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17th international conference and workshops on algorithms and computation, walcom 2023

17th International Conference and Workshops on Algorithms an...

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17th international conference and workshops on algorithms and computation, walcom 2023

ISBN: (纸本)9783031270505

the proceedings contain 32 papers. the special focus in this conference is on algorithms and computation. the topics include: Internal Longest Palindrome Queries in Optimal Time;finding the Cyclic Covers of a String;efficient Non-isomorphic Graph Enumeration algorithms for Subclasses of Perfect Graphs;better Hardness Results for the Minimum Spanning Tree Congestion Problem;energy Efficient Sorting, Selection and Searching;reconfiguration of Vertex-Disjoint Shortest Paths on Graphs;k-Transmitter Watchman Routes;splitting Plane Graphs to Outerplanarity;the Family of Fan-Planar Graphs;certifying Induced Subgraphs in Large Graphs;some Algorithmic Results for Eternal Vertex Cover Problem in Graphs;on the Complexity of Distance-d Independent Set Reconfiguration;on Star-Multi-interval Pairwise Compatibility Graphs;parameterized Complexity of Optimizing List Vertex-Coloring through Reconfiguration;parameterized Complexity of Path Set Packing;interweaving Real-Time Jobs with Energy Harvesting to Maximize throughput;recognizing When a Preference System is Close to Admitting a Master List;groups Burning: Analyzing Spreading Processes in Community-Based Networks;roman k-Domination: Hardness, Approximation and Parameterized Results;minimum Ply Covering of Points with Unit Squares;on the Parameterized Complexity of Compact Set Packing;structural Parameterization of Cluster Deletion;parity Permutation Pattern Matching;overlapping Edge Unfoldings for Archimedean Solids and (Anti)prisms;flipping Plane Spanning Paths;away from Each Other;piercing Diametral Disks Induced by Edges of Maximum Spanning Trees;reflective Guarding a Gallery;improved and Generalized algorithms for Burning a Planar Point Set;preface.

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Special Issue Dedicated to 16th international conference and workshops on algorithms and computation, walcom 2022

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ALGORIthMICA 2023年第11期85卷 3325-3326页

作者： Rahman, Md. Saidur Mutzel, Petra Slamin Bangladesh Univ Engn & Technol Dhaka Bangladesh Univ Bonn Bonn Germany Univ Jember Jember Indonesia

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Special issue on selected papers from the 16th international conference and workshops on algorithms and computation (walcom 2022)

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thEORETICAL COMPUTER SCIENCE 2023年 973卷

作者： Rahman, Md. Saidur Mutzel, Petra Slamin Bangladesh Univ Engn & Technol Dhaka Bangladesh Univ Bonn Bonn Germany Univ Jember Jember Indonesia

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Deep Learning (DL) Dense Classifier with Long Short-Term Memory Encoder Detection and Classification against Network Attacks 17

Deep Learning (DL) Dense Classifier with Long Short-Term Mem...

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17th international conference on Electronics Computer and computation, ICECCO 2023

作者： Gulbarga, Mohammad Imtiyaz Cankurt, Selcuk Shaidullaev, Nurlan Khan, A.L. Alatoo International University Computer Science Department Bishkek Kyrgyzstan Vistula University Computer Engineering Department Warsaw Poland

ISBN: (纸本)9798350339611

the increase in network attacks is a serious threat. For the purpose of supporting study in connected areas, researchers provide datasets for network assaults. Following that, other attack detection techniques based on these datasets are suggested. In this paper, we have proposed a Deep Learning (DL) model called DL Dense Classifier with Long Short-Term Memory (LSTM) which is combination of Encoder and classifier modules to identify the type of network attacks from a massive malware dataset with 12 key malware categories and 141 features. Moreover, we have evaluated 3 classifier models on the CCCS-CIC-AndMal-2020 dataset utilizingprecision, recall, F-score, and accuracy metrics. the results of the experiments show that adding an LSTM encoder module to the DL Dense Classifier model successfully improves the accuracy of DL Dense Classifier from %87 to %91 and perform same as the ensemble model of Random Forest, which is one of the best ranked algorithms in the other research. © 2023 IEEE.

关键词： Long short-term memory

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Deep Learning (DL) Dense Classifier with Long Short-Term Memory Encoder Detection and Classification against Network Attacks

Deep Learning (DL) Dense Classifier with Long Short-Term Mem...

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international conference on Electronics, Computer and computation (ICECCO)

作者： Mohammad Imtiyaz Gulbarga Selcuk Cankurt Nurlan Shaidullaev AL Khan Computer Science Department Alatoo International University Bishkek Kyrgyzstan Computer Engineering Department Vistula University Warsaw Poland

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SociableSense: Exploring the trade-offs of adaptive sampling and computation offloading for social sensing 11

SociableSense: Exploring the trade-offs of adaptive sampling...

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17th Annual international conference on Mobile Computing and Networking, MobiCom'11 and Co-Located workshops

作者： Rachuri, Kiran K. Mascolo, Cecilia Musolesi, Mirco Rentfrow, Peter J. Computer Laboratory University of Cambridge Cambridge United Kingdom School of Computer Science University of Birmingham Birmingham United Kingdom Faculty of Politics Psychology Sociology and International Studies University of Cambridge Cambridge United Kingdom

ISBN: (纸本)9781450304924

the interactions and social relations among users in workplaces have been studied by many generations of social psychologists. there is evidence that groups of users that interact more in workplaces are more productive. However, it is still hard for social scientists to capture fine-grained data about phenomena of this kind and to find the right means to facilitate interaction. It is also difficult for users to keep track of their level of sociability with colleagues. While mobile phones offer a fantastic platform for harvesting long term and fine grained data, they also pose challenges: battery power is limited and needs to be traded-off for sensor reading accuracy and data transmission, while energy costs in processing computationally intensive tasks are high. In this paper, we propose SociableSense, a smart phones based platform that captures user behavior in office environments, while providing the users with a quantitative measure of their sociability and that of colleagues. We tackle the technical challenges of building such a tool: the system provides an adaptive sampling mechanism as well as models to decide whether to perform computation of tasks, such as the execution of classification and inference algorithms, locally or remotely. We perform several micro-benchmark tests to fine-tune and evaluate the performance of these mechanisms and we show that the adaptive sampling and computation distribution schemes balance trade-offs among accuracy, energy, latency, and data traffic. Finally, by means of a social psychological study with ten participants for two working weeks, we demonstrate that SociableSense fosters interactions among the participants and helps in enhancing their sociability. © 2011 ACM.

关键词： Behavioral research

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