A continuous dynamic model for the development of a gas field is studied. Two mathematical problems are posed, solved and analyzed. In the direct problem, we are looking for the maximum accumulated profit on a set of ...
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The problem of the rational use of energy resources remains constantly relevant and requires the search for new approaches. One of them is power control. In AC circuits, the authors see the most promising method of ph...
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A rising variety of platforms and software programs have leveraged repository-stored datasets and remote access in recent years. As a result, datasets are more vulnerable to malicious attacks. As a result, network sec...
A rising variety of platforms and software programs have leveraged repository-stored datasets and remote access in recent years. As a result, datasets are more vulnerable to malicious attacks. As a result, network security has grown in importance as a research topic. The usage of intrusion detection systems is a well-known strategy for safeguarding computer networks. This paper proposes an anomaly detection method that blends rule-based and machine-learning-based methods. In order to construct the appropriate rules, a genetic algorithm is utilized. Principal component analysis is used to extract the relevant features aimed to improve the performance. The suggested method is validated experimentally using the KDD Cup 1999 dataset, which meets the requirement of using appropriate data. The proposed method is applied to detect and analyze four types of attacks in a well-known benchmark dataset: Neptune, Ipsweep, Pod, and Teardrop, utilizing Support Vector Machine, Decision Tree, and Naive Bayes algorithms. After testing the characteristics specified in the training phase, the data is classified into attack categories and normal behavior during the machine learning phase.
Background: In this Innovative Practice Work in Progress, we present our initial efforts to integrate formal methods, with a focus on model-checking specifications written in Temporal Logic of Actions $(\text{TLA}^{+}...
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ISBN:
(数字)9798350351507
ISBN:
(纸本)9798350363067
Background: In this Innovative Practice Work in Progress, we present our initial efforts to integrate formal methods, with a focus on model-checking specifications written in Temporal Logic of Actions $(\text{TLA}^{+})$ , into computer science education, targeting undergraduate juniors/seniors and graduate students. Many safety-critical systems and services crucially depend on correct and reliable behavior. Formal methods can play a key role in ensuring correct and safe system behavior, yet remain underutilized in educational and industry contexts. Aims: We aim to (1) qualitatively assess the state of formal methods in computer science programs, (2) construct level-appropriate examples that could be included midway into one's undergraduate studies, (3) demonstrate how to address successive “failuresy” through progressively stringent safety and liveness requirements, and (4) establish an ongoing framework for assessing interest and relevance among students. Methods: We detail our pedagogical strategy for embedding $\text { TLA }^{+}$ into an intermediate course on formal methods at our institution. After starting with a refresher on mathematical logic, students specify the rules of simple puzzles in $\text { TLA }^{+}$ and use its included model checker (known as TLC) to find a solution. We gradually escalate to more complex, dynamic, event-driven systems, such as the control logic of a microwave oven, where students will study safety and liveness requirements. We subsequently discuss explicit concurrency, along with thread safety and deadlock avoidance, by modeling bounded counters and buffers. Results: Our initial findings suggest that through careful curricular design and choice of examples and tools, it is possible to inspire and cultivate a new generation of software engineers proficient in formal methods. Conclusions: Our initial efforts suggest that 84% of our students had a positive experience in our formal methods course. Our future plans include a longitudi
The paper focuses on the problem of technical social engineering attacks that encompass the manipulation of individuals to reveal sensitive information, execute actions, or breach security systems. These exploits freq...
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We deigned a spiking neural network that computes network weights in the temporal dimension. Such a network can be used for artificial intelligence and deep learning. We demonstrate circuits implementing blocks for bu...
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This research introduces a novel approach, MBO-NB, that leverages Migrating Birds Optimization (MBO) coupled with Naive Bayes as an internal classifier to address feature selection challenges in text classification ha...
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The integration and detection of AI (Artificial Intelligence) in a variety of fields, primarily education, are examined in this paper. With an emphasis on virtual assistants and their uses, it explores the potential a...
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ISBN:
(数字)9798350376449
ISBN:
(纸本)9798350376456
The integration and detection of AI (Artificial Intelligence) in a variety of fields, primarily education, are examined in this paper. With an emphasis on virtual assistants and their uses, it explores the potential and constraints of such technology. A study was conducted with students at the Technical University of Sofia, to assess their ability to distinguish between texts written by humans and AI. The results showcase that learners need to develop their critical analysis skills evidenced by their mixed expertise.
Warehouses are an important logistic component of various companies. Warehouses may have different layouts, equipment and their own features. Optimization of warehouse operations can decrease overhead costs and increa...
Warehouses are an important logistic component of various companies. Warehouses may have different layouts, equipment and their own features. Optimization of warehouse operations can decrease overhead costs and increase the economic efficiency of industry. The technological process of steel sheet production at a metallurgical company includes two major stages: casting of liquid steel into billets and rolling of these billets on a rolling mill. In order to coordinate the productivity of these two stages and to be able to fulfill orders promptly, a warehouse of slabs (billets) is used. Billets of different parties and steel grades are stored in stacks. The billets are moved to the warehouse for storage and from the warehouse to the rolling mill by bridge cranes. In this paper the problem of optimization of the process of continuous cast billets storage is solved to minimize the number of slab handling operations. The problem is decomposed into two subproblems SLAP (Storage Location Assignment Problem) and CSP (Crane Scheduling Problem). A modified genetic algorithm was applied to solve the problem. Using a simulation model of the warehouse, the efficiency of the algorithm was evaluated using different approaches to take the restrictions imposed on the process of slab handling into account. It is shown that the most effective is the algorithm in which there is no restriction on the placement of stacks of billets belonging to one melting._
Detailed forecasting of time series is one of the fields where the latest advancements in information technology make significant contributions. Operating with financial data poses noteworthy challenges owing to its i...
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ISBN:
(数字)9798350358100
ISBN:
(纸本)9798350358117
Detailed forecasting of time series is one of the fields where the latest advancements in information technology make significant contributions. Operating with financial data poses noteworthy challenges owing to its inherent nature and substantial impact on economic dynamics within society. This study explores the utilization of automated tools as a set of resources for both unifactorial and multifactorial forecasting, drawing conclusions and providing recommendations.
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