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2nd International Conference on Cyber Resilience, ICCR 2024

作者： Al-Najjar, Hazem Al-Rousan, Nadia College Of Information Technology University Of Petra Department Of Computer Science Amman Jordan German Jordanian University Faculty Of Electrical Engineering And Information Systems Department Of Computer Engineering Jordan

ISBN: (纸本)9798350394962

This paper investigated the predictive capabilities of three decision tree models for IoT botnet attack prediction using packet information while minimizing the number of predictors. The study employed three decision tree models (C5, CHAID, and Random Forest) and two additional models (Logistic Regression and Bayesian Network) for comparison purposes. The IoT botnet attack dataset comprised various devices, mainly two types of attacks (Gafgyt and Mirai) and 23 feature engineering variables. Simulation results from all models showed that Accuracy, Precision, Recall, and False Omission Rate (FOR) values are approximately one, with an F1 score of around 0.5. CHAID and C5 models outperform other models in predicting IoT botnet attacks, as they are developed using only four and two variables, respectively. These results demonstrated that decision tree models with fewer variables can perform better than models that utilize all predictors. © 2024 IEEE.

关键词： Forecasting

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Automated Scoring Model for Semi-Open-Ended Question in Scientific Explanation

Automated Scoring Model for Semi-Open-Ended Question in Scie...

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2024 IEEE International Conference on Cybernetics and Innovations, ICCI 2024

作者： Lertchaturaporn, Teevit Songmuang, Pokpong Thammasat University Faculty Of Science And Technology Department Of Computer Science Pathumthani Thailand

ISBN: (纸本)9798350370096

Scientific explanation is a crucial skill for analyzing data and drawing reasonable conclusions, especially in the context of semi-open-ended and open-ended questions. However, evaluating such questions requires significant effort from teachers, leading to a labor-intensive grading process influenced by class size and teacher expertise, potentially compromising the question's reliability. Consequently, students may lack valuable feedback, hindering the effective development of their skills. This paper presents our research focus on designing a system to automatically score students' responses. We leverage natural language processing techniques and machine learning algorithms to construct an automatic assessment model for scientific explanations in semi-open-ended questions. The responses were obtained from eighth-grade students in the fundamental science subject of the Thai curriculum, totaling 100 responses. Initially, Thai natural language processing is employed to preprocess the responses. Subsequently, N-Gram and word embedding techniques are utilized to represent the responses in a trainable format. Finally, the performance of various machine learning models trained with different word representation techniques is reported using F1-score. The experimental results demonstrate that a common method of word representation, combined with a simple machine learning model, can achieve high performance. © 2024 IEEE.

关键词： Students

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Virtualization of teaching at the department of kvd uwb in pilsen, new features and benefits

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Recent Patents on computer science 2012年第1期5卷 37-50页

作者： Toman, Jiří Michalík, Petr Department of Computer Science and Educational Technology Faculty of Education University of West Bohemia Klatovska 51 30619 Pilsen Czech Republic

The existence and functionality of virtual environment at the department of computer science and Educational technology (KVD) of the University West Bohemia (UWB) in Pilsen are the current reality. The VMware ESX server has been in operation sinece 2007 at the KVD department. The software ESX 3.5.0 SP2 has been installed on the server Dell PE2900. Current status is as follows: about 10 virtual machines (VM) are used by department members, 6 virtual machines are used as a variety of servers and services for education and teaching, about 30 VM are designed as virtual labs to teach students. Earlier model to manage the VM bases solely on access via the ESX server using VMware Infrastructure client which is not effective and safe. In particular, the system of permissions and roles is not effective enough. It is not possible to set access rights (ACL) to each single VM separately. The new solution has been installed since September 2009, ESX host server and vCenter server as one entity. The new ELMS licensing model for VMware vSphere 4 provides unprecedented efficiency, control and choice. Virtual Center Server 4.0 (recently called vCenter Server 4.0) has been implemented on the operating system MS Srv2008 and as one of the virtual machines. information systems educators must balance the need to protect the stability, availability, and security of computer laboratories with the learning objectives of various courses. The same requirements and needs have to be considered on our side. This paper presents this basic environment, configuration, licensing model and sample teaching laboratories at the KVD. The manuscript demonstrates the advantages, strengths but also the weaknesses in the creation of virtual laboratories for teaching purposes. The final chapter deals with considerations on the coexistence of virtual computer environments to traditional classrooms. We then review the main body of research in this area and identify the key patents that have emerged in this fiel

关键词： Virtualization

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Agent based preprocessing

Agent based preprocessing

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2007 International Conference on Intelligent and Advanced systems, ICIAS 2007

作者： Othman, Zulaiha Ali Abu Bakar, Azuraliza Hamdan, Abdul Razak Omar, Khairuddin Mohd Shuib, Nor Liyana Faculty of Information Science and Technology Department of System Science and Management Universiti Kebangsaan Malaysia Malaysia

ISBN: (纸本)1424413559

The current data mining tools is used to build knowledge based on a huge historical data. At present, businesses are facing with fast growing data that are very valuable in contributing knowledge. Knowledge should be updated regularly in order to ensure its quality and precision thus improve the decision making process. Data mining has shown great potential in extracting valuable knowledge from large databases. However, current data mining algorithms and tools are costly and several are too complex in their operations when dealing with large databases. In recent years, agents have become a popular paradigm in computing, because its autonomous, flexible and provides intelligence. Embedding agents in the current data mining processes and tools are believed to be able to solve the obstacle. One of the most important process in data mining is data preprocessing. It is reported that 60% of the data mining project is on preprocessing. Data preprocessing involves integration, selection, cleaning and transformation of data set that will be used for mining. This paper focuses on an agent-based preprocessing framework. The aims is to provides an auto preprocessing a set of new data, which suite to data mining novice user. The proposed agent based preprocessing framework consists of seven agents: User Interface agents, Coordinator Agent, Identify Agent, CleanMiss Agent, CleanNoisy Agent, Transformation Agent and Discretization Agent. User Interface Agent is designed in such a way to provide interface suite to novice users. Coordinator agent is responsible for coordinating and cooperating with all other agents to achieve the goals. Identify agent responsible to provide an adaptive user data cleaning profiling. CleanMiss Agent, CleanNoisy Agent, Transformation Agent and Discretization Agent provide various types of techniques autonomously, which ended with proposing the best cleaning techniques from various types of techniques to keep in the preprocessing profile. This paper is

关键词： Data mining

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Alternate link maximum energy level ad hoc distance vector scheme for energy efficient Ad Hoc Networks routing

Alternate link maximum energy level ad hoc distance vector s...

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International Conference on computer and Communication Engineering, ICCCE'10

作者： Tie, Tai Hieng Tan, Chong Eng Lau, Sei Ping Department of Computer Systems and Communication Technologies Faculty of Computer Science and Information Technology University Malaysia Sarawak 94300 Kota Samarahan Sarawak Malaysia

ISBN: (纸本)9781424462346

Energy conservation is a very important design issue and has been attracting a lot of attention in recent years. The typical Mobile Ad Hoc Networks (MANET) routing protocols of the Internet Engineering Task Force (IETF) are mainly the shortest path routing protocols and do not consider the energy aware issue. This paper describes improvement of the conventional routing protocol by utilizing higher energy path and backup route. Our proposed algorithms adapt the existing AODV routing protocol to select the optimal route based on the basis of the maximum energy of each route. computer simulations using ns-2 simulator are performed with comparison to the conventional methods and the effectiveness of the proposed methods is quantitatively validated. © 2010 IEEE.

关键词： Routing protocols

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A Bayesian Optimization Approach for Attenuation Correction in SPECT Brain Imaging

A Bayesian Optimization Approach for Attenuation Correction ...

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2021 IEEE Nuclear science Symposium and Medical Imaging Conference, NSS/MIC 2021

作者： Koutsantonis, Loizos Makki, Ayman Carneiro, Tiago Kieffer, Emmanuel Bouvry, Pascal University of Luxembourg Faculty of Science Technology and Medicine Department of Computer Science Luxembourg

ISBN: (纸本)9781665421133

Photon attenuation and scatter are the two main physical factors affecting the diagnostic quality of SPECT in its applications in brain imaging. In this work, we present a novel Bayesian Optimization approach for Attenuation Correction (BOAC) in SPECT brain imaging. BOAC utilizes a prior model parametrizing the head geometry and exploits High Performance Computing (HPC) to reconstruct attenuation corrected images without requiring prior anatomical information from complementary CT scans. BOAC is demonstrated in SPECT brain imaging using noisy and attenuated sinograms, simulated from numerical phantoms. The quality of the tomographic images obtained with the proposed method is compared to those obtained without attenuation correction by employing the appropriate image quality metrics. The quantitative results show the capacity of BOAC to provide images exhibiting higher contrast and less background artifacts as compared to the non-attenuation corrected MLEM images. © 2021 IEEE.

关键词： Brain mapping

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Secure-CamFlow: A device-oriented security model to assist information flow control systems in cloud environments for IoTs

Secure-CamFlow: A device-oriented security model to assist i...

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作者： Khurshid, Anum Khan, Abdul Nasir Khan, Fiaz Gul Ali, Mazhar Shuja, Junaid Khan, Atta ur Rehman Department of Computer Science COMSATS Institute of Information Technology Abbottabad Pakistan Department of Computer Science Air University Islamabad Pakistan

Recent developments in the cloud technologies have motivated the migration of distributed large systems, specifically the Internet of Things to the cloud architecture. Since Internet of Things consist of a vast network and variety of objects, the cloud platform proves to be an ideal option. It is essential for the proper functioning of the Internet of Things to be able to share data among the system processes. The biggest problem faced during the transition of the IoTs to the cloud is the security of data especially while data sharing within the cloud and among its tenants. information Flow Control mechanisms are one of the many solutions to enable a controlled sharing of data. Integration of information Flow Control systems to the existing architecture requires various levels of re-engineering efforts. Moreover, most of the information Flow Control systems focus on data flow within the cloud and neglect the security and integrity of data while it is being transferred to the cloud from various devices. This research focuses on securing the entire process of data migration to cloud from devices while the in-cloud data flow is monitored by the information Flow Control policies specified by the users. We have developed a prototype for the proposed model, and results are evaluated on the basis of energy consumption and execution time. As proposed model provides security services such as privacy, integrity, and authentication, hence it takes more execution time and consumes more energy as compared with the existing model. © 2018 John Wiley & Sons, Ltd.

关键词： Internet of things

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A Novel QoS Interval Prediction Method for Web Services Based on Random Walk 4

A Novel QoS Interval Prediction Method for Web Services Base...

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4th International Conference on computers and Artificial Intelligence technology, CAIT 2023

作者： Zhang, Tingting Wang, Shiya Tang, Mingdong Nie, Jun Faculty of Computer Guangdong University of Science and Technology Dongguan China Guangdong University of Foreign Studies Faculty of Information Science and Technology Guangzhou China

ISBN: (纸本)9798350326710

The quality of service (QoS) of a candidate service plays a decisive role in Web service recommendation. How to accurately predict the QoS value of a service for specific users is a recent research hotspot. Previous work has focused on using a single value (i.e., a pip value) to predict the QoS of a web service. However, in reality, the QoS value of a web service is often uncertain and varies depending on the user's location, network status, and service load. Using intervals to estimate the QoS value of a web service may be more in line with the needs and realities of the user. Based on the fact that the QoS of a web service is often affected by the location of users and services, some research efforts suggest that additional user or service location information can be used to better address the data sparsity problem. On the other hand, the sparseness of the user's service call data makes the location-aware approach take into account the QoS experience of neighbors who are not very close or similar, which may reduce the prediction accuracy. In order to find a good balance, we propose a random walk-based QoS interval prediction method for Web services, which effectively combines location awareness and collaborative filtering methods. To evaluate the performance of our proposed method, we conducted a series of comprehensive experiments on a real web service dataset. The experimental results showed that our proposed random walk method achieved a better balance between confidence and accuracy compared to other collaborative filtering methods in service recommendation. Similarly, considering the dynamic changes in web service QoS, adopting interval based QoS prediction methods is more convincing than previous methods that predict precise QoS point values. © 2023 IEEE.

关键词： Web services

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A Machine Learning Approach for the Classification of Methamphetamine Dealers on Twitter in Thailand. 15

A Machine Learning Approach for the Classification of Metham...

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15th International Joint Symposium on Artificial Intelligence and Natural Language Processing, iSAI-NLP 2020

作者： Khowrurk, Punnavich Kongkachandra, Rachada Thammasat University Faculty of Science and Technology Department of Computer Science Bangkok Thailand

ISBN: (纸本)9780738130682

This research presents a method to classify messages from Twitter (tweet) related to Methamphetamine. The messages are classified into three classes: normal, seller, buyer. The models presented in this research are Multinomial Naive Bayes, Multi-Class LSTM, and Hierarchical LSTM. Model training uses a balanced and imbalanced dataset. The text used for Model training is tokenized from four tokenizers: Tlex+, Lexto+, Attacut, and Deepcut. To study the model performance's effect, we divide the data with a different dataset and tokenizer. The results showed that all models could classify the messages into the three classes. The most effective model built from a balanced dataset is the Hierarchical LSTM model using the Lexto+ Tokenizer provides the highest Accuracy, and the most effective model build from an imbalanced dataset is the Multi-Class LSTM model using the Lexto+ Tokenizer. This model gave the highest Accuracy, but the Fl-Score of the Hierarchical LSTM model gave better Accuracy in each *** creation of a text classification model related to Methamphetamine uses Twitter messages. Most of them are Thai grammatical errors and has many slang usage. We found that Lexto+ is the best tokenizer to build a model. However, it is not much different from other tokenizers. On the other hand, the best dataset to build the model is a balanced dataset that significantly affects model performance. © 2020 IEEE.

关键词： Classification (of information)

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SNR and RSSI Based an Optimized Machine Learning Based Indoor Localization Approach:Multistory Round Building Scenario over LoRa Network

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computers, Materials & Continua 2024年第8期80卷 1927-1945页

作者： Muhammad Ayoub Kamal Muhammad Mansoor Alam Aznida Abu Bakar Sajak Mazliham Mohd Su’ud Malaysian Institute of Information Technology(MIIT) Universiti Kuala LumpurKuala Lumpur50250Malaysia Faculty of Computing and Informatics Multimedia UniversityCyberjaya63100Malaysia Depertment of Computer Science DHA Suffa UniversityKarachiSindh75500Pakistan Riphah Institute of System Engineering(RISE) Faculty of ComputingRiphah International UniversityIslamabad46000Pakistan Malaysian France Institute(MFI) Universiti Kuala LumpurKuala Lumpur50250Malaysia Faculty of Engineering and Information Technology School of Computer ScienceUniversity of Technology SydneyUltimoNSW 2007Australia

In situations when the precise position of a machine is unknown,localization becomes *** research focuses on improving the position prediction accuracy over long-range(LoRa)network using an optimized machine learning-based *** order to increase the prediction accuracy of the reference point position on the data collected using the fingerprinting method over LoRa technology,this study proposed an optimized machine learning(ML)based *** signal strength indicator(RSSI)data from the sensors at different positions was first gathered via an experiment through the LoRa network in a multistory round layout *** noise factor is also taken into account,and the signal-to-noise ratio(SNR)value is recorded for every RSSI *** study concludes the examination of reference point accuracy with the modified KNN method(MKNN).MKNN was created to more precisely anticipate the position of the reference *** findings showed that MKNN outperformed other algorithms in terms of accuracy and complexity.

关键词： Indoor localization MKNN LoRa machine learning classification RSSI SNR localization

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