Abstract There are two main approaches to tackle the challenge of finding the best filter or embedded feature selection (FS) algorithm: searching for the one best FS algorithm and creating an ensemble of all available FS algorithms. However, in practice, these two processes usually occur as part of a larger machine learning pipeline and not separately. We posit that, due to the influence of the filter FS on the embedded FS, one should aim to optimize both of them as a single FS pipeline rather than separately. We propose a meta-learning approach that automatically finds the best filter and embedded FS pipeline for a given dataset called FSPL. We demonstrate the performance of FSPL on n = 90 datasets, obtaining 0.496 accuracy for the optimal FS pipeline, revealing an improvement of up to 5.98 percent in the model’s accuracy compared to the second-best meta-learning method.
{"title":"FSPL: A Meta–Learning Approach for a Filter and Embedded Feature Selection Pipeline","authors":"T. Lazebnik, A. Rosenfeld","doi":"10.34768/amcs-2023-0009","DOIUrl":"https://doi.org/10.34768/amcs-2023-0009","url":null,"abstract":"Abstract There are two main approaches to tackle the challenge of finding the best filter or embedded feature selection (FS) algorithm: searching for the one best FS algorithm and creating an ensemble of all available FS algorithms. However, in practice, these two processes usually occur as part of a larger machine learning pipeline and not separately. We posit that, due to the influence of the filter FS on the embedded FS, one should aim to optimize both of them as a single FS pipeline rather than separately. We propose a meta-learning approach that automatically finds the best filter and embedded FS pipeline for a given dataset called FSPL. We demonstrate the performance of FSPL on n = 90 datasets, obtaining 0.496 accuracy for the optimal FS pipeline, revealing an improvement of up to 5.98 percent in the model’s accuracy compared to the second-best meta-learning method.","PeriodicalId":50339,"journal":{"name":"International Journal of Applied Mathematics and Computer Science","volume":"102 1","pages":"103 - 115"},"PeriodicalIF":1.9,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74973659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
H. N. Fadhilah, D. Adzkiya, D. K. Arif, G. Zhai, Mardlijah
Abstract Many interconnected systems in the real world, such as power systems and chemical processes, are often composed of subsystems. A decentralized controller is suitable for an interconnected system because of its more practical and accessible implementation. We use the homotopy method to compute a decentralized controller. Since the centralized controller constitutes the starting point for the method, its existence becomes very important. This paper introduces a non-singular matrix and a design parameter to generate a centralized controller. If the initial centralized controller fails, we can change the value of the design parameter to generate a new centralized controller. A sufficient condition for a decentralized controller is given as a bilinear matrix inequality with three matrix variables: a controller gain matrix and a pair of other matrix variables. Finally, we present numerical examples to validate the proposed decentralized controller design method.
{"title":"Decentralized Static Output Feedback Controller Design for Linear Interconnected Systems","authors":"H. N. Fadhilah, D. Adzkiya, D. K. Arif, G. Zhai, Mardlijah","doi":"10.34768/amcs-2023-0007","DOIUrl":"https://doi.org/10.34768/amcs-2023-0007","url":null,"abstract":"Abstract Many interconnected systems in the real world, such as power systems and chemical processes, are often composed of subsystems. A decentralized controller is suitable for an interconnected system because of its more practical and accessible implementation. We use the homotopy method to compute a decentralized controller. Since the centralized controller constitutes the starting point for the method, its existence becomes very important. This paper introduces a non-singular matrix and a design parameter to generate a centralized controller. If the initial centralized controller fails, we can change the value of the design parameter to generate a new centralized controller. A sufficient condition for a decentralized controller is given as a bilinear matrix inequality with three matrix variables: a controller gain matrix and a pair of other matrix variables. Finally, we present numerical examples to validate the proposed decentralized controller design method.","PeriodicalId":50339,"journal":{"name":"International Journal of Applied Mathematics and Computer Science","volume":"329 1","pages":"83 - 96"},"PeriodicalIF":1.9,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75238464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Linna Yang, Tao Xie, Mingxing Liu, Mingjiang Zhang, S. Qi, Jung-Mo Yang
Abstract Small target detection under a complex background has always been a hot and difficult problem in the field of image processing. Due to the factors such as a complex background and a low signal-to-noise ratio, the existing methods cannot robustly detect targets submerged in strong clutter and noise. In this paper, a local gradient contrast method (LGCM) is proposed. Firstly, the optimal scale for each pixel is obtained by calculating a multiscale salient map. Then, a subblockbased local gradient measure is designed; it can suppress strong clutter interference and pixel-sized noise simultaneously. Thirdly, the subblock-based local gradient measure and the salient map are utilized to construct the LGCM. Finally, an adaptive threshold is employed to extract the final detection result. Experimental results on six datasets demonstrate that the proposed method can discard clutters and yield superior results compared with state-of-the-art methods.
{"title":"Infrared Small–Target Detection Under a Complex Background Based on a Local Gradient Contrast Method","authors":"Linna Yang, Tao Xie, Mingxing Liu, Mingjiang Zhang, S. Qi, Jung-Mo Yang","doi":"10.34768/amcs-2023-0003","DOIUrl":"https://doi.org/10.34768/amcs-2023-0003","url":null,"abstract":"Abstract Small target detection under a complex background has always been a hot and difficult problem in the field of image processing. Due to the factors such as a complex background and a low signal-to-noise ratio, the existing methods cannot robustly detect targets submerged in strong clutter and noise. In this paper, a local gradient contrast method (LGCM) is proposed. Firstly, the optimal scale for each pixel is obtained by calculating a multiscale salient map. Then, a subblockbased local gradient measure is designed; it can suppress strong clutter interference and pixel-sized noise simultaneously. Thirdly, the subblock-based local gradient measure and the salient map are utilized to construct the LGCM. Finally, an adaptive threshold is employed to extract the final detection result. Experimental results on six datasets demonstrate that the proposed method can discard clutters and yield superior results compared with state-of-the-art methods.","PeriodicalId":50339,"journal":{"name":"International Journal of Applied Mathematics and Computer Science","volume":"80 1","pages":"33 - 43"},"PeriodicalIF":1.9,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80031078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Transition systems (TSs) and Petri nets (PNs) are important models of computation ubiquitous in formal methods for modeling systems. A crucial problem is how to extract, from a given TS, a PN whose reachability graph is equivalent (with a suitable notion of equivalence) to the original TS. This paper addresses the decomposition of transition systems into synchronizing state machines (SMs), which are a class of Petri nets where each transition has one incoming and one outgoing arc. Furthermore, all reachable markings (non-negative vectors representing the number of tokens for each place) of an SM have only one marked place with only one token. This is a significant case of the general problem of extracting a PN from a TS. The decomposition is based on the theory of regions, and it is shown that a property of regions called excitation-closure is a sufficient condition to guarantee the equivalence between the original TS and a decomposition into SMs. An efficient algorithm is provided which solves the problem by reducing its critical steps to the maximal independent set problem (to compute a minimal set of irredundant SMs) or to satisfiability (to merge the SMs). We report experimental results that show a good trade-off between quality of results vs. computation time.
{"title":"Generation of Synchronizing State Machines from a Transition System: A Region–Based Approach","authors":"Viktor Teren, J. Cortadella, T. Villa","doi":"10.34768/amcs-2023-0011","DOIUrl":"https://doi.org/10.34768/amcs-2023-0011","url":null,"abstract":"Abstract Transition systems (TSs) and Petri nets (PNs) are important models of computation ubiquitous in formal methods for modeling systems. A crucial problem is how to extract, from a given TS, a PN whose reachability graph is equivalent (with a suitable notion of equivalence) to the original TS. This paper addresses the decomposition of transition systems into synchronizing state machines (SMs), which are a class of Petri nets where each transition has one incoming and one outgoing arc. Furthermore, all reachable markings (non-negative vectors representing the number of tokens for each place) of an SM have only one marked place with only one token. This is a significant case of the general problem of extracting a PN from a TS. The decomposition is based on the theory of regions, and it is shown that a property of regions called excitation-closure is a sufficient condition to guarantee the equivalence between the original TS and a decomposition into SMs. An efficient algorithm is provided which solves the problem by reducing its critical steps to the maximal independent set problem (to compute a minimal set of irredundant SMs) or to satisfiability (to merge the SMs). We report experimental results that show a good trade-off between quality of results vs. computation time.","PeriodicalId":50339,"journal":{"name":"International Journal of Applied Mathematics and Computer Science","volume":"51 1","pages":"133 - 149"},"PeriodicalIF":1.9,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79236195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Forecasting the number of hospitalization patients is important for hospital management. The number of hospitalization patients depends on three types of patients, namely admission patients, discharged patients, and inpatients. However, previous works focused on one type of patients rather than the three types of patients together. In this paper, we propose a multi-task forecasting model to forecast the three types of patients simultaneously. We integrate three neural network modules into a unified model for forecasting. Besides, we extract date features of admission and discharged patient flows to improve forecasting accuracy. The algorithm is trained and evaluated on a real-world data set of a one-year daily observation of patient numbers in a hospital. We compare the performance of our model with eight baselines over two real-word data sets. The experimental results show that our approach outperforms other baseline algorithms significantly.
{"title":"Hospitalization Patient Forecasting Based on Multi–Task Deep Learning","authors":"Mingjie Zhou, Xiaoxiao Huang, Haipeng Liu, Dingchang Zheng","doi":"10.34768/amcs-2023-0012","DOIUrl":"https://doi.org/10.34768/amcs-2023-0012","url":null,"abstract":"Abstract Forecasting the number of hospitalization patients is important for hospital management. The number of hospitalization patients depends on three types of patients, namely admission patients, discharged patients, and inpatients. However, previous works focused on one type of patients rather than the three types of patients together. In this paper, we propose a multi-task forecasting model to forecast the three types of patients simultaneously. We integrate three neural network modules into a unified model for forecasting. Besides, we extract date features of admission and discharged patient flows to improve forecasting accuracy. The algorithm is trained and evaluated on a real-world data set of a one-year daily observation of patient numbers in a hospital. We compare the performance of our model with eight baselines over two real-word data sets. The experimental results show that our approach outperforms other baseline algorithms significantly.","PeriodicalId":50339,"journal":{"name":"International Journal of Applied Mathematics and Computer Science","volume":"33 1","pages":"151 - 162"},"PeriodicalIF":1.9,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78484881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Segmentation of the border of the human pigmented lesions has a direct impact on the diagnosis of malignant melanoma. In this work, we examine performance of (i) morphological segmentation of a pigmented lesion by region growing with the adaptive threshold and density-based DBSCAN clustering algorithm, and (ii) morphological segmentation of the pigmented lesion border by region growing of the lesion and the background skin. Research tasks (i) and (ii) are evaluated by a human expert and tested on two data sets, A and B, of different origins, resolution, and image quality. The preprocessing step consists of removing the black frame around the lesion and reducing noise and artifacts. The halo is removed by cutting out the dark circular region and filling it with an average skin color. Noise is reduced by a family of Gaussian filters 3×3−7×7 to improve the contrast and smooth out possible distortions. Some other filters are also tested. Artifacts like dark thick hair or ruler/ink markers are removed from the images by using the DullRazor closing images for all RGB colors for a hair brightness threshold below a value of 25 or, alternatively, by the BTH transform. For the segmentation, JFIF luminance representation is used. In the analysis (i), out of each dermoscopy image, a lesion segmentation mask is produced. For the region growing we get a sensitivity of 0.92/0.85, a precision of 0.98/0.91, and a border error of 0.08/0.15 for data sets A/B, respectively. For the density-based DBSCAN algorithm, we get a sensitivity of 0.91/0.89, a precision of 0.95/0.93, and a border error of 0.09/0.12 for data sets A/B, respectively. In the analysis (ii), out of each dermoscopy image, a series of lesion, background, and border segmentation images are derived. We get a sensitivity of about 0.89, a specificity of 0.94 and an accuracy of 0.91 for data set A, and a sensitivity of about 0.85, specificity of 0.91 and an accuracy of 0.89 for data set B. Our analyses show that the improved methods of region growing and density-based clustering performed after proper preprocessing may be good tools for the computer-aided melanoma diagnosis.
{"title":"Segmentation of the Melanoma Lesion and its Border","authors":"G. Surówka, M. Ogorzałek","doi":"10.34768/amcs-2022-0047","DOIUrl":"https://doi.org/10.34768/amcs-2022-0047","url":null,"abstract":"Abstract Segmentation of the border of the human pigmented lesions has a direct impact on the diagnosis of malignant melanoma. In this work, we examine performance of (i) morphological segmentation of a pigmented lesion by region growing with the adaptive threshold and density-based DBSCAN clustering algorithm, and (ii) morphological segmentation of the pigmented lesion border by region growing of the lesion and the background skin. Research tasks (i) and (ii) are evaluated by a human expert and tested on two data sets, A and B, of different origins, resolution, and image quality. The preprocessing step consists of removing the black frame around the lesion and reducing noise and artifacts. The halo is removed by cutting out the dark circular region and filling it with an average skin color. Noise is reduced by a family of Gaussian filters 3×3−7×7 to improve the contrast and smooth out possible distortions. Some other filters are also tested. Artifacts like dark thick hair or ruler/ink markers are removed from the images by using the DullRazor closing images for all RGB colors for a hair brightness threshold below a value of 25 or, alternatively, by the BTH transform. For the segmentation, JFIF luminance representation is used. In the analysis (i), out of each dermoscopy image, a lesion segmentation mask is produced. For the region growing we get a sensitivity of 0.92/0.85, a precision of 0.98/0.91, and a border error of 0.08/0.15 for data sets A/B, respectively. For the density-based DBSCAN algorithm, we get a sensitivity of 0.91/0.89, a precision of 0.95/0.93, and a border error of 0.09/0.12 for data sets A/B, respectively. In the analysis (ii), out of each dermoscopy image, a series of lesion, background, and border segmentation images are derived. We get a sensitivity of about 0.89, a specificity of 0.94 and an accuracy of 0.91 for data set A, and a sensitivity of about 0.85, specificity of 0.91 and an accuracy of 0.89 for data set B. Our analyses show that the improved methods of region growing and density-based clustering performed after proper preprocessing may be good tools for the computer-aided melanoma diagnosis.","PeriodicalId":50339,"journal":{"name":"International Journal of Applied Mathematics and Computer Science","volume":"29 1","pages":"683 - 699"},"PeriodicalIF":1.9,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89474917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract To solve the mismatch between the supply and demand of shared electric vehicles (SEVs) caused by the uneven distribution of SEVs in space and time, an SEV relocating optimization model is designed based on a reward mechanism. The aim of the model is to achieve a cost-minimized rebalancing of the SEV system. Users are guided to attend the relocating SEVs by a reward mechanism, and employees can continuously relocate multiple SEVs before returning to the supply site. The optimization problem is solved by a heuristic column generation algorithm, in which the driving routes of employees are added into a pool by column generation iteratively. In the pricing subproblem of column generation, the Shuffled Complex Evolution–University of Arizona (SCE–UA) is designed to generate a driving route. The proposed model is verified with the actual data of the Dalian city. The results show that our model can reduce the total cost of relocating and improve the service efficiency.
摘要为解决由于共享电动汽车在空间和时间上分布不均匀而导致的共享电动汽车供需不匹配问题，设计了基于奖励机制的共享电动汽车配置优化模型。该模型的目标是实现SEV系统的成本最小化再平衡。通过奖励机制引导用户参加sev的搬迁，员工可以连续搬迁多个sev，然后返回供应现场。采用启发式列生成算法，迭代生成列，将员工驾驶路线添加到池中，求解优化问题。在列生成的定价子问题中，设计了shuffle Complex Evolution-University of Arizona (SCE-UA)算法来生成一条行车路线。用大连市的实际数据对该模型进行了验证。结果表明，该模型能够降低企业搬迁总成本，提高服务效率。
{"title":"A Coordinated Optimization of Rewarded Users and Employees in Relocating Station–Based Shared Electric Vehicles","authors":"Lan Yu, Jiaming Liu, Zhuo Sun","doi":"10.34768/amcs-2022-0037","DOIUrl":"https://doi.org/10.34768/amcs-2022-0037","url":null,"abstract":"Abstract To solve the mismatch between the supply and demand of shared electric vehicles (SEVs) caused by the uneven distribution of SEVs in space and time, an SEV relocating optimization model is designed based on a reward mechanism. The aim of the model is to achieve a cost-minimized rebalancing of the SEV system. Users are guided to attend the relocating SEVs by a reward mechanism, and employees can continuously relocate multiple SEVs before returning to the supply site. The optimization problem is solved by a heuristic column generation algorithm, in which the driving routes of employees are added into a pool by column generation iteratively. In the pricing subproblem of column generation, the Shuffled Complex Evolution–University of Arizona (SCE–UA) is designed to generate a driving route. The proposed model is verified with the actual data of the Dalian city. The results show that our model can reduce the total cost of relocating and improve the service efficiency.","PeriodicalId":50339,"journal":{"name":"International Journal of Applied Mathematics and Computer Science","volume":"8 1","pages":"523 - 535"},"PeriodicalIF":1.9,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81356938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Public transportation is often disrupted by disturbances, such as the uncertain travel time caused by road congestion. Therefore, the operators need to take real-time measures to guarantee the service reliability of transit networks. In this paper, we investigate a dynamic scheduling problem in a transit network, which takes account of the impact of disturbances on bus services. The objective is to minimize the total travel time of passengers in the transit network. A two-layer control method is developed to solve the proposed problem based on a hybrid control strategy. Specifically, relying on conventional strategies (e.g., holding, stop-skipping), the hybrid control strategy makes full use of the idle standby buses at the depot. Standby buses can be dispatched to bus fleets to provide temporary or regular services. Besides, deep reinforcement learning (DRL) is adopted to solve the problem of continuous decision-making. A long short-term memory (LSTM) method is added to the DRL framework to predict the passenger demand in the future, which enables the current decision to adapt to disturbances. The numerical results indicate that the hybrid control strategy can reduce the average headway of the bus fleet and improve the reliability of bus service.
{"title":"A Hybrid Control Strategy for a Dynamic Scheduling Problem in Transit Networks","authors":"Zhongshan Liu, B. Yu, Li Zhang, Wensi Wang","doi":"10.34768/amcs-2022-0039","DOIUrl":"https://doi.org/10.34768/amcs-2022-0039","url":null,"abstract":"Abstract Public transportation is often disrupted by disturbances, such as the uncertain travel time caused by road congestion. Therefore, the operators need to take real-time measures to guarantee the service reliability of transit networks. In this paper, we investigate a dynamic scheduling problem in a transit network, which takes account of the impact of disturbances on bus services. The objective is to minimize the total travel time of passengers in the transit network. A two-layer control method is developed to solve the proposed problem based on a hybrid control strategy. Specifically, relying on conventional strategies (e.g., holding, stop-skipping), the hybrid control strategy makes full use of the idle standby buses at the depot. Standby buses can be dispatched to bus fleets to provide temporary or regular services. Besides, deep reinforcement learning (DRL) is adopted to solve the problem of continuous decision-making. A long short-term memory (LSTM) method is added to the DRL framework to predict the passenger demand in the future, which enables the current decision to adapt to disturbances. The numerical results indicate that the hybrid control strategy can reduce the average headway of the bus fleet and improve the reliability of bus service.","PeriodicalId":50339,"journal":{"name":"International Journal of Applied Mathematics and Computer Science","volume":"1 1","pages":"553 - 567"},"PeriodicalIF":1.9,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79897654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Danijel Ðošić, D. Milic, Nataša Kontrec, C. Stefanovic, Srđan Milosavljević, D. Stefanovic
Abstract This paper considers direct mobile-to-mobile (M2M) communications with a dual antenna selection (AS) system at a destination mobile node (DMN) in interference limited, dissimilar composite fading environments. In particular, we model dissimilar interference limited signals at the inputs of the dual branch AS system as (i) the ratio of two Nakagami-m (N) random variables (RVs) at the first branch and (ii) the ratio of two Rice RVs at the second branch, in order to account for non line-of-sight (NLOS) and line-of-sight (LOS) communications, respectively. Moreover, we assume variable powers of the desired as well as interference signals at the output of the DMN in order to account for the impact of shadowing. For the proposed model, we derive probability density functions, cumulative distribution functions, outage probabilities and average level crossing rates. The derived statistical results are evaluated for all the statistical measures considered and are graphically presented in order to provide insight into the impact of composite fading severities and LOS factors for the desired signal, as well as for the interference, on the system performances.
{"title":"Analytical Performance Analysis of the M2M Wireless Link with an Antenna Selection System Over Interference Limited Dissimilar Composite Fading Environments","authors":"Danijel Ðošić, D. Milic, Nataša Kontrec, C. Stefanovic, Srđan Milosavljević, D. Stefanovic","doi":"10.34768/amcs-2022-0040","DOIUrl":"https://doi.org/10.34768/amcs-2022-0040","url":null,"abstract":"Abstract This paper considers direct mobile-to-mobile (M2M) communications with a dual antenna selection (AS) system at a destination mobile node (DMN) in interference limited, dissimilar composite fading environments. In particular, we model dissimilar interference limited signals at the inputs of the dual branch AS system as (i) the ratio of two Nakagami-m (N) random variables (RVs) at the first branch and (ii) the ratio of two Rice RVs at the second branch, in order to account for non line-of-sight (NLOS) and line-of-sight (LOS) communications, respectively. Moreover, we assume variable powers of the desired as well as interference signals at the output of the DMN in order to account for the impact of shadowing. For the proposed model, we derive probability density functions, cumulative distribution functions, outage probabilities and average level crossing rates. The derived statistical results are evaluated for all the statistical measures considered and are graphically presented in order to provide insight into the impact of composite fading severities and LOS factors for the desired signal, as well as for the interference, on the system performances.","PeriodicalId":50339,"journal":{"name":"International Journal of Applied Mathematics and Computer Science","volume":"151 1","pages":"569 - 582"},"PeriodicalIF":1.9,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77771047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
F. Di Giandomenico, Giulio Masetti, S. Chiaradonna
Abstract Borrowing from well known fault tolerant approaches based on redundancy to mask the effect of faults, redundancy-based intrusion tolerance schemes are proposed in this paper, where redundancy of ICT components is exploited as a first defense line against a subset of compromised components within the redundant set, due to cyberattacks. Features to enhance defense and tolerance capabilities are first discussed, covering diversity-based redundancy, confusion techniques, protection mechanisms, locality policies and rejuvenation phases. Then, a set of intrusion tolerance variations of classical fault tolerant schemes (including N Version Programming and Recovery Block, as well as a few hybrid approaches) is proposed, by enriching each original scheme with one or more of the previously introduced defense mechanisms. As a practical support to the system designer in making an appropriate choice among the available solutions, for each developed scheme a schematic summary is provided, in terms of resources and defense facilities needed to tolerate f value failures and k omission failures, as well as observations regarding time requirements. To provide an example of more detailed analysis, useful to set up an appropriate intrusion tolerance configuration, a trade-off study between cost and additional redundancy employed for confusion purposes is also carried out.
{"title":"Redundancy–Based Intrusion Tolerance Approaches Moving from Classical Fault Tolerance Methods","authors":"F. Di Giandomenico, Giulio Masetti, S. Chiaradonna","doi":"10.34768/amcs-2022-0048","DOIUrl":"https://doi.org/10.34768/amcs-2022-0048","url":null,"abstract":"Abstract Borrowing from well known fault tolerant approaches based on redundancy to mask the effect of faults, redundancy-based intrusion tolerance schemes are proposed in this paper, where redundancy of ICT components is exploited as a first defense line against a subset of compromised components within the redundant set, due to cyberattacks. Features to enhance defense and tolerance capabilities are first discussed, covering diversity-based redundancy, confusion techniques, protection mechanisms, locality policies and rejuvenation phases. Then, a set of intrusion tolerance variations of classical fault tolerant schemes (including N Version Programming and Recovery Block, as well as a few hybrid approaches) is proposed, by enriching each original scheme with one or more of the previously introduced defense mechanisms. As a practical support to the system designer in making an appropriate choice among the available solutions, for each developed scheme a schematic summary is provided, in terms of resources and defense facilities needed to tolerate f value failures and k omission failures, as well as observations regarding time requirements. To provide an example of more detailed analysis, useful to set up an appropriate intrusion tolerance configuration, a trade-off study between cost and additional redundancy employed for confusion purposes is also carried out.","PeriodicalId":50339,"journal":{"name":"International Journal of Applied Mathematics and Computer Science","volume":"914 1","pages":"701 - 719"},"PeriodicalIF":1.9,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77517114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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