Digital Commons Network^™

Green Ai-Enhanced Deep Learning Model For Breast Cancer Detection And Classification In Mammography Images: Bc-Net-512, Nesma Abd El-Mawla, Mohamed A. Berbar, Nawal A. El-Fishawy, Mohamed A. El-Rashidy

Mansoura Engineering Journal

This study champions a sustainable approach for developing a Deep Learning (DL) model for medical image analysis, specifically focusing on breast cancer (BC) detection in mammograms. By prioritizing low-computing algorithms to achieve high diagnostic accuracy while minimizing the model's environmental footprint, that aligns with the principles of Green AI. In this paper, an innovative architecture called BC-Net-512 was constructed for the classification of BC mammography. It is composed of lightweight Convolutional Neural Network (CNN) blocks for texture, density, and structure feature extraction and detection, a thin, fully connected layer for learning complex patterns and correlations in the extracted features, and …

A Comprehensive Review Of Dental Diseases Detection And Classification Based On Artificial Intelligence Techniques, Nermeen N. Noaman, Yasmin M. Alsakar, Naira E. Elazab, Waleed M. Mohamed, Mohamed E. Ezzat, Mohammed M. Elmogy

Mansoura Engineering Journal

In dentistry, many diseases, such as gum, cavities, and oral cancer, affect people of all ages. Early treatment and diagnosis are crucial for minimizing dental diseases' effect on overall health and saving money in the long run. Traditional dental diagnosis methods, such as manual probing and visual inspection, are time-consuming and can be subject to human errors. Hence, a computer-aided diagnosis system based on computer vision and artificial intelligence (AI) techniques is needed. The considerable progress in computer vision and AI techniques offers many possibilities in dental diagnosis based on dental X-ray imaging modalities. Dental X-rays are used to diagnose …

Retracted: A Novel Benchmarking Framework For Selecting The Best Deep Learning Model Diagnosing Covid-19 Based On New Development For Dual Mcdm Methods, Mahmood M. Salih, Yousif Raad Muhsen, M.A. Ahmed, Reem D. Ismael, Moceheb Lazam Shuwandy, Z.T. Al-Qaysi

Iraqi Journal for Computer Science and Mathematics

COVID-19 was diagnosed using deep learning models by a group of studies. Evaluating and benchmarking these models are essential to achieving the most suitable model for diagnosing coronavirus. Objective: In this investigation, we offer an inclusive valuation of several deep learning models to detect the maximum appropriate and active model which gratifies doctors' requirements and assessment criteria. Method: This study combines Fuzzy decision by the opinion score method (FDOSM) and Fuzzy-Weighted Zero-Inconsistency (FWZIC). According to the advantage of Trapezoidal Intuitionistic fuzzy, we developed FWZIC into Trapezoidal Intuitionistic fuzzy named (TrIF-FWZIC) for weighting criteria and FDOSM into Trapezoidal Intuitionistic fuzzy FDOSM …

The Permutation Annihilator Ideals In Commutative Permutation Bck–Algebras With Their Applications, Shuker Khalil, Ali Abbas Asmae

Iraqi Journal for Computer Science and Mathematics

This paper introduces new concepts such as permutation BCK--algebra, permutation involutory ideal, commutative permutation BCK--algebra, and prime permutation ideal. Additionally, their attributes are examined. This paper elucidates a method for determining a relationship between the chemical structure of atoms for the chemical element Cadmium, and some of our suggestions are given here. In this work, the structure of the sets 𝒜 and λ_n^β∗𝒜 are defined. Next, we show that if 𝒜 is a permutation ideal, then λ_n^β∗𝒜 is a permutation ideal that contains 𝒜. Also, in any commutative permutation BCK--algebra the …

Integrating Fuzzy Set Theory With Association Rule Mining For Advanced E-Commerce Recommendations, Hind Raad Ibraheem, Murtadha Mohammed Hamad

Iraqi Journal for Computer Science and Mathematics

The dynamic nature of e-commerce necessitates the adoption of cutting-edge technologies to improve the online shopping experience. Our research introduces a groundbreaking methodology called Fuzzy Association Rule Mining (FARM), combining fuzzy set theory with traditional Association Rule Mining (ARM). Unlike conventional ARM, which focuses solely on the frequency of jointly purchased items, FARM also considers the sold quantities, leveraging the Apriori algorithm to discern customer preferences from historical sales data across the UCI Online Retail II, Market Basket, and Movielens datasets. This hybrid of fuzzy set theory with ARM enables a better understanding of complicated consumer behaviors and associations between …

Chaotic-Encode Quantum Pso Algorithm For Flexible Job-Shop Scheduling Problem, Yuanxing Xu, Mengjian Zhang, Deguang Wang

Journal of System Simulation

Abstract: To solve the flexible job-shop scheduling problem (FJSP), a chaotic-encode quantum PSO (CQPSO) algorithm is proposed. Aiming at the premature convergence of particles to local optimum in standard QPSO, the methods for computing the adaptive contraction-expansion coefficient and mean best position using fitness values of associated particles are proposed to improve the global search ability of QPSO. Through chaotic boundary variation strategy, the probability of a large number of particles gathering at the boundary is reduced and the population diversity is increased to enhance the ability of searching the optimal solution. According to the iterative property of QPSO, a …

Development Of Hybrid Multi Criteria Decision Making Techniques For Efficient Cloud Service Selection, Obulaporam Gireesha

Theses and Dissertations

During the past few decades, cloud computing became a primary driver for the next generation of digital technology due to the increase in organizational performance and profitability based on a ‘pay-as-you-use’ fashion at anytime and anywhere across the globe. Cloud computing enables various enterprises to access pooled resources (like storage, network bandwidth, software applications, processing power, etc.) over the Internet with minimal Information Technology (IT) infrastructure and capital expenditure.

Indeed, the enormous popularity of cloud computing in both academia & industry over the decade has resulted in a wide range of similar cloud services offered by numerous service providers. Even …

A Fuzzy Group Decision-Making-Based Method For Green Supplier Selection And Order Allocation, Lu Liu, Wenxin Li, Xiao Song, Bingli Sun, Guanghong Gong

Journal of System Simulation

Abstract: With the intensity of market competitiveness, the worsening of the global environment, and the improvement of public concern about environmental protection, the issue of green purchasing has received considerable attention. The vast majority of existing studies on green purchasing have concentrated on supplier selection with green criteria, so as to realize sustainable operations, whereas it is more feasible and economical for businesses to obtain the proper products from adaptable and suitable suppliers at the right times, rates, and volumes, which is referred to as supplier selection and order allocation. To resolve the aforementioned two crucial challenges, we propose a …

Neutrosophic Adaptive Lsb And Deep Learning Hybrid Framework For Ecg Signal Classification, Abdallah Rezk, Ahmed S. Sakr, H. M. Abdulkader

Applied Mathematics & Information Sciences

This paper proposes a novel hybrid framework for ECG signal classification and privacy preservation. The framework includes two phases: the first phase uses LSTM+CNN with attention gate for ECG classification, while the second phase utilizes adaptive least signal bit with neutrosophic for hiding important data during transmission. The proposed framework converts data into three sets of degrees (true, false, and intermediate) using neutrosophic and passes them to an embedding layer. In the sender part, the framework hides important data in ECG signal as true and false degrees, using the intermediate set as a shared dynamic key between sender and receiver. …

Generalization Of Renyi’S Entropy And Its Application In Source Coding, Ashiq Hussain Bhat, Niyamat Ali Siddiqui, Ismail A Mageed, Shawkat Alkhazaleh, Vidyanand Rabi Das, M. A. K Baig

Applied Mathematics & Information Sciences

In this paper, we introduce a new generalization of Renyis entropy β(P) and the most important feature of this generalized entropy Rαβ (P) is that it derives most important entropies that are well known and influence information theory and applied mathematics. Some significant properties of Rαβ (P) has been undertaken in this article. In addition, we introduce a new generalized exponentiated mean codeword length Lβα (P) in this article then determine how Rβα (P) and Lβα (P) are related in terms of source coding theorem.

An Integrated Optimal Method For Cloud Service Ranking, Mohammad Hossein Nejat, Homayun Motameni, Hamed Vahdat-Nejad

Turkish Journal of Electrical Engineering and Computer Sciences

Many cloud providers present various services with different attributes. It is a complex, lengthy process to select a cloud service that meets user requirements from an assortment of services. At the same time, user requirements are sometimes defined with imprecision (sets or intervals), whereas it is also important to consider the quality of user feedback (QoU) and quality of service (QoS) attributes for ranking. Besides, each MADM method has a di erent procedure, which causes functional contradictions. These contradictions have led to confusion in choosing the best MADM method. It is necessary to provide a method that harmonizes the results. …

Brain Tumor Detection From Mri Images With Using Proposed Deep Learningmodel: The Partial Correlation-Based Channel Selection, Atinç Yilmaz

Turkish Journal of Electrical Engineering and Computer Sciences

A brain tumor is an abnormal growth of a mass or cell in the brain. Early diagnosis of the tumor significantly increases the chances of successful treatment. Artificial intelligence-based systems can detect the tumor in early stages. In this way, it could be possible to detect a tumor and resolve this problem that may endanger human life early. In the study, the partial correlation-based channel selection formula was presented that allowed the selection of the most prominent feature that differs from the other studies in the literature. Additionally, the multi-channel convolution structure was proposed for the feature network phase of …

A Novel Framework Using Neutrosophy For Integrated Speech And Text Sentiment Analysis, Florentin Smarandache, Kritika Mishra, Ilanthenral Kandasamy, Vasantha Kandasamy W.B.

Branch Mathematics and Statistics Faculty and Staff Publications

With increasing data on the Internet, it is becoming difficult to analyze every bit and make sure it can be used efficiently for all the businesses. One useful technique using Natural Language Processing (NLP) is sentiment analysis. Various algorithms can be used to classify textual data based on various scales ranging from just positive-negative, positive-neutral-negative to a wide spectrum of emotions. While a lot of work has been done on text, only a lesser amount of research has been done on audio datasets. An audio file contains more features that can be extracted from its amplitude and frequency than a …

Intelligent Algorithm For Trapezoidal Interval Valued Neutrosophic Network Analysis, Florentin Smarandache, Said Broumi, Deivanayagampillai Nagarajan, Malayalan Lathamaheswari, Mohamed Talea, Assia Bakali

Branch Mathematics and Statistics Faculty and Staff Publications

The shortest path problem has been one of the most fundamental practical problems in network analysis. One of the good algorithms is Bellman-Ford, which has been applied in network, for the last some years. Due to complexity in the decision-making process, the decision makers face complications to express their view and judgment with an exact number for single valued membership degrees under neutrosophic environment. Though the interval number is a special situation of the neutrosophic, it did not solve the shortest path problems in an absolute manner. Hence, in this work, the authors have introduced the score function and accuracy …

Computational Techniques In Medical Image Analysis Application For White Blood Cells Classification., Omar Dekhil

Electronic Theses and Dissertations

White blood cells play important rule in the human body immunity and any change in their count may cause serious diseases. In this study, a system is introduced for white blood cells localization and classification. The dataset used in this study is formed by two components, the first is the annotation dataset that will be used in the localization (364 images), and the second is labeled classes that will be used in the classification (12,444 images). For the localization, two approaches will be discussed, a classical approach and a deep learning based approach. For the classification, 5 different deep learning …

A Direct Data-Cluster Analysis Method Based On Neutrosophic Set Implication, Florentin Smarandache, Sudan Jha, Gyanendra Prasad Joshi, Lewis Nkenyereya, Dae Wan Kim

Branch Mathematics and Statistics Faculty and Staff Publications

Raw data are classified using clustering techniques in a reasonable manner to create disjoint clusters. A lot of clustering algorithms based on specific parameters have been proposed to access a high volume of datasets. This paper focuses on cluster analysis based on neutrosophic set implication, i.e., a k-means algorithm with a threshold-based clustering technique. This algorithm addresses the shortcomings of the k-means clustering algorithm by overcoming the limitations of the threshold-based clustering algorithm. To evaluate the validity of the proposed method, several validity measures and validity indices are applied to the Iris dataset (from the University of California, Irvine, Machine …

(Φ, Ψ)-Weak Contractions In Neutrosophic Cone Metric Spaces Via Fixed Point Theorems, Florentin Smarandache, Wadei F. Al-Omeri

Branch Mathematics and Statistics Faculty and Staff Publications

In this manuscript, we obtain common fixed point theorems in the neutrosophic cone metric space. Also, notion of (Φ, Ψ)-weak contraction is defined in the neutrosophic cone metric space by using the idea of altering distance function. Finally, we review many examples of cone metric spaces to verify some properties.

Large-Scale Green Supplier Selection Approach Under A Q-Rung Interval-Valued Orthopair Fuzzy Environment, Limei Liu, Wenzhi Cao, Biao Shi, Ming Tang

Articles

As enterprises pay more and more attention to environmental issues, the green supply chain management (GSCM) mode has been extensively utilized to guarantee profit and sustainable development. Greensupplierselection(GSS),whichisakeysegmentofGSCM,hasbeeninvestigated to put forward plenty of GSS approaches.

Neutrosophic Set Is A Generalization Of Intuitionistic Fuzzy Set, Inconsistent Intuitionistic Fuzzy Set (Picture Fuzzy Set, Ternary Fuzzy Set), Pythagorean Fuzzy Set, Q-Rung Orthopair Fuzzy Set, Spherical Fuzzy Set, And N-Hyperspherical Fuzzy Set, While Neutrosophication Is A Generalization Of Regret Theory, Grey System Theory, And Three-Ways Decision (Revisited), Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

In this paper we prove that Neutrosophic Set (NS) is an extension of Intuitionistic Fuzzy Set (IFS) no matter if the sum of single-valued neutrosophic components is < 1, or > 1, or = 1. For the case when the sum of components is 1 (as in IFS), after applying the neutrosophic aggregation operators one gets a different result from that of applying the intuitionistic fuzzy operators, since the intuitionistic fuzzy operators ignore the indeterminacy, while the neutrosophic aggregation operators take into consideration the indeterminacy at the same level as truth-membership and falsehood-nonmembership are taken. NS is also more flexible and effective because it …

Improvement Of The Material’S Mechanical Characteristics Using Intelligent Real Time Control Interfaces In Hfc Hardening Process, Florentin Smarandache, Luige Vladareanu, Mihaiela Iliescu, Victor Vladareanu, Alexandru Gal, Octavian Melinte, Adrian Margean

Branch Mathematics and Statistics Faculty and Staff Publications

The paper presents Intelligent Control (IC) Interfaces for real time control of mechatronic systems applied to Hardening Process Control (HPC) in order to improvement of the material’s mechanical characteristics. Implementation of IC laws in the intelligent real time control interfaces depends on the particular circumstances of the models characteristics used and the exact definition of optimization problem. The results led to the development of the IC interfaces in real time through Particle Swarm Optimization (PSO) and neural networks (NN) using off- line the regression methods.

Some Aggregation Operators For Bipolar-Valued Hesitant Fuzzy Information, Florentin Smarandache, Tahir Mahmood, Kifayat Ullah, Qaisar Khan

Branch Mathematics and Statistics Faculty and Staff Publications

In this article we define some aggregation operators for bipolar-valued hesitant fuzzy sets. These operations include bipolar-valued hesitant fuzzy ordered weighted averaging (BPVHFOWA) operator, bipolar-valued hesitant fuzzy ordered weighted geometric (BPVHFOWG) operator and their generalized forms. We also define hybrid aggregation operators and their generalized forms and solved a decision-making problem on these operation.

Special Issue: Neutrosophic Information Theory And Applications, Florentin Smarandache, Jun Ye

Branch Mathematics and Statistics Faculty and Staff Publications

Neutrosophiclogic,symboliclogic,set,probability,statistics,etc.,are,respectively,generalizations of fuzzy and intuitionistic fuzzy logic and set, classical and imprecise probability, classical statistics, and so on. Neutrosophic logic, symbol logic, and set are gaining significant attention in solving many real-life problems that involve uncertainty, impreciseness, vagueness, incompleteness, inconsistency, and indeterminacy. A number of new neutrosophic theories have been proposed and have been applied in computational intelligence, multiple-attribute decision making, image processing, medical diagnosis, fault diagnosis, optimization design, etc. This Special Issue gathers original research papers that report on the state of the art, as well as on recent advancements in neutrosophic information theory in soft computing, artificial intelligence, …

Fundamentals Of Neutrosophic Logic And Sets And Their Role In Artificial Intelligence (Fundamentos De La Lógica Y Los Conjuntos Neutrosóficos Y Su Papel En La Inteligencia Artificial ), Florentin Smarandache, Maykel Leyva-Vazquez

Branch Mathematics and Statistics Faculty and Staff Publications

Neutrosophy is a new branch of philosophy which studies the origin, nature and scope of neutralities. This has formed the basis for a series of mathematical theories that generalize the classical and fuzzy theories such as the neutrosophic sets and the neutrosophic logic. In the paper, the fundamental concepts related to neutrosophy and its antecedents are presented. Additionally, fundamental concepts of artificial intelligence will be defined and how neutrosophy has come to strengthen this discipline.

Modelo De Recomendación Basado En Conocimiento Y Números Svn, Maykel Leyva-Vazquez, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

Recommendation models are useful in the decision-making process that allow the user a set of options that are expected to meet their expectations. Recommendation models are useful in the decision-making process that offer the user a set of options that are expected to meet their SVN expectations to express linguistic terms.

A Lattice Theoretic Look: A Negated Approach To Adjectival (Intersective, Neutrosophic And Private) Phrases, Florentin Smarandache, Selcuk Topal

Branch Mathematics and Statistics Faculty and Staff Publications

No abstract provided.

Computation Of Shortest Path Problem In A Network With Sv-Triangular Neutrosophic Numbers, Florentin Smarandache, Said Broumi, Assia Bakali, Mohamed Talea

Branch Mathematics and Statistics Faculty and Staff Publications

In this article, we present an algorithm method for finding the shortest path length between a paired nodes on a network where the edge weights are characterized by single valued triangular neutrosophic numbers. The proposed algorithm gives the shortest shortest path length from source node to destination node based on a ranking method. Finally, a numerical example is also presented to illustrate the efficiency of the proposed approach.

An Operational View In Computational Construction Of Information, Florentin Smarandache, Stefan Vladutescu, Constantin Dima, Valeriu Voinea

Branch Mathematics and Statistics Faculty and Staff Publications

The paper aims to explain the technology of emergence of information. Our research proves that information as communicational product is the result of processing within some operations, actions, mechanisms and strategies of informational material meanings. Are determined eight computational-communicative operations of building information. Information occurs in two communication phases, syncretic and the segregation-synthetic. The syncretic phase consists of four operations: referral of significant field, primary delimitation of information, detection-looking information and an anticipative-draft constitution (feedforward). The segregation-synthetic phase also includes four operations: discrimination, identification, interpretation and confrontation (feedback). In the future we will investigate informational actions, mechanisms and strategies.

Applying Dijkstra Algorithm For Solving Neutrosophic Shortest Path Problem, Florentin Smarandache, Luige Vladareanu, Said Broumi, Assia Bakali, Muhammad Akram

Branch Mathematics and Statistics Faculty and Staff Publications

The selection of shortest path problem is one the classic problems in graph theory. In literature, many algorithms have been developed to provide a solution for shortest path problem in a network. One of common algorithms in solving shortest path problem is Dijkstra’s algorithm. In this paper, Dijkstra’s algorithm has been redesigned to handle the case in which most of parameters of a network are uncertain and given in terms of neutrosophic numbers. Finally, a numerical example is given to explain the proposed algorithm.

Neutrosophic Logic Approaches Applied To ”Rabot” Real Time Control, Alexandru Gal, Luige Vladareanu, Florentin Smarandache, Hongnian Yu, Mincong Deng

Branch Mathematics and Statistics Faculty and Staff Publications

In this paper we present a way of deciding which control law should operate at a time for a mobile walking robot. The proposed deciding method is based on the new research field, called Neutrosophic Logic. The results are presented as a simulated system for which the output is related to the inputs according to the Neutrosophic Logic.

Distance In Matrices And Their Applications To Fuzzy Models And Neutrosophic Models, Florentin Smarandache, W.B. Vasantha Kandasamy, K. Ilanthenral

Branch Mathematics and Statistics Faculty and Staff Publications

In this book authors for the first time introduce the notion of distance between any two m  n matrices. If the distance is 0 or m  n there is nothing interesting. When the distance happens to be a value t; 0 < t < m  n the study is both innovating and interesting. The three cases of study which is carried out in this book are 1. If the difference between two square matrices is large, will it imply the eigen values and eigen vectors of those matrices are distinct? Several open conjectures in this direction are given. 2. The difference between parity check matrix and the generator matrix for the same C(n, k) code is studied. This will help in detecting errors in storage systems as well as in cryptography.