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Two-Level Supply Chain Inventory Model for Perishable Goods with Fuzzy Lead-Time and Shortages

International Journal of Applied and Computational Mathematics 2021年第5期7卷 1-18页

作者： Mallick, Rabin Kumar Manna, Amalesh Kumar Shaikh, Ali Akbar Mondal, Shyamal Kumar Department of Applied Mathematics With Oceanology and Computer Programming Vidyasagar University Midnapore 721102 West Bengal India Department of Mathematics The University of Burdwan Burdwan 713104 India

This study deals with a supplier-retailer supply chain system for perishable goods under fuzzy lead-time and fully backlogged shortages. In this proposed model, a supplier collects the deteriorating goods and fulfills the retailer's demand. Also, two different cases are considered. In the first case, retailer's fully backlogged shortages are incorporated whereas in the second case, retailer's shortages are not allowed. Lead-time of the system is considered as fuzzy in nature. In the first case, the integrated average profit of the supply chain system is obtained in fuzzy nature and the centroid method is used for defuzzification. The aim of this study is to maximize the integrated average profit by optimizing retailer's reorder level and business period. Three numerical examples are considered and solved for justification of the proposed model. Finally, the sensitivity analyses are performed with respect to the values of different system parameters. © 2021, The Author(s), under exclusive licence to Springer Nature India Private Limited.

关键词： Fuzzy lead-time Perishable goods Shortages Supply chain

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Simulating Structural Plasticity of the Brain more Scalable than Expected

arXiv

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arXiv 2022年

作者： Czappa, Fabian Geiß, Alexander Wolf, Felix Laboratory for Parallel Programming Department of Computer Science Technical University of Darmstadt Germany

Structural plasticity of the brain describes the creation of new and the deletion of old synapses over time. Rinke et al. (JPDC 2018) introduced a scalable algorithm that simulates structural plasticity for up to one billion neurons on current hardware using a variant of the Barnes–Hut algorithm. They demonstrate good scalability and prove a runtime complexity of O(n log2 n). In this comment paper, we show that with careful consideration of the algorithm and a rigorous proof, the theoretical runtime can even be classified as O(n log n). © 2022, CC BY-NC-ND.

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Analyzing the impact of machine learning and artificial intelligence and its effect on management of lung cancer detection in covid-19 pandemic

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Materials Today: Proceedings 2022年 56卷 2213-2216页

作者： Boddu, Raja Sarath Kumar Karmakar, Partha Bhaumik, Ankan Nassa, Vinay Kumar Vandana Bhattacharya, Sumanta Department of CSE Lenora College of Engineering Andhra Pradesh Rampachodavaram India Government of West Bengal Bikash Bhawan Salt Lake W.B. Kolkata India Dept. of Applied Mathematics With Oceanology and Computer Programming Vidyasagar University Midnapore India Department of Computer Science Engineering South Point Group of Institutions Sonepat Haryana India Department of Mathematics Dasmesh Khalsa College Zirakpur India Department of Science and Technology and Biotechnology MAKAUT India

Cancer victims, particularly those with lung cancer, are more susceptible and at higher danger of COVID-19 and associated consequences as a result of their compromised immune systems, which makes them particularly sensitive. Because of a variety of circumstances, cancer patients' diagnosis, treatment, and aftercare are very complicated and time-consuming during an epidemic. In such circumstances, advances in artificial intelligence (AI) and machine learning algorithms (ML) offer the capacity to boost cancer sufferer diagnosis, therapy, and care via the use of cutting technologies. For example, using clinical and imaging data combined with machine learning methods, the researchers may be able to distinguish among lung alterations induced by corona virus and those produced by immunotherapy and radiation. During this epidemic, artificial intelligence (AI) may be utilized to guarantee that the appropriate individuals are recruited in cancer clinical trials more quickly and effectively than in the past, which was done in a conventional and complicated manner. In order to better care for cancer patients and find novel and more effective therapies, It is critical that we move beyond traditional research methods and use artificial intelligence (AI) and machine learning to update our research (ML). Artificial intelligence (AI) and machine learning (ML) are being utilised to help with several aspects of the COVID-19 epidemic, such as epidemiology, molecular research and medication development, medical diagnosis and treatment, and socioeconomics. The use of artificial intelligence (AI) and machine learning (ML) in the diagnosis and treatment of COVID-19 patients is also being investigated. The combination of artificial intelligence and machine learning in COVID-19 may help to identify positive patients more quickly. In order to understand the dynamics of an epidemic that is relevant to artificial intelligence, when used in different patient groups, AI-based algorithms can quic

关键词： COVID-19

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WIP: An Engaging Undergraduate Intro to Model Checking in Software Engineering Using TLA+

arXiv

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arXiv 2024年

作者： Läufer, Konstantin Mertin, Gunda Thiruvathukal, George K. Software and Systems Laboratory Department of Computer Science Loyola University Chicago United States Institute for Software Engineering and Programming Languages University of Lübeck Germany

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 (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 "failures" 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 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 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 longitudinal analysis within our own institution and

关键词： Students

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Traffic Modeling for the Industrial Internet of NanoThings 4

Traffic Modeling for the Industrial Internet of NanoThings

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4th IEEE KhPI Week on Advanced Technology, KhPI Week 2023

作者： Kuchuk, Nina Kovalenko, Andriy Ruban, Igor Shyshatskyi, Andrii Zakovorotnyi, Oleksandr Sheviakov, Iurii Department of Computer Engineering and Programming National Technical University "Kharkiv Polytechnic Institute" Kharkiv Ukraine Department of Electronic Computers Kharkiv National University of Radio Electronics Kharkiv Ukraine Department of Computerized Management Systems National Aviation University Kyiv Ukraine Civil AviationI nstitute Ivan Kozhedub Kharkiv National Air Force University Kharkiv Ukraine

ISBN: (纸本)9798350395532

Industrial Internet of NanoThings (IIoNT) traffic model proposed. The model is based on the developed algorithm for Dynamic Data Composition Control. The application of the algorithm made it possible to reduce the total amount of transmitted information from the end nodes of IIoNT. The model made it possible to determine the parameters of aggregation traffic of IIoNT cluster gateway. With the calculated parameters, the value of the aggregated package is maximized. The main limitation is not exceeding the value of the boundary delay for the transmission of sensor readings. The model also allows you to dynamically determine the required amount of the gateway buffer memory. © 2023 IEEE.

关键词： Internet of things

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Personalize Web Searching Strategies Classification and Comparison

arXiv

引用

arXiv 2022年

作者： Evtimova, Mariya Savova Momtchev, Ivan Momtchilov Faculty of Computer Systems and Control Programming Computer Technologies Department Technical University of Sofia Sofia1000 Bulgaria

Personalization is becoming very important direction in semantic web search for the users that needs to find appropriate information. In this paper, a classification of web personalization is proposed and semantic web search tools are investigated. Building user interest profile is essential for personalizing. Nowadays, semantic web tools use ontologies for personalization because of their advantages. It is important to mention that most of the semantic web search tools use agent technologies for implementation. © 2022, CC BY.

关键词： Search engines

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An Experiment to Evaluate IoT Application Security Scheme (IoTGazePass)

An Experiment to Evaluate IoT Application Security Scheme (I...

引用

2022 International Conference on Engineering and MIS, ICEMIS 2022

作者： Keshlaf, Ayad A. Alfard, Faheemah M. Bouzid, Omar M. Sabratha University Faculty of Engineering Computer Eng. and It Department Sabratha Libya Libyan Center for Electronic Systems Programming and Aviation Research University of Zawia Computer Department Faculty of Engineering Zawia Libya University of Gharyan Faculty of Engineering Elec. and Electronic Eng. Dept Gharyan Libya

ISBN: (数字)9781665454360

ISBN: (纸本)9781665454360

IoTGazePass is a new password scheme that has been designed to tackle the weaknesses of existing types of passwords. It is intended to be suitable for IoT applications. An experiment was conducted to evaluate the strengths and weaknesses of the IoTGazePass scheme (e.g., security, usability and memorability). The evaluation aspects include a comparison with traditional textual and graphical based passwords in terms of memorability and security of the passwords. The results of the evaluation indicate that the IoTGazePass scheme is easy to use, memorable and flexible, as it can generate strong, secure and scalable passwords. The experiment results have also showed that the IoTGazePass scheme have good ability to deal with shoulder surfing attacks. In fact, the experiment results lead to some recommendations and suggestions to improve the planned performance. © 2022 IEEE.

关键词： Authentication

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Method of Detection of Intrusions Based on Stacking Meta-Algorithm

Method of Detection of Intrusions Based on Stacking Meta-Alg...

引用

Advanced Technology (KhPIWeek), IEEE KhPI Week on

作者： Svitlana Gavrylenko Vladislav Zozulia Nataliia Khatsko Department of Computer Engineering and Programming National Technical University “Kharkiv Polytechnic Institute” Kharkiv Ukraine Department Information Systems and Technologies National Technical University «Kharkiv Polytechnic Institute» Kharkiv Ukraine

ISBN: (数字)9798350384499

ISBN: (纸本)9798350384505

An analysis of modern computer network intrusion detection systems was carried out. The application of machine and deep learning methods for classification problems has been investigated. The UNSW-NB15 dataset, developed at the Australian Cyber Security Center's (ACCS) Cyber Range Laboratory, contains data on normal network operations and synthetic intrusions. Data pre-processing was performed, including class balancing using the SMOTEENN method and selection of informative features using the Recursive Feature Elimination method. The possibility of using the stacking meta-algorithm to detect intrusions into computer networks has been investigated. A new algorithm for generating packets of raw data is proposed, which generates two sets of training data: one for training basic models, the other for a meta-model. A study of the effectiveness of using Random Forest, ANN, K Nearest Neighbor methods and Support Vector Machine and Random Forest as a decision-making meta-model was conducted. The use of the stacking meta-algorithm with the proposed algorithm for forming packets of output data, as well as basic models and a meta-model, led to a significant improvement in the quality of the model. It was found that, on average, recall and f1 score increased by 55.6% and 37.4%, respectively, compared to raw data and other models.

关键词： Training Support vector machines Computational modeling Stacking Training data Intrusion detection Predictive models Nearest neighbor methods Data models Random forests

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Automated System for Freight Transportation Optimization on the Transport Network

引用

Periodica Polytechnica Transportation Engineering 2023年第4期51卷 386-393页

作者： Dekhtyaruk, Mykola Department of Information Technologies and Programming Institute of Computer Technologies Open International University of Human Development "Ukraine" 23 Lvivska Str. Kyiv03115 Ukraine

An automated system for freight traffic optimization on a transport network has been developed, which is realized in the form of a complex computer program with application of the visual design environment of Embarcadero RAD Studio. The program complex consists of the main form from which two subprograms are loaded. The search of optimum routes performed by the routing optimization subprogram is used at transportations of freight on the set transport network based on different schemes (from one vertex (the supplier) to all other vertices (consumers), serially - from each vertex to all other vertices, and from two (or several) set of vertices to all other vertices). Freight delivery between the supply and consumption points was optimized by means of the freight transportation optimization subprogram, taking into account the restrictions on the volume of freight at the points of departure and destination. © 2023 Budapest University of Technology and Economics. All rights reserved.

关键词： Freight transportation

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Research of Neural Network Methods of Visual Defectoscopy of Metal Structures

Research of Neural Network Methods of Visual Defectoscopy of...

引用

2023 International Conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2023

作者： Chernikov, Alexander Smirnova, Elena Zhavoronkov, Oleg Peter the Great St. Petersburg Polytechnic University Higher School of Automation and Robotics St. Petersburg Russia Saint Petersburg State University Department of System Programming St. Petersburg Russia Computer Vision Systems Llc St. Petersburg Russia

ISBN: (纸本)9781665475952

The production of metal pipes is an important component of metallurgy and the entire industry as a whole. Traditional surface quality control is carried out by human inspectors, which is unsatisfactory due to low productivity, reliability and economy. Therefore, the introduction of an automatic visual inspection system into this production allows you to quickly find defects in products and reduce economic losses. To solve this problem, an algorithm based on the neural networks of the YOLOv5 and Unet architectures has been created, which allows finding the bounding frames of defects and their segmentation mask from the image. The created algorithm was applied to two control sites: mandrel defectoscopy and pipe defectoscopy. For mandrel defectoscopy, the accuracy for mAP 0.5 detection is 0.785, for iou_score segmentation - 0.562. For pipe defectoscopy, the accuracy for mAP 0.5 detection is 0.693, for iou_score segmentation - 0.526. © 2023 IEEE.

关键词： computer vision

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