A reasoned argument or tarka is essential for a wholesome vāda that aims at establishing the truth. A strong tarka constitutes of a number of elements including an anumāna based on a valid hetu. Several scholars, such as Dharmakīrti, Vasubandhu and Dignāga, have worked on theories for the establishment of a valid hetu to distinguish it from an invalid one. This paper aims to interpret Dignāga’s hetu-cakra, called the wheel of grounds, from a modern philosophical perspective by deconstructing it into (...) a simple probabilistic mathematical model. The objective is to understand how and why a vāda based on a probabilistically weaker hetu can degrade into a Jalpa or vitaṇḍā. To do so, the paper maps the concept of ‘Bounded Rationality’ onto the hetu-cakra. Bounded Rationality, an idea coined by the management thinker Herbert Simon, is often employed in understanding decision-making processes of rational agents. In the context of this paper, the concept would state that the prativādin and ālocaka (debater) may not hold unbounded information to back their pratijñā (proposition). The paper argues that within the probabilistically deconstructed hetu-cakra model, most people argue in the ‘Zone of Bounded Rationality’, and thus, the probability of a debate degrading into Jalpa or vitaṇḍā is high. -/- . (shrink)

So-called ‘distinctively mathematical explanations’ (DMEs) are said to explain physical phenomena, not in terms of contingent causal laws, but rather in terms of mathematical necessities that constrain the physical system in question. Lange argues that the existence of four or more equilibrium positions of any double pendulum has a DME. Here we refute both Lange’s claim itself and a strengthened and extended version of the claim that would pertain to any n-tuple pendulum system on the ground that such explanations are (...) actually causal explanations in disguise and their associated modal conditionals are not general enough to explain the said features of such dynamical systems. We argue and show that if circumscribing the antecedent for a necessarily true conditional in such explanations involves making a causal analysis of the problem, then the resulting explanation is not distinctively mathematical or non-causal. Our argument generalises to other dynamical systems that may have purported DMEs analogous to the one proposed by Lange, and even to some other counterfactual accounts of non-causal explanation given by Reutlinger and Rice. (shrink)

It is often argued that the indispensability of continuum models comes from their empirical adequacy despite their decoupling from the microscopic details of the modelled physical system. There is thus a commonly held misconception that temperature varying across a region of space or time can always be accurately represented as a continuous function. We discuss three inter-related cases of temperature modelling — in phase transitions, thermal boundary resistance and slip flows — and show that the continuum view is fallacious on (...) the ground that the microscopic details of a physical system are not necessarily decoupled from continuum models. We show how temperature discontinuities are present in both data (experiments and simulations) and phenomena (theory and models) and how discontinuum models of temperature variation may have greater empirical adequacy and explanatory power. The conclusions of our paper are: a) continuum idealisations are not indispensable to modelling physical phenomena and both continuous and discontinuous representations of phenomena work depending on the context; b) temperature is not necessarily a continuously defined function in our best scientific representations of the world; and c) that its continuity, where applicable, is a contingent matter. We also raise a question as to whether discontinuous representations should be considered truly de-idealised descriptions of physical phenomena. (shrink)

Modelling ethics is critical to understanding and analysing social phenomena. However, prior literature either incorporates ethics into agent strategies or uses it for evaluation of agent behaviour. This work proposes a framework that models both, ethical decision making as well as evaluation using virtue ethics and utilitarianism. In an iteration, agents can use either the classical Continuous Prisoner's Dilemma or a new type of interaction called moral interaction, where agents donate or steal from other agents. We introduce moral interactions to (...) model ethical decision making. We also propose a novel agent type, called virtue agent, parametrised by the agent's level of ethics. Virtue agents' decisions are based on moral evaluations of past interactions. Our simulations show that unethical agents make short term gains but are less prosperous in the long run. We find that in societies with positivity bias, unethical agents have high incentive to become ethical. The opposite is true of societies with negativity bias. We also evaluate the ethicality of existing strategies and compare them to those of virtue agents. (shrink)

The study of Vedas has been an ongoing endeavor for centuries with various interpretations made to understand their essence. A commentary by Sri Aurobindo on Rigveda discussed in his book "The Secret of the Veda" is considered to provide a deeper understanding of the teachings of the Vedas in a contemporary context, as it removes difficulties posed by the ancient form of Sanskrit and interpretations done over different times and contexts. This recomprehension of the Vedas aims to change the perception (...) of the Vedas from being a collection of nonsensical hymns to a more insightful and profound collection of teachings, drawing upon the works of modern scholars of Sanskrit. In this text, we aim to encapsulate the interpretation of Sri Aurobindo in a chapter form so that it becomes accessible to the general audience. (shrink)

There is a major debate as to whether there are non-causal mathematical explanations of physical facts that show how the facts under question arise from a degree of mathematical necessity considered stronger than that of contingent causal laws. We focus on Marc Lange’s account of distinctively mathematical explanations to argue that purported mathematical explanations are essentially causal explanations in disguise and are no different from ordinary applications of mathematics. This is because these explanations work not by appealing to what the (...) world must be like as a matter of mathematical necessity but by appealing to various contingent causal facts. (shrink)

This research explores a theoretical concept: the idea that by controlling entropy, we may be able to control the flow of time. In classical physics, time is known to move forward because entropy the measure of disorder in a system naturally increases. This study proposes a new framework in which entropy is treated as a controllable variable, and time becomes a consequence of its behavior. A mathematical model is introduced, where a control function f(t) determines how entropy changes over time. (...) Based on this, different scenarios emerge: increasing entropy leads to forward time, constant entropy results in frozen time, decreasing entropy may cause time reversal, and entropy reaching zero could reset the universe to its most ordered state. The model is entirely theoretical but opens new possibilities in thermodynamics, cosmology, and quantum mechanics. Although this idea challenges the Second Law of Thermodynamics and has no experimental support yet, it aligns with speculative areas of physics that deal with black holes, information theory, and the early universe. Future research may explore these concepts in quantum systems, simulated environments, or theoretical cosmological models. This paper offers a fresh perspective on how we understand time and its relationship to entropy, encouraging further exploration and dialogue in advanced theoretical physics. Keywords: Entropy, Time travel, Entropy control, Arrow of time, Thermodynamics, Entropy- time relationship, Mathematical modeling. (shrink)

As cloud computing continues to dominate modern IT infrastructure, ensuring its security remains a primary concern. Traditional security mechanisms often fall short in protecting high-performance cloud systems against sophisticated cyber-attacks, data breaches, and unauthorized access. Blockchain technology, with its decentralized and immutable nature, has emerged as a promising solution to enhance the security of cloud environments. This paper explores the potential of blockchain technologies in securing high-performance cloud systems, focusing on aspects such as data integrity, secure transactions, access control, and (...) transparency. We discuss how blockchain can address challenges such as centralized vulnerabilities, trust issues, and latency concerns in cloud systems. Through a comparative analysis of blockchain-based security models and traditional cloud security methods, we evaluate the feasibility, benefits, and limitations of blockchain adoption in high-performance cloud environments. Our findings suggest that integrating blockchain with cloud systems can significantly improve security without compromising performance. (shrink)

The increasing number of smart devices in the Internet of Things (IoT) has led to a surge in cyber- attacks, posing significant security risks to personal and industrial systems. Traditional centralized intrusion detection systems (IDS) often face challenges related to privacy, scalability, and the heterogeneity of data generated by smart devices. This paper introduces a novel approach, Federated Learning (FL) for smart device security, to address these challenges. By utilizing FL, multiple smart devices can collaboratively learn a shared intrusion detection (...) model without exposing their raw data, ensuring privacy while improving detection accuracy. This paper presents the architecture of a federated intrusion detection system (FIDS), explores various FL algorithms suitable for smart device security, and evaluates the performance of the proposed system using real-world IoT datasets. The results show that the federated approach achieves comparable or even superior performance in detecting intrusions while preserving data privacy and reducing communication overhead. This paper concludes that federated learning has the potential to revolutionize smart device security by enabling decentralized, scalable, and privacy-preserving intrusion detection systems. (shrink)

Job enrichment atau pengayaan pekerjaan, merupakan salah satu prinsip dalam manajemen, khususnya di bidang manajemen sumber daya manusia, yang hadir dengan sebuah klaim : bahwa hal ini dilakukan dengan tujuan agar pekerja merasa pekerjaannya lebih bermanfaat, lebih menarik, dan lebih menantang serta menyenangkan. Pertanyaan yang muncul dalam situasi yang sensitif terhadap kelas sosial adalah; apakah job enrichment benar-benar memberikan kesempatan bagi manusia untuk berkembang (dan oleh karenanya menjadi terbebaskan), atau hanya sekadar istilah pengganti untuk “eksploitasi”? Dengan pendekatan filsafat Neo-Marxist, makalah (...) ini akan mencoba untuk menjawab; 1) Realitas eksploitasi yang dilakukan korporasi; 2) Akar “kekerasan” Manajemen dalam relasi borjuis – proletar, dan legitimasi ilmu pengetahuan; dan 3) Hubungan prinsip job enrichment dan Marxisme sebagai ideologi pembebasan. Dengan metode filsafat tulisan ini menghasilkan argumen bahwa; pertama, manajemen sebagai keahlian memiliki akar historis yang lekat dengan hegemoni kelas borjuis terhadap kelas pekerja. Kedua, manajemen sebagai ilmu pengetahuan diinspirasi oleh dorongan akan efektiftas perbudakan. Jejak-jejak watak represif ini ditunjukkan oleh beragam ekploitasi yang dilakukan oleh jejaring borjuasi - perusahaan, korporat, dan bentuk perkongsian kapitalistik lainnya – sebagai sebuah bentuk “the dark side of management”. Meski masih berada di bawah bayang-bayang produksi kapitalisme – job enrichment – merupakan moda kerja yang paling tidak, cukup mendekati emansipasi sebagaimana yang dimaksud oleh Marx. (shrink)

Time is something that humans naturally sense we feel it passing through our experiences, memories, and daily routines. This sense of time is closely connected to the idea of entropy, which in physics refers to the amount of disorder or randomness in a system. As time passes, things tend to become more disordered, and this increase in entropy helps us perceive the flow of time. But what about machines? Can artificial systems like AI or robots have any kind of time (...) perception? While machines do not feel or experience time the way humans do, this paper explores a new idea: machines might be able to simulate a kind of “sense” of time by observing how entropy changes within their systems. We propose a model called the Synthetic Entropy Clock, where a machine watches how much internal disorder (entropy) increases or decreases. For example: • If entropy increases over time, the machine interprets that as time moving forward. • If entropy stays the same, it feels like time is frozen. • If entropy is reduced, such as through resetting memory or compressing data, the system might treat that as time going backward. This idea connects with how humans perceive time (through memory and brain activity) and offers a new way for machines to measure or respond to time in a more intelligent and adaptive way. It also links to broader theories about how time might be manipulated by controlling entropy. In summary, this paper presents a fresh way of thinking about time in artificial systems by using entropy as a tool to simulate temporal awareness. This could lead to new designs for AI systems that are more aware of their own internal states over time, and even open up discussions about using entropy to influence how machines experience or manipulate time itself. Keywords: Entropy, Time perception, Artificial intelligence, Synthetic entropy clock, Temporal awareness, Information theory, Thermodynamics of computation, Autonomous systems, Entropy- based timekeeping, Time manipulation theories. (shrink)

As global manufacturing industries evolve, the demand for smarter, more efficient, and predictive production systems is intensifying. The integration of analyzer instrumentation with Artificial Intelligence (AI) in manufacturing environments presents a transformative opportunity to optimize processes, enhance product quality, and reduce operational costs. This research explores the convergence of analyzer technologies and AI-driven automation to create predictive manufacturing ecosystems. Through the use of smart sensors, real-time data analytics, and machine learning algorithms, modern manufacturing setups are becoming increasingly self-aware, adaptive, and (...) proactive. This paper reviews current advancements in analyzer instrumentation—such as gas chromatographs, spectrometers, and thermal analyzers—coupled with AI applications like predictive maintenance, quality forecasting, and anomaly detection. It also investigates key case studies from industries such as pharmaceuticals, automotive, and petrochemicals, highlighting how real-time monitoring and AI-based decision-making are reshaping production efficiency. The study utilizes a qualitative methodology, including a literature review and selected case analysis, to assess the benefits and challenges of these technologies. Findings reveal that predictive process optimization leads to significant improvements in throughput, energy consumption, and defect reduction. However, successful integration relies heavily on data quality, sensor accuracy, and workforce adaptability. The paper concludes by proposing a roadmap for industries aiming to transition toward nextgen manufacturing through AI-integrated analyzer instrumentation, emphasizing strategic planning, cross-disciplinary collaboration, and continuous learning. (shrink)

Using cutting-edge technologies like artificial intelligence (AI), machine learning and Bluetooth connectivity, this paper introduces a state-of-the-art assistive device made especially for blind and visually impaired people. The primary objective of the device is to enhance user mobility, safety and independence in navigating public spaces. Key features include Al-powered real-time navigation, camera-based text recognition and audio feedback, as well as emergency SOS functionality to address critical situations. The Al system processes environmental data through integrated sensors and cameras, providing auditory feedback (...) and voice-assisted navigation to guide users effectively. Bluetooth connectivity enables seamless integration with smartphones and other compatible devices, enhancing accessibility in smart environments. The device’s capacity to instantaneously recognize and vocalize text from signs, labels and papers promises to empower users in daily activities. Security and privacy are prioritized through encrypted data transmission and customized settings. The benefits of this method are compared to those of current technologies based on attributes like ease of use, real-time responsiveness, and user independence. The latest developments in wearable assistive technology are highlighted in a thorough literature review, with an emphasis on user-centered design and useful AI applications for people with visual impairments. The findings suggest that the proposed device could significantly improve the quality of life for blind and visually impaired individuals by offering an intuitive and reliable tool for independent navigation and information access. (shrink)

The integration of performance optimization techniques in cloud security is increasingly becoming essential as businesses leverage cloud environments to store, manage, and process data. Cloud computing offers a multitude of advantages such as scalability, flexibility, and cost efficiency; however, it also exposes organizations to various security threats. This paper explores the latest trends in cloud security and investigates how performance optimization techniques can enhance security while ensuring minimal impact on system performance. By reviewing current research and emerging technologies, we propose (...) a framework for combining security and performance optimization strategies, emphasizing machine learning, cryptography, and automated threat detection systems. We also examine the role of virtualization and containerization in cloud security. The findings indicate that with the right balance, performance and security can coexist without compromising the quality of service. (shrink)

Generative AI has rapidly advanced in recent years, producing impressive outcomes across various domains such as art, music, writing, and design. While much of this progress is attributed to deep learning techniques like GANs (Generative Adversarial Networks) and VAEs (Variational Autoencoders), reinforcement learning (RL) has emerged as a promising approach for enhancing the creative potential of generative models. By framing content generation as a sequential decision-making process, RL enables AI models to improve through interaction with their environment, receiving feedback in (...) the form of rewards or penalties. This ability to learn through trial and error closely mirrors human creativity, where experimentation and feedback drive improvement. In this paper, we explore the intersection of reinforcement learning (RL) and generative AI, examining how RL techniques can be applied to enhance the creative capabilities of AI models. Unlike supervised learning, which requires large labeled datasets, reinforcement learning allows AI to learn in environments where direct supervision is minimal or absent. This opens up possibilities for AI to autonomously generate novel content in an iterative, adaptive manner. By using reward signals to guide the learning process, generative AI models can explore a wider range of possibilities, fostering creativity and novelty. We delve into various techniques within reinforcement learning, such as policy gradient methods, Q-learning, and actor-critic architectures, to understand how these methods contribute to the creativity of generative models. Case studies and applications from diverse fields, such as image generation, music composition, and game design, demonstrate the practical utility of combining RL and generative AI. Ultimately, this paper argues that reinforcement learning holds immense potential for training machines not just to replicate human creativity, but to push the boundaries of it. (shrink)

As statistics is the backbone of the digital financial system dependence on centralized cloud storage structures makes users prone to troubles concerning statistics breaches operational price and lack of control this paper examines the deployment of a decentralized cloud storage DCS framework with the use of interplanetary file system IPFS and Ethereum blockchain clever contracts to triumph over those drawbacks the gadget proposed here improves protection and information availability by incorporating aes-256 encryption sharding of records and decentralized metadata control by (...) the introduction of a working prototype based on react.js, Ethereum wallet, ether.js and solidity this mission illustrates the viability of a decentralized statistics garage whilst resolving troubles with latency user adoption and value effectiveness experimental consequences affirm enhancements in safety and availability establishing a strong platform for additional research on decentralized storage architectures. (shrink)

The use of tobacco is a major cause of preventable mortality. The estimated number of smokers is 1.1 billion. Of these, 700 million men and 100 million women are in developing countries. The objective of this study was to find out attitude towards tobacco consumption among residents of Dhankuta Municipality. The cross sectional study was conducted among the residents of Dhankuta Municipality where 205 households were taken as subjects. Pretested semi structured questionnaire was administered to the study subjects and face (...) to face interview was conducted. The collected data was entered in MS Excel 2000. The quantitative data was analyzed using Statistical Package for the Social Sciences SPSS software package. The study subjects consist of 50.2 of male and 49.8 of female. Regarding respondent's education, study population showed high level of SLC and above 40.5 followed by below SLC 36.1 and very less was illiterate 14.1 . Majority of the respondents think that there should be ban of the advertising of tobacco products 87.3 and smoking in public places 79 . Almost 67 of respondents think that patient's chances of quitting smoking will be increased if health professionals will give advice to patients. Almost 72.6 of the study population feel cut down tobacco use and 80.3 feel guilty about this habit. Almost 65.8 have tried to discontinue tobacco consumption. We conclude that the residents of Dhankuta reflect good attitude towards cessation of tobacco but poor practice to prevent of tobacco consumption. Dr. Ram Bilakshan Sah | Jha N "Attitude towards tobacco consumption among residents of Dhankuta Municipality of Nepal" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-1 | Issue-4 , June 2017. (shrink)

Built-in decision thresholds for AI diagnostics are ethically problematic, as patients may differ in their attitudes about the risk of false-positive and false-negative results, which will require that clinicians assess patient values.

Meta-learning, or learning to learn, has emerged as a powerful paradigm for creating adaptive models that can quickly adapt to new tasks with minimal data. In the context of personalized healthcare, meta-learning holds the potential to revolutionize precision medicine by enabling models that can personalize treatments based on individual characteristics. These models can leverage prior knowledge across multiple patients or conditions to provide rapid and accurate predictions for new patients, improving the efficiency and effectiveness of healthcare delivery. This paper explores (...) how meta-learning techniques can be applied to personalized healthcare, addressing the challenges of patient variability, data scarcity, and the need for individualized predictions. We also discuss several meta-learning strategies, such as Model-Agnostic Meta-Learning (MAML) and Prototypical Networks, and their integration into healthcare systems. Furthermore, we present case studies in areas like chronic disease management and treatment recommendation, highlighting the promise of meta-learning in precision medicine. (shrink)

The increase in number of vehicles on the road is being observed day by day, and the responsibilities that should be upheld by vehicle owners are frequently neglected. To ensure that the rules defined by the RTO are adhered to by every vehicle owner, the "Vehicle Surveillance System using deep learning" is proposed. This system is designed to capture vehicle data through web-app, with the identification of vehicles being achieved through the recognition of their number plates, and the extraction of (...) characters from the plates. Once the vehicle's number plate is recognized, the vehicle's information and owner's details will be verified with RTO data using Application programming interface (API). If any unfulfilled criteria are identified by the system, a notification will be generated. Vehicle detection is carried out using the Common Objects in Context Single Shot MultiBox Detection (COCOSSD) model, while the Russian model is utilized for number plate recognition. The extraction of characters from the number plate is executed through Optical Character Recognition (OCR), which includes character extraction and segmentation. (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 eighth volume of Collected Papers includes 75 papers comprising 973 pages on (theoretic and applied) neutrosophics, written between 2010-2022 by the author alone or in collaboration with the following 102 co-authors (alphabetically ordered) from 24 countries: Mohamed Abdel-Basset, Abduallah Gamal, Firoz Ahmad, Ahmad Yusuf Adhami, Ahmed B. Al-Nafee, Ali Hassan, Mumtaz Ali, Akbar Rezaei, Assia Bakali, Ayoub Bahnasse, Azeddine Elhassouny, Durga Banerjee, Romualdas Bausys, Mircea Boșcoianu, Traian Alexandru Buda, Bui Cong Cuong, Emilia Calefariu, Ahmet Çevik, Chang Su Kim, Victor (...) Christianto, Dae Wan Kim, Daud Ahmad, Arindam Dey, Partha Pratim Dey, Mamouni Dhar, H. A. Elagamy, Ahmed K. Essa, Sudipta Gayen, Bibhas C. Giri, Daniela Gîfu, Noel Batista Hernández, Hojjatollah Farahani, Huda E. Khalid, Irfan Deli, Saeid Jafari, Tèmítópé Gbóláhàn Jaíyéolá, Sripati Jha, Sudan Jha, Ilanthenral Kandasamy, W.B. Vasantha Kandasamy, Darjan Karabašević, M. Karthika, Kawther F. Alhasan, Giruta Kazakeviciute-Januskeviciene, Qaisar Khan, Kishore Kumar P K, Prem Kumar Singh, Ranjan Kumar, Maikel Leyva-Vázquez, Mahmoud Ismail, Tahir Mahmood, Hafsa Masood Malik, Mohammad Abobala, Mai Mohamed, Gunasekaran Manogaran, Seema Mehra, Kalyan Mondal, Mohamed Talea, Mullai Murugappan, Muhammad Akram, Muhammad Aslam Malik, Muhammad Khalid Mahmood, Nivetha Martin, Durga Nagarajan, Nguyen Van Dinh, Nguyen Xuan Thao, Lewis Nkenyereya, Jagan M. Obbineni, M. Parimala, S. K. Patro, Peide Liu, Pham Hong Phong, Surapati Pramanik, Gyanendra Prasad Joshi, Quek Shio Gai, R. Radha, A.A. Salama, S. Satham Hussain, Mehmet Șahin, Said Broumi, Ganeshsree Selvachandran, Selvaraj Ganesan, Shahbaz Ali, Shouzhen Zeng, Manjeet Singh, A. Stanis Arul Mary, Dragiša Stanujkić, Yusuf Șubaș, Rui-Pu Tan, Mirela Teodorescu, Selçuk Topal, Zenonas Turskis, Vakkas Uluçay, Norberto Valcárcel Izquierdo, V. Venkateswara Rao, Volkan Duran, Ying Li, Young Bae Jun, Wadei F. Al-Omeri, Jian-qiang Wang, Lihshing Leigh Wang, Edmundas Kazimieras Zavadskas. (shrink)

This twelfth volume of Collected Papers includes 86 papers comprising 976 pages on Neutrosophics Theory and Applications, published between 2013-2021 in the international journal and book series “Neutrosophic Sets and Systems” by the author alone or in collaboration with the following 112 co-authors (alphabetically ordered) from 21 countries: Abdel Nasser H. Zaied, Muhammad Akram, Bobin Albert, S. A. Alblowi, S. Anitha, Guennoun Asmae, Assia Bakali, Ayman M. Manie, Abdul Sami Awan, Azeddine Elhassouny, Erick González-Caballero, D. Dafik, Mithun Datta, Arindam Dey, (...) Mamouni Dhar, Christopher Dyer, Nur Ain Ebas, Mohamed Eisa, Ahmed K. Essa, Faruk Karaaslan, João Alcione Sganderla Figueiredo, Jorge Fernando Goyes García, N. Ramila Gandhi, Sudipta Gayen, Gustavo Alvarez Gómez, Sharon Dinarza Álvarez Gómez, Haitham A. El-Ghareeb, Hamiden Abd El-Wahed Khalifa, Masooma Raza Hashmi, Ibrahim M. Hezam, German Acurio Hidalgo, Le Hoang Son, R. Jahir Hussain, S. Satham Hussain, Ali Hussein Mahmood Al-Obaidi, Hays Hatem Imran, Nabeela Ishfaq, Saeid Jafari, R. Jansi, V. Jeyanthi, M. Jeyaraman, Sripati Jha, Jun Ye, W.B. Vasantha Kandasamy, Abdullah Kargın, J. Kavikumar, Kawther Fawzi Hamza Alhasan, Huda E. Khalid, Neha Andalleb Khalid, Mohsin Khalid, Madad Khan, D. Koley, Valeri Kroumov, Manoranjan Kumar Singh, Pavan Kumar, Prem Kumar Singh, Ranjan Kumar, Malayalan Lathamaheswari, A.N. Mangayarkkarasi, Carlos Rosero Martínez, Marvelio Alfaro Matos, Mai Mohamed, Nivetha Martin, Mohamed Abdel-Basset, Mohamed Talea, K. Mohana, Muhammad Irfan Ahamad, Rana Muhammad Zulqarnain, Muhammad Riaz, Muhammad Saeed, Muhammad Saqlain, Muhammad Shabir, Muhammad Zeeshan, Anjan Mukherjee, Mumtaz Ali, Deivanayagampillai Nagarajan, Iqra Nawaz, Munazza Naz, Roan Thi Ngan, Necati Olgun, Rodolfo González Ortega, P. Pandiammal, I. Pradeepa, R. Princy, Marcos David Oviedo Rodríguez, Jesús Estupiñán Ricardo, A. Rohini, Sabu Sebastian, Abhijit Saha, Mehmet Șahin, Said Broumi, Saima Anis, A.A. Salama, Ganeshsree Selvachandran, Seyed Ahmad Edalatpanah, Sajana Shaik, Soufiane Idbrahim, S. Sowndrarajan, Mohamed Talea, Ruipu Tan, Chalapathi Tekuri, Selçuk Topal, S. P. Tiwari, Vakkas Uluçay, Maikel Leyva Vázquez, Chinnadurai Veerappan, M. Venkatachalam, Luige Vlădăreanu, Ştefan Vlăduţescu, Young Bae Jun, Wadei F. Al-Omeri, Xiao Long Xin.‬‬‬‬‬‬. (shrink)

This tenth volume of Collected Papers includes 86 papers in English and Spanish languages comprising 972 pages, written between 2014-2022 by the author alone or in collaboration with the following 105 co-authors (alphabetically ordered) from 26 countries: Abu Sufian, Ali Hassan, Ali Safaa Sadiq, Anirudha Ghosh, Assia Bakali, Atiqe Ur Rahman, Laura Bogdan, Willem K.M. Brauers, Erick González Caballero, Fausto Cavallaro, Gavrilă Calefariu, T. Chalapathi, Victor Christianto, Mihaela Colhon, Sergiu Boris Cononovici, Mamoni Dhar, Irfan Deli, Rebeca Escobar-Jara, Alexandru Gal, N. (...) Gandotra, Sudipta Gayen, Vassilis C. Gerogiannis, Noel Batista Hernández, Hongnian Yu, Hongbo Wang, Mihaiela Iliescu, F. Nirmala Irudayam, Sripati Jha, Darjan Karabašević, T. Katican, Bakhtawar Ali Khan, Hina Khan, Volodymyr Krasnoholovets, R. Kiran Kumar, Manoranjan Kumar Singh, Ranjan Kumar, M. Lathamaheswari, Yasar Mahmood, Nivetha Martin, Adrian Mărgean, Octavian Melinte, Mingcong Deng, Marcel Migdalovici, Monika Moga, Sana Moin, Mohamed Abdel-Basset, Mohamed Elhoseny, Rehab Mohamed, Mohamed Talea, Kalyan Mondal, Muhammad Aslam, Muhammad Aslam Malik, Muhammad Ihsan, Muhammad Naveed Jafar, Muhammad Rayees Ahmad, Muhammad Saeed, Muhammad Saqlain, Muhammad Shabir, Mujahid Abbas, Mumtaz Ali, Radu I. Munteanu, Ghulam Murtaza, Munazza Naz, Tahsin Oner, ‪Gabrijela Popović‬‬‬‬‬, Surapati Pramanik, R. Priya, S.P. Priyadharshini, Midha Qayyum, Quang-Thinh Bui, Shazia Rana, Akbara Rezaei, Jesús Estupiñán Ricardo, Rıdvan Sahin, Saeeda Mirvakili, Said Broumi, A. A. Salama, Flavius Aurelian Sârbu, Ganeshsree Selvachandran, Javid Shabbir, Shio Gai Quek, Son Hoang Le, Florentin Smarandache, Dragiša Stanujkić, S. Sudha, Taha Yasin Ozturk, Zaigham Tahir, The Houw Iong, Ayse Topal, Alptekin Ulutaș, Maikel Yelandi Leyva Vázquez, Rizha Vitania, Luige Vlădăreanu, Victor Vlădăreanu, Ștefan Vlăduțescu, J. Vimala, Dan Valeriu Voinea, Adem Yolcu, Yongfei Feng, Abd El-Nasser H. Zaied, Edmundas Kazimieras Zavadskas.‬‬. (shrink)