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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Jiamin Chen Zhenpeng Wu Jianliang Gao Xiaohua Hu School of Computer Science and Engineering Central South University Changsha China College of Computing & Informatics Drexel University USA

ISBN: (数字)9781665468190

ISBN: (纸本)9781665468206

Glycans play an indispensable role in various bio-logical processes, such as cancer and autoimmune diseases. The function of glycan is closely determined by its structure. Due to the branch and nonlinear properties of glycans, previous research treats the glycans graph structure as a topological graph to represent glycans data effectively. Graph neural networks (GNNs) are an efficient graph mining method and have many applications in bioinformatics. Therefore, researchers have successfully used handcrafted GNNs to predict glycan immunogenicity. However, a GNN architecture contains many different components, and designing GNN architectures for specific graphs in the bioinformatics field is time-consuming and expert-dependent. To address this challenge, we propose an efficient automatic graph neural network method called EAGNN that can efficiently and automatically construct GNN architecture for glycan immunogenicity prediction. We design an effective graph attention pooling (GAP) search space. We use differential architecture search to efficiently create the optimal GNN architecture in the search space to build the GNN model for glycan immunogenicity prediction. We test EAGNN on the data set SugarBase based on the glycan immunogenicity prediction task. The experiment results show that EAGNN can work more superiorly than the baseline model and achieve the best performance.

关键词： Biological system modeling Manuals Predictive models Graph neural networks Data models Data mining Task analysis

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An Exploratory Case Study on Effort Estimation in Microservices

An Exploratory Case Study on Effort Estimation in Microservi...

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Euromicro Conference on Software engineering and Advanced Applications (SEAA)

作者： Hüseyin Ünlü Tuna Hacaloğlu Neslihan Küçükateş Ömüral Neslihan Çalişkanel Onur Leblebici Onur Demirörs Computer Engineering Izmir Institute of Technology Izmir Turkey Information Systems Engineering Atilim University Ankara Turkey Informatics Institute Middle East Technical University Ankara Turkey Univera Inc. Izmir Turkey

Software project management plays an important role in producing high-quality software, and effort estimation can be considered as a backbone for successful project management. Size is a very significant attribute of software by being the only input to perform early effort estimation. Even though functional size measurement methods showed successful results in effort estimation of traditional data-centric architectures such as monoliths, they were not designed for today’s architectures which are more service-based and decentralized such as microservices. In these new systems, the event concept is highly used specifically for communication among different services. By being motivated by this fact, in this study, we looked for more microservice-compatible ways of sizing microservices using events and developed a method accordingly. Then, we conducted an exploratory case study in an organization using agile methods and measured the size of 17 Product Backlog Items (PBIs) to assess how this proposed method can be useful in effort estimation in microservices. The implication from the case study is that despite performing a more accurate effort estimation using the proposed size measurement than COSMIC, we were unable to significantly outperform using the total number of events. However, our suggested approach demonstrated to us a different way to use software size in terms of events, namely, to determine the coupling complexity of the project. This finding can be beneficial specifically when evaluating the change requests.

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The Implementation of TOGAF for Enterprise System Planning on XYZ Campus

The Implementation of TOGAF for Enterprise System Planning o...

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Networking, Electrical engineering, computer Science, and Technology (IConNECT), International Conference on

作者： Tamsir Hasudungan Sirait Ford Lumban Gaol Suhono Harso Supangkat Benny Ranti Binus Graduate Program Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department Bina Nusantara University Jakarta Indonesia School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia Computer Science Department Universitas Indonesia Jakarta Indonesia

Universities can employ information technology as one means of achieving their goals and objectives. Universities can get advantages from information technology, such as effective resource management and information management for decision-making. However, don't forget that the campus must consider what technology is appropriate to assist them achieve their goals, particularly in the current industrial era 4.0 where technology is available with many different choices. The campus requires an enterprise architecture in order to design, manage, and coordinate information technology infrastructure, applications, and processes strategically and thoroughly. The adoption of enterprise information system architecture (EA) is also intended to improve the quality of services provided to internal and external stakeholders. In this case, Enterprise Architecture can help an organization to match its information technology resources with business processes and strategies to achieve their goals. This research was conducted using TOGAF ADM, also known as the Open Group Architecture Framework Architecture Development Method. This method offers best practices for creating enterprise architecture and emphasizes several steps that include creating an architectural vision, information systems, business architecture modeling to help XYZ campus manage all their information technology.

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Stabilization and trajectory tracking of a subactuated aircraft based on a Geometric Algebra approach

Stabilization and trajectory tracking of a subactuated aircr...

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American Control Conference (ACC)

作者： Leonardo Escamilla Luis Rodolfo Garcia Carrillo Steven Sandoval Eduardo Steed Espinoza Quesada Klipsch School of Electrical and Computer Engineering New Mexico State University Las Cruces NM USA French-Mexican Laboratory of Informatics and Automatic Control Mexico City Mexico

A novel approach to the modeling and control of a subactuated aircraft is performed based on Geometric Algebra (GA) principles. The selected platform for analysis is a quad rotorcraft. The derived model leverages objects from GA, such as the rotor, to perform rotations, replacing the need for Euler angles and quaternions. Controllers, which operate exclusively on GA objects, are developed to regulate the altitude, attitude, and translation of the quad rotorcraft. Numerical examples, including way-point navigation and trajectory tracking, illustrate the feasibility of the GA approach.

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Analysis and Performance Evaluation of OpenFlow Controller in SDN using N-Policy

Analysis and Performance Evaluation of OpenFlow Controller i...

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Recent Advances in Science and engineering Technology (ICRASET), International Conference on

作者： Mahmoud Al Ahmad Maisa Diab Sudhansu Shekhar Patra IT Department College of Engineering University of Kalamoon Damascus Suburb Syria IT Department College of Informatics Engineering Arab Private University for Science and Technology Hama Syria School of Computer Applications KIIT Deemed to be University Bhubaneswar India

The OpenFlow protocol facilitates the communication between the control and forwarding planes within a software-defined networking (SDN) framework. In SDN, the control plane is housed in a distinct entity known as the OpenFlow controller, which assumes the responsibility of making high-level determinations regarding the forwarding of network traffic. With the OpenFlow controller, network administrators can centrally program and manage network behavior, incorporating functionalities like traffic engineering, load balancing, QoS enforcement, security policies, and more. By segregating the control plane from the data plane, SDN utilizing OpenFlow empowers flexible network management, automation, and programmability. Through the utilization of the OpenFlow protocol, the OpenFlow controller interacts with the forwarding plane, typically implemented in network switches or routers. This approach offers a centralized perspective of the network and grants dynamic control over the behavior of network devices by installing flow entries into their forwarding tables. In this research, we use a single-controller N-policy finite buffer waiting queue model to investigate the system performance metrics. Numerical examples and different indices are presented to illustrate the proposed model.

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Prediction of the Effect of Electrical Defibrillation Based on the Wavelet Transform with Pseudo-Differential Operators

Prediction of the Effect of Electrical Defibrillation Based ...

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International Conference on Electrical, Control and Instrumentation engineering (ICECIE)

作者： Yuta Yoshikawa Takayuki Okai Hidetoshi Oya Yoshikatsu Hoshi Kazushi Nakano Graduate School of Integrative Science and Engineering Tokyo City University Tokyo Japan Department of Computer Science Tokyo City University Tokyo Japan Graduate School of Informatics and Engineering The University of Electro-Communications Tokyo Japan

This paper proposes a prediction system of the effect of electrical defibrillation based on the wavelet transform with pseudo-differential operators. To construct this system first, we analyze and extract features from pre-shock (before defibrillation) ECGs (ElectroCardioGrams) by using Gabor wavelet transform with pseudo-differential operators. Next, the effective feature parameters are selected based on the χ 2 test. Finally, this system predicts two states such as "Effective" and "Ineffective" defibrillation by using the SVM (Support Vector Machine). In this way, we show the effectiveness of the proposed feature extraction method and prediction system.

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Medical Feature Selection Approach Based on Generalized Normal Distribution Algorithm

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computers, Materials & Continua 2021年第12期69卷 2883-2901页

作者： Mohamed Abdel-Basset Reda Mohamed Ripon K.Chakrabortty Michael J.Ryan Yunyoung Nam Mohamed Abouhawwash Faculty of Computers and Informatics Zagazig UniversityZagazig44519Egypt Capability Systems Centre School of Engineering and ITUNSWCanberraAustralia Department of Computer Science and Engineering Soonchunhyang UniversityAsan31538Korea Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast Lansing48824MIUSA

This paper proposes a new pre-processing technique to separate the most effective features from those that might deteriorate the performance of the machine learning classifiers in terms of computational costs and classification accuracy because of their irrelevance,redundancy,or less information;this pre-processing process is often known as feature *** technique is based on adopting a new optimization algorithm known as generalized normal distribution optimization(GNDO)supported by the conversion of the normal distribution to a binary one using the arctangent transfer function to convert the continuous values into binary ***,a novel restarting strategy(RS)is proposed to preserve the diversity among the solutions within the population by identifying the solutions that exceed a specific distance from the best-so-far and replace them with the others created using an effective updating *** strategy is integrated with GNDO to propose another binary variant having a high ability to preserve the diversity of the solutions for avoiding becoming stuck in local minima and accelerating convergence,namely improved GNDO(IGNDO).The proposed GNDO and IGNDO algorithms are extensively compared with seven state-of-the-art algorithms to verify their performance on thirteen medical instances taken from the UCI *** is shown to be superior in terms of fitness value and classification accuracy and competitive with the others in terms of the selected *** the principal goal in solving the FS problem is to find the appropriate subset of features that maximize classification accuracy,IGNDO is considered the best.

关键词： Generalized normal distribution optimization feature selection transfer function novel restarting strategy UCI repository

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Latency Minimization for Wireless Federated Learning with Heterogeneous Local Updates

Latency Minimization for Wireless Federated Learning with He...

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IEEE Conference on Wireless Communications and Networking

作者： Jingyang Zhu Yuanming Shi Min Fu Yong Zhou Youlong Wu Liqun Fu School of Information Science and Technology ShanghaiTech University Shanghai China Department of Electrical and Computer Engineering National University of Singapore Singapore School of Informatics Xiamen University Xiamen China

In this paper, we study the latency minimization problem for a wireless federated learning (FL) system with heterogeneous computation capability, where different edge devices perform different numbers of local updates in each communication round. We formulate a total latency minimization problem, taking into account both the communication and computation latency in the whole FL procedure. We reveal that decoupling the resource allocation variables from the model convergence is essential to reduce the problem to a single-round latency minimization problem. To solve this simplified problem, we propose an alternating optimization scheme to jointly consider communication and computation resource allocation and mitigate the straggler effect. We prove that the resulting sub-problems, i.e., bandwidth and computation capacity allocation, are both convex and can be optimally solved in closed form, respectively. Simulations show that compared with the baseline scheme that allocates the communication and computation resources equally across edge devices, the proposed scheme can achieve single-round latency reduction.

关键词： Performance evaluation Training Federated learning Computational modeling Wireless networks Simulation Minimization

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An approach to Physics Based Single Photon Vision System Design

arXiv

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arXiv 2023年

作者： Lu, Yizhou Seets, Trevor Gutierrez-Barragan, Felipe Ahmadi, Ehsan Velten, Andreas Department of Electrical and Computer Engineering University of Wisconsin-Madison Madison United States Department of Computer Sciences University of Wisconsin-Madison Madison United States Department of Biostatistics and Medical Informatics University of Wisconsin-Madison Madison United States

The design of the camera and optical measurement is a crucial part of optimizing machine vision systems. However, camera designs are usually optimized to produce human-interpretable images. Moreover, camera optimization typically makes the assumption of additive noise, while modern optical imaging systems are mainly affected by photon noise which is not additive. Previous studies have highlighted the fundamental effect of the noise model on the outcome of the design process in the context of coded single-pixel and compressed sensing cameras. In addition to the exact noise model, the nature of the data encountered and the vision task fundamentally affect the optimal hardware design. This means that a camera or compressed sensing code that is optimal for capturing images is almost certainly not optimal for any downstream vision task. In this work, we used a simple end-to-end model on a single-pixel camera to study the effects of the noise model for different vision tasks. We demonstrate the importance of incorporating non-linear noise features in optimizing even the simplest vision systems. © 2023, CC BY.

关键词： Machine vision

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Priority Based Cyber Incident Handling: Work in Progress

Priority Based Cyber Incident Handling: Work in Progress

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International Conference on Electrical engineering, computer Science and informatics (EECSI)

作者： Mulyati Deris Stiawan Wijang Widhiarso Rahmat Budiarto Department of Information System Multi Data Palembang University & Faculty of Engineering Universitas Sriwijaya Palembang Indonesia Faculty of Computer Science Sriwijaya University Palembang Indonesia Department of Informatics Multi Data Palembang University Palembang Indonesia College of Computer Science & IT Albaha University Saudi Arabia

ISBN: (数字)9798350355314

ISBN: (纸本)9798350355321

Effective and efficient cyber incident handling is crucial for maintaining the security of information systems and organizational data. This research aims to develop a priority-based cyber incident handling method by adopting the NIST 2.0 framework and utilizing machine learning classification algorithms. This method enables organizations to quickly and accurately identify and respond to incidents based on threat levels and impact, focusing resources on the most critical incidents. The research employs the Support Vector Machine (SVM) classification algorithm to determine incident priorities. The study is still developing for handling cyber incidents, followed by testing and evaluating the system prototype within organizations. Initial results indicate that the priority-based approach using the SVM classification algorithm achieves a True Positive (TP) Rate of 0.999 and a False Positive (FP) Rate of 0.008, with a correlation of 98.88%, resulting in excellent performance in identifying positive cases and a low error rate.

关键词： Support vector machines Error analysis Prototypes Focusing Organizations Machine learning NIST Classification algorithms Security informatics

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