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25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2017

作者： Eldawy, Ahmed Haynes, David Niu, Lyuye Su, Zhiba Computer Science and Engineering University of California Riverside United States Program in Health Disparities University of Minnesota Twin Cities United States Computer Science and Engineering University of California Riverside United States Computer Science and Engineering University of California Riverside United States

ISBN: (纸本)9781450354905

Significant increases in the volume of big spatial data have driven researchers and practitioners to build specialized systems to process and analyze this data. Existing efforts focus on either big raster data, e.g., remote sensing data or medical images, or big vector data, e.g., geotagged tweets or trajectories. However, when raster and vector data mix, one dataset must be converted to the other representation requiring vector-to-raster or raster-to-vector transformation before processing, which is extremely inefficient for large datasets. In this paper, we advocate a third approach that mixes the raw representations of both vector and raster data in the query processor. As a case study, we apply this to the zonal statistics problem, which computes the statistics over a raster layer for each polygon in a vector layer. We propose a novel method, called Scanline method, which does not require a conversion between raster and vector. Experimental evaluation on real datasets as large as 840 billion pixels shows up to three orders of magnitude speedup over the baseline methods. © 2017 Copyright held by the owner/author(s).

关键词： Vectors

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BME Senior design and freshmen engineering

BME Senior design and freshmen engineering

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2005 ASEE Annual Conference and Exposition: The Changing Landscape of engineering and Technology Education in a Global World

作者： Rowley, Blair A. College of Engineering and Computer Science Wright State University Dayton OH 45435 United States Biomedical Industrial and Human Factors Engineering United States Freshman Engineering and Computer Science Program United States

This paper reports the results for a senior-freshman teaming event that took place during the fall quarter 2004. It describes the rational for the event, the design leadership required of the seniors, the structure of the design environment, project reports, student reactions, and the event evaluations. This is the second year that our biomedical engineering seniors have been coupled with our engineering and computer science freshmen on a joint design project. The first year results were promising enough to continue doing it the second year. The second year had improved expectations for the seniors coupled with more time to interact with the freshmen. Seniors gained valuable experience leading a design team while the freshmen gained experience teaming and interacting with upperclassmen. This event was possible as the director of the freshman engineering and computer science program was also the professor for the initial course in BME senior design. Over all this has been a win-win effort.

关键词： Structural design

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DeepDTAGen: a multitask deep learning framework for drug-target affinity prediction and target-aware drugs generation

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Nature communications 2025年第1期16卷 5021页

作者： Pir Masoom Shah Huimin Zhu Zhangli Lu Kaili Wang Jing Tang Min Li School of Computer Science and Engineering Central South University Changsha China. School of Computer Science and Technology Donghua University Shanghai China. Research Program in Systems Oncology Faculty of Medicine University of Helsinki Helsinki Finland. Department of Biochemistry and Developmental Biology Faculty of Medicine University of Helsinki Helsinki Finland. School of Computer Science and Engineering Central South University Changsha China. limin@***. Xiangjiang Laboratory Changsha China. limin@***. Furong Laboratory Central South University Changsha China. limin@***.

Identifying novel drugs that can interact with target proteins is a highly challenging, time-consuming, and costly task in drug discovery and development. Numerous machine learning-based models have recently been utilized to accelerate the drug discovery process. However, these existing methods are primarily uni-tasking, either designed to predict drug-target interaction (DTI) or generate new drugs. Through the lens of pharmacological research, these tasks are intrinsically interconnected and play a critical role in effective drug development. Therefore, the learning models must be utilized in such a manner to learn the structural properties of drug molecules, the conformational dynamics of proteins, and the bioactivity between drugs and targets. To this end, this paper develops a novel multitask learning framework that can predict drug-target binding affinities and simultaneously generate new target-aware drug variants, using common features for both tasks. In addition, we developed the FetterGrad algorithm to address the optimization challenges associated with multitask learning particularly those caused by gradient conflicts between distinct tasks. Comprehensive experiments on three real-world datasets demonstrate that the proposed model provides an effective mechanism for predicting drug-target binding affinities and generating novel drugs, thus greatly facilitating the drug discovery process.

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Formalizing concurrent common knowledge as product of modal logics

Formalizing concurrent common knowledge as product of modal ...

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作者： Costa, Vania Benevides, Mario System Engineering and Computer Science Program UFRJ Mailbox 68511 21945-970 Rio de Janeiro Brazil System Engineering and Computer Science Program Institute of Mathematics UFRJ Mailbox 68511 21945-970 Rio de Janeiro Brazil

This work introduces a two-dimensional modal logic to represent agents' Concurrent Common Knowledge in distributed systems. Unlike Common Knowledge, Concurrent Common Knowledge is a kind of agreement reachable in asynchronous environments. The formalization of such type of knowledge is based on a model for asynchronous systems and on the definition of Concurrent Knowledge introduced before in paper [5]. As a proper semantics, we review our concept of closed sub-product of modal logics which is based on the product of modal logics. The key idea is to reason about Concurrent Knowledge under a two-dimensional approach, regarding asynchronous runs and consistent global states as dimensions. We present an axiomatic system for the logic and issue the corresponding soundness and completeness proofs. © 2005 Oxford University Press.

关键词： Semantics

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On a combined electrical engineering and computer science Department

On a combined electrical engineering and Computer Science De...

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114th Annual ASEE Conference and Exposition, 2007

作者： Blandford, Dick Hwang, Deborah University of Evansville United States Electrical Engineering and Computer Science Department University of Evansville United States Computer Science Program University of Evansville United States

In the United States, more than 10% of traditional electrical engineering programs have combined with computer science into a single department \Historically computer science programs emerged from mathematics or electrical engineering departments in the mid to late 1960's. Since mathematics is not typically in the engineering college many computer science programs developed independently from engineering programs. In the 1970's and early 1980's, with the advent of the microprocessor and embedded computer systems, computer engineering evolved mostly out of existing electrical engineering programs and has since become a separate discipline distinct from electrical engineering with its own accreditation process. It is common to see electrical engineering and computer engineering in the same department. computer engineering course work complements courses in computer science and in many cases there is considerable duplication. Thus, it makes sense to consider a combined electrical engineering and computer science department. At the authors' university, electrical engineering and computer science have been combined into a single department since 1990, with computer science, computer engineering, and the more traditional electrical engineering as ABET accredited programs within that department. A combined department offers the obvious advantages of administrative efficiency and elimination of duplication. There are many not-so-obvious advantages as well in the areas of program assessment, shared resources, team projects, and the new ideas and opportunities that are generated when programs are mixed. Disadvantages of a combined department have arisen as well. This paper presents the advantages and disadvantages of a combined department, details the methods used to accomplish the successful combination, and provides advice for those contemplating such a change. © American Society for engineering Education, 2007.

关键词： Electrical engineering

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Enhancing Security Information and Event Management (SIEM) by Incorporating Machine Learning for Cyber Attack Detection 9

Enhancing Security Information and Event Management (SIEM) b...

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9th IEEE International Conference on Computing, engineering and Design, ICCED 2023

作者： Ayu, Media Anugerah Erlangga, Dimas Mantoro, Teddy Handayani, Dini Sampoerna University Faculty of Engineering and Technology Department of Computer Science Jakarta Indonesia Nusa Putra University - Sukabumi Postgraduate Program - School of Computer Science Indonesia

ISBN: (纸本)9798350370126

Network security is a crucial component of Information Technology, yet organizations continue to grapple with meeting established security benchmarks. Given the rise in cyber-attacks and the continuous emergence of new attack types, it's practically infeasible to persistently update attack patterns or signatures within security parameters. Key tools such as Intrusion Detection Systems (IDS) and Security Information and Event Management (SIEM) are instrumental in monitoring network traffic and identifying potential threats. However, these tools face limitations, such as the high volume of alerts produced by IDS and the use of rule-based method, also the inability of SIEM tools to analyze logs comprehensively to identify inappropriate activities. This research has conducted anomaly detection using machine learning process to classify cyber-attacks network flow collected from IDS that installed incident network infrastructure. The analysis of IDS using machine learning, integrated with SIEM. The algorithm used in this research was Random Forest Classifier using CSE-CID-IDS2018 dataset pre-processed with Principal Component Analysis (PCA). Results of the experiments show that Random Forest Classifier Model, when combined with Principal Component Analysis (PCA), yields the most commendable results when applied to a 70/30 training/testing data ratio with accuracy of 0.99953. © 2023 IEEE.

关键词： Network security

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Diabetes Classification Using Support Vector Machine: Binary Classification Model 4

Diabetes Classification Using Support Vector Machine: Binary...

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4th International Conference on Information and Communications Technology, ICOIACT 2021

作者： Rabiha, Suciana Ghadati Wibowo, Antoni Lukas Heryadi, Yaya Computer Science Department BINUS Graduate Program-Doctor of Computer Science. Information Systems Department BINUS Online Learning Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program-Doctor of Computer Science Bina Nusantara University 11480 Indonesia Faculty of Engineering Universitas Katolik Indonesia Atma Jaya Indonesia Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University 11480 Indonesia

ISBN: (纸本)9781665433945

One of the health problems that require special attention is diabetes, besides the growth of this disease infection is increasing in various circles ranging from children, adults, men, women and the elderly. So to detect diabetes at an early stage, machine learning algorithms are the right choice to help detect indications of diabetes. This paper presents experimental results related to the exploration of the use of a Super Vector Machine (SVM) for data classification of Diabetes. The model used in this experiment is the Binary Classification Model. Based on the test results, the highest accuracy is obtained by using a total of 700 lines of data, which is 75,7143%. The Best estimated feasible point in Box Constraint is 272.29 with a KernelScale area of 72.627. © 2021 IEEE

关键词： Face recognition

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Sentiment Analysis with N-Gram Preprocessing for Online-Shopping Reviews in Indonesian Language 9

Sentiment Analysis with N-Gram Preprocessing for Online-Shop...

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9th IEEE International Conference on Computing, engineering and Design, ICCED 2023

作者： Asian, Jelita Putra, Oktavianus Tegar N.K. Ayu, Media Anugerah Mantoro, Teddy Nusa Putra University Postgraduate Program - School of Computer Science Sukabumi Indonesia Sampoerna University Faculty of Engineering and Technology Department of Computer Science Jakarta Indonesia

ISBN: (纸本)9798350370126

Currently, online Shopping platforms have grown significantly, especially during the COVID-19 pandemic. This condition motivates the need for analyzing how the users/customers' opinions on using such platform. Sentiment analysis, as a process of detecting, extracting, and classifying users' opinions and attitudes toward specific topics, is a good tool for the required analysis. This study aims to evaluate the performance of machine learning approach which combined with N-Gram technique in doing sentiment analysis. The dataset used in this study comes from scraping reviews in Bahasa Indonesia regarding the Shopee Apps. In this study, N=2 for the N-Gram was employed in the preprocessing process. Our main goal is to investigate whether the performance of machine learning in doing sentiment analysis can be improved by adding the N-Gram technique in its preprocessing. This work applied the Naive Bayes Classifier and k-Nearest Neighbor with K=11 as the machine learning algorithms. The best accuracy in this study was achieved by Naive Bayes Classifier after applying N-Gram Terms (N=2) with Split Validation (8:2), which is 97.26%. © 2023 IEEE.

关键词： Sentiment analysis

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Using modal logics to express and check global graph properties

Using modal logics to express and check global graph propert...

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作者： Benevides, Mario R.F. Schechter, L. Menasché Computer Science Department Systems and Computer Engineering Program Federal University of Rio de Janeiro Rio de Janeiro Brazil Systems and Computer Engineering Program Federal University of Rio de Janeiro Rio de Janeiro Brazil

Graphs are among the most frequently used structures in computer science. Some of the properties that must be checked in many applications are connectivity, acyclicity and the Eulerian and Hamiltonian properties. In this work, we analyze how we can express these four properties with modal logics. This involves two issues: whether each of the modal languages under consideration has enough expressive power to describe these properties and how complex (computationally) it is to use these logics to actually test whether a given graph has some desired property. First, we show that these properties are not definable in a basic modal logic or in any bisimulation-invariant extension of it, like the modal μ-calculus. We then show that it is possible to express some of the above properties in a basic hybrid logic. Unfortunately, the Hamiltonian and Eulerian properties still cannot be efficiently checked. In a second attempt, we propose an extension of CTL* with nominals and show that the Hamiltonian property can be more efficiently checked in this logic than in the previous one. In a third attempt, we extend the basic hybrid logic with the ↓ operator and show that we can check the Hamiltonian property with optimal (NP) complexity in this logic. Finally, we tackle the Eulerian property in two different ways. First, we develop a generic method to express edge-related properties in hybrid logics and use it to express the Eulerian property. Second, we express a necessary and sufficient condition for the Eulerian property to hold using a graded modal logic. © The Author 2009. Published by Oxford University Press. All rights reserved.

关键词： Model checking

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An efficient decryption method for RSA cryptosystem

An efficient decryption method for RSA cryptosystem

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19th International Conference on Advanced Information Networking and Applications, AINA 2005

作者： Hwang, Ren-Junn Su, Feng-Fu Yeh, Yi-Shiung Chen, Chia-Yao Department of Computer Science and Information Engineering TamKang University Tamsui Taipei 251 Taiwan Degree Program of Electrical Engineering and Computer Science National Chiao Tung University Hsinchu 300 Taiwan

ISBN: (纸本)0769522491

This paper proposes an efficient method to implement RSA decryption algorithm. RSA cryptosystem is the most attractive and popular security technique for many applications, such as electronic commerce and secure internet access. It has to perform modular exponentiation with large exponent and modulus for security consideration. The RSA cryptosystem takes great computational cost. In many RSA applications, user uses a small public key to speed up the encryption operation. However, the decryption operation has to take more computational cost to perform modular exponentiation by this case. This paper proposes an efficient decryption method not only based on Chinese Remainder Theorem (CRT) but also the strong prime of RSA criterion. The proposed decryption method only takes 10% computational costs of the traditional decryption method. It also reduces 66% computational costs than that of decryption methods based on CRT only. In a word, the speed of our proposed method is almost 2.9 times faster than the decryption method based on CRT only. The proposed method enhances the performance of the RSA decryption operation. © 2005 IEEE.

关键词： Cryptography

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