Accurate and reliable prediction of Perfobond Rib Shear Strength Connector is considered as a major issue in the structural engineering sector. Besides, selecting the most significant variables that have a major influence on PRSC in every important step for attaining economic and more accurate predictive models, this study investigates the capacity of deep learning neural network for shear strength prediction of PRSC. The proposed DLNN model is validated against support vector regression, artificial neural network, and M5 tree model. In the (...) second scenario, a comparable AI model hybridized with genetic algorithm as a robust bioinspired optimization approach for optimizing the related predictors for the PRSC is proposed. Hybridizing AI models with GA as a selector tool is an attempt to acquire the best accuracy of predictions with the fewest possible related parameters. In accordance with quantitative analysis, it can be observed that the GA-DLNN models required only 7 input parameters and yielded the best prediction accuracy with highest correlation coefficient and lowest value root mean square error. However, the other comparable models such as GA-M5Tree, GA-ANN, and GA-SVR required 10 input parameters to obtain a relatively acceptable level of accuracy. Employing GA as a feature parameter selection technique improves the precision of almost all hybrid models by optimally removing redundant variables which decrease the efficiency of the model. (shrink)

The efficiency of distribution networks is hugely affected by active and reactive power flows in distribution electric power systems. Currently, distributed generators (DGs) of energy are extensively applied to minimize power loss and improve voltage deviancies on power distribution systems. The best position and volume of DGs produce better power outcomes. This work prepares a new hybrid SSA–GWO metaheuristic optimization algorithm that combines the salp swarm algorithm (SSA) and the gray wolf optimizer (GWO) algorithm. The SSA–GWO algorithm ensures generating the (...) best size and site of one and multi-DGs on the radial distribution network to decrease real power losses (RPL) (kW) on lines and resolve voltage deviancies. Our novel algorithm is executed on IEEE 123-bus radial distribution test systems. The results confirm the success of the suggested hybrid SSA–GWO algorithm compared with implementing the SSA and GWO individually. Through the proposed SSA–GWO algorithm, the study decreases the RPL and improves the voltage profile on distribution networks with multiple DGs units. (shrink)

This study elucidates the nursing of undernourished patients as experienced by eight registered clinical nurses and five nursing assistants by using content analysis. The participants' narratives describe the inner perspective of caring for undernourished patients, known in Sweden as `the thin ones'. Categories identified were: frustration in nursing, joy in nursing and that undernourishment is taboo. The taboo was narrated as feelings of guilt and shame. Frustration in nursing could be seen as feeling stressed, exposed, lonely, powerless, helpless, and being (...) torn between demands and needs. Joy in nursing was experienced when creating a trusting relationship, promoting pleasure in the meal situation and working with respect for each individual's life-style and context of life. Understanding staff members' views is important when implementing guidelines as well as in the teaching situation in order to identify where staff stand with regard to knowledge and attitudes. (shrink)

In this article, we propose an initial formal model of computationalism based on mathematical relations between cognition and computation. More specifically, based on a set of cognitive constituents as a domain, and a set of computational implementations as a range, we define two relations of transformation over these sets. Moreover, we define the principles of implementability, describability, and phenomena correspondence, and we conjecture that full computationalism does not hold since these principles are not fulfilled. Particularly, many cognitively-tied phenomena fail to (...) respect the describability principle which is necessary for representing a cognitive state by a computational state. (shrink)

Abstract:This article explores the representation of human‒animal interaction in D. H. Lawrence's poems "Bat" and "Man and Bat." Many influential critics interpret the poems as emphasizing the lack of connection, hospitality, and empathy between the poet and the bats, focusing on the relentless objectification of the animals and the poet's negative attitude towards them. We argue, however, that these poems can also invite different types of readings, by investigating the ways in which Lawrence employs perceptual and kinetic imagery to create (...) a certain degree of embodied, kinesthetic empathy with the bats. Using theoretical and methodological frameworks from cognitive-literary approaches to kinesthesia and human‒animal studies, we analyze Lawrence's multilayered poetic rendition of human‒animal interaction, to understand how the poet stages the tension between the symbolic/cultural connotations associated with bats and humans' perception of their embodied, affective, and kinetic being. (shrink)

With the rapid growth of informatics systems’ technology in this modern age, the Internet of Things (IoT) has become more valuable and vital to everyday life in many ways. IoT applications are now more popular than they used to be due to the availability of many gadgets that work as IoT enablers, including smartwatches, smartphones, security cameras, and smart sensors. However, the insecure nature of IoT devices has led to several difficulties, one of which is distributed denial-of-service (DDoS) attacks. IoT (...) systems have several security limitations due to their disreputability characteristics, like dynamic communication between IoT devices. The dynamic communications resulted from the limited resources of these devices, such as their data storage and processing units. Recently, many attempts have been made to develop intelligent models to protect IoT networks against DDoS attacks. The main ongoing research issue is developing a model capable of protecting the network from DDoS attacks that is sensitive to various classes of DDoS and can recognize legitimate traffic to avoid false alarms. Subsequently, this study proposes combining three deep learning algorithms, namely recurrent neural network (RNN), long short-term memory (LSTM)-RNN, and convolutional neural network (CNN), to build a bidirectional CNN-BiLSTM DDoS detection model. The RNN, CNN, LSTM, and CNN-BiLSTM are implemented and tested to determine the most effective model against DDoS attacks that can accurately detect and distinguish DDoS from legitimate traffic. The intrusion detection evaluation dataset (CICIDS2017) is used to provide more realistic detection. The CICIDS2017 dataset includes benign and up-to-date examples of typical attacks, closely matching real-world data of Packet Capture. The four models are tested and assessed using Confusion Metrix against four commonly used criteria: accuracy, precision, recall, and F-measure. The performance of the models is quite effective as they obtain an accuracy rate of around 99.00%, except for the CNN model, which achieves an accuracy of 98.82%. The CNN-BiLSTM achieves the best accuracy of 99.76% and precision of 98.90%. (shrink)

In recent years there has been an increase in research conducted in the Middle East, with a corresponding increase in the challenges faced by members of the Research Ethics Committees. This study compares the structures of Omani and Jordanian RECs and investigates the perceptions of the challenges affecting the work of the REC members in Oman and Jordan. A convenience sample of 34 Omani and 66 Jordanian participants from 21 universities was recruited in this cross-sectional study. Almost 70% disagreed that (...) the members of RECs are unqualified, providing comments without justification; half believed that members have limited experience in research, and almost three-quarters that they have different opinions regarding some ethical issues. No significant differences were found between Omani and Jordanian REC members regarding their perception of the challenges, except for the perception that reviewing proposals is a time-consuming task and that multi-REC centres are less available. The regression model showed that there were significantly more male members of Jordanian RECs, and that Jordanian members were less likely to receive formal training. In conclusion, the current structure of RECs and the challenges faced by members need to be re-evaluated by decision makers to improve the overall quality of research activities, and to ensure that current REC members’ practices adhere to international standards. (shrink)

Floods are one of the most common natural disasters in the world that affect all aspects of life, including human beings, agriculture, industry, and education. Research for developing models of flood predictions has been ongoing for the past few years. These models are proposed and built-in proportion for risk reduction, policy proposition, loss of human lives, and property damages associated with floods. However, flood status prediction is a complex process and demands extensive analyses on the factors leading to the occurrence (...) of flooding. Consequently, this research proposes an Internet of Things-based flood status prediction (IoT-FSP) model that is used to facilitate the prediction of the rivers flood situation. The IoT-FSP model applies the Internet of Things architecture to facilitate the flood data acquisition process and three machine learning (ML) algorithms, which are Decision Tree (DT), Decision Jungle, and Random Forest, for the flood prediction process. The IoT-FSP model is implemented in MATLAB and Simulink as development platforms. The results show that the IoT-FSP model successfully performs the data acquisition and prediction tasks and achieves an average accuracy of 85.72% for the three-fold cross-validation results. The research finding shows that the DT scores the highest accuracy of 93.22%, precision of 92.85, and recall of 92.81 among the three ML algorithms. The ability of the ML algorithm to handle multivariate outputs of 13 different flood textual statuses provides the means of manifesting explainable artificial intelligence and enables the IoT-FSP model to act as an early warning and flood monitoring system. (shrink)

Recent advances in machine learning methods have created opportunities to eliminate unfairness from algorithmic decision making. Multiple computational techniques (i.e., algorithmic fairness criteria) have arisen out of this work. Yet, urgent questions remain about the perceived fairness of these criteria and in which situations organizations should use them. In this paper, we seek to gain insight into these questions by exploring fairness perceptions of five algorithmic criteria. We focus on two key dimensions of fairness evaluations: distributive fairness and procedural fairness. (...) We shed light on variation in the potential for different algorithmic criteria to facilitate distributive fairness. Subsequently, we discuss procedural fairness and provide a framework for understanding how algorithmic criteria relate to essential aspects of this construct, which helps to identify when a specific criterion is suitable. From a practical standpoint, we encourage organizations to recognize that managing fairness in machine learning systems is complex, and that adopting a blind or one-size-fits-all mentality toward algorithmic criteria will surely damage people’s attitudes and trust in automated technology. Instead, firms should carefully consider the subtle yet significant differences between these technical solutions. (shrink)

Abstract The goal of the study was to investigate the current situation with Human Resources (HR) systems in the Saudi market on the basis of survey conducted among 100 organizations. Their HR and IT experts were to fill out a questionnaire that allowed receiving their expert opinion and make conclusions considering the HR systems usage in this country. In the course of the study, eight hypotheses were investigated and proved: the number of companies’ users of Human Resource Management (HRM) systems (...) does not exceed a half of the staff; most companies use additional resources for HR management apart from HR automated systems; many companies use systems developed by their specialists for HRM; companies are satisfied with the level of HRM systems’ performance; companies are ready to implement new, more effective systems in their practice; Saudi market is not ready for SaaS model; companies are not ready to implement SaaS model; companies have high development potential despite impediments. The results have shown that the Saudi market is ready for implementation of the new technologies, while the level of satisfaction by the current solutions is comparatively low and requires urgent measures. New developments, preferably on the basis of SaaS model, are required to improve the situation and make a step towards successful future. Content Type Journal Article Category Original Paper Pages 1-14 DOI 10.1007/s13520-012-0015-7 Authors Bandar Khalaf Alharthey, Department of Management, Faculty of Management and Human Resource Development, University Technology of Malaysia, 81310 UTM, Johor Bahru, Johor, Malaysia Amran Rasli, Department of Management, Faculty of Management and Human Resource Development, University Technology of Malaysia, 81310 UTM, Johor Bahru, Johor, Malaysia Journal Asian Journal of Business Ethics Online ISSN 2210-6731 Print ISSN 2210-6723. (shrink)

Studies investigating the COVID-19 pandemic from a psychological point of view have mostly focused on psychological distress. This study adopts the framework of existential positive psychology, a second wave of positive psychology that emphasizes the importance of effective coping with the negative aspects of living in order to achieve greater wellbeing. Trait emotional intelligence (trait EI) can be crucial in this context as it refers to emotion-related personality dispositions concerning the understanding and regulation of one’s emotions and those of others. (...) The present study investigated the relationship between trait EI and both wellbeing and psychological distress (i.e., depression, anxiety, and stress), while exploring the mediating role of meaning-centered coping (proactive transformative strategies based on meaning in life) and maladaptive coping (i.e., behavioral disengagement and self-blame) during the first few months of the COVID-19 pandemic. A sample of 326 Lebanese adults completed measures of trait EI, wellbeing, psychological distress, coping, and meaning-centered coping. Results showed a strong positive correlation between trait EI and meaning-centered coping. Trait EI also correlated positively with wellbeing and negatively with psychological distress. Structural equation modeling showed that meaning-centered coping partially mediated the relationship between trait EI and wellbeing. Maladaptive coping fully mediated the relationship between trait EI and psychological distress. Findings indicate that trait EI is positively related to dealing with a stressful situation such as the pandemic in positive ways at both the cognitive level, by reformulating the situation to see something valuable in it, and behavioral level, by being proactive about it. Trait EI was positively linked to seeing the situation as an opportunity for personal growth, finding personal meaning in this situation, maintaining an attitude of hope and courage, and acting more responsibly with one’s self and others during the current crisis. In turn, this coping formula was related to lower psychological distress and improved mental health. These results are consistent with the existential positive psychology framework and can inform implementation programs and policies aiming at raising awareness and promoting healthy and successful coping during the pandemic. (shrink)

Similarity profiled association mining from time stamped transaction databases is an important topic of research relatively less addressed in the field of temporal data mining. Mining temporal patterns from these time series databases requires choosing and applying similarity measure for similarity computations and subsequently pruning temporal patterns. This research proposes a novel z-space based interest measure named as Krishna Sudarsana for time-stamped transaction databases by extending interest measure Srihass proposed in previous research. Krishna Sudarsana is designed by using the product (...) based fuzzy Gaussian membership function and performs similarity computations in z-space to determine the similarity degree between any two temporal patterns. The interest measure is designed by considering z-values between z = 0 and z = 3.09. Applying the Krishna Sudarsana requires moving the threshold value given by user to a different transformation space which is a defined as a function of standard deviation. In addition to proposing interest measure, new expressions for standard deviation and equivalent z-space threshold are derived for similarity computations. For experimental evaluation, we considered Naïve, Sequential and Spamine algorithms that applies Euclidean distance function and compared performance of these three approaches to Z-Spamine algorithm that uses Krishna Sudarsana by choosing various test cases. Experiment results proved the performance of the proposed approach is better to Sequential approach that uses snapshot database scan strategy and Spamine approach that uses lattice based database scan strategy. (shrink)

Business Ethics, the Environment &Responsibility, Volume 31, Issue 4, Page 1157-1173, October 2022.

Name der Zeitschrift: Der Islam Jahrgang: 93 Heft: 2 Seiten: 433-459.

The issue of Christ’s two natures and the Trinitarian persons of God in the Christian conception have posed a conundrum in Christian-Muslim Relations. Islam has historically held to a formulation of absolute unity while the historic Christian faith prefers to see a plurality of union as the proper expression of divine unity. The debate raged throughout the medieval period. The contemporary Egyptian intellectual Awwaḍ Simʽān is one outstanding voice in the current nexus of Muslim-Christian engagement. Simʽān presents a rationally appealing (...) formulation of the Christian doctrine, avoiding or carefully explaining some of the Christian Trinitarian terminology which Muslims regard as most egregious. He appeals to Muslim philosophers as well as historic Christian apologists to buttress his views. It is a winsome and rationally appealing formulation from an Arabic-writing theologian from within the Muslim context. This article seeks to examine the salient points of Simʽān’s formulation and ask if it could be heard in today’s Muslim milieu with all its attending dissonance due to the realities of religious militancy and social displacement. The communal unity of the Trinity may yet find corners of the Muslim world where it is welcomed and embraced. If so, Awwaḍ Simʽān’s formulation will play a visible role. (shrink)

A Poet of the Abbasid Period, Abū al-Qāsim al-Zāhī 313–352 AH/925– 963 CE: His Life and Poetry. By Khalid Sindawi. Codices Arabici Antiqui, vol. 12. Wiesbaden: Harrassowitz, 2010. Pp. 59 + 180. €54.

Abstract“The Book of Secrets in the Results of Ideas”, usually called “The Book of Secrets” is a codex containing drawings and descriptions of thirty-one artifacts attributed to the engineer Alī Ibn Khalaf al-Murādī, who lived in Andalusia in southern Spain at the beginning of the 11th century. This manuscript is one of the first written testimonies that describe medieval mechanisms with complex precision. The aim of this work is to reconstruct and study from a historical and technological point of (...) view two of the ancient artifacts contained in the “Book of Secrets”, the “Fortress Demolisher” and the “Magic Well”. The “Fortress Demolisher” is a war machine designed to demolish the upper part of the walls or towers and consists of a battering ram mounted on a platform that can be raised several meters above the ground using a scissor mechanism. The “Magic Well” is a mechanism with several pulleys whose purpose is to raise water several meters from the bottom of a well by collecting a small portion of rope. To reconstruct the two artifacts, a digital model and a detailed study of the geometry and operation of the mechanisms, were first carried out. 3D printing, using the Fused Deposition Modelling technology, made the physical reproduction. The digitization and physical reproduction by 3D printing of the mechanisms represent an update of the traditional ways of transmitting knowledge. The use of these new technologies makes the knowledge more accessible, understandable and attractive. (shrink)

Astrolabes serving all latitudes are very rare. This recently rediscovered sixteenth-century Spanish example raises a host of questions which can only be addressed by considering all other such instruments and the few available textual sources. The instruments can all be traced back, not always directly, to an invention of the eleventh-century Andalusian astronomer Ali ibn Khalaf, preserved in the Old Castillian Libros del Saber de Astronomía of King Alfonso X. The design of this particular astrolabe and the engraving on (...) it are investigated in detail, and the as yet unidentified maker is associated with the circle around Juan de Herrera, architect of the palace-monastery of San Lorenzo de El Escorial. (shrink)