Search Results (14)

As open-pit mining extends to greater depths, slope stability is becoming a critical factor in ensuring safe production. This issue is particularly pronounced in geological settings with weak interlayers, where sudden slope failures are more likely to occur, demanding precise and reliable stability assessment methods. In this study, a typical open-pit slope with weak interlayers was investigated. Acoustic testing and ground-penetrating radar were employed to identify rock mass structural features and delineate loose zones, enabling detailed rock mass zoning and the development of numerical simulation models for stability analysis. The results indicate that (1) the slope exhibits poor overall integrity, dominated by blocky to fragmented structures with well-developed joints and significant weak interlayers, posing a severe threat to stability; (2) in the absence of support, the slope’s dissipated energy, displacement, and plastic zone volume all exceeded the failure threshold (Δ < 0), and the safety factor was only 0.962, indicating a near-failure state; after implementing support measures, the safety factor increased to 1.31, demonstrating a significant improvement in stability; (3) prior to excavation, the energy damage index (ds) in the 1195–1240 m platform zone reached 0.82, which dropped to 0.48 after reinforcement, confirming the effectiveness of support in reducing energy damage and enhancing slope stability; (4) field monitoring data of displacement and anchor rod forces further validated the stabilizing effect of the support system, providing strong assurance for safe mine operation. By integrating cusp catastrophe theory with energy-based analysis, this study establishes a comprehensive evaluation framework for slope stability under complex geological conditions, offering substantial practical value for deep open-pit mining projects. Full article

The concept of domination is introduced within the context of signed fuzzy graphs (signed-FGs), along with examples, as a novel metric to evaluate graph stability under varying conditions. This metric particularly focuses on dominant sets and integrity measures, providing a well-rounded approach to assessing the structural stability of signed- FGs. The necessity of fulfilling the domination integrity condition in evaluating the performance of signed-FGs is highlighted through a discussion on its formulation and an analysis of its upper and lower bounds. An algorithm for identifying strong arcs and classifying them is presented, along with an algorithm for identifying signed fuzzy trees. Furthermore, the role of symmetry in signed-FGs is explored, revealing that symmetrical structures often correspond to higher domination integrity, thus contributing to the improved stability and predictability of the graphs. The paper also establishes important connections with classical graph varieties, such as complete graphs and their variations, demonstrating that changes in domination integrity increase with certain parameters. Additionally, real-life scenarios where these concepts are applicable serve to complement the theoretical results. The case study findings illustrate the significance of domination integrity in practical contexts by emphasizing various instances where it can be determined and utilized. Such instances include identifying independent dominant sets in path and cycle diagrams, as well as estimating the lower bounds of domination integrity in these structures. The estimation of domination integrity using block graph methods is underscored as crucial for enhancing the efficiency of signed-FG applications. Full article

Stripe rust (Puccinia striiformis West. f.sp. tritici, Pst) is a destructive disease that seriously threatens wheat production globally. Exploring novel resistance genes for use in wheat breeding is an urgent need, as continuous Pst evolution frequently leads to a breakdown of host resistance. Here, we identified a set of wheat–Dasypyrum villosum 01I139 (V#6) disomic introgression lines for the purpose of determining their responses to a mixture of Pst isolates CYR32, CYR33 and CYR34 at both seedling and adult-plant stages. The results showed that all introgression lines exhibited high susceptibility at the seedling stage, with infection-type (IT) scores in the range of 6–8, whereas, for chromosomes 5V#6 and 7V#6, disomic addition lines NAU5V#6-1 and NAU7V#6-1 displayed high resistance at the adult-plant stage, indicating that adult-plant resistance (APR) genes were located on them. Further, in order to transfer the stripe-rust resistance on chromosome 7V#6, four new wheat–D. villosum introgression lines were identified, by the use of molecular cytogenetic approaches, from the self-pollinated seeds of 7D and 7V#6, in double monosomic line NAU7V#6-2. Among them, NAU7V#6-3 and NAU7V#6-4 were t7V#6L and t7V#6S monosomic addition lines, and NAU7V#6-5 and NAU7V#6-6 were homozygous T7DS·7V#6L and T7DL·7V#6S whole-arm translocation lines. Stripe-rust tests and genetic analyses of chromosome 7V#6 introgression lines revealed a dominant APR gene designated as Yr7VS on the chromosome arm 7V#6S. Comparison with the homozygous T7DL·7V#6S translocation line and the recurrent parent NAU0686 showed no significant differences in yield-related traits. Thus, T7DL·7V#6S whole-arm translocation with the APR gene Yr7VS provided a valuable germplasm for breeding for resistance. Full article

Claude Berge (1987) introduced the concept of k-extendable graphs, wherein any independent set of size k is inherently a constituent of a maximum independent set within a graph $H=(V,E)$. Graphs possessing the property of being 1-extendable are termedas Berge graphs. This introduction gave rise to the notion of well-covered graphs and well-dominated graphs. A graph is categorized as well-covered if each of its maximal independent sets is, in fact, a maximum independent set. Similarly, a graph attains the classification of well-dominated if every minimal dominating set (DS) within it is a minimum dominating set. In alignment with the concept of k-extendable graphs, the framework of $(k,\gamma )$-endowed graphs and symmetric $(k,\gamma )$-endowed graphs are established. In these graphs, each DS of size k encompasses a minimum DS of the graph. In this article, a study of $\gamma$-endowed dominating sets is initiated. Various results providing a deep insight into $\gamma$-endowed dominating sets in graphs such as those characterizing the ones possessing a unique minimum DS are proven. We also introduce and study the symmetric $\gamma$-endowed graphs and minimality of dominating sets in them. In addition, we give a solution to an open problem in the literature. which seeks to find a domination-based parameter that has a correlation coefficient of $\rho >0.9967$ with the total $\pi$-electronic energy of lower benzenoid hydrocarbons. We show that the upper dominating number $\Gamma \left(H\right)$ studied in this paper delivers a strong prediction potential. Full article

In this manuscript, we introduce a few new types of dominations in intuitionistic fuzzy directed graphs (IFDGs) based on different types of strong arcs (SAs). Our work is not only a direct extension of domination in directed fuzzy graphs (DFGs) but also fills the gap that exists in the literature regarding the dominations in different extended forms of fuzzy graphs (FGs). In the beginning, we introduce several types of strong arcs in IFDGs, like semi-$\beta$ strong arcs, semi-$\delta$ strong arcs, etc. Then, we introduce the concepts of domination in IFDGs based on these strong arcs and discuss its various useful characteristics. Moreover, the dominating set (DS), minimal dominating set (MDS), etc., are described with some fascinating results. We also introduce the concept of an independent set in IFDGs and investigate its relations with the DS, minimal independent set (MIS) and MDS. We also provide numerous important characterizations of domination in IFDGs based on minimal and maximal dominating sets. In this context, we discuss the lower and upper dominations of some IFDGs. In addition, we introduce the terms status and structurally equivalent and examine a few relationships with the dominations in IFDGs. Finally, we investigate the most expert (influential) person in the organization by utilizing the concepts of domination in IFGs. Full article

With the rise of DDoS attacks, several machine learning-based attack detection models have been used to mitigate malicious behavioral attacks. Understanding how machine learning models work is not trivial. This is particularly true for complex and nonlinear models, such as deep learning models that have high accuracy. The struggle to explain these models creates a tension between accuracy and explanation. Recently, different methods have been used to explain deep learning models and address ambiguity issues. In this paper, we utilize the LSTM model to classify DDoS attacks. We then investigate the explanation of LSTM using LIME, SHAP, Anchor, and LORE methods. Predictions of 17 DDoS attacks are explained by these methods, where common explanations are obtained for each class. We also use the output of the explanation methods to extract intrinsic features needed to differentiate DDoS attacks. Our results demonstrate 51 intrinsic features to classify attacks. We finally compare the explanation methods and evaluate them using descriptive accuracy (DA) and descriptive sparsity (DS) metrics. The comparison and evaluation show that the explanation methods can explain the classification of DDoS attacks by capturing either the dominant contribution of input features in the prediction of the classifier or a set of features with high relevance. Full article

This paper is devoted to the study of the double domination in vague graphs, and it is a contribution to the Special Issue “Advances in graph theory and Symmetry/Asymmetry” of Symmetry. Symmetry is one of the most important criteria that illustrate the structure and properties of fuzzy graphs. It has many applications in dominating sets and helps find a suitable place for construction. Vague graphs (VGs), which are a family of fuzzy graphs (FGs), are a well-organized and useful tool for capturing and resolving a range of real-world scenarios involving ambiguous data. In the graph theory, a dominating set (DS) for a graph $G^{*}=(X,E)$ is a subset $\mathfrak{D}$ of the vertices X so that every vertex which is not in $\mathfrak{D}$ is adjacent to at least one member of $\mathfrak{D}$. The subject of energy in graph theory is one of the most attractive topics serving a very important role in biological and chemical sciences. Hence, in this work, we express the notion of energy on a dominating vague graph (DVG) and also use the concept of energy in modeling problems related to DVGs. Moreover, we introduce a new notion of a double dominating vague graph (DDVG) and provide some examples to explain various concepts introduced. Finally, we present an application of energy on DVGs. Full article

In the context of new power systems, reasonable capacity optimization of multiple power systems can not only reduce carbon emissions, but also improve system safety and stability. This paper proposes a situation awareness-based capacity optimization strategy for wind-photovoltaic-thermal power systems and establishes a bi-level model for system capacity optimization. The upper-level model considers environmental protection and economy, and carries out multi-objective optimization of the system capacity planning solution with the objectives of minimizing carbon emissions and total system cost over the whole life cycle of the system, further obtaining a set of capacity planning solutions based on the Pareto frontier. A Pareto optimal solution set decision method based on grey relativity analysis is proposed to quantitatively assess the comprehensive economic–environmental properties of the system. The capacity planning solutions obtained from the upper model are used as the input to the lower model. The lower model integrates system stability, environmental protection, and economy and further optimizes the set of capacity planning solutions obtained from the upper model with the objective of maximizing the inertia security region and the best comprehensive economic–environmental properties to obtain the optimal capacity planning scheme. The NSGA-II modified algorithm (improved NSGA-II algorithm based on dominant strength, INSGA2-DS) is used to solve the upper model, and the Cplex solver is called on to solve the lower model. Finally, the modified IEEE-39 node algorithm is used to verify that the optimized capacity planning scheme can effectively improve the system security and stability and reduce the carbon emissions and total system cost throughout the system life cycle. Full article

Fuzzy graphs (FGs), broadly known as fuzzy incidence graphs (FIGs), have been acknowledged as being an applicable and well-organized tool to epitomize and solve many multifarious real-world problems in which vague data and information are essential. Owing to unpredictable and unspecified information being an integral component in real-life problems that are often uncertain, it is highly challenging for an expert to illustrate those problems through a fuzzy graph. Therefore, resolving the uncertainty accompanying the unpredictable and unspecified information of any real-world problem can be done by applying a vague incidence graph (VIG), based on which the FGs may not engender satisfactory results. Similarly, VIGs are outstandingly practical tools for analyzing different computer science domains such as networking, clustering, and also other issues such as medical sciences, and traffic planning. Dominating sets (DSs) enjoy practical interest in several areas. In wireless networking, DSs are being used to find efficient routes with ad-hoc mobile networks. They have also been employed in document summarization, and in secure systems designs for electrical grids; consequently, in this paper, we extend the concept of the FIG to the VIG, and show some of its important properties. In particular, we discuss the well-known problems of vague incidence dominating set, valid degree, isolated vertex, vague incidence irredundant set and their cardinalities related to the dominating, etc. Finally, a DS application for VIG to properly manage the COVID-19 testing facility is introduced. Full article

The survival rate of multiple myeloma (MM) patients has drastically increased recently as a result of the wide treatment options now available. Younger patients truly benefit from these innovations as they can support more intensive treatment, such as autologous stem cell transplant or multiple drug association (triplet, quadruplet). The emergence of immunotherapy allowed new combinations principally based on monoclonal anti-CD38 antibodies for these patients. Still, the optimal induction treatment has not been found yet. While consolidation is still debated, maintenance treatment is now well acknowledged to prolong survival. Lenalidomide monotherapy is the only drug approved in that setting, but many innovations are expected. Older patients, now logically named not transplant-eligible, also took advantage of these breakthrough innovations as most of the recent drugs have a more acceptable safety profile than previous cytotoxic agents. For this heterogenous subgroup, geriatric assessment has become an essential tool to identify frail patients and provide tailored strategies. At relapse, options are now numerous, especially for patients who were not treated with lenalidomide, or not refractory at least. Concerning lenalidomide refractory patients, approved combinations are lacking, but many trials are ongoing to fill that space. Moreover, innovative therapeutics are increasingly being developed with modern immunotherapy, such as chimeric antigen receptor T-cells (CAR-T cells), bispecific antibodies, or antibody–drug conjugates. For now, these treatments are usually reserved to heavily pre-treated patients with a poor outcome. MM drug classes have tremendously extended from historical alkylating agents to current dominant associations with proteasome inhibitors, immunomodulatory agents, and monoclonal anti-CD38/anti SLAMF7 antibodies. Plus, in only a couple of years, several new classes will enter the MM armamentarium, such as cereblon E3 ligase modulators (CELMoDs), selective inhibitors of nuclear export, and peptide–drug conjugates. Among the questions that will need to be answered in the years to come is the position of these new treatments in the therapeutic strategy, as well as the role of minimal residual disease-driven strategies which will be a key issue to elucidate. Through this review, we chose to enumerate and comment on the most recent advances in MM therapeutics which have undergone major transformations over the past decade. Full article

Fuzzy graph models enjoy the ubiquity of being present in nature and man-made structures, such as the dynamic processes in physical, biological, and social systems. As a result of inconsistent and indeterminate information inherent in real-life problems that are often uncertain, for an expert, it is highly difficult to demonstrate those problems through a fuzzy graph. Resolving the uncertainty associated with the inconsistent and indeterminate information of any real-world problem can be done using a vague graph (VG), with which the fuzzy graphs may not generate satisfactory results. The limitations of past definitions in fuzzy graphs have led us to present new definitions in VGs. The objective of this paper is to present certain types of vague graphs (VGs), including strongly irregular (SI), strongly totally irregular (STI), neighborly edge irregular (NEI), and neighborly edge totally irregular vague graphs (NETIVGs), which are introduced for the first time here. Some remarkable properties associated with these new VGs were investigated, and necessary and sufficient conditions under which strongly irregular vague graphs (SIVGs) and highly irregular vague graphs (HIVGs) are equivalent were obtained. The relation among strongly, highly, and neighborly irregular vague graphs was established. A comparative study between NEI and NETIVGs was performed. Different examples are provided to evaluate the validity of the new definitions. A new definition of energy called the Laplacian energy (LE) is presented, and its calculation is shown with some examples. Likewise, we introduce the notions of the adjacency matrix (AM), degree matrix (DM), and Laplacian matrix (LM) of VGs. The lower and upper bounds for the Laplacian energy of a VG are derived. Furthermore, this study discusses the VG energy concept by providing a real-time example. Finally, an application of the proposed concepts is presented to find the most effective person in a hospital. Full article

This study addresses a two-machine job-shop scheduling problem with fixed lower and upper bounds on the job processing times. An exact value of the job duration remains unknown until completing the job. The objective is to minimize a schedule length (makespan). It is investigated how to best execute a schedule, if the job processing time may be equal to any real number from the given (closed) interval. Scheduling decisions consist of the off-line phase and the on-line phase of scheduling. Using the fixed lower and upper bounds on the job processing times available at the off-line phase, a scheduler may determine a minimal dominant set of schedules (minimal DS), which is based on the proven sufficient conditions for a schedule dominance. The DS optimally covers all possible realizations of the uncertain (interval) processing times, i.e., for each feasible scenario, there exists at least one optimal schedule in the minimal DS. The DS enables a scheduler to make the on-line scheduling decision, if a local information on completing some jobs becomes known. The stability approach enables a scheduler to choose optimal schedules for most feasible scenarios. The on-line scheduling algorithms have been developed with the asymptotic complexity $O(n^2)$ for n given jobs. The computational experiment shows the effectiveness of these algorithms. Full article

We study two-machine shop-scheduling problems provided that lower and upper bounds on durations of n jobs are given before scheduling. An exact value of the job duration remains unknown until completing the job. The objective is to minimize the makespan (schedule length). We address the issue of how to best execute a schedule if the job duration may take any real value from the given segment. Scheduling decisions may consist of two phases: an off-line phase and an on-line phase. Using information on the lower and upper bounds for each job duration available at the off-line phase, a scheduler can determine a minimal dominant set of schedules (DS) based on sufficient conditions for schedule domination. The DS optimally covers all possible realizations (scenarios) of the uncertain job durations in the sense that, for each possible scenario, there exists at least one schedule in the DS which is optimal. The DS enables a scheduler to quickly make an on-line scheduling decision whenever additional information on completing jobs is available. A scheduler can choose a schedule which is optimal for the most possible scenarios. We developed algorithms for testing a set of conditions for a schedule dominance. These algorithms are polynomial in the number of jobs. Their time complexity does not exceed $O\left(n^2\right)$ . Computational experiments have shown the effectiveness of the developed algorithms. If there were no more than 600 jobs, then all 1000 instances in each tested series were solved in one second at most. An instance with 10,000 jobs was solved in 0.4 s on average. The most instances from nine tested classes were optimally solved. If the maximum relative error of the job duration was not greater than $20\%$ , then more than $80\%$ of the tested instances were optimally solved. If the maximum relative error was equal to $50\%$ , then $45\%$ of the tested instances from the nine classes were optimally solved. Full article

The present study deals with wind energy analysis and the selection of an optimum type of wind turbine in terms of the feasibility of installing wind power system at three locations in South Korea: Deokjeok-do, Baengnyeong-do and Seo-San. The wind data measurements were conducted during 2005–2015 at Deokjeok-do, 2001–2016 at Baengnyeong-do and 1997–2016 at Seo-San. In the first part of this paper wind conditions, like mean wind speed, wind rose diagrams and Weibull shape and scale parameters are presented, so that the wind potential of all the locations could be assessed. It was found that the prevailing wind directions at all locations was either southeast or southwest in which the latter one being more dominant. After analyzing the wind conditions, 50-year and 1-year extreme wind speeds (EWS) were estimated using the graphical method of Gumbel distribution. Finally, according to the wind conditions at each site and international electro-technical commission (IEC) guidelines, a set of five different wind turbines best suited for each location were shortlisted. Each wind turbine was evaluated on the basis of technical parameters like monthly energy production, annual energy production (AEP) and capacity factors (CF). Similarly, economical parameters including net present value (NPV), internal rate of return (IRR), payback period (PBP) and levelized cost of electricity (LCOE) were considered. The analysis shows that a Doosan model WinDS134/3000 wind turbine is the most suitable for Deokjeok-do and Baengnyeong-do, whereas a Hanjin model HJWT 87/2000 is the most suitable wind turbine for Seo-San. Economic sensitivity analysis is also included and discussed in detail to analyze the impact on economics of wind power by varying turbine’s hub height. Full article