Transcendental Ego is the principle of principles that philosophization of great philosophers such as Husserl has been based upon it. Husserl, too, as a follower of Descartes meditations and philosophy with attemption in intentionality of transcendental ego accepts it as the base of principles of philosophization and declares himself as a New Cartesian. In this study, the author develops an original reading of the Cartesian Meditation. This text, far from giving rise to a “Transcendental solipsism”, leads to a constitution of (...) intersubjectivity on various levels (“primordial”, “Intersubjective” et “Objective”). In its center, a “Phenomenological Construction” operates, i.e. a methodological piece that masters the genetic approach of intersubjectivity. Closely following the “almost mathematical” rigour of this crucial text of Husserl’s phenomenology, in this way equally tackles the issue of the constitution of the experience of the other and the truly intersubjective structure of transcendental subjectivity. This study concludes with the metaphysical results of the analysis of the experience of the other. (shrink)

During the initial phases of the COVID-19 pandemic, stress and anxiety were pervasive among the masses due to high morbidity and mortality. Besides the fear of coronavirus was also particularly driven by social media. Many people started to look for faith and spiritual connections to gain comfort. The role of spiritual ties and religious beliefs in relation to coping with pandemic stress gained the attention of researchers in some parts of the world. This cross-sectional survey aimed at assessing the intensity (...) of stress and anxiety symptoms experienced by people and how much they were alleviated by employing spiritual connections. The study sample comprises 795 respondents with 52% males and 48% females living in Saudi Arabia. The brief online study questionnaire collected data about background variables, anxiety and stress scale from DASS-21, and items from the WHOQOL instrument assessed the use of spiritual beliefs to cope. Multiple regression models were tested to determine the role of spiritual connections after adjusting demographic variables. Results illustrated that after adjusting for gender and age, participants' anxiety symptoms decreased by units with each unit increase in the use of spiritual connections, and participants’ stress symptoms reduce by units with each unit increase in coping with spirituality. Additionally, females’ risk to experience anxiety and stress symptoms was more than males and, respectively. An increase in age decreases the likelihood of experiencing anxiety symptoms and stress symptoms by and units respectively. Findings support the protective role of spiritual connections despite small beta coefficients. The social and cultural context in Saudi Arabia favors deep-rooted connections with spirituality and faith. Our findings support that the reliance on spiritual connections helped older people to deal with exaggerated fear during the initial phase of the COVID-19 pandemic and reduces the risk of experiencing anxiety and stress symptoms. Females and younger participants were relatively vulnerable to developing these symptoms. We discussed these findings considering some recent studies that reported similar relationships and made recommendations for future research. (shrink)

This paper unravels an unprecedented interplay between board gender diversity (BGD) and corporate environmental, social, and governance (ESG) disputes among Chinese A-share-listed nonfinancial companies from 2017 to 2021. Framed within a knowledge-based and sensemaking perspective of institutional frameworks, the research not only illuminates the profound impact of internal (corporate governance ratings) and external (regional institutional development) institutional factors on this intricate relationship but also brings to light a paradigm-shifting revelation. The study employed a diverse set of empirical tests, ranging from (...) ordinary least squares regression to advanced methods such as the generalized method of moments, two-stage least squares, and propensity score matching, providing a nuanced and comprehensive analysis. The findings highlight the pivotal role of female directors in significantly mitigating ESG disputes. A mechanism analysis further uncovers that internal and external institutional quality are potent positive moderators in shaping the BGD–ESG dispute dynamic. This research has profound implications, providing valuable insights for stakeholders, policymakers, and scholars, offering a comprehensive understanding of how gender diversity fosters sustainability while unravelling the intricate tapestry of internal and external institutional dynamics that shape ESG outcomes. (shrink)

Introduction There is a paramount need for moral development for pharmacists and pharmacy students to practice the patient-centered profession. We aimed to explore the current situational judgment utilizing ethical reasoning among undergraduate pharmacy students. Methods A set of ten ethical dilemmas, representing potential real-life situations that the students come across in the university and may face in the future as a pharmacist were developed by a team of students, academic staff, and stakeholders. These ethical dilemmas were validated, checked for accuracy, (...) and piloted. An online questionnaire was created consisting of these ten scenarios as open-ended questions and administered to fourth year and fifth year PharmD students in a public university located at the city of Mecca, Saudi Arabia, asking them how they would react in that situation. Responses of the participants were analyzed using thematic analysis independently by four researchers and inter-rater agreement were achieved through consensus. Results Out of 205, 186 students completed the questionnaire with a response rate of 90.7%. Analysis and resulted in the generation of 32 codes, which were then categorized into seven overarching themes: student engagement, social and professional responsibility, academic integrity, legal obligation, moral obligation, signposting, and moral engagement and patient safety. Conclusions Undergraduate pharmacy students experience complex state of mind in connection with ethical reasoning. The participants’ situational judgment were driven by cultural norm, authority, and responsibility. Student engagement is also affected by the state of mind and feelings of mutual trust, perceived cultural influence and peer pressure. The students were prone to seek help from university administrators or teachers when faced with situations in which they were helpless. (shrink)

A system of system’s ability to function is derived from the integration of systems from different sources. An SOS’s systems serve two purposes: first, to accomplish their own specific aims, and second, to provide resources to the SOS as a whole. In the last few decades, machine learning and data analytics have been widely used in system design and acquisitions. Every organisation that acquires a sophisticated system employs some type of data analytics to evaluate the system’s independent objectives, which is (...) universally accepted. Data analytics and decision-making regarding the independent system is rarely shared across SOS stakeholders, even though the systems contribute to and benefit from the larger SOS. The goal of this research is to determine how the exchange of data sets and the corresponding analytics by SOS stakeholders can improve SOS capacity. Predicting SOS capabilities by exchanging relevant data sets and prescribing information connections between systems, we propose to use machine learning techniques. This article serves as an intermediate analysis of the above research work and aims to estimate the benefit of information sharing among the SOS stakeholders. In this research, we have applied different machine learning models to the IBM HR analytics data set to determine the corresponding analytics by SOS stakeholders that can improve SOS capacity. We propose using machine learning techniques to forecast SOS capabilities through the sharing of relevant data sets, and we prescribe the information linkages across systems to make this possible. This paper provides an update on the progress being made toward the aforementioned research project, and its primary focus is on developing a method to put a dollar amount on the benefits of information sharing among the many parties involved in the SOS. (shrink)

Prediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure which is physically related to rainfall on land and thus able to predict unseen rainfall (...) events. Daily rainfall of east coast of Peninsular Malaysia was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine, Bayesian regularized neural networks, Bayesian additive regression trees, extreme gradient boosting, and hybrid neural fuzzy inference system were used considering the complex relationship of rainfall with sea level pressure. Principle components of SLP domain correlated with daily rainfall were used as predictors. The results revealed that the efficacy of AI models is predicting daily rainfall one day before. The relative performance of the models revealed the higher performance of BRNN with normalized root mean square error of 0.678 compared with HNFIS, BART, xgBoost, and ELM. Visual inspection of predicted rainfall during model validation using density-scatter plot and other novel ways of visual comparison revealed the ability of BRNN to predict daily rainfall one day before reliably. (shrink)

Drought is a creeping phenomenon that slowly holds an area over time and can be continued for many years. The impacts of drought occurrences can affect communities and environments worldwide in several ways. Thus, assessment and monitoring of drought occurrences in a region are crucial for reducing its vulnerability to the negative impacts of drought. Therefore, comprehensive drought assessment techniques and methods are required to develop adaptive strategies that a region can undertake to reduce its vulnerability to drought substantially. For (...) this purpose, this study proposes a new method known as a regional comprehensive assessment of meteorological drought. The Standardized Precipitation Index, Standardized Precipitation Evapotranspiration Index, and Standardized Precipitation and Temperature Index are jointly used for the development of the RCAMD. Further, the RCAMD employs Monte Carlo feature selection and steady-state probabilities to comprehensively collect information from various stations and drought indices. Moreover, the RCAMD is validated on the six selected stations in the northern areas of Pakistan. The outcomes associated with the RCAMD provide a comprehensive regional assessment of meteorological drought and become the initial source for bringing more considerations to drought monitoring and early warning systems. (shrink)

In developing countries, the patriarchal social construct, unsatisfactory legal protection, and underlying cultural bias against women have resulted in increasing intimate partner violence, which largely goes unaddressed, undocumented, and unreported in healthcare settings. This case study presents a common scenario of intimate partner violence and carefully analyzes its ethical implications in an emergency case at a tertiary care hospital in Karachi, Pakistan. In this study, basic ethical principles are used to discuss important ethical challenges faced daily by healthcare workers in (...) the medical, social, and legal context. It further highlights the dire need of patient education, safety, and a solid framework for addressing, documenting, and reporting intimate partner violence for healthcare workers. (shrink)

The development of the Minimalist Program, Noam Chomsky's most recent generative model of linguistics, has been highly influential over the last twenty years. It has had significant implications not only for the conduct of linguistic analysis itself, but also for our understanding of the status of linguistics as a science. The reflections and analyses in this book contain insights into the strengths and the weaknesses of the MP. Among these are, a clarification of the content of the Strong Minimalist Thesis (...) ; a synthesis of Chomsky's linguistic and interdisciplinary discourses; and an analysis of the notion of optimal computation from conceptual, empirical and philosophical perspectives. This book will encourage graduate students and researchers in linguistics to reflect on the foundations of their discipline, and the interdisciplinary nature of the topics explored will appeal to those studying biolinguistics, neurolinguistics, the philosophy of language and other related disciplines. (shrink)

The Islamic finance industry is relatively new and vibrant. It is becoming a mainstream industry in the MENA. The industry is based on a number of Sharia’a maxims and in particular the prohibition of Riba. Islamic law scholars’ emphasis on the ethical dimension of this industry and how it can be seen as a solution to existing capitalism. The current financial crisis presented this industry with an unprecedented test and an opportunity to influence and merge into main stream finance. This (...) paper presents an evaluation of Islamic finance industry in the current financial crisis and whether the governance and ethical foundation of Islamic finance institutions distinguished itself from conventional finance. Thus, this paper begins with an overview of Islamic finance, then it discusses the governance framework structure of Islamic finance institutions and the role of its organs. In addition, this paper will compare between the ethical framework of the Islamic finance institutions and the conventional institutions. Finally, this paper will discover the ethical failure of the current global financial system and its relation with the current financial crisis. (shrink)

The present commentary considers the question of what must be learned in different types of motor skills, thereby limiting the question of what should be adjusted in the APG model in order to explain successful learning. It is concluded that an open loop model like the APG might well be able to describe the learning pattern of motor skills in a stable, predictable environment. Recent research on saccadic plasticity, however, illustrates that motor skills performed in an unpredictable environment depend heavily (...) on sensory (mostly visual) feedback, [HOUK et al.]. (shrink)

Measuring and evaluating a learner’s learning ability is always the focus of every person whose aim is to develop strategies and plans for their learners to improve the learning process. For example, classroom assessments, self-assessment using computer systems such as Intelligent Tutoring Systems, and other approaches are available. Assessment of metacognition is one of these techniques. Having the ability to evaluate and monitor one’s learning is known as metacognition. An individual can then propose adjustments to their learning process based on (...) this assessment. By monitoring, improving, and planning their activities, learners who can manage their cognitive skills are better able to manage their knowledge about a particular subject. It is common knowledge that students’ metacognitive and self-assessment skills and abilities have been extensively studied, but no research has been carried out on the mistakes that novice developers make because they do not use their self-assessment abilities enough. This study aims to assess the metacognitive skills and abilities of novice software developers working in the industry and to describe the consequences of awareness of metacognition on their performance. In the proposed study, we experimented with novice software developers and collected data using Devskiller and a self-assessment log to analyze their use of self-regulation skills. The proposed study showed that when developers are asked to reflect upon their work, they become more informed about their habitual mistakes, and using a self-assessment log helps them highlight their repetitive mistakes and experiences which allows them to improve their performance on future tasks. (shrink)

Data analytics, machine intelligence, and other cognitive algorithms have been employed in predicting various types of diseases in health care. The revolution of artificial neural networks in the medical discipline emerged for data-driven applications, particularly in the healthcare domain. It ranges from diagnosis of various diseases, medical image processing, decision support system, and disease prediction. The intention of conducting the research is to ascertain the impact of parameters on diabetes data to predict whether a particular patient has a disease or (...) not. This paper develops an improved ANN model trained using an artificial backpropagation scaled conjugate gradient neural network algorithm to predict diabetes effectively. For validating the performance of the proposed model, we conduct a large set of experiments on a Pima Indian Diabetes dataset using accuracy and mean squared error as evaluation metrics. We use different number of neurons in the hidden layer, ranging from 5 to 50, to train the ANN models. The experimental results show that the ABP-SCGNN model, containing 20 neurons, attains 93% accuracy on the validation set, which is higher than using the other ANNs models. This result confirms the model’s effectiveness and efficiency in predicting diabetes disease from the required data attributes. (shrink)

With the advancement of internet and the emergence of network globalization, security has always been a major concern. During the trial operation, the management control platform discussed in this article included more than 600 network security vulnerabilities in the industry, with dozens of incidents, which were promptly dealt with and rectified, effectively improving the level of network security management and protection in the industry. As networks are very much vulnerable to denial of service attacks, much more emphasis has been given (...) to security. By improving their network security, network administrators have often tried their best. To attempt penetration testing, it is the best way of ensuring the system security. With the development of information technology, the security requirement of information system is increasing day by day. The use of penetration testing technology is conducive to the realization of accurate positioning, accurate detection, and active alarm of security vulnerabilities, and the optimization of monitoring and rectification of the combination of network security management control system. Taking penetration testing technology as one of the core elements of management and control, the risk index model is optimized to make network security management controllable and efficient, and effectively achieve management and control objectives. (shrink)

In order to correct the deficiencies of intrusion detection technology, the entire computer and network security system are needed to be more perfect. This work proposes an improved k-means algorithm and an improved Apriori algorithm applied in data mining technology to detect network intrusion and security maintenance. The classical KDDCUP99 dataset has been utilized in this work for performing the experimentation with the improved algorithms. The algorithm’s detection rate and false alarm rate are compared with the experimental data before the (...) improvement. The outcomes of proposed algorithms are analyzed in terms of various simulation parameters like average time, false alarm rate, absolute error as well as accuracy value. The results show that the improved algorithm advances the detection efficiency and accuracy using the designed detection model. The improved and tested detection model is then applied to a new intrusion detection system. After intrusion detection experiments, the experimental results show that the proposed system improves detection accuracy and reduces the false alarm rate. A significant improvement of 90.57% can be seen in detecting new attack type intrusion detection using the proposed algorithm. (shrink)

Mining social network data and developing user profile from unstructured and informal data are a challenging task. The proposed research builds user profile using Twitter data which is later helpful to provide the user with personalized recommendations. Publicly available tweets are fetched and classified and sentiments expressed in tweets are extracted and normalized. This research uses domain-specific seed list to classify tweets. Semantic and syntactic analysis on tweets is performed to minimize information loss during the process of tweets classification. After (...) precise classification and sentiment analysis, the system builds user interest-based profile by analyzing user’s post on Twitter to know about user interests. The proposed system was tested on a dataset of almost 1 million tweets and was able to classify up to 96% tweets accurately. (shrink)

Starting from macroscopic and microscopic facts of cerebellar histology, we propose a new functional interpretation that may elucidate the role of the cerebellum in movement control. The idea is that the cerebellum is a large collection of individual lines (Eccles's : Eccles et al. 1967a) that respond specifically to certain sequences of events in the input and in turn produce sequences of signals in the output. We believe that the sequence-in/sequence-out mode of operation is as typical for the cerebellar cortex (...) as the transformation of sets into sets of active neurons is typical for the cerebral cortex, and that both the histological differences between the two and their reciprocal functional interactions become understandable in the light of this dichotomy. The response of Purkinje cells to sequences of stimuli in the mossy fiber system was shown experimentally by Heck on surviving slices of rat and guinea pig cerebellum. Sequential activation of a row of eleven stimulating electrodes in the granular layer, imitating a of the stimuli along the folium, produces a powerful volley in the parallel fibers that strongly excites Purkinje cells, as evidenced by intracellular recording. The volley, or has maximal amplitude when the stimulus moves toward the recording site at the speed of conduction in parallel fibers, and much smaller amplitudes for lower or higher The succession of stimuli has no effect when they in the opposite direction. Synchronous activation of the stimulus electrodes also had hardly any effect. We believe that the sequences of mossy fiber activation that normally produce this effect in the intact cerebellum are a combination of motor planning relayed to the cerebellum by the cerebral cortex, and information about ongoing movement, reaching the cerebellum from the spinal cord. The output elicited by the specific sequence to which a is tuned may well be a succession of well timed inhibitory volleys the motor sequences so as to adapt them to the complicated requirements of the physics of a multijointed system. (shrink)

Academic performance is among the several components of academic success. Many factors, including socioeconomic status, student temperament and motivation, peer and parental support influence academic performance. Our study aims to investigate the determinants of academic performance with emphasis on the role of parental styles in adolescent students in Peshawar Pakistan. A total of 456 students from 4 public and 4 private schools were interviewed. Academic performance was assessed based on self-reported grades in the latest internal examinations. Parenting styles were assessed (...) through the administration of the Parental bonding instrument. Regression analysis was conducted to assess the influence of socio-demographic factors and parenting styles on academic performance. Factors associated with and differences between “care” and “overprotection” scores of fathers and mothers were analyzed. Higher socio-economic status, father’s education level and higher care scores were independently associated with better academic performance in adolescent students. Affectionless control was the most common parenting style for fathers and mothers. When adapted by the father, it was also the only parenting style independently improving academic performance. Overall, mean “care” scores were higher for mothers and mean “overprotection” scores were higher for fathers. Parenting workshops and school activities emphasizing the involvement of mothers and fathers in the parenting of adolescent students might have a positive influence on their academic performance. Affectionless control may be associated with improved academics but the emotional and psychosocial effects of this style of parenting need to be investigated before recommendations are made. (shrink)

Impairment of spatial memory, including an inability to recall previous locations and navigate the world, is often one of the first signs of functional disability on the road to cognitive impairment. While there are many screening and diagnostic tools which attempt to measure spatial memory ability, they are often not representative of real-life situations and can therefore lack applicability. One potential solution to this problem involves the use of virtual reality, which immerses individuals in a virtually-simulated environment, allowing for scenarios (...) more representative of real-life without any of the associated risks. Here, we review the evidence surrounding the use of VR for the screening and diagnosis of spatial memory impairments, including potential limitations and how it compares to standard neuropsychological tests. We will also discuss the evidence regarding the potential use of VR in the rehabilitation of spatial memory deficits, which has not been well studied, but which could be game-changing if proven successful. (shrink)

The liver is the human body’s mandatory organ, but detecting liver disease at an early stage is very difficult due to the hiddenness of symptoms. Liver diseases may cause loss of energy or weakness when some irregularities in the working of the liver get visible. Cancer is one of the most common diseases of the liver and also the most fatal of all. Uncontrolled growth of harmful cells is developed inside the liver. If diagnosed late, it may cause death. Treatment (...) of liver diseases at an early stage is, therefore, an important issue as is designing a model to diagnose early disease. Firstly, an appropriate feature should be identified which plays a more significant part in the detection of liver cancer at an early stage. Therefore, it is essential to extract some essential features from thousands of unwanted features. So, these features will be mined using data mining and soft computing techniques. These techniques give optimized results that will be helpful in disease diagnosis at an early stage. In these techniques, we use feature selection methods to reduce the dataset’s feature, which include Filter, Wrapper, and Embedded methods. Different Regression algorithms are then applied to these methods individually to evaluate the result. Regression algorithms include Linear Regression, Ridge Regression, LASSO Regression, Support Vector Regression, Decision Tree Regression, Multilayer Perceptron Regression, and Random Forest Regression. Based on the accuracy and error rates generated by these Regression algorithms, we have evaluated our results. The result shows that Random Forest Regression with the Wrapper Method from all the deployed Regression techniques is the best and gives the highest R2-Score of 0.8923 and lowest MSE of 0.0618. (shrink)

This paper aims to introduce a robust framework for forecasting demand, including data preprocessing, data transformation and standardization, feature selection, cross-validation, and regression ensemble framework. Bagging ), boosting and extreme gradient boosting regression ), and stacking are employed as ensemble models. Different machine learning approaches, including support vector regression, extreme learning machine, and multilayer perceptron neural network, are adopted as reference models. In order to maximize the determination coefficient value and reduce the root mean square error, hyperparameters are set using (...) the grid search method. Using a steel industry dataset, all tests are carried out under identical experimental conditions. In this context, STACK1 and STACK2 models provided better performance than other models. The highest accuracies of R2 of 0.97 and 0.97 are obtained using STACK1 and STACK2, respectively. Moreover, the rank according to performances is STACK1, STACK2, XGBR, GBR, RFR, MLP, ELM, and SVR. As it improves the performance of models and reduces the risk of decision-making, the ensemble method can be used to forecast the demand in a steel industry one month ahead. (shrink)

Artificial Immune Systems (AIS) are intelligent algorithms derived on the principles inspired by human immune system. In this research work, electroencephalography (EEG) signals for four distinct motor movement of human limbs are detected and classified using Negative Selection Classification Algorithm (NSCA). For this study, a widely studied open source EEG signal database (BCI IV - Graz dataset 2a, comprising 9 subjects) has been used. Mel Frequency Cepstral Coefficients (MFCCs) are extracted as selected feature from recorded EEG signals. Dimensionality reduction of (...) data is carried out by applying two hidden layered stacked auto-encoder. Genetic Algorithm (GA) optimized detectors (Artificial Lymphocytes) are trained using Negative Selection Algorithm (NSA) for detection and classification of four motor movements. The trained detectors consist of four sets of detectors, each set is trained for detection and classification of one of the four movements from the other three movements. The optimized radius of detector is small enough not to mis-detect the sample. Euclidean distance of each detector with every training dataset sample is taken and compared with optimized radius of detector as a non-self detector. Our proposed approach achieved a mean classification accuracy of 86.39% for limb movements over 9 subjects with a maximum individual subject classification accuracy of 97.5 % for subject number eight. (shrink)

Although our idea of sequential input being a key to cerebellar function was taken seriously by most commentators, there were also objections, based in part on experimental evidence that seems to contradict our intuitions and in part on commentators' preferences for different schemes. Several were suspicious of experiments (performed on slices of cerebellar tissue) that may have severed some of the synaptic connections, particularly the inhibitory ones. It is our feeling that a modi-fication of our theory that could satisfy most (...) critics would not have to be very radical. (shrink)

Corporate Social Responsibility and environmental sustainability have become urgent concerns for contemporary businesses. This study focuses on the interplay between corporate social responsibility perceptions and pro-environmental behaviour in response to experts’ call for research on the micro-foundations of corporate social responsibility. In addition, it reveals the mechanism underpinning how perceived CSR shapes pro-environmental behaviour in an understudied developing context. Empirically, a qualitative multiple-case research design is utilised by selecting three business schools from Peshawar, Pakistan. Fourteen semi-structured interviews were conducted with (...) senior management and faculty to collect data. Besides primary data, a qualitative documentary review is used to enhance the research. Data analysis is done through the thematic network technique. Plantation, cleanliness, waste reduction, and energy conservation are the environmental aspects of CSR as regarded by employees. In addition, perceived CSR shapes pro-environmental behaviour via environmental knowledge and awareness, eco-civic sense, environmental values, personality traits, religious perspective, and perceived organisational support for the environment. This study provides original additions to the CSR literature by suggesting eco-civic sensibility and religious perspective as new CSR drivers for pro-environmental conduct. Incorporating stakeholder salience into the context of the present study also advances CSR research. The findings are also valuable for management to make the CSR agenda of business schools more strategic, comprehensive, and centred on the priorities of salient stakeholders. (shrink)

The investigation of users' satisfactions and intentions in using the services provided by commercial banks needs to be focused on internet banking, since this is the widely used banking service. This paper analyzed the satisfactions and behavioral intentions of Malaysian customers in using Internet Banking, applying the Information System Success Model by the integration of adoption and application technology theory. Some criteria, which were taken into consideration, are as follows: perceived Risk, facilitating Conditions, Price, Performance expectancy, Information Quality, Service Quality, (...) and System Quality. These aspects are important to measure customers' satisfaction and behavior toward Internet and Online Banking. A sample of 362 valid responses, consisting of Malaysian customers who used E-Banking, was used for the purpose of data collection. The relationship between customers' satisfaction and factors influencing their contentment in using Online Banking was investigated. In order to evaluate this, a model called “Structural Equation Model ” was developed and used. Findings showed that most of the Online Banking users were satisfied with the system. Hence, it proves that Online Banking System was generally accepted in the Malaysian community. However, this current research is solely focused on the Malaysian community. Therefore, it may provide the necessary grounds for the study of internet banking accreditation, some useful information for the practitioners, policy makers, and the researchers to improve the system of online banking in Malaysia only. For a future study, a more well-structured research, which can accommodate the global need, would be required. (shrink)

Emotion-based sentimental analysis has recently received a lot of interest, with an emphasis on automated identification of user behavior, such as emotional expressions, based on online social media texts. However, the majority of the prior attempts are based on traditional procedures that are insufficient to provide promising outcomes. In this study, we categorize emotional sentiments by recognizing them in the text. For that purpose, we present a deep learning model, bidirectional long-term short-term memory, for emotion recognition that takes into account (...) five main emotions. We use our experimental assessments on the emotion dataset to accomplish the emotion categorization job. The datasets were evaluated and the findings revealed that, when compared to state-of-the-art methodologies, the proposed model can successfully categorize user emotions into several classifications. Finally, we assess the efficacy of our strategy using statistical analysis. This research’s findings help firms to apply best practices in the selection, management, and optimization of policies, services, and product information. (shrink)

This fourteenth volume of Collected Papers is an eclectic tome of 87 papers in Neutrosophics and other fields, such as mathematics, fuzzy sets, intuitionistic fuzzy sets, picture fuzzy sets, information fusion, robotics, statistics, or extenics, comprising 936 pages, published between 2008-2022 in different scientific journals or currently in press, by the author alone or in collaboration with the following 99 co-authors (alphabetically ordered) from 26 countries: Ahmed B. Al-Nafee, Adesina Abdul Akeem Agboola, Akbar Rezaei, Shariful Alam, Marina Alonso, Fran Andujar, (...) Toshinori Asai, Assia Bakali, Azmat Hussain, Daniela Baran, Bijan Davvaz, Bilal Hadjadji, Carlos Díaz Bohorquez, Robert N. Boyd, M. Caldas, Cenap Özel, Pankaj Chauhan, Victor Christianto, Salvador Coll, Shyamal Dalapati, Irfan Deli, Balasubramanian Elavarasan, Fahad Alsharari, Yonfei Feng, Daniela Gîfu, Rafael Rojas Gualdrón, Haipeng Wang, Hemant Kumar Gianey, Noel Batista Hernández, Abdel-Nasser Hussein, Ibrahim M. Hezam, Ilanthenral Kandasamy, W.B. Vasantha Kandasamy, Muthusamy Karthika, Nour Eldeen M. Khalifa, Madad Khan, Kifayat Ullah, Valeri Kroumov, Tapan Kumar Roy, Deepesh Kunwar, Le Thi Nhung, Pedro López, Mai Mohamed, Manh Van Vu, Miguel A. Quiroz-Martínez, Marcel Migdalovici, Kritika Mishra, Mohamed Abdel-Basset, Mohamed Talea, Mohammad Hamidi, Mohammed Alshumrani, Mohamed Loey, Muhammad Akram, Muhammad Shabir, Mumtaz Ali, Nassim Abbas, Munazza Naz, Ngan Thi Roan, Nguyen Xuan Thao, Rishwanth Mani Parimala, Ion Pătrașcu, Surapati Pramanik, Quek Shio Gai, Qiang Guo, Rajab Ali Borzooei, Nimitha Rajesh, Jesús Estupiñan Ricardo, Juan Miguel Martínez Rubio, Saeed Mirvakili, Arsham Borumand Saeid, Saeid Jafari, Said Broumi, Ahmed A. Salama, Nirmala Sawan, Gheorghe Săvoiu, Ganeshsree Selvachandran, Seok-Zun Song, Shahzaib Ashraf, Jayant Singh, Rajesh Singh, Son Hoang Le, Tahir Mahmood, Kenta Takaya, Mirela Teodorescu, Ramalingam Udhayakumar, Maikel Y. Leyva Vázquez, V. Venkateswara Rao, Luige Vlădăreanu, Victor Vlădăreanu, Gabriela Vlădeanu, Michael Voskoglou, Yaser Saber, Yong Deng, You He, Youcef Chibani, Young Bae Jun, Wadei F. Al-Omeri, Hongbo Wang, Zayen Azzouz Omar. (shrink)

This sixth volume of Collected Papers includes 74 papers comprising 974 pages on (theoretic and applied) neutrosophics, written between 2015-2021 by the author alone or in collaboration with the following 121 co-authors from 19 countries: Mohamed Abdel-Basset, Abdel Nasser H. Zaied, Abduallah Gamal, Amir Abdullah, Firoz Ahmad, Nadeem Ahmad, Ahmad Yusuf Adhami, Ahmed Aboelfetouh, Ahmed Mostafa Khalil, Shariful Alam, W. Alharbi, Ali Hassan, Mumtaz Ali, Amira S. Ashour, Asmaa Atef, Assia Bakali, Ayoub Bahnasse, A. A. Azzam, Willem K.M. Brauers, Bui (...) Cong Cuong, Fausto Cavallaro, Ahmet Çevik, Robby I. Chandra, Kalaivani Chandran, Victor Chang, Chang Su Kim, Jyotir Moy Chatterjee, Victor Christianto, Chunxin Bo, Mihaela Colhon, Shyamal Dalapati, Arindam Dey, Dunqian Cao, Fahad Alsharari, Faruk Karaaslan, Aleksandra Fedajev, Daniela Gîfu, Hina Gulzar, Haitham A. El-Ghareeb, Masooma Raza Hashmi, Hewayda El-Ghawalby, Hoang Viet Long, Le Hoang Son, F. Nirmala Irudayam, Branislav Ivanov, S. Jafari, Jeong Gon Lee, Milena Jevtić, Sudan Jha, Junhui Kim, Ilanthenral Kandasamy, W.B. Vasantha Kandasamy, Darjan Karabašević, Songül Karabatak, Abdullah Kargın, M. Karthika, Ieva Meidute-Kavaliauskiene, Madad Khan, Majid Khan, Manju Khari, Kifayat Ullah, K. Kishore, Kul Hur, Santanu Kumar Patro, Prem Kumar Singh, Raghvendra Kumar, Tapan Kumar Roy, Malayalan Lathamaheswari, Luu Quoc Dat, T. Madhumathi, Tahir Mahmood, Mladjan Maksimovic, Gunasekaran Manogaran, Nivetha Martin, M. Kasi Mayan, Mai Mohamed, Mohamed Talea, Muhammad Akram, Muhammad Gulistan, Raja Muhammad Hashim, Muhammad Riaz, Muhammad Saeed, Rana Muhammad Zulqarnain, Nada A. Nabeeh, Deivanayagampillai Nagarajan, Xenia Negrea, Nguyen Xuan Thao, Jagan M. Obbineni, Angelo de Oliveira, M. Parimala, Gabrijela Popovic, Ishaani Priyadarshini, Yaser Saber, Mehmet Șahin, Said Broumi, A. A. Salama, M. Saleh, Ganeshsree Selvachandran, Dönüș Șengür, Shio Gai Quek, Songtao Shao, Dragiša Stanujkić, Surapati Pramanik, Swathi Sundari Sundaramoorthy, Mirela Teodorescu, Selçuk Topal, Muhammed Turhan, Alptekin Ulutaș, Luige Vlădăreanu, Victor Vlădăreanu, Ştefan Vlăduţescu, Dan Valeriu Voinea, Volkan Duran, Navneet Yadav, Yanhui Guo, Naveed Yaqoob, Yongquan Zhou, Young Bae Jun, Xiaohong Zhang, Xiao Long Xin, Edmundas Kazimieras Zavadskas. (shrink)

This seventh volume of Collected Papers includes 70 papers comprising 974 pages on (theoretic and applied) neutrosophics, written between 2013-2021 by the author alone or in collaboration with the following 122 co-authors from 22 countries: Mohamed Abdel-Basset, Abdel-Nasser Hussian, C. Alexander, Mumtaz Ali, Yaman Akbulut, Amir Abdullah, Amira S. Ashour, Assia Bakali, Kousik Bhattacharya, Kainat Bibi, R. N. Boyd, Ümit Budak, Lulu Cai, Cenap Özel, Chang Su Kim, Victor Christianto, Chunlai Du, Chunxin Bo, Rituparna Chutia, Cu Nguyen Giap, Dao The (...) Son, Vinayak Devvrat, Arindam Dey, Partha Pratim Dey, Fahad Alsharari, Feng Yongfei, S. Ganesan, Shivam Ghildiyal, Bibhas C. Giri, Masooma Raza Hashmi, Ahmed Refaat Hawas, Hoang Viet Long, Le Hoang Son, Hongbo Wang, Hongnian Yu, Mihaiela Iliescu, Saeid Jafari, Temitope Gbolahan Jaiyeola, Naeem Jan, R. Jeevitha, Jun Ye, Anup Khan, Madad Khan, Salma Khan, Ilanthenral Kandasamy, W.B. Vasantha Kandasamy, Darjan Karabašević, Kifayat Ullah, Kishore Kumar P.K., Sujit Kumar De, Prasun Kumar Nayak, Malayalan Lathamaheswari, Luong Thi Hong Lan, Anam Luqman, Luu Quoc Dat, Tahir Mahmood, Hafsa M. Malik, Nivetha Martin, Mai Mohamed, Parimala Mani, Mingcong Deng, Mohammed A. Al Shumrani, Mohammad Hamidi, Mohamed Talea, Kalyan Mondal, Muhammad Akram, Muhammad Gulistan, Farshid Mofidnakhaei, Muhammad Shoaib, Muhammad Riaz, Karthika Muthusamy, Nabeela Ishfaq, Deivanayagampillai Nagarajan, Sumera Naz, Nguyen Dinh Hoa, Nguyen Tho Thong, Nguyen Xuan Thao, Noor ul Amin, Dragan Pamučar, Gabrijela Popović, S. Krishna Prabha, Surapati Pramanik, Priya R, Qiaoyan Li, Yaser Saber, Said Broumi, Saima Anis, Saleem Abdullah, Ganeshsree Selvachandran, Abdulkadir Sengür, Seyed Ahmad Edalatpanah, Shahbaz Ali, Shahzaib Ashraf, Shouzhen Zeng, Shio Gai Quek, Shuangwu Zhu, Shumaiza, Sidra Sayed, Sohail Iqbal, Songtao Shao, Sundas Shahzadi, Dragiša Stanujkić, Željko Stević, Udhayakumar Ramalingam, Zunaira Rashid, Hossein Rashmanlou, Rajkumar Verma, Luige Vlădăreanu, Victor Vlădăreanu, Desmond Jun Yi Tey, Selçuk Topal, Naveed Yaqoob, Yanhui Guo, Yee Fei Gan, Yingcang Ma, Young Bae Jun, Yuping Lai, Hafiz Abdul Wahab, Wei Yang, Xiaohong Zhang, Edmundas Kazimieras Zavadskas, Lemnaouar Zedam. (shrink)

This ninth volume of Collected Papers includes 87 papers comprising 982 pages on Neutrosophic Theory and its applications in Algebra, written between 2014-2022 by the author alone or in collaboration with the following 81 co-authors (alphabetically ordered) from 19 countries: E.O. Adeleke, A.A.A. Agboola, Ahmed B. Al-Nafee, Ahmed Mostafa Khalil, Akbar Rezaei, S.A. Akinleye, Ali Hassan, Mumtaz Ali, Rajab Ali Borzooei , Assia Bakali, Cenap Özel, Victor Christianto, Chunxin Bo, Rakhal Das, Bijan Davvaz, R. Dhavaseelan, B. Elavarasan, Fahad Alsharari, (...) T. Gharibah, Hina Gulzar, Hashem Bordbar, Le Hoang Son, Emmanuel Ilojide, Tèmítópé Gbóláhàn Jaíyéolá, M. Karthika, Ilanthenral Kandasamy, W.B. Vasantha Kandasamy, Huma Khan, Madad Khan, Mohsin Khan, Hee Sik Kim, Seon Jeong Kim, Valeri Kromov, R. M. Latif, Madeleine Al-Tahan, Mehmat Ali Ozturk, Minghao Hu, S. Mirvakili, Mohammad Abobala, Mohammad Hamidi, Mohammed Abdel-Sattar, Mohammed A. Al Shumrani, Mohamed Talea, Muhammad Akram, Muhammad Aslam, Muhammad Aslam Malik, Muhammad Gulistan, Muhammad Shabir, G. Muhiuddin, Memudu Olaposi Olatinwo, Osman Anis, Choonkil Park, M. Parimala, Ping Li, K. Porselvi, D. Preethi, S. Rajareega, N. Rajesh, Udhayakumar Ramalingam, Riad K. Al-Hamido, Yaser Saber, Arsham Borumand Saeid, Saeid Jafari, Said Broumi, A.A. Salama, Ganeshsree Selvachandran, Songtao Shao, Seok-Zun Song, Tahsin Oner, M. Mohseni Takallo, Binod Chandra Tripathy, Tugce Katican, J. Vimala, Xiaohong Zhang, Xiaoyan Mao, Xiaoying Wu, Xingliang Liang, Xin Zhou, Yingcang Ma, Young Bae Jun, Juanjuan Zhang. (shrink)