If $G$ is a graph with vertex set $V(G)$, then let $N[u]$ be the closed neighborhood of the vertex $uin V(G)$. A total double Italian dominating function (TDIDF) on a graph $G$ is a function $f:V(G)rightarrow{0,1,2,3}$ satisfying (i) $f(N[u])ge 3$ for every vertex $uin V(G)$ with $f(u)in{0,1}$ and (ii) the subgraph induced by the vertices with a non-zero label has no isolated vertices. A TDIDF is an outer-independent total double Italian dominating function (OITDIDF) on $G$ if the set of vertices labeled $0$ induces an edgeless subgraph. The weight of an OITDIDF is the sum of its function values over all vertices, and the outer independent total double Italian domination number $gamma_{tdI}^{oi}(G)$ is the minimum weight of an OITDIDF on $G$. In this paper, we establish various bounds on $gamma_{tdI}^{oi}(G)$, and we determine this parameter for some special classes of graphs.
{"title":"Outer independent total double Italian domination number","authors":"S. M. Sheikholeslami, L. Volkmann","doi":"10.56415/csjm.v32.02","DOIUrl":"https://doi.org/10.56415/csjm.v32.02","url":null,"abstract":"If $G$ is a graph with vertex set $V(G)$, then let $N[u]$ be the closed neighborhood of the vertex $uin V(G)$. A total double Italian dominating function (TDIDF) on a graph $G$ is a function $f:V(G)rightarrow{0,1,2,3}$ satisfying (i) $f(N[u])ge 3$ for every vertex $uin V(G)$ with $f(u)in{0,1}$ and (ii) the subgraph induced by the vertices with a non-zero label has no isolated vertices. A TDIDF is an outer-independent total double Italian dominating function (OITDIDF) on $G$ if the set of vertices labeled $0$ induces an edgeless subgraph. The weight of an OITDIDF is the sum of its function values over all vertices, and the outer independent total double Italian domination number $gamma_{tdI}^{oi}(G)$ is the minimum weight of an OITDIDF on $G$. In this paper, we establish various bounds on $gamma_{tdI}^{oi}(G)$, and we determine this parameter for some special classes of graphs.","PeriodicalId":42293,"journal":{"name":"Computer Science Journal of Moldova","volume":null,"pages":null},"PeriodicalIF":0.3,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140761771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this decade, the internet becomes indispensable in companies and people life. Therefore, a huge quantity of data, which can be a source of hidden information such as association rules that help in decision-making, is stored. Association rule mining (ARM) becomes an attractive data mining task to mine hidden correlations between items in sizeable databases. However, this task is a combinatorial hard problem and, in many cases, the classical algorithms generate extremely large number of rules, that are useless and hard to be validated by the final user. In this paper, we proposed a binary version of grey wolf optimizer that is based on sigmoid function and mutation technique to deal with ARM issue, called BGWOARM. It aims to generate a minimal number of useful and reduced number of rules. It is noted from the several carried out experimentations on well-known benchmarks in the field of ARM, that results are promising, and the proposed approach outperforms other nature-inspired algorithms in terms of quality, number of rules, and runtime consumption.
在这十年里，互联网已成为公司和人们生活中不可或缺的一部分。因此，大量数据被存储起来，这些数据可能是有助于决策的关联规则等隐藏信息的来源。关联规则挖掘（ARM）成为一项极具吸引力的数据挖掘任务，它可以在庞大的数据库中挖掘项目之间隐藏的关联。然而，这项任务是一个难以解决的组合问题，在很多情况下，经典算法会生成大量规则，而这些规则毫无用处，也很难被最终用户验证。在本文中，我们提出了一种基于西格玛函数和突变技术的二进制灰狼优化器来解决 ARM 问题，称为 BGWOARM。它旨在生成最少的有用规则，并减少规则数量。在 ARM 领域的知名基准上进行的几项实验表明，结果很有希望，所提出的方法在质量、规则数量和运行时间消耗方面都优于其他自然启发算法。
{"title":"A Binary Grey Wolf Optimizer with Mutation for Mining Association Rules","authors":"K. Heraguemi, Nadjet Kamel, Majdi M. Mafarja","doi":"10.56415/csjm.v32.06","DOIUrl":"https://doi.org/10.56415/csjm.v32.06","url":null,"abstract":"In this decade, the internet becomes indispensable in companies and people life. Therefore, a huge quantity of data, which can be a source of hidden information such as association rules that help in decision-making, is stored. Association rule mining (ARM) becomes an attractive data mining task to mine hidden correlations between items in sizeable databases. However, this task is a combinatorial hard problem and, in many cases, the classical algorithms generate extremely large number of rules, that are useless and hard to be validated by the final user. In this paper, we proposed a binary version of grey wolf optimizer that is based on sigmoid function and mutation technique to deal with ARM issue, called BGWOARM. It aims to generate a minimal number of useful and reduced number of rules. It is noted from the several carried out experimentations on well-known benchmarks in the field of ARM, that results are promising, and the proposed approach outperforms other nature-inspired algorithms in terms of quality, number of rules, and runtime consumption.","PeriodicalId":42293,"journal":{"name":"Computer Science Journal of Moldova","volume":null,"pages":null},"PeriodicalIF":0.3,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140786147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Umamaheswari, Y. Birnica, J. Boobalan, V. S. Akshaya
This study presents an approach to optimize cervical cancer classification using Support Vector Machines (SVM) and an improved Genetic Algorithm (GA) on Pap smear images. The proposed methodology involves preprocessing the images, extracting relevant features, and employing a genetic algorithm for feature selection. An SVM classifier is trained using the selected features and optimized using the genetic algorithm. The performance of the optimized model is evaluated, demonstrating improved accuracy and efficiency in cervical cancer classification. The findings hold the potential for assisting healthcare professionals in early cervical cancer diagnosis based on Pap smear images.
{"title":"Optimizing Cervical Cancer Classification with SVM and Improved Genetic Algorithm on Pap Smear Images","authors":"S. Umamaheswari, Y. Birnica, J. Boobalan, V. S. Akshaya","doi":"10.56415/csjm.v32.05","DOIUrl":"https://doi.org/10.56415/csjm.v32.05","url":null,"abstract":"This study presents an approach to optimize cervical cancer classification using Support Vector Machines (SVM) and an improved Genetic Algorithm (GA) on Pap smear images. The proposed methodology involves preprocessing the images, extracting relevant features, and employing a genetic algorithm for feature selection. An SVM classifier is trained using the selected features and optimized using the genetic algorithm. The performance of the optimized model is evaluated, demonstrating improved accuracy and efficiency in cervical cancer classification. The findings hold the potential for assisting healthcare professionals in early cervical cancer diagnosis based on Pap smear images.","PeriodicalId":42293,"journal":{"name":"Computer Science Journal of Moldova","volume":null,"pages":null},"PeriodicalIF":0.3,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140780221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Improving safety is a main objective for medical systems. To assist the modelling and formal analysis of medical systems, we define a language for multi-agent systems handling information, timed communication, and timed migration. We use a simplified airway laser surgery scenario to demonstrate our approach. An implementation in Maude is presented; we use the strategies allowed by Maude to guide the rules application in order to decrease substantially the number of possible executions and results in the highly nondeterministic and concurrent multi-agent systems. Finally, we present how the executable specifications can be verified with the model-checking tools in Maude to detect the behavioural problems or desired properties of the~agents.
{"title":"Formal Analysis of Medical Systems using Multi-Agent Systems with Information Sharing","authors":"Bogdan Aman, Gabriel Ciobanu","doi":"10.56415/csjm.v32.01","DOIUrl":"https://doi.org/10.56415/csjm.v32.01","url":null,"abstract":"Improving safety is a main objective for medical systems. To assist the modelling and formal analysis of medical systems, we define a language for multi-agent systems handling information, timed communication, and timed migration. We use a simplified airway laser surgery scenario to demonstrate our approach. An implementation in Maude is presented; we use the strategies allowed by Maude to guide the rules application in order to decrease substantially the number of possible executions and results in the highly nondeterministic and concurrent multi-agent systems. Finally, we present how the executable specifications can be verified with the model-checking tools in Maude to detect the behavioural problems or desired properties of the~agents.","PeriodicalId":42293,"journal":{"name":"Computer Science Journal of Moldova","volume":null,"pages":null},"PeriodicalIF":0.3,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140769621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ramesha Rehman, Mashood Ul Haq Chishti, Hamza Yamin
The rapid rise in power usage by GPUs due to advances in machine and deep learning has led to an increase in power consumption of GPUs in Deep Learning workloads. To address this issue, a novel research project focuses on integrating Particle Swarm Optimization into a model training optimization framework to effectively reduce GPU power consumption during machine learning and deep learning training workloads. By utilizing the Particle Swarm Optimization (PSO)protecthyperlink{b1}{{[}1{]}} algorithm within the proposed framework, we show the effectiveness of PSO in creating a more efficient power management strategy while also maintaining the performance. Upon evaluation of the proposed framework, it shows a reduction of 15.8% to 75.8% in power consumption across multiple workloads, with little to no performance loss.
{"title":"Efficient GPU Power Management through Advanced Framework Utilizing Optimization Algorithms","authors":"Ramesha Rehman, Mashood Ul Haq Chishti, Hamza Yamin","doi":"10.56415/csjm.v32.08","DOIUrl":"https://doi.org/10.56415/csjm.v32.08","url":null,"abstract":"The rapid rise in power usage by GPUs due to advances in machine and deep learning has led to an increase in power consumption of GPUs in Deep Learning workloads. To address this issue, a novel research project focuses on integrating Particle Swarm Optimization into a model training optimization framework to effectively reduce GPU power consumption during machine learning and deep learning training workloads. By utilizing the Particle Swarm Optimization (PSO)protecthyperlink{b1}{{[}1{]}} algorithm within the proposed framework, we show the effectiveness of PSO in creating a more efficient power management strategy while also maintaining the performance. Upon evaluation of the proposed framework, it shows a reduction of 15.8% to 75.8% in power consumption across multiple workloads, with little to no performance loss.","PeriodicalId":42293,"journal":{"name":"Computer Science Journal of Moldova","volume":null,"pages":null},"PeriodicalIF":0.3,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140767020","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The central issue of the development of the multivariate public key algorithms is the design of reversible non-linear mappings of $n$-dimensional vectors over a finite field, which can be represented in a form of a set of power polynomials. For the first time, finite fields $GFleft((2^d)^mright)$ of characteristic two, represented in the form of $m$-dimensional finite algebras over the fields $GF(2^d)$ are introduced for implementing the said mappings as exponentiation operation. This technique allows one to eliminate the use of masking linear mappings, usually used in the known approaches to the design of multivariate cryptography algorithms and causing the sufficiently large size of the public key. The issues of using the fields $GFleft((2^d)^mright)$ as algebraic support of non-linear mappings are considered, including selection of appropriate values of $m$ and $d$. In the proposed approach to development of the multivariate cryptography algorithms, a superposition of two non-linear mappings is used to define resultant hard-to-reverse mapping with a secret trap door. The used two non-linear mappings provide mutual masking of the corresponding reverse maps, due to which the size of the public key significantly reduces as compared with the known algorithms-analogues at a given security level.
{"title":"Vector finite fields of characteristic two as algebraic support of multivariate cryptography","authors":"A. Moldovyan, N. Moldovyan","doi":"10.56415/csjm.v32.04","DOIUrl":"https://doi.org/10.56415/csjm.v32.04","url":null,"abstract":"The central issue of the development of the multivariate public key algorithms is the design of reversible non-linear mappings of $n$-dimensional vectors over a finite field, which can be represented in a form of a set of power polynomials. For the first time, finite fields $GFleft((2^d)^mright)$ of characteristic two, represented in the form of $m$-dimensional finite algebras over the fields $GF(2^d)$ are introduced for implementing the said mappings as exponentiation operation. This technique allows one to eliminate the use of masking linear mappings, usually used in the known approaches to the design of multivariate cryptography algorithms and causing the sufficiently large size of the public key. The issues of using the fields $GFleft((2^d)^mright)$ as algebraic support of non-linear mappings are considered, including selection of appropriate values of $m$ and $d$. In the proposed approach to development of the multivariate cryptography algorithms, a superposition of two non-linear mappings is used to define resultant hard-to-reverse mapping with a secret trap door. The used two non-linear mappings provide mutual masking of the corresponding reverse maps, due to which the size of the public key significantly reduces as compared with the known algorithms-analogues at a given security level.","PeriodicalId":42293,"journal":{"name":"Computer Science Journal of Moldova","volume":null,"pages":null},"PeriodicalIF":0.3,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140797261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A vertex $v$ is said to be over-dominated by a set $S$ if $|N[u]cap S|geq 2$. The cardinality--redundance of $S$, $CR(S)$, is the number of vertices of $G$ that are over-dominated by $S$. The cardinality--redundance of $G$, $CR(G)$, is the minimum of $CR(S)$ taken over all dominating sets $S$. A dominating set $S$ with $CR(S) = CR(G)$ is called a $CR(G)$-set. In this paper, we prove an upper bound for the cardinality--redundance in trees in terms of the order and the number of leaves, and characterize all trees achieving equality for the proposed bound.
{"title":"On the trees with maximum Cardinality-Redundance number","authors":"Elham Mohammadi, N. J. Rad","doi":"10.56415/csjm.v32.03","DOIUrl":"https://doi.org/10.56415/csjm.v32.03","url":null,"abstract":"A vertex $v$ is said to be over-dominated by a set $S$ if $|N[u]cap S|geq 2$. The cardinality--redundance of $S$, $CR(S)$, is the number of vertices of $G$ that are over-dominated by $S$. The cardinality--redundance of $G$, $CR(G)$, is the minimum of $CR(S)$ taken over all dominating sets $S$. A dominating set $S$ with $CR(S) = CR(G)$ is called a $CR(G)$-set. In this paper, we prove an upper bound for the cardinality--redundance in trees in terms of the order and the number of leaves, and characterize all trees achieving equality for the proposed bound.","PeriodicalId":42293,"journal":{"name":"Computer Science Journal of Moldova","volume":null,"pages":null},"PeriodicalIF":0.3,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140761127","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Emergency Department (ED) plays an important role in the healthcare field, due to the nature of the services it provides, especially for patients with urgent cases. Therefore, good management of ED is very important in improving the quality of services. Good management depends on the effective use of material and human resources. One of the most common problems that the ED suffers from is the long waiting period and the length of the patient’s stay. Many researchers have proposed many solutions to reduce waiting time and length of stay (LOS). One of the best solutions for resource optimization is modeling and simulation based on inputs such as patient length of stay and door-to-doctor time (DTDT). In this study, the ED was modeled using a Coloured Petri Net, and to determine the number of resources needed, genetic algorithms were used. This study was conducted in the ED of Hassani Abdelkader Hospital in Sidi Bel Abbes, and several simulation models were evaluated, which reduced the waiting time and the length of stay for the patient.
急诊科（ED）在医疗保健领域发挥着重要作用，因为它提供的服务性质特殊，尤其是为急诊病人提供服务。因此，良好的急诊室管理对提高服务质量非常重要。良好的管理取决于对物质和人力资源的有效利用。急诊室最常见的问题之一是病人等候时间长，住院时间长。许多研究人员提出了许多减少等候时间和住院时间（LOS）的解决方案。资源优化的最佳解决方案之一是根据病人住院时间和门到医生时间（DTDT）等输入数据进行建模和模拟。在这项研究中，使用彩色 Petri 网对急诊室进行建模，并使用遗传算法来确定所需资源的数量。这项研究是在 Sidi Bel Abbes 的 Hassani Abdelkader 医院急诊室进行的，对几个模拟模型进行了评估，这些模型缩短了病人的等待时间和住院时间。
{"title":"A Coloured Petri Net-based approach and Genetic Algorithms for improving services in the Emergency Department","authors":"Zouaoui Louhab, Fatma Boufera","doi":"10.56415/csjm.v32.07","DOIUrl":"https://doi.org/10.56415/csjm.v32.07","url":null,"abstract":"The Emergency Department (ED) plays an important role in the healthcare field, due to the nature of the services it provides, especially for patients with urgent cases. Therefore, good management of ED is very important in improving the quality of services. Good management depends on the effective use of material and human resources. One of the most common problems that the ED suffers from is the long waiting period and the length of the patient’s stay. Many researchers have proposed many solutions to reduce waiting time and length of stay (LOS). One of the best solutions for resource optimization is modeling and simulation based on inputs such as patient length of stay and door-to-doctor time (DTDT). In this study, the ED was modeled using a Coloured Petri Net, and to determine the number of resources needed, genetic algorithms were used. This study was conducted in the ED of Hassani Abdelkader Hospital in Sidi Bel Abbes, and several simulation models were evaluated, which reduced the waiting time and the length of stay for the patient.","PeriodicalId":42293,"journal":{"name":"Computer Science Journal of Moldova","volume":null,"pages":null},"PeriodicalIF":0.3,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140772005","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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