The study aimed to identify the role of administrative procedures and systems in enhancing the performance of the educational institutions in the Islamic University in Gaza. To achieve the research objectives, the researchers used the analytical descriptive approach to collect information. The researchers used the questionnaire distributed to three categories of employees at the Islamic University (senior management, faculty members, their assistants and members of the administrative board). A random sample of 314 employees was selected and 276 questionnaires were retrieved (...) with a recovery rate of 88.1%. The Statistical Analysis Program (SPSS) was used to enter process and analyze data. The results of the research showed a positive role for the administrative procedures and systems in enhancing the performance of the Islamic University from the point of view of the members (senior management, teaching staff and their assistants and the administrative body), where the relative weight of all the paragraphs (73.728%). The analysis of the results revealed that the administrative procedures at the Islamic University in Gaza are used to an acceptable degree. The relative weight of all the paragraphs is 70%. This indicates a relationship between administrative procedures and regulations and the performance of the Islamic University in the Gaza Strip. The study found that there was a good degree of approval from the sample regarding the administrative procedures and their relationship to the job performance. There exist a sufficient degree of powers to the deans and department managers to carry out their tasks, with the use of plans as control tools. And that there are rules and procedures provided for decision-making in the University Council. It also has full powers to manage the university to improve the teaching and learning environment. The researchers also recommended a number of recommendations, including the need to follow up on the procedures and systems of management and update them continuously in the light of changes that may occur and to ensure the existence of a strong system of electronic information systems within the university. There is a need to provide mechanisms for obtaining information about the surrounding external environment, and effective mechanisms to provide managers with the necessary information in a timely manner. The importance of providing channels of communication that enables staff to communicate information about any violations and breaches. The study also recommended the follow-up, review, procedures and administrative systems, and work to modify them in line with the mission of the university and the objectives that the university seeks to reach. (shrink)

The aim of the research is to identify the relationship between the performance criteria and the achievement of the objectives of supervision which is represented in the performance of the job at the Islamic University in Gaza Strip. To achieve the objectives of the research, the researchers used the descriptive analytical approach to collect information. The questionnaire consisted of (22) paragraphs distributed to three categories of employees of the Islamic University (senior management, faculty members, their assistants and members of the (...) administrative board). A random sample of 314 employees was selected, 276 responses were retrieved with a return rate of 88.1%. The SPSS program was used to enter, process, and analyze the data. The results of the study showed a positive relationship between the performance criteria and the achievement of the control objectives represented by the job performance in the Islamic University from the point of view of the members (senior management, faculty and their assistants and the administrative board). The researchers also recommended a number of recommendations, including the provision of an appropriate level of control system components today through the continuous updating and development of performance standards and the need to provide the necessary physical and financial resources to continue the development and achievement within the university. Expand the development of technology in the various activities of the university through the construction of a complete and integrated system to support the control systems in the university to suit its size. The researchers also recommended the follow-up, review of the performance standards and work to modify them in line with the mission of the university and the goals that the university seeks to reach. (shrink)

Deep learning may transform health care, but model development has largely been dependent on availability of advanced technical expertise. The aim of this study is to develop a deep learning model to predict the gender from retinal fundus images. The proposed model was based on the Xception pre-trained model. The proposed model was trained on 20,000 retinal fundus images from Kaggle depository. The dataset was preprocessed them split into three datasets (training, validation, Testing). After training and cross-validating the proposed model, (...) it was evaluated using the testing dataset. The result of testing, the area under receiver operating characteristic curve (AUROC) of the model was 0.99, precision, recall, f1-score and accuracy were 99%, precision, recall, f1-score and accuracy were 96.83%, 96.83%, 96.82% and 96.83% respectively.. Clinicians are presently unaware of dissimilar retinal feature variants between females and males, stressing the importance of model explain ability for the prediction of gender from retinal fundus images. The proposed deep learning may enable clinician-driven automated discovery of novel visions and disease biomarkers. (shrink)

The study highlights the advantages telemedicine offers, such as increased flexibility, reduced commuting time, and better time management. It also examines the challenges doctors face, including the demands of always being digitally accessible, the learning curve of new technologies, and the difficulty in maintaining boundaries between personal and professional life. Using both quantitative and qualitative data, this research compares the telemedicine adaptation experiences of doctors in public versus private hospitals, considering factors such as hospital infrastructure, support systems, and patient load.

Results indicate substantial improvements in efficiency, accuracy, and personalized care, but also highlight the challenges of data privacy, ethical considerations, and system scalability. By providing a structured analysis, this research contributes insights into optimizing generative AI deployments for both banking and healthcare, ensuring a balance between innovation and risk management. The study concludes with recommendations for future research directions, including advanced model training, ethical guidelines, and enhanced privacy measures. These insights aim to inform practitioners on the benefits of generative AI, (...) ensuring sustainable integration into banking and healthcare ecosystems. (shrink)

This article endeavors to recognize the consumer perception towards the Apple products and what is Apple’s ideology. In this article the researcher has listed down 12 variables which affect the consumer behavior most while purchasing Apple products. The researcher took 50 sample sizes to make this paper and this study is being done in Tiruchirappalli District. To prepare the factors, I have used Factor analysis test.

The EdTech revolution in India has emerged as a transformative force, particularly during and after the COVID-19 pandemic, when traditional education systems faced unprecedented disruptions. While digital technologies have unlocked new opportunities for teaching and learning, they have also exposed systemic inequities and deepened the existing digital divide. This paper examines how EdTech is reshaping India's education landscape by addressing these challenges, with a focus on both the opportunities it presents and the barriers it creates. The shift to digital learning (...) platforms has empowered students with access to a broader array of learning resources, interactive content, and personalized learning paths. However, millions of students, particularly those from rural areas or lower-income families, struggle to access these resources due to a lack of digital infrastructure, reliable internet connectivity, and affordability of devices. Furthermore, the role of teachers has evolved, requiring new pedagogical approaches and technical skills to effectively harness these digital tools. (shrink)

This paper provides a comprehensive workflow for organizations considering a move from legacy database systems to Snowflake, demonstrating how a structured migration process can result in enhanced data accessibility, operational flexibility, and long-term scalability. Future directions for research are also discussed, including integration with advanced analytics and machine learning applications, which could further augment Snowflake’s utility in big data ecosystems.

This paper provides a comprehensive workflow for organizations considering a move from legacy database systems to Snowflake, demonstrating how a structured migration process can result in enhanced data accessibility, operational flexibility, and long-term scalability. Future directions for research are also discussed, including integration with advanced analytics and machine learning applications, which could further augment Snowflake’s utility in big data ecosystems.

Abstract: The rapid advancement of artificial intelligence (AI) has catalyzed significant developments in autonomous systems, which are increasingly shaping diverse sectors including transportation, robotics, and industrial automation. This paper explores the evolution of AI technologies that underpin these autonomous systems, focusing on their capabilities, applications, and the challenges they present. Key areas of discussion include the technological innovations driving autonomy, such as machine learning algorithms and sensor integration, and the practical implementations observed in autonomous vehicles, drones, and robotic systems. Additionally, (...) the paper addresses critical challenges including safety, ethical concerns, and regulatory issues that influence the deployment and acceptance of autonomous technologies. By examining current trends and future prospects, this research aims to provide a comprehensive overview of how AI is transforming the landscape of autonomous systems and to identify key areas for future research and development. (shrink)

. The accuracy levels of VGG19 and 3D CNN are compared using the performance metrics. This comparison helps in identifying which model performs better in the task of facial reconstruction from distorted images. Visualizing the results in the form of a graph provides a clear and concise way to understand the comparative performance of the algorithms. The ultimate goal of this project is to develop a system that can accurately reconstruct distorted faces, which can be invaluable in identifying accident victims (...) or assisting in medical treatments. By providing a reliable method for facial reconstruction, this technology can potentially save lives and improve outcomes for individuals involved in accidents. (shrink)

Accelerated computing leverages specialized hardware and software techniques to optimize the performance of computationally intensive tasks, offering significant speed-ups in scientific, engineering, and data-driven fields. This paper presents a comprehensive study examining the role of accelerated computing in enhancing processing capabilities and reducing execution times in diverse applications. Using a custom-designed experimental framework, we evaluated different methodologies for parallelization, GPU acceleration, and CPU-GPU coordination. The aim was to assess how various factors, such as data size, computational complexity, and task concurrency, (...) impact processing efficiency. (shrink)

This paper explores the application of AI-driven HR analytics in shaping workforce agility, focusing on how real-time data collection, analysis, and modeling foster an adaptable workforce. It highlights the role of predictive analytics in forecasting workforce needs, identifying skill gaps, and optimizing talent deployment. Additionally, the paper discusses how AI enhances strategic decision-making by providing precise metrics and insights into employee behavior, productivity, and satisfaction. The integration of AI into HR systems ultimately shifts HR from a traditionally reactive to a (...) highly proactive, data-driven function. (shrink)

The classification system was evaluated using benchmark phishing datasets, and the results demonstrated a significant improvement in detection accuracy and reduced false positives. The proposed model outperformed traditional machine learning algorithms, showing promise for real-world deployment in phishing detection systems. We conclude with suggestions for future improvements, such as incorporating more behavioral data and deploying the system in realtime monitoring applications.

This essay briefly evaluates the ongoing controversy between LIU Qingping and GUO Qiyong (and their followers) about the “moral heart ”of Confucianism in order to draw acomparison with Islamic ethics for mutual illumination of the two traditions.

Water quality assessment is critical for environmental sustainability and public health. This research employs neural networks to predict water quality, utilizing a dataset of 21 diverse features, including metals, chemicals, and biological indicators. With 8000 samples, our neural network model, consisting of four layers, achieved an impressive 94.22% accuracy with an average error of 0.031. Feature importance analysis revealed arsenic, perchlorate, cadmium, and others as pivotal factors in water quality prediction. This study offers a valuable contribution to enhancing water quality (...) monitoring and decision-making for stakeholders and policymakers. (shrink)

This article looks at some of the salient analyses of moderation in the ancient Greek and the Islamic traditions and uses them to develop a contemporary view of the matter. Greek ethics played a huge role in shaping the ethical views of the Muslim philosophers and theologians, and thus the article starts with an overview of the revival of contemporary western virtue ethics--in many ways an extension of Platonic-Aristotelian ethics--and then looks at the place of moderation or temperance in Platonic-Aristotelian (...) ethics. This sets the stage for an exposition of the position taken by Ibn Miskawayh and al-Ghazali, which is then used as a backdrop for suggesting a revival of the Quran's virtue ethics. After outlining a basis for its virtue ethics, the Quranic view of wasatiyya or moderation is discussed briefly. (shrink)

We investigate the application of Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM) networks, and a hybrid CNN-LSTM model for forecasting air pollution levels based on historical data. Our experimental setup uses real-world air quality datasets from multiple regions, containing measurements of pollutants like PM2.5, PM10, CO, NO2, and SO2, alongside meteorological data such as temperature, humidity, and wind speed. The models are trained, validated, and tested using a split dataset, and their accuracy is evaluated using performance metrics like Mean (...) Absolute Error (MAE), Root Mean Squared Error (RMSE), and R-squared. (shrink)

The exponential growth of data storage requirements has become a pressing challenge in hybrid cloud environments, necessitating efficient data deduplication methods. This research proposes a novel Smart Deduplication Framework (SDF) designed to identify and eliminate redundant data, thus optimizing storage usage and improving data retrieval speeds. The framework leverages a hybrid cloud architecture, combining the scalability of public clouds with the security of private clouds. By employing a combination of client-side hashing, metadata indexing, and machine learning-based duplicate detection, the framework (...) achieves significant storage savings without compromising data integrity. Real-time testing on a hybrid cloud setup demonstrated a 65% reduction in storage needs and a 40% improvement in data retrieval times. Additionally, the system employs blockchain for immutable logging of deduplication activities, enhancing transparency and traceability. This study concludes with an evaluation of the deduplication framework's impact on cost efficiency, system performance, and potential scalability. Future enhancements aim to integrate multi-cloud interoperability and advanced compression algorithms to further refine storage management. (shrink)

With the proliferation of sophisticated cyber threats, traditional malware detection techniques are becoming inadequate to ensure robust cybersecurity. This study explores the integration of deep learning (DL) techniques into malware detection systems to enhance their accuracy, scalability, and adaptability. By leveraging convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformers, this research presents an intelligent malware detection framework capable of identifying both known and zero-day threats. The methodology involves feature extraction from static, dynamic, and hybrid malware datasets, followed by (...) training DL models to classify malicious and benign software with high precision. A robust experimental setup evaluates the framework using benchmark malware datasets, yielding a 96% detection accuracy and demonstrating resilience against adversarial attacks. Real-time analysis capabilities further improve response times, reducing the risk of potential damage. The study also incorporates visualization tools to provide interpretable insights into model decisions, enhancing transparency for cybersecurity practitioners. Concluding with a discussion on the challenges and future prospects, this research paves the way for scalable, AI-driven solutions to combat evolving cyber threats. (shrink)

Scott Soames argues that interpreted in the light of Quine's holistic verificationism, Quine's thesis of underdetermination leads to a contradiction. It is contended here that if we pay proper attention to the evolution of Quine's thinking on the subject, particularly his criterion of theory individuation, Quine's thesis of underdetermination escapes Soames' charge of paradoxicality.

This article is focused on some conditions in today’s world of globalized media, which are producing either an uncritical acquiescence or fright in Muslim societies as a result of the interaction between these societies and the contemporary Western powers that represent modernity and postmodernity on the global stage. The rise of fundamentalism, a tendency toward returning to the roots and stringently insisting upon some pure and literal interpretation of them, in almost all the religions of the world is a manifestation (...) of this fright. The central concern of this article is to suggest that fundamentalism is neither the only nor the most reasonable response for Muslim societies in the face of contemporary modernity. Muslims need to adopt an independent and critical attitude toward modernity and reshape their societies in the light of the ethics of the Qur’an, keeping in view the historical link between Islam and science in as much as Islamic culture paved the way for emergence of modern science during European Renaissance. The necessity of a pluralistic or contextualized modernization of Muslim societies is discussed along with the need for the removal of cultural duplicity in the role of the West in relation to Muslim societies. All this leads to an overall proposal for modernization which is given towards the end. (shrink)

Abstract: In this study, we explore the possibility of classifying the plant species. We collected the plant species from Kaggle website. This dataset encompasses 544 samples, encompassing 136 distinct plant species. Recent advancements in machine learning, particularly Artificial Neural Networks (ANNs), offer promise in enhancing plant Species classification accuracy and efficiency. This research explores plant Species classification, harnessing neural networks' power. Utilizing a rich dataset from Kaggle, containing 544 entries, we develop and evaluate a neural network model. Our neural network, (...) featuring a single hidden layer, achieves remarkable results—a staggering 100% accuracy and a minute average error rate of 0.002. Beyond performance metrics, we delve into the intricacies of plant Species classification through feature importance analysis. The most influential features— Vegsout, durflow, semiros, pdias, begflow, wind, leafy, autopoll and insects— uncover the physiological traits underpinning accurate rice classification. This research contributes to advancing rice classification methods and highlights the potential of ANNs in optimizing agricultural practices, ensuring plant safety, and bolstering global trade. (shrink)

The study aimed to identify the relationship between correcting the deviations in the measurement of performance and achieving the objectives of control and the performance of the job at the Islamic University in the Gaza Strip. To achieve the objectives of the research, the researchers used the descriptive analytical approach to collect information. The questionnaire consisted of (20) statements distributed to three categories of employees of the Islamic University (senior management, faculty members, their assistants and members of the administrative board). (...) A random sample of 314 employees was selected and 276 responses were retrieved with a recovery rate of 88.1%. The Statistical Analysis Program (SPSS) was used to enter, process, and analyze the data. The results of the study showed a positive relationship between correcting deviations in performance measurement and achieving the control objectives represented by the functional performance in the Islamic University from the point of view of the members (senior management, faculty and their assistants, and the administrative board), where the relative weight of all the paragraphs was (74.25%). The study recommended the need to ensure that the actual performance of the planned performance is matched and decisions are taken to correct the serious deviations and take the necessary measures in terms of retraining and change in regulations, wages and bonuses and punishment of the culprit, neglect and negligence by mistake. (shrink)

In the General Psychopathology Jaspers famously draws a distinction between the understandable and explainable. Meaningful connections between psychic events, he argues, can only be understood empathetically and cannot be explained causally. The idea behind this distinction, according to some interpreters at least, seems to be that psychic events do not fall under any general causal rules whereas ordinary events do fall under such rules. Also Jaspers distinguishes empathetic understanding of the connection between two psychic events from a mere interpretation of (...) it, which may turn out to be false. Hence, understanding seems to be able to give us the truth about the connection and is factive as well as self-evident in nature. Contemporary epistemologists, such as Linda Zagzebsky, Duncan Pritchard, and Jonathan Kvanvig, for example, distinguish three varieties: propositional, objectual or holistic, and atomistic understanding. They do not agree on factivity and transparency of understanding. What then is the difference between their views and that of Jaspers? This essay compares recent epistemological views of understanding with those of Jaspers and critiques his claims about empathetic understanding as being both factive and self-evident or transparent; to show that empathetic understanding of connections between psychic events needs a public criterion for its individuation. (shrink)

The study aimed to identify the role of measuring and evaluating performance in achieving the objectives of control and the performance of the job at the Islamic University in Gaza Strip. To achieve the objectives of the research, the researchers used the descriptive analytical approach to collect information which is the questionnaire that consisted of (22) phrases were distributed to three categories of employees of the Islamic University (Faculty Members and Their Assistants, Members of the Administrative Board, Senior Management). A (...) random sample of (314) employees was selected and 276 responses were retrieved with a recovery rate of 88.1%. The Statistical Analysis Program (SPSS) was used to enter process and analyze the data. The results of the research showed a positive role between measuring and evaluating the performance and achieving the objectives of the control of performance in the Islamic University from the point of view of the members (senior management, faculty and their assistants, and members of administrative board). The researchers also recommended a number of recommendations, most notably the provision of an appropriate level of the elements of the control systems today through the modernization and continuous development of performance measures and the need to provide the physical and financial resources necessary to continue the development and achievement within the university, to expand the development of technology in the various activities of the university through the construction of a complete and integrated system to support supervision systems in the university to suit the size of the university. The researchers also recommended following up and reviewing the performance measures and work to modify them in line with the mission and the goals of the university that it seeks to reach. (shrink)

Abstract: The integration of Artificial Intelligence (AI) into medical imaging represents a transformative shift in healthcare, offering significant improvements in diagnostic accuracy, efficiency, and patient outcomes. This paper explores the application of AI technologies in the analysis of medical images, focusing on techniques such as convolutional neural networks (CNNs) and deep learning models. We discuss how these technologies are applied to various imaging modalities, including X-rays, MRIs, and CT scans, to enhance disease detection, image segmentation, and diagnostic support. Additionally, the (...) paper addresses the challenges faced in AI-driven medical imaging, including data quality, model interpretability, and ethical considerations. By examining recent advancements and real-world case studies, this paper provides insights into the current state of AI in medical imaging and its potential future directions. The findings highlight the ongoing evolution of AI technologies and their crucial role in advancing medical diagnostics and treatment strategies. (shrink)

According to the literature review, there is much room for improvement of college student retention. The aim of this research is to evaluate the possibility of using deep and machine learning algorithms to predict whether students continue to attend college or will stop attending college. In this research a feature assessment is done on the dataset available from Kaggle depository. The performance of 20 learning supervised machine learning algorithms and one deep learning algorithm is evaluated. The algorithms are trained using (...) 11 features from 1000 records of previous student registrations that have been enrolled in college. The best performing classifier after tuning the parameters was NuSVC. It achieved Accuracy (91.00%), Precision (91.00%), Recall (91.00%), F1-score (91.00%), and time required for training and testing (0.04 second). Additionally, the proposed DL algorithm scored: Accuracy (93.00%), Precision (93.00%), Recall (93.00%), F1-score (93.00%), time required for training and testing (0.66 second) for predicting whether student will continue to attend college or not. (shrink)

Abstract: Lung cancer is the top reason of cancer-associated deaths globally. Surgery is the typical treatment for early-stage non-small cell lung cancer (NSCLC). Advancement in the knowledge of the biology of non-small cell lung cancer has shown molecular evidence used for systemic cancer therapy aiming metastatic disease, with a significant impact on patients’ overall survival (OS) and eminence of life. Though, a biopsy of overt metastases is an invasive technique restricted to assured positions and not effortlessly satisfactory in the clinic. (...) The examination of peripheral blood samples of cancer patients embodies a new basis of cancer-derived material, recognized as liquid biopsy, and its constituents (circulating tumour cells (CTCS), circulating free DNA (cfDNA), exosomes, and tumour-educated platelets (TEP)) may be gotten from nearly any body liquids. These constituents have shown to imitate features of the status of both the primary and metastatic diseases, aiding the clinicians to go towards a tailored medicine. In this paper, the reasons of lung cancer will be recognized and the risk elements that initiated the increase of infection, for instance Smoking, Disclosure to secondhand smoke, Disclosure to radon gas, Disclosure to asbestos and other compounds, Family past history of lung cancer, and decrease of the spread of disease and approaches of handling and prevention of lung cancer. (shrink)

This study aimed to identify the role of strategic leadership in activating time management strategies to enhance administrative creativity skills at Al-Azhar University. The sample of the study was random stratified sample from (245) administrative employees using questionnaire as a main tool for primary data collection. Total respondent were (112) questioners. Descriptive and quantitative approach used in this study. The general results of the study showed high levels of strategic leadership at Al-Azhar University, average level of application of time management (...) strategies and administrative creativity. This means there is acceptance approval that there is a statistically significant relationship between strategic leadership and time management strategies in Palestinian universities in Gaza Strip with a correlation level (0.724). Also, there is a statistically significant relationship between time management strategies and administrative creativity in Palestinian universities in Gaza Strip under study with a correlation level (0.848). According to static analysis, there is a statistically significant relationship between the dimensions of strategic leadership and administrative creativity in Palestinian universities in Gaza Strip under study, with a level of correlation (0.767%). This leases to high investment process for all available factors and elements in order to maximize and increase production and eliminate waste, wasted and unexploited employees' time and capabilities, which leads to achieving more effectiveness, positivity, productivity and increased organized effort. The study recommended necessity of having the elements of strategic academic leadership and activating time management strategies towards enhancing administrative creativity among workers in Palestinian universities in Gaza Strip. Also study recommended to encourage, support, and reward personal initiatives and creative ideas. Also study recommended available of wise and conscious strategic leadership to rationalize the behavior of individuals, mobilize their energies, mobilize their capabilities, coordinate their efforts, organize their affairs and direct them in the right direction towards achieving the desired goals and objectives. (shrink)

This study assessed the administration of punishment, students’ test anxiety, and performance in mathematics in secondary schools of Cross River State. Three null hypotheses were formulated following a correlational research design. Proportionate stratified random sampling technique was employed in selecting a sample of 2,554 respondents representing 5% of the population of 51,097 junior secondary school students distributed across 271 public secondary schools in Cross River State. Administration of Punishment Questionnaire (APQ) designed by the researchers, Test Anxiety Inventory (TAI) developed by (...) Dawood et al., (2016), and Mathematics Achievement Test (MAT) designed by Owan (2012), were used as instruments for data collection. The null hypotheses were tested using one-way MANOVA), Pearson Product Moment Correlation, and Multiple regression analyses with the aid of SPSS v23. Findings revealed amongst others that administration of punishment has a significant influence on students’ test anxiety and performance in mathematics F (6, 5098) = 24.149, p<.05; Wilk’s Λ = 0.945, partial η2 = .028 on a joint basis; administration of punishment has a significant influence respectively on students’ test anxiety F (3, 2550) = 22.697, p<.0005, partial η2 =.026 and performance in mathematics F (3, 2550) = 23.090, P<.0005, partial η2 =.026; there is an inverse significant relationship (r= -339, p<0.05) between students’ tests anxiety and performance in mathematics. It was recommended that the use of corporal punishment should be totally abolished on strict grounds that it hurts the psychological disposition of learners resulting in a dip in their performance consequently. (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 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)