Search results for: cognitive complexity metric

Authors: Jorge Iván Bañol-Betancur, Lina María Martínez-Sánchez, María de los Ángeles Rodríguez-Gázquez, Estefanía Bahamonde-Olaya, Ana María Gutiérrez-Tamayo, Laura Isabel Jaramillo-Jaramillo, Camilo Ruiz-Mejía, Natalia Morales-Quintero

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Acute chest pain is a distressing sensation between the diaphragm and the base of the neck and it represents a diagnostic challenge for any physician in the emergency department. Objective: To establish the main clinical and epidemiological characteristics of patients who present with chest pain to the emergency department in a private clinic from the city of Medellin, during 2014-2015. Methods: Cross-sectional retrospective observational study. Population and sample were patients who consulted for chest pain in the emergency department who met the eligibility criteria. The information was analyzed in SPSS program vr.21; qualitative variables were described through relative frequencies, and the quantitative through mean and standard deviation ‬or medians according to their distribution in the study population. Results: A total of 231 patients were evaluated, the mean age was 49.5 ± 19.9 years, 56.7% were females. The most frequent pathological antecedents were hypertension 35.5%, diabetes 10,8%, dyslipidemia 10.4% and coronary disease 5.2%. Regarding pain features, in 40.3% of the patients the pain began abruptly, in 38.2% it had a precordial location, for 20% of the cases physical activity acted as a trigger, and 60.6% was oppressive. Costochondritis was the most common cause of chest pain among patients with an established etiologic diagnosis, representing the 18.2%. Conclusions: Although the clinical features of pain reported coincide with the clinical presentation of an acute coronary syndrome, the most common cause of chest pain in study population was costochondritis instead, indicating that it is a differential diagnostic in the approach of patients with pain acute chest.

Keywords: acute coronary syndrome, chest pain, epidemiology, osteochondritis

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Authors: Jamerson Felipe Pereira Lima, Jeane Cecília Bezerra de Melo

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The difficulty and cost related to obtaining of protein tertiary structure information through experimental methods, such as X-ray crystallography or NMR spectroscopy, helped raising the development of computational methods to do so. An approach used in these last is prediction of tridimensional structure based in the residue chain, however, this has been proved an NP-hard problem, due to the complexity of this process, explained by the Levinthal paradox. An alternative solution is the prediction of intermediary structures, such as the secondary structure of the protein. Artificial Intelligence methods, such as Bayesian statistics, artificial neural networks (ANN), support vector machines (SVM), among others, were used to predict protein secondary structure. Due to its good results, artificial neural networks have been used as a standard method to predict protein secondary structure. Recent published methods that use this technique, in general, achieved a Q3 accuracy between 75% and 83%, whereas the theoretical accuracy limit for protein prediction is 88%. Alternatively, to achieve better results, support vector machines prediction methods have been developed. The statistical evaluation of methods that use different AI techniques, such as ANNs and SVMs, for example, is not a trivial problem, since different training sets, validation techniques, as well as other variables can influence the behavior of a prediction method. In this study, we propose a prediction method based on artificial neural networks, which is then compared with a selected SVM method. The chosen SVM protein secondary structure prediction method is the one proposed by Huang in his work Extracting Physico chemical Features to Predict Protein Secondary Structure (2013). The developed ANN method has the same training and testing process that was used by Huang to validate his method, which comprises the use of the CB513 protein data set and three-fold cross-validation, so that the comparative analysis of the results can be made comparing directly the statistical results of each method.

Keywords: artificial neural networks, protein secondary structure, protein structure prediction, support vector machines

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Authors: Galal Omer, Onisimo Mutanga, Elfatih M. Abdel-Rahman, Elhadi Adam

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Threatened tree species (TTS) play a significant role in ecosystem functioning and services, land use dynamics, and other socio-economic aspects. Such aspects include ecological, economic, livelihood, security-based, and well-being benefits. The development of techniques for mapping and monitoring TTS is thus critical for understanding the functioning of ecosystems. The advent of advanced imaging systems and supervised learning algorithms has provided an opportunity to classify TTS over fragmenting landscape. Recently, vegetation maps have been produced using advanced imaging systems such as WorldView-2 (WV-2) and robust classification algorithms such as support vectors machines (SVM) and artificial neural network (ANN). However, delineation of TTS in a fragmenting landscape using high resolution imagery has widely remained elusive due to the complexity of the species structure and their distribution. Therefore, the objective of the current study was to examine the utility of the advanced WV-2 data for mapping TTS in the fragmenting Dukuduku indigenous forest of South Africa using SVM and ANN classification algorithms. The results showed the robustness of the two machine learning algorithms with an overall accuracy (OA) of 77.00% (total disagreement = 23.00%) for SVM and 75.00% (total disagreement = 25.00%) for ANN using all eight bands of WV-2 (8B). This study concludes that SVM and ANN classification algorithms with WV-2 8B have the potential to classify TTS in the Dukuduku indigenous forest. This study offers relatively accurate information that is important for forest managers to make informed decisions regarding management and conservation protocols of TTS.

Keywords: artificial neural network, threatened tree species, indigenous forest, support vector machines

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Authors: Jean-François Pouilly

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This study addresses the growing complexity of embedded systems and the critical need for secure, reliable software. Traditional cybersecurity testing methods, often conducted late in the development cycle, struggle to keep pace. This talk explores how formal methods, integrated with advanced analysis tools, empower C/C++ developers to 1) Proactively address vulnerabilities and bugs, which includes formal methods and abstract interpretation techniques to identify potential weaknesses early in the development process, reducing the reliance on penetration and fuzz testing in later stages. 2) Streamline development by focusing on bugs that matter, with close to no false positives and catching flaws earlier, the need for rework and retesting is minimized, leading to faster development cycles, improved efficiency and cost savings. 3) Enhance software dependability which includes combining static analysis using abstract interpretation with full context sensitivity, with hardware memory awareness allows for a more comprehensive understanding of potential vulnerabilities, leading to more dependable and secure software. This approach aligns with industry best practices (ISO2626 or ISO 21434) and empowers C/C++ developers to deliver robust, secure embedded systems that meet the demands of today's and tomorrow's applications. We will illustrate this approach with the TrustInSoft analyzer to show how it accelerates verification for complex cases, reduces user fatigue, and improves developer efficiency, cost-effectiveness, and software cybersecurity. In summary, integrating formal methods and sound Analyzers enhances software reliability and cybersecurity, streamlining development in an increasingly complex environment.

Keywords: safety, cybersecurity, ISO26262, ISO24434, formal methods

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Authors: Jasna Prester, Ivana Rašić Bakarić, Božidar Matijević

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Various prominent scholars and substantial practitioner-oriented literature on innovation orientation have shown positive effects on firm performance. There is a myriad of factors that influence and enhance innovation but it has been found in the literature that new product innovations accounted for an average of 14 percent of sales revenues for all firms. If there is one thing that has changed in innovation management during the last decade, it is the growing reliance on external partners. As a consequence, a new task for purchasing arises, as firms need to understand which suppliers actually do have high potential contributing to the innovativeness of the firm and which do not. Purchasing function in an organization is extremely important as it deals on an average of 50% or more of a firm's expenditures. In the nineties the purchasing department was largely seen as a transaction-oriented, clerical function but today purchasing integration provides a formal interface mechanism between purchasing and other firm functions that services other functions within the company. Purchasing function has to be organized differently to enable firm innovation potential. However, innovations are inherently risky. There are behavioral risk (that some partner will take advantage of the other party), technological risk in terms of complexity of products and processes of manufacturing and incoming materials and finally market risks, which in fact judge the value of the innovation. These risks are investigated in this work since it has been found in the literature that the higher the technological risk, higher will be the centralization of the purchasing function as an interface with other supply chain members. Most researches on organization of purchasing function were done by case study analysis of innovative firms. This work actually tends to prove or discard results found in the literature based on case study method. A large data set of 1493 companies, from 25 countries collected in the GMRG 4 survey served as a basis for analysis.

Keywords: purchasing function organization, innovation, technological risk, GMRG 4 survey

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Authors: Hazem Abd El Megeed, Mohamed El-Refaay, Norhan Magdi Osman

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Spectrum scarcity is a challenging obstacle in wireless communications systems. It hinders the introduction of innovative wireless services and technologies that require larger bandwidth comparing to legacy technologies. In addition, the current worldwide allocation of radio spectrum bands is already congested and can not afford additional squeezing or optimization to accommodate new wireless technologies. This challenge is a result of accumulative contributions from different factors that will be discussed later in this paper. One of these factors is the radio spectrum allocation policy governed by national regulatory authorities nowadays. The framework for this policy allocates specified portion of radio spectrum to a particular wireless service provider on exclusive utilization basis. This allocation is executed according to technical specification determined by the standard bodies of each Radio Access Technology (RAT). Dynamic access of spectrum is a framework for flexible utilization of radio spectrum resources. In this framework there is no exclusive allocation of radio spectrum and even the public safety agencies can share their spectrum bands according to a governing policy and service level agreements. In this paper, we explore different methods for accessing the spectrum dynamically and its associated implementation challenges.

Keywords: licensed shared access, cognitive radio, spectrum sharing, spectrum congestion, dynamic spectrum access, spectrum database, spectrum trading, reconfigurable radio systems, opportunistic spectrum allocation (OSA)

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Authors: Jun Hong Lee

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Background: Many dementia patients complain insomnia and depressive mood, and hypnotics and antidepressants are being prescribed. As prevalence of dementia is increasing, insomnia and depressive mood are becoming more important. Objective: We evaluated insomnia and depression in outpatients of dementia center. Patients and Methods/Material and Methods: We reviewed medical records of the patients who visited outpatients clinic of NHIS Ilsan Hospital Dementia Center during 2016. Results: Total 716 patients are included; Subjective Memory Impairment (SMI) : 143 patients (20%), non-amnestic Mild Cognitive Impairment (MCI): single domain 70 (10%), multiple domain 34 (5%), amnestic MCI: single domain 74 (10%), multiple domain 159 (22%), Early onset Alzheimer´s disease (AD): 9 (1%), AD 121 (17%), Vascular dementia: 62 (9%), Mixed dementia 44 (6%). Hypnotics and antidepressants are prescribed as follows; SMI : hypnotics 14 patients (10%), antidepressants 27 (19%), non-amnestic MCI: single domain hypnotics 9 (13%), antidepressants 12 (17%), multiple domain hypnotics 4 (12%), antidepressants 6 (18%), amnestic MCI: single domain hypnotics 10 (14%), antidepressants 16 (22%), multiple domain hypnotics 22 (14%), antidepressants 24 (15%), Early onset Alzheimer´s disease (AD): hypnotics 1 (11%), antidepressants 2 (22%), AD: hypnotics 10 (8%), antidepressants 36 (30%), Vascular dementia: hypnotics 8 (13%), antidepressants 20 (32%), Mixed dementia: hypnotics 4 (9%), antidepressants 17 (39%). Conclusion: Among the outpatients of Dementia Center, MCI and SMI are majorities, and the number of MCI patients are almost half. Depression is more prevalent in AD, and Vascular dementia than MCI and SMI, and about 22% of patients are being prescribed by antidepressants and 11% by hypnotics.

Keywords: insomnia, depression, dementia, antidepressants, hypnotics

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Authors: Yehjune Heo

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As biometric systems become widely deployed, the security of identification systems can be easily attacked by various spoof materials. This paper contributes to finding a reliable and practical anti-spoofing method using Convolutional Neural Networks (CNNs) based on the types of loss functions and optimizers. The types of CNNs used in this paper include AlexNet, VGGNet, and ResNet. By using various loss functions including Cross-Entropy, Center Loss, Cosine Proximity, and Hinge Loss, and various loss optimizers which include Adam, SGD, RMSProp, Adadelta, Adagrad, and Nadam, we obtained significant performance changes. We realize that choosing the correct loss function for each model is crucial since different loss functions lead to different errors on the same evaluation. By using a subset of the Livdet 2017 database, we validate our approach to compare the generalization power. It is important to note that we use a subset of LiveDet and the database is the same across all training and testing for each model. This way, we can compare the performance, in terms of generalization, for the unseen data across all different models. The best CNN (AlexNet) with the appropriate loss function and optimizers result in more than 3% of performance gain over the other CNN models with the default loss function and optimizer. In addition to the highest generalization performance, this paper also contains the models with high accuracy associated with parameters and mean average error rates to find the model that consumes the least memory and computation time for training and testing. Although AlexNet has less complexity over other CNN models, it is proven to be very efficient. For practical anti-spoofing systems, the deployed version should use a small amount of memory and should run very fast with high anti-spoofing performance. For our deployed version on smartphones, additional processing steps, such as quantization and pruning algorithms, have been applied in our final model.

Keywords: anti-spoofing, CNN, fingerprint recognition, loss function, optimizer

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Authors: Tamara Díaz-Chang, Elizabeth-H Arredondo

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This article presents the results of mixed approach research, where the ocular movements of students are examined while they solve questionnaires related to some abstract mathematical concepts. The objective of this research is to determine possible correlations between the parameters of ocular activity and the level of difficulty of the tasks. The difficulty level categories were established based on two types of criteria: a subjective one, through an evaluation, carried out by the subjects, and a behavioral one, related to obtaining the correct solution. Correlations of these criteria with ocular activity parameters, which were considered indicators of mental effort, were identified. The analysis of the data obtained allowed us to observe discrepancies in the categorization of difficulty levels based on subjective and behavioral criteria. There was a negative correlation of the eye movement parameters with the students' opinions on the level of difficulty of the questions, while a strong positive and significant correlation was noted between most of the parameters of ocular activity and the level of difficulty, determined by the percentage of correct answers. The results obtained by the analysis of the data suggest that eye movement parameters can be taken as indicators of the difficulty level of the tasks related to the study of some abstract mathematical concepts at the university.

Keywords: abstract mathematical concepts, cognitive neuroscience, eye-tracking, university education

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Authors: Hind Bouami

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Handling life-critical systems complexity requires to be equipped with appropriate technology and the right human agents’ functions such as knowledge, experience, and competence in problem’s prevention and solving. Human agents are involved in the management and control of human-machine system’s performance. Documenting human agent’s situation awareness is crucial to support human-machine designers’ decision-making. Knowledge about risks, critical parameters and factors that can impact and threaten automation system’s performance should be collected using preventive and retrospective approaches. This paper aims to document operators’ situation awareness through the analysis of automated organizations’ feedback. The analysis of automated hospital pharmacies feedbacks helps to identify and control critical parameters influencing human machine interaction in order to enhance system’s performance and security. Our human machine system evaluation approach has been deployed in Macon hospital center’s pharmacy which is equipped with automated drug dispensing systems since 2015. Automation’s specifications are related to technical aspects, human-machine interaction, and human aspects. The evaluation of drug delivery automation performance in Macon hospital center has shown that the performance of the automated activity depends on the performance of the automated solution chosen, and also on the control of systemic factors. In fact, 80.95% of automation specification related to the chosen Sinteco’s automated solution is met. The performance of the chosen automated solution is involved in 28.38% of automation specifications performance in Macon hospital center. The remaining systemic parameters involved in automation specifications performance need to be controlled.

Keywords: life-critical systems, situation awareness, human-machine interaction, decision-making

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Authors: Hsiao-Wen Tsai

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Motor vehicle accident is the first cause of head injury in the world; severe head injury cases may cause conscious disturbance and death. This is a report about a case of a young adult patient suffering from motor vehicle accident leading to severe head injury who passed through three time surgical procedures, and his mother (who is the informal caregiver). This case was followed from 28th January to 15th February 2011 by using Gordon’s 11 functional health patterns. Patient’s cognitive-perceptual and self-perception-self-concept patterns were altered. Anxiety was also noted on his informal caregiver due to patients’ condition. During the intensive care period, maintaining patient’s vital signs and cerebral perfusion pressure were essential to avoid secondary neuronal injury. Multi-sensory stimulation, caring accompanying, supporting, listening and encouraging patient’s family involved in patient care were very important to reduce informal caregiver anxiety. Finally, the patient consciousness improved from GCS 4 to GCS 11 before discharging from ICU. Patient’s primary informal caregiver, his mother, also showed anxiety improvement. This is was successful case with traumatic brain injury recovered from coma.

Keywords: anxiety, multi-sensory stimulation, reduce intracranial adaptive capacity, traumatic brain injury

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Authors: Rochelle Elva

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Faculty in Higher Education today are faced with the challenge of convincing their students of the importance of learning and mastery of skills. This is because most students often have a single motivation -to get high grades. If it appears that this goal will not be met, they lose their motivation, and their academic efforts wane. This is true even for students in the competitive fields of STEM, including Computer Science majors. As educators, we have to understand our students and leverage what motivates them to achieve our learning outcomes. This paper presents a case study that utilizes cognitive psychology’s Expectancy Value Theory and Motivation Theory to investigate the effect of sustained expectancy for success on students’ learning outcomes. In our case study, we explore how students’ motivation and persistence in their academic efforts are impacted by providing them with an unexpected possible path to success that continues to the end of the semester. The approach was tested in an undergraduate computer science course with n = 56. The results of the study indicate that when presented with the real possibility of success, despite existing low grades, both low and high-scoring students persisted in their efforts to improve their performance. Their final grades were, on average, one place higher on the +/-letter grade scale, with some students scoring as high as three places above their predicted grade.

Keywords: expectancy for success and persistence, motivation and performance, computer science education, motivation and performance in computer science

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Authors: Dana Hisham Mohamed Abdrabo

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The paper examines the effect of Drama works on the Egyptian public opinion regarding the religion of Judaism, Israel as a state and the Jew's image to Egyptian Muslims. The paper examines the role of Media and in particular, Dramas on achieving interreligious dialogue between Judaism and Islam and its role in making peace between the Egyptian Muslims -and Arabs in general- on the one hand, and the Jew on the other hand, and the implications of this on the relationship between Arab countries and Israel as a state. The research uses the Survey method with Egyptian Muslims as a main sample for the research to examine such effect. Dramas have a role in presenting the Jew, Judaism, and Israel as a state and as a political system in various ways. The paper is related to multidisciplinary fields; it is related to political sciences, political sociology, communication, social change, and cognitive sociology fields. The research adds a new analytical study for a new tool for the peacemaking process in the Middle East region through adopting an interdisciplinary approach which is needed in the studies aim to achieve stability and peace in the Middle East region and its neighboring countries.

Keywords: dramas tool, Egyptian public opinion, interreligious dialogue, Israel & Egyptian relations , Judaism

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Authors: Xingyu Gao, Qiang Wu

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Patents play a crucial role in protecting innovation and intellectual property. Early prediction of the impact of artificial intelligence (AI) patents helps researchers and companies allocate resources and make better decisions. Understanding the key factors that influence patent impact can assist researchers in gaining a better understanding of the evolution of AI technology and innovation trends. Therefore, identifying highly impactful patents early and providing support for them holds immeasurable value in accelerating technological progress, reducing research and development costs, and mitigating market positioning risks. Despite the extensive research on AI patents, accurately predicting their early impact remains a challenge. Traditional methods often consider only single factors or simple combinations, failing to comprehensively and accurately reflect the actual impact of patents. This paper utilized the artificial intelligence patent database from the United States Patent and Trademark Office and the Len.org patent retrieval platform to obtain specific information on 35,708 AI patents. Using six machine learning models, namely Multiple Linear Regression, Random Forest Regression, XGBoost Regression, LightGBM Regression, Support Vector Machine Regression, and K-Nearest Neighbors Regression, and using early indicators of patents as features, the paper comprehensively predicted the impact of patents from three aspects: technical, social, and economic. These aspects include the technical leadership of patents, the number of citations they receive, and their shared value. The SHAP (Shapley Additive exPlanations) metric was used to explain the predictions of the best model, quantifying the contribution of each feature to the model's predictions. The experimental results on the AI patent dataset indicate that, for all three target variables, LightGBM regression shows the best predictive performance. Specifically, patent novelty has the greatest impact on predicting the technical impact of patents and has a positive effect. Additionally, the number of owners, the number of backward citations, and the number of independent claims are all crucial and have a positive influence on predicting technical impact. In predicting the social impact of patents, the number of applicants is considered the most critical input variable, but it has a negative impact on social impact. At the same time, the number of independent claims, the number of owners, and the number of backward citations are also important predictive factors, and they have a positive effect on social impact. For predicting the economic impact of patents, the number of independent claims is considered the most important factor and has a positive impact on economic impact. The number of owners, the number of sibling countries or regions, and the size of the extended patent family also have a positive influence on economic impact. The study primarily relies on data from the United States Patent and Trademark Office for artificial intelligence patents. Future research could consider more comprehensive data sources, including artificial intelligence patent data, from a global perspective. While the study takes into account various factors, there may still be other important features not considered. In the future, factors such as patent implementation and market applications may be considered as they could have an impact on the influence of patents.

Keywords: patent influence, interpretable machine learning, predictive models, SHAP

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Authors: Hani Mustafa, Cristina Gonzalez Ruiz, Estelle Bech

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The growing influence of digital technologies has made learning and interaction more accessible, resulting in effective collaboration if properly managed. Technology enabled learning has become an important conduit for learning, including collaborative learning. The use of wiki technology, for example, has opened a new learning platform that enables the integration of social, linguistic, and cognitive processes of language learning. It encourages students to collaborate in the construction, analysis, and understanding of knowledge. But to what extent is the use of wikis effective in promoting collaborative learning among students. In addition, how do students perceive this technology in enhancing their language learning? In this study, students were be given a wiki project to complete collaboratively with their group members. Students had to write collaboratively to produce and present a seven-day travel plan in which they had to describe places to visit and things to do to explore the best historical and cultural aspects of the country. The study involves students learning French, Malay, and Spanish as a foreign language. In completing this wiki project, students will move from passive learning of language to real engagement with classmates, requiring them to collaborate and negotiate effectively with one another. The objective of the study is to ascertain to what extent does wiki technology helped in promoting collaborative learning and improving language skills from students’ perception. It is found that while there was improvement in students language skills, the overall experience was less positive due to unfamiliarity with a new learning tool.

Keywords: collaborative learning, foreign language, wiki, teaching

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Authors: Tarik Sipahi

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Photonics research continues to push the boundaries of optical science, and the development of metasurface technology has emerged as a transformative force in this domain. The work presents the intricacies of a unified metasurface design tailored for efficient polarization and color control in optical systems. The proposed unified metasurface serves as a singular, nanoengineered optical element capable of simultaneous polarization modulation and color encoding. Leveraging principles from metamaterials and nanophotonics, this design allows for unprecedented control over the behavior of light at the subwavelength scale. The metasurface's spatially varying architecture enables seamless manipulation of both polarization states and color wavelengths, paving the way for a paradigm shift in optical system design. The advantages of this unified metasurface are diverse and impactful. By consolidating functions that traditionally require multiple optical components, the design streamlines optical systems, reducing complexity and enhancing overall efficiency. This approach is particularly promising for applications where compactness, weight considerations, and multifunctionality are crucial. Furthermore, the proposed unified metasurface design not only enhances multifunctionality but also addresses key challenges in optical system design, offering a versatile solution for applications demanding compactness and lightweight structures. The metasurface's capability to simultaneously manipulate polarization and color opens new possibilities in diverse technological fields. The research contributes to the evolution of optical science by showcasing the transformative potential of metasurface technology, emphasizing its role in reshaping the landscape of optical system architectures. This work represents a significant step forward in the ongoing pursuit of pushing the boundaries of photonics, providing a foundation for future innovations in compact and efficient optical devices.

Keywords: metasurface, nanophotonics, optical system design, polarization control

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Authors: Hector Jose Velazquez-Gonzalez, Norma Maldonado-Santiago, Laura Pietri-Gomez

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Cancer is one of the first cause of death in the world, most of them are women. In Puerto Rico, there is a permanent controversy on the conceptuation of what really involves a disability, also in when a chronic illness, like cancer, should be considered a disability. The aim of the research was to identify functional limitation in 50 women survivors of cancer. In turn, to know the meanings that 6 women attributed to cancer with a focus on functionality. We conducted a mix method research based on surveys and narratives. We administered the World Health Organization Disability Assessment, version 2.0, which obtained a Cronbach’s alpha of .949 on the general scale, and from .773 to .956 on the six domains. The domain that obtained the highest average was social participation (M= 33.89, SD= 20.434), but it was not significant in the disability percentage. Also, there was no significance in the disability percentage in the other five domains. In a matter of meanings, we conduct a semistructured interview to 6 participants. All of them do not refer to cancer as a disability, either they do not know that in Puerto Rico cancer is considered as a disability by the law. However, participants agree that cancer at the time of treatment and subsequent to it, has significant effects on functional limitations (fatigue, pain, cognitive limitations, and weakness, among others. Psychooncologic practice should encourage the constant assessment of the functionality to identify the needs that emerge from oncological diagnosis. So that psychosocial intervention could be considered as critical in cancer treatment to promote a better quality of life and well-being in a person with cancer.

Keywords: cancer, Puerto Rico, disability, psychosocial approach

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Authors: Pinhas Dannon, Aviv Weinstein

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Impulsivity is raising major interest clinically because it is associated with various clinical conditions such as delinquency, antisocial behavior, suicide attempts, aggression, and criminal activity. The evolutionary perspective argued that impulsivity relates to self-regulation and it has predicted that female individuals should have evolved a greater ability to inhibit pre-potent responses. There is supportive evidence showing that female individuals have better performance on cognitive tasks measuring impulsivity such as delay in gratification and delayed discounting mainly in childhood. During adolescence, brain imaging studies using diffusion tensor imaging on white matter architecture indicated contrary to the evolutionary perspective hypothesis, that young adolescent male individuals may be less vulnerable than age-matched female individuals to risk- and reward- related maladaptive behaviors. In adults, the results are mixed presumably owing to hormonal effects on neuro-biological mechanisms of reward. Consequently, female individuals were less impulsive than male individuals only during fertile stages of the menstrual cycle. Finally, there is evidence the serotonin (5-HT) system is more involved in the impulsivity of men than in that of women. Overall, there seem to be sex differences in impulsivity but these differences are more pronounced in childhood and they are later subject to maturational and hormonal changes during adolescence and adulthood and their effects on the brain, cognition, and behavior.

Keywords: impulse control, male population, female population, gender differences, reward, neurocognitive tests

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Authors: Olusegun Akinsiku, Olukayode Oyediran, Koleola Odusami

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A construction project is usually made up of a variety of stakeholders whose interests may positively or negatively impact on the outcome of the project execution. The variability of project stakeholders is apparent in their cultural differences, professional background and ethics, and differences in ideas. The need for the effectiveness of construction teams has been investigated as this is an important aspect to meeting client’s expectations in the construction industry. This study adopts a cross-sectional descriptive survey with the purpose of identifying the critical success factors (CSFs) associated with the team effectiveness of construction projects stakeholders, their relationship and the effects on construction project performance. The instrument for data collection was a designed questionnaire which was administered to construction professionals in the construction industry in Lagos State, Nigeria using proportionate stratified sampling. The highest ranked identified CSFs include “team trust”, “esprit de corps among members” and “team cohesiveness”. Using factor analysis and considering the effects of team cohesiveness on project performance, the identified CSFs were categorized into three groups namely cognitive attributes, behavior and processes attributes and affective attributes. All the three groups were observed to have a strong correlation with project performance. The findings of this study are useful in helping construction stakeholders benchmark the team effectiveness factors that will guarantee project success.

Keywords: construction, critical success factors, performance, stakeholders, team effectiveness

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Authors: Mounir Kehal, Adel Al Araifi

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The post-globalisation epoch has placed businesses everywhere in new and different competitive situations where knowledgeable, effective and efficient behaviour has come to provide the competitive and comparative edge. Enterprises have turned to explicit- and even conceptualising on tacit- Knowledge Management to elaborate a systematic approach to develop and sustain the Intellectual Capital needed to succeed. To be able to do that, you have to be able to visualize your organization as consisting of nothing but knowledge and knowledge flows, whilst being presented in a graphical and visual framework, referred to as automated organizational cartography. Hence, creating the ability of further actively classifying existing organizational content evolving from and within data feeds, in an algorithmic manner, potentially giving insightful schemes and dynamics by which organizational know-how is visualised. It is discussed and elaborated on most recent and applicable definitions and classifications of knowledge management, representing a wide range of views from mechanistic (systematic, data driven) to a more socially (psychologically, cognitive/metadata driven) orientated. More elaborate continuum models, for knowledge acquisition and reasoning purposes, are being used for effectively representing the domain of information that an end user may contain in their decision making process for utilization of available organizational intellectual resources (i.e. Autocart). In this paper we present likewise an empirical research study conducted previously to try and explore knowledge diffusion in a specialist knowledge domain.

Keywords: knowledge management, knowledge maps, knowledge diffusion, organizational cartography

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Authors: Thomas Wimmer, Bernhard Weigand

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The improvement of gas turbine efficiency is one of the main drivers of research and development in the gas turbine market. This has led to elevated gas turbine inlet temperatures beyond the melting point of the utilized materials. The turbine parts need to be actively cooled in order to withstand these harsh environments. However, the usage of compressor air as coolant decreases the overall gas turbine efficiency. Thus, coolant consumption needs to be minimized in order to gain the maximum advantage from higher turbine inlet temperatures. Therefore, sophisticated cooling designs for gas turbine parts aim to minimize coolant mass flow. New design space is accessible as additive manufacturing is maturing to industrial usage for the creation of hot gas flow path parts. By making use of this technology more efficient cooling schemes can be manufacture. In order to find such cooling schemes a generative design method is being developed. It generates cooling schemes randomly which adhere to a set of rules. These assure the sanity of the design. A huge amount of different cooling schemes are generated and implemented in a simulation environment where it is validated. Criteria for the fitness of the cooling schemes are coolant mass flow, maximum temperature and temperature gradients. This way the whole design space is sampled and a Pareto optimum front can be identified. This approach is applied to a flat plate, which resembles a simplified section of a hot gas flow path part. Realistic boundary conditions are applied and thermal barrier coating is accounted for in the simulation environment. The resulting cooling schemes are presented and compared to representative conventional cooling schemes. Further development of this method can give access to cooling schemes with an even better performance having higher complexity, which makes use of the available design space.

Keywords: additive manufacturing, cooling, gas turbine, heat transfer, heat transfer design, optimization

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Authors: Graham Wood

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The 20th Century saw the introduction of many new approaches to music making, including the structured and academic study of jazz improvisation. The rise of many school and tertiary jazz programs was rapid and quickly spread around the globe in a matter of decades. It could be said that the curriculum taught in these new programs was often developed in an ad-hoc manner due to the lack of written literature in this new and rapidly expanding area and the vastly different pedagogical principles when compared to classical music education that was prevalent in school and tertiary programs. There is widespread information regarding the theory and techniques used by jazz improvisers, but methods to practice these concepts in order to achieve the best outcomes for students and teachers is much harder to find. This research project explores the authors’ experiences as a studio jazz piano teacher, ensemble teacher and classroom improvisation lecturer over fifteen years and suggests an alignment with Bloom’s taxonomy of learning domains. This alignment categorizes the different tasks that need to be taught and practiced in order for the teacher and the student to devise a well balanced and effective practice routine and for the teacher to develop an effective teaching program. These techniques have been very useful to the teacher and the student to ensure that a good balance of cognitive, psychomotor and affective skills are taught to the students in a range of learning contexts.

Keywords: bloom, education, jazz, learning, music, teaching

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Authors: Elisabeth Pedersen

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Representations and interpretations of womanhood and female sexualities bring forth various questions regarding gender norms, and the implications of these norms, which are permeating and repetitive within various societies. Literature is one form of media which provides the space to represent and interpret women, their bodies, and sexualities, and also reveals the power of language as an affective and affected force. As literature allows an opportunity to explore history and the representations of gender, power dynamics, and sexuality through historical contexts, this paper uses engaged theory through a comparative analysis of two work of literature, The Duchess of Malfi by John Wester, and The Sound and the Fury by William Faulkner. These novels span across space and time, which lends to the theory that repetitive tropes of womanhood and female sexuality in literature are influenced by and have an influence on the hegemonic social order throughout history. It analyzes how the representation of the dichotomy of male chivalry and honor, and female purity are disputed and questioned when a woman is portrayed as sexually emancipated, and explores the historical context in which these works were written to examine how socioeconomic events challenged the hegemonic social order. The analysis looks at how stereotypical ideals of womanhood and manhood have damaging implications on women, as the structure of society provides more privilege and power to men than to women, thus creating a double standard for men and women in regards to sexuality, sexual expression, and rights to sexual desire. This comparative analysis reveals how strict gender norms are permeating and have negative consequences. However, re-reading stories through a critical lens can provide an opportunity to challenge the repetitive tropes of female sexuality, and thus lead to the embrace of the complexity of female sexuality and expression.

Keywords: femininity, literature, representation, sexuality

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Authors: Igbozuruike Chigozie Jude, Agwu Agwu Ejem

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This study investigated that advertisement has an impact on audience retention on YouTube Comedy skits, which is the most watched content on YouTube in Lagos, Nigeria. The main objective was to determine if the advertisements affect the average number of times they spend watching YouTube comedy skits. The study was anchored on Festinger's (1952) cognitive dissonance theory. The research method for this exercise was a survey to get responses from people in Lagos state on how they react to the advertisements they face when watching YouTube comedy skits in Lagos state. The sample size derived from the Krejcie and Morgan (1970) Table was 384 YouTube users. The instrument that was used to gather data was a questionnaire. The findings showed that the adverts have far-reaching exposure by the target audience, but most of the audience perceived them to be intrusive. It was also found that there is not enough evidence to infer that advertisement is indeed impacting audience retention on YouTube comedy skits in Lagos, Nigeria. The reason is that, for a majority of the audience, adverts do not essentially affect their retention on those skits, but for a considerable percentage (34%), these adverts do break their concentration and affect how much time they end up spending on the YouTube comedy skits. It was recommended that, among others, there should be regular monitoring and adaptation of YouTube advertisements to the audience preferences and behaviors of the audience. Insights on changes or trends in audience preferences can be gained through surveys.

Keywords: advertisement, audience, YouTube, comedy skits, Lagos Nigeria

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Authors: Pascal Mwenge, Tumisang Seodigeng

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The combination of world population and the third industrial revolution led to high demand for fuels. On the other hand, the decrease of global fossil 8fuels deposits and the environmental air pollution caused by these fuels has compounded the challenges the world faces due to its need for energy. Therefore, new forms of environmentally friendly and renewable fuels such as biodiesel are needed. The primary analytical techniques for methanolysis yield monitoring have been chromatography and spectroscopy, these methods have been proven reliable but are more demanding, costly and do not provide real-time monitoring. In this work, the in situ monitoring of biodiesel from sunflower oil using FTIR (Fourier Transform Infrared) has been studied; the study was performed using EasyMax Mettler Toledo reactor equipped with a DiComp (Diamond) probe. The quantitative monitoring of methanolysis was performed by building a quantitative model with multivariate calibration using iC Quant module from iC IR 7.0 software. 15 samples of known concentrations were used for the modelling which were taken in duplicate for model calibration and cross-validation, data were pre-processed using mean centering and variance scale, spectrum math square root and solvent subtraction. These pre-processing methods improved the performance indexes from 7.98 to 0.0096, 11.2 to 3.41, 6.32 to 2.72, 0.9416 to 0.9999, RMSEC, RMSECV, RMSEP and R2Cum, respectively. The R² value of 1 (training), 0.9918 (test), 0.9946 (cross-validation) indicated the fitness of the model built. The model was tested against univariate model; small discrepancies were observed at low concentration due to unmodelled intermediates but were quite close at concentrations above 18%. The software eliminated the complexity of the Partial Least Square (PLS) chemometrics. It was concluded that the model obtained could be used to monitor methanol of sunflower oil at industrial and lab scale.

Keywords: biodiesel, calibration, chemometrics, methanolysis, multivariate analysis, transesterification, FTIR

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Authors: Ruoya Huang, Ruoxian Huang, Edgar Huang

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Based on a convenience sample of 2,092 participants from across all 50 states of the United States, a survey was conducted to explore Americans’ mask-wearing behaviors during COVID-19 according to their political convictions, religious beliefs, and ethnic cultures from late July to early September, 2020. The purpose of the study is to provide evidential support for government policymaking so as to drive up more effective public policies by taking into consideration the variance in these social factors. It was found that the respondents’ party affiliation or preference, religious belief, and ethnicity, in addition to their health condition, gender, level of concern of contracting COVID-19, all affected their mask-wearing habits both in March, the initial coronavirus outbreak stage, and in August, when mask-wearing had been made mandatory by state governments. The study concludes that pandemic awareness campaigns must be run among all citizens, especially among African Americans, Muslims, and Republicans, who have the lowest rates of wearing masks, in order to protect themselves and others. It is recommended that complementary cognitive bias awareness programs should be implemented in non-Black and non-Muslim communities to eliminate social concerns that deter them from wearing masks.

Keywords: COVID-19 pandemic, ethnicity, mask-wearing, policymaking implications, political affiliations, religious beliefs, United States

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Authors: Nurwati Djaman, Suradi Tahmir, Nurdin Arsyad

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The major objective of this study was to implement and evaluate the use of the implementation of social responsibility with the approach of Indonesian Realistic Mathematics Education (PMRI) in teaching and learning mathematics on students’ engagement and learning. The research problems investigated in this research: 1) What were the effects of the implementation of social responsibility with PMRI approach to learning mathematics? 2) What were the effects of the approach to students’ engagement? An action research and grounded theory methodology were adopted for the study. This study used mixed methods to collect, describe, and interpret the data. The data were collected through focus group discussion, classroom observations, questionnaire, interview, and students’ work. The participants in this study consisted of 45 students. The study revealed that the approach has given students the opportunity to develop their understanding of concepts and procedures, problem-solving ability, and communication ability. Also, students’ involvement in the approach improved their engagement in learning mathematics in the three domains of cognitive engagement, effective engagement, and behavioral engagement. In particular, the data collection from the focus group, classroom observations, and interviews suggest that, during this study, the students became more active participants in the mathematics lessons.

Keywords: Indonesian Realistic Mathematics Education, PMRI, learning mathematics, social responsibility, students' engagement

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Authors: Fatmah Almathkour

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Managing and controlling the construction supply chain (CSC) are very important components of effective construction project execution. The goals of managing the CSC are to reduce uncertainty and optimize the performance of a construction project by improving efficiency and reducing project costs. The heart of much SC activity is addressing risk, and the CSC is no different. The delivery and consumption of construction materials is highly variable due to the complexity of construction operations, rapidly changing demand for certain components, lead time variability from suppliers, transportation time variability, and disruptions at the job site. Current notions of managing and controlling CSC, involve focusing on one project at a time with a push-based material ordering system based on the initial construction schedule and, then, holding a tremendous amount of inventory. A two-stage methodology was proposed to coordinate the feed-forward control of advanced order placement with a supplier to a feedback local control in the form of adding the ability to transship materials between projects to improve efficiency and reduce costs. It focused on the single supplier integrated production and transshipment problem with multiple products. The methodology is used as a design tool for the CSC because it includes an external storage site not associated with one of the projects. The idea is to add this feature to a highly constrained environment to explore its effectiveness in buffering the impact of variability and maintaining project schedule at low cost. The methodology uses deterministic optimization models with objectives that minimizing the total cost of the CSC. To illustrate how this methodology can be used in practice and the types of information that can be gleaned, it is tested on a number of cases based on the real example of multiple construction projects in Kuwait.

Keywords: construction supply chain, inventory control supply chain, transshipment

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Authors: Sean Gay, Cristina Tat

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This presentation will detail how a university in Western Japan has implemented its English for Academic Purposes (EAP) program during the onset of CoViD-19 in the spring semester of 2020. In the spring semester of 2020, after a 2 week delay, all courses within the School of Policy Studies EAP Program at Kwansei Gakuin University were offered in an online asynchronous format. The rationale for this decision was not to disadvantage students who might not have access to devices necessary for taking part in synchronous online lessons. The course coordinators were tasked with consolidating the materials originally designed for face-to-face14 week courses for a 12 week asynchronous online semester and with uploading the modified course materials to Luna, the university’s network, which is a modified version of Blackboard. Based on research to determine the social and academic impacts of this CoViD-19 ERT approach on the students who took part in this EAP program, this presentation explains how future curriculum design and implementation can be managed in a post-CoViD world. There are a wide variety of lessons that were salient. The role of the classroom as a social institution was very prominent; however, awareness of cognitive burdens and strategies to mitigate that burden may be more valuable for teachers. The lessons learned during this period of ERT can help teachers moving forward.

Keywords: asynchronous online learning, emergency remote teaching (ERT), online curriculum design, synchronous online learning

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Authors: Samson Ehindero, Oluwole Akinola

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Substantial evidence has shown an association between type 2 diabetes (T2D) and cognitive decline, Trans Cinnamaldehyde (TCA) has been shown to have many potent pharmacological properties. In this present study, we are currently investigating the effects of TCA on type II diabetes-induced neurodegeneration. Neurodegeneration was induced in forty (40) adult wistar rats using high fat diet (HFD) for 4 months followed by low dose of streptozotocin (STZ) (40 mg/kg, i.p.) administration. TCA was administered orally for 30 days at the doses of 40mg/kg and 60mg/kg body weight. Animals were randomized and divided into following groups; A- control group, B- diabetic group, C- TCA (high dose), D- diabetic + TCA (high dose), E- diabetic + TCA (high dose) with high fat diet, F- TCA Low dose, G- diabetic + TCA (low dose) and H- diabetic + TCA (low dose) with high fat diet. Animals were subjected to behavioral tests followed by histological studies of the hippocampus. Demented rats showed impaired behavior in Y- Maze test compared to treated and control groups. Trans Cinnamaldehyde restores the histo architecture of the hippocampus of demented rats. This present study demonstrates that treatment with trans- cinnamaldehyde improves behavioral deficits, restores cellular histo architecture in rat models of neurodegeneration.

Keywords: neurodegeneration, trans cinnamaldehyde, high fat diet, streptozotocin

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