The Impact of Perceived Corporate Social Responsibility on Consumer Happiness and Brand Admiration
No full textPurposeThis study examines the effect of perceived corporate social responsibility (CSR) on consumer happiness and brand admiration as a consequence of consumer happiness. It suggests an original conceptual model that investigates perceived CSR, ethical consumption and hope as antecedents of consumer happiness.Design/methodology/approachThe study followed a quantitative approach. A face-to-face survey was conducted to examine the conceptual model. Data were analyzed with partial least squares structural equation modeling (PLS-SEM).FindingsHope and perceived CSR significantly influence consumer happiness. Consumer happiness is a significant antecedent of brand admiration. Although consumers' ethical position (idealism and relativism) is linked to ethical consumption, ethical consumption does not influence consumer happiness. Idealism and relativism are insignificant in moderating the perceived CSR-consumer happiness relationship.Practical implicationsBrands' CSR actions create a positive atmosphere and contribute to consumer happiness and brand admiration. Managers can emphasize happiness and hope in CSR programs to build stronger consumer relationships. CSR activities can be engaging for consumers regardless of their ethical consumption levels.Originality/valueAlthough CSR, consumer happiness and their impacts on consumer-brand relationships are crucial, previous studies mainly focused on the organizational perspective and employee emotions regarding CSR. This study focused on consumer happiness in the CSR context and tested a conceptual model that revealed the significant relationships between hope, perceived CSR, consumer happiness and brand admiration. It extended previous findings by showing the direct positive impact of perceived CSR on consumer happiness
Pinstimation: an R Package for Estimating Probability of Informed Trading Models
No full textGhachem, Montassar/0000-0001-6991-3316The purpose of this paper is to introduce the R package PINstimation. The package is designed for fast and accurate estimation of the probability of informed trading models through the implementation of well-established estimation methods. The models covered are the original PIN model (Easley and O'Hara 1992; Easley et al. 1996), the multilayer PIN model (Ersan 2016), the adjusted PIN model (Duarte and Young 2009), and the volume-synchronized PIN (Easley, De Prado, and O'Hara 2011; Easley, Lopez De Prado, and O'Hara 2012). These core functionalities of the package are supplemented with utilities for data simulation, aggregation and classification tools. In addition to a detailed overview of the package functions, we provide a brief theoretical review of the main methods implemented in the package. Further, we provide examples of use of the package on trade-level data for 58 Swedish stocks, and report straightforward, comparative and intriguing findings on informed trading. These examples aim to highlight the capabilities of the package in tackling relevant research questions and illustrate the wide usage possibilities of PINstimation for both academics and practitioners.Science Citation Index Expande
Deep Learning Algorithms for the Prediction of Renal Failure: A Case Study from Tanzania's Muhimbili National Hospital
No full textIEEE; The Nelson Mandela, African Institution of Science and Technology, Academia for Society and Industry; The University of DodomaRenal failure occurs when kidney function fails, and the nephron is the major engine for renal function. Patients fail to detect kidney disease in its early stages, leaving them with just two options: kidney transplantation or renal dialysis, both of which are excessively expensive, with dialysis costing roughly 27,440 USD per year and kidney transplants costing 45,000 USD. As a result, developing the framework for the decision support system will aid doctors in reaching the study's goal. This study proposes that Deep learning be used to predict renal failure before it proceeds to the chronic stage. The data set was given by Tanzania's Muhimbili National Hospital. The framework predictor of renal failure was determined using six machine learning techniques (Logistic Regression, Linear Discriminant Analysis, K-Neighbors Classifier, Decision Tree Classifier, Gaussian Naive Bayes, and Support Vector Machine). The best performance was reported to be a Gaussian Naive Bayes and Decision Tree classifier with 100% accuracy, followed by a Support Vector Machine and Logistic Regression with 98.6% accuracy. Cross-validation, confusion matrix, and receiver operating characteristics were also used to evaluate the framework. The precision measurements, recall measures, and f1-score scores serve as the foundation for the renal failure framework's 100% accuracy performance. We proposed that Gaussian Naive Bayes and Decision Tree classifiers be used to predict renal failure. © 2023 IEEE
The Personal Health Applications of Machine Learning Techniques in the Internet of Behaviors
No full textWith the swift pace of the development of artificial intelligence (AI) in diverse spheres, the medical and healthcare fields are utilizing machine learning (ML) methodologies in numerous inventive ways. ML techniques have outstripped formerly state-of-the-art techniques in medical and healthcare practices, yielding faster and more precise outcomes. Healthcare practitioners are increasingly drawn to this technology in their initiatives relating to the Internet of Behavior (IoB). This area of research scrutinizes the rationales, approaches, and timing of human technology adoption, encompassing the domains of the Internet of Things (IoT), behavioral science, and edge analytics. The significance of ML in medical and healthcare applications based on the IoB stems from its ability to analyze and interpret copious amounts of complex data instantly, providing innovative perspectives that can enhance healthcare outcomes and boost the efficiency of IoB-based medical and healthcare procedures and thus aid in diagnoses, treatment protocols, and clinical decision making. As a result of the inadequacy of thorough inquiry into the employment of ML-based approaches in the context of using IoB for healthcare applications, we conducted a study on this subject matter, introducing a novel taxonomy that underscores the need to employ each ML method distinctively. With this objective in mind, we have classified the cutting-edge ML solutions for IoB-based healthcare challenges into five categories, which are convolutional neural networks (CNNs), recurrent neural networks (RNNs), deep neural networks (DNNs), multilayer perceptions (MLPs), and hybrid methods. In order to delve deeper, we conducted a systematic literature review (SLR) that examined critical factors, such as the primary concept, benefits, drawbacks, simulation environment, and datasets. Subsequently, we highlighted pioneering studies on ML methodologies for IoB-based medical issues. Moreover, several challenges related to the implementation of ML in healthcare and medicine have been tackled, thereby gradually fostering further research endeavors that can enhance IoB-based health and medical studies. Our findings indicated that Tensorflow was the most commonly utilized simulation setting, accounting for 24% of the proposed methodologies by researchers. Additionally, accuracy was deemed to be the most crucial parameter in the majority of the examined papers
Mcdm-Based Wildfire Risk Assessment: a Case Study on the State of Arizona
No full textSimic, Vladimir/0000-0001-5709-3744; Jovcic, Stefan/0000-0002-9162-2133; Hashemkhani Zolfani, Sarfaraz/0000-0002-2602-3986The increasing frequency of wildfires has posed significant challenges to communities worldwide. The effectiveness of all aspects of disaster management depends on a credible estimation of the prevailing risk. Risk, the product of a hazard's likelihood and its potential consequences, encompasses the probability of hazard occurrence, the exposure of assets to these hazards, existing vulnerabilities that amplify the consequences, and the capacity to manage, mitigate, and recover from their consequences. This paper employs the multiple criteria decision-making (MCDM) framework, which produces reliable results and allows for the customization of the relative importance of factors based on expert opinions. Utilizing the AROMAN algorithm, the study ranks counties in the state of Arizona according to their wildfire risk, drawing upon 25 factors categorized into expected annual loss, community resilience, and social vulnerability. A sensitivity analysis demonstrates the stability of the results when model parameters are altered, reinforcing the robustness of this approach in disaster risk assessment. While the paper primarily focuses on enhancing the safety of human communities in the context of wildfires, it highlights the versatility of the methodology, which can be applied to other natural hazards and accommodate more subjective risk and safety assessments
Annenin ve Babanın Nedensel Dil Girdisi Çocuğun Nedensel Dil Üretimi ve Karşı Olgusal Düşünmesi ile Nasıl İlişkilidir
No full textNeden-sonuç ilişkisi ürettiğimiz sözlü yapıları kapsayan nedensel dil, günlük yaşamımızda gözlemlediğimiz nedensel olayları ifade etmek için kullandığımız dil yapısıdır. Bu yapıları erken çocukluk döneminden itibaren kullanmaya başlarız ve bu noktada hem anne hem de baba önemli roller oynar. Bir olayın sebep ve sonucunu anlamak, potansiyel olarak diğer olası senaryoları düşünmeyi gerektirebilir ve dolaylı olarak nedensel dilin karşı olgusal düşünceyle ilişkili olmasını sağlayabilir. Karşı olgusal düşünce, gerçekleşmiş veya henüz gerçekleşmemiş bir olayın alternatif sonuçlarını düşünme yeteneğidir. Mevcut çalışmada, (1) annelerin ve babaların nedensel dil girdisindeki farklılıkların, (2) anne ve babanın nedensel dil girdileri ile çocuğun nedensel dil üretimi arasındaki ilişkinin, (3) çocuğun nedensel dil üretimi ile karşı olgusal düşünceleri arasındaki ilişkinin ve (4) annelerin ve babaların nedensel dil girdileri ile çocuğun karşı olgusal düşüncesi arasındaki ilişkinin araştırılması amaçlanmıştır. Çevrimiçi yürütülen çalışma, 60 ebeveyn-çocuk çiftinin (Myaş: 56 ay) katılımı ile gerçekleşmiş ve anne-babalar çalışmaya birbirlerinden ayrı katılım göstermiştir. Baba-çocuk ve anne-çocuk ikili oturumları için tangram oyunu ve hikaye anlatma görevleri kullanılmıştır. Çocuk oturumu için hikaye anlatma, karşı olgusal düşünme, nedensel fiil üretimi, inhibisyon kontrolü görevleri ve TIFALDI ifade edici dil alt testi kullanılmıştır. Araştırma bulgularına bakıldığında, babaların annelere kıyasla daha fazla nedensel dil kullandığı görülmektedir. Annenin nedensel dil girdisi ile çocuğun annesine yönelik kullandığı nedensel dil arasında pozitif bir ilişki bulunmuştur. Benzer şekilde, babanın nedensel dil girdisi ile çocuğun babasına yönelik kullandığı nedensel dili arasında pozitif bir ilişki vardır. Babanın nedensel dil girdisi çocuğun karşı olgusal düşüncesiyle ilişkili bulunmazken annenin nedensel dil girdisi ile çocuğun karşı olgusal düşüncesi arasında negatif yönlü bir ilişki bulunmuştur. Yalnızca çocuğun annesine yönelik kullandığı nedensel dilin karşı olgusal düşüncesiyle negatif bir ilişki içinde olduğu görülmektedir. Anne veya babanın nedensel dil girdisi çocuğun hikaye anlatma ve nedensel fiil üretimi görevlerinin puanlarıyla ilişkili bulunmamıştır. Sonuç olarak, bu çalışma çocukların nedensel dil ve karşı olgusal düşünceleri arasındaki ilişkiyi incelerken hem anneleri hem de babaları odak noktasına alarak literatüre katkıda bulunmaktadır.Causal language encompasses the verbal structures we use to produce causal events that we observe in our daily lives. We begin using these structures from early childhood, and both the mother and father play crucial roles. Understanding the cause and effect of an event can potentially involve considering other possible scenarios, may indirectly linking causal language to counterfactual thinking. Counterfactual thinking is the ability to contemplate alternative outcomes of an event that has occurred or not yet occurred. In the present study, we aimed to investigate (1) the differences in maternal and paternal causal language input, (2) the association between maternal and paternal causal language inputs and children's causal language production, (3) the association between children's causal language production and their counterfactual thinking, and (4) the association between maternal and paternal causal language inputs and the child's counterfactual thinking. The online study involved 60 parent-child pairs (Mage: 56 months) and both mothers and fathers attended to the study separately. Tangram play and story-telling tasks were used for father-child and mother-child dyadic sessions. For the child session, storytelling, counterfactual thinking, causal verb production, inhibitory control tasks, and the TIFALDI-expressive subtest were employed. Results indicated that fathers tend to use more causal language compared to mothers. There was a positive relationship between maternal causal language input and child causal language directed to the mother. There was a positive relationship between paternal causal language input and child causal language directed to the father. However, while the father's causal language input was not associated with child counterfactual thinking, maternal causal language input negatively associated with child counterfactual thinking. Only child causal language directed to the mother was negatively associated with counterfactual thinking. Maternal or paternal causal language input were not associated with the child's story-telling and causal verb production task scores. In conclusion, this study contributes to the literature by focusing on both mothers and fathers, as well as investigating the relationship between child's causal language and counterfactual thinking
The Impact of Haptic Feedback During Sudden, Rapid Virtual Interactions
No full textBatmaz, Anil Ufuk/0000-0001-7948-8093; Hudhud Mughrabi, Moaaz/0000-0001-5381-0427Haptic feedback is known to improve the realism and the performance of virtual tasks during manipulation or teleoperation tasks. However, these benefits might depend on the nature of virtual tasks or the intensity of haptic rendering. In this paper, we focused on the impact of the presence and the intensity of the haptic stimulus during sudden, rapid virtual interactions through a variation of an ISO 9241:411 - task instead of calm, exploration-based interactions. We conducted a user study where the haptic stimulus is rendered through a realistic 1-DoF fingertip haptic device with different intensity levels (full-strength, half-strength, and no-strength) as they are asked to choose highlighted targets on a 6-by-5 grid as fast and correctly as possible. Our results show that haptic feedback did not significantly affect user performance regarding time, throughput, or the nature of the selection behavior. However, participants made significantly more errors when haptic feedback was present in half-strength compared to full-strength and no-strength conditions. In the post-experiment questionnaire, participants reported having favored haptic feedback in full strength in terms of perceived realism, enjoyment, and immersion.TUBITAK 1001 Program [221M458]This work is funded by TUBITAK 1001 Program number 221M458
Gestures Cued by Demonstratives in Speech Guide Listeners' Visual Attention During Spatial Language Comprehension
No full textGestures help speakers and listeners during communication and thinking, particularly for visual-spatial information. Speakers tend to use gestures to complement the accompanying spoken deictic constructions, such as demonstratives, when communicating spatial information (e.g., saying The candle is here and gesturing to the right side to express that the candle is on the speaker's right). Visual information conveyed by gestures enhances listeners' comprehension. Whether and how listeners allocate overt visual attention to gestures in different speech contexts is mostly unknown. We asked if (a) listeners gazed at gestures more when they complement demonstratives in speech (here) compared to when they express redundant information to speech (e.g., right) and (b) gazing at gestures related to listeners' information uptake from those gestures. We demonstrated that listeners fixated gestures more when they expressed complementary than redundant information in the accompanying speech. Moreover, overt visual attention to gestures did not predict listeners' comprehension. These results suggest that the heightened communicative value of gestures as signaled by external cues, such as demonstratives, guides listeners' visual attention to gestures. However, overt visual attention does not seem to be necessary to extract the cued information from the multimodal message.TUBITAK's (The Scientific and Technological Research Council of Turkey) International Research Fellowship Programme for PhD Students [2214-A]; Tuerkiye Bilimler Akademisi (Turkish Academy of Sciences) Outstanding Young Scientist Award 2018; James McDonnell Foundation Scholar Award [220020510]This work was supported by the TUBITAK's (The Scientific and Technological Research Council of Turkey) International Research Fellowship Programme for PhD Students (2214-A) given to Demet Ozer, Tuerkiye Bilimler Akademisi (Turkish Academy of Sciences) Outstanding Young Scientist Award 2018 and a James McDonnell Foundation Scholar Award (Grant 220020510) given to Tilbe Goksun
A New Design of a 3 X 3 Reversible Circuit Based on a Nanoscale Quantum-Dot Cellular Automata
No full textQuantum-dot cellular automata (QCA) is the best-suggested nanotechnology for designing digital electronic circuits. It has a higher switching frequency, low-power expenditures, low area, high speed and higher scale integration. Recently, many types of research have been on the design of reversible logic gates. Nevertheless, a high demand exists for designing high-speed, high-performance and low-area QCA circuits. Reversible circuits have notably improved with developments in complementary metal-oxide-semiconductor (CMOS) and QCA technologies. In QCA systems, it is important to communicate with other circuits and reversible gates reliably. So, we have used efficient approaches for designing a 3 x 3 reversible circuit based on XOR gates. Also, the suggested circuits can be widely used in reversible and high-performance systems. The suggested architecture for the 3 x 3 reversible circuit in QCA is composed of 28 cells, occupying only 0.04 mu m(2). Compared to the state-of-the-art, shorter time, smaller areas, more operational frequency and better performance are the essential benefits of the suggested reversible gate design. Full simulations have been conducted with the utilization of QCADesigner software. Additionally, the proposed 3 x 3 gate has been schematized using two XOR gates
<i>le</I><i> Comte</I><i> De</I><i> Monte</I><i>-cristo< in Karamanlidika: in the Footsteps of Teodor Kasap
No full textLe Comte de Monte-Cristo (1844) by Alexandre Dumas pere is among the popular novels translated into many languages and scripts in the Ottoman Empire in the nineteenth century. The Karamanlidika (Turkish in Greek script) edition of 1882-83 has not hitherto been studied in a comparative reading with the source text. This article identifies the source text as the Turkish in Arabic script translation of Monte Kristo (1871) by Teodor Kasap, a prominent figure in Ottoman Turkish literature and press. This source text affected the ornate language in the Karamanlidika translation, in sharp contrast to the general tendency towards plainness in the Karamanlidika fiction of the time. Taking "translation" (terceme) as an umbrella term, the article analyses the practices of both Kasap and the unknown Karamanlidika translator in translating the novel. The paper also analyses the conventional paratexts of the Karamanlidika edition, such as the publication house, the dedication page and the subscriber's list in the back of the book to understand the mechanisms of book production and circulation among the Turcophone Orthodox community. One volume published in an Armeno-Turkish publishing house indicates an intercommunal publishing activity between Christian communities in mid-1gth century. The subscriber's list from various cities of Asia Minor and the dedication to an Anatolian notable is typical in the sense it shows the dominance of the Anatolian readers in the style, language and vocabulary of the texts produced in Karamanlidika.Arts &- Humanities Citation Inde