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Increasing awareness of computer science in high school girls

Increasing awareness of computer science in high school girl...

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Frontiers in Education (FIE) Conference

作者： Gerald C. Gannod Janet E. Burge Victoria McIe Maureen Doyle Karen C. Davis Department of Computer Science and Software Engineering Miami University Oxford OH Department of Computer Science Northern Kentucky University Highland Heights KY Electrical Engineering and Computing Systems University of Cincinnati Cincinnati OH

ISBN: (纸本)9781479939237

The "Girls on the Go: The Mobile computing College Experience" is a residential summer camp whose aim is to encourage female high school students to attend college, to consider computer science as viable major, and to pursue computing related degrees. The camp content is designed primarily around a user-centered design process, with the students gaining experience in the development of a zoo-themed mobile app. In addition to technical experience, students participate in sessions that educate them on campus life, the admissions process, and more importantly, what a computing-related career may hold for them. The camp was offered in two consecutive summers, with approximately 20 participants in each iteration. In this paper, we compare differences between the two iterations with the intent of identifying both lessons learned and avenues for improving the experience. We investigate whether the camp had an effect on attitudes towards computer science as a major, and on the careers available to computer science graduates. To this end, our analysis revealed a statistically significant effect upon raising awareness of the role of computer scientists and the relevancy of computing for solving real world problems.

关键词： Computer science Educational institutions engineering profession Computers Mobile communication Employee welfare Mathematics

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A Further Investigation on the Reliability of Extreme Learning Machines

A Further Investigation on the Reliability of Extreme Learni...

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IEEE International Conference on Data Mining Workshops (ICDM Workshops)

作者： Yanxing Hu Yuan Wang Jane Jia You Jame N.K. Liu Yulin He Department of Computing Hong Kong Polytechnic University Smart Solutions Experts College of Computer Science & Software Engineering Shenzhen University Shenzhen China

ISBN: (纸本)9781479942732

Research community has recently put more attention to the Extreme Learning Machines (ELMs) algorithm in Neural Network (NN) area. The ELMs are much faster than the traditional gradient-descent-based learning algorithms due to its analytical determination of output weights with the random choice of input weights and hidden layer bias. However, since the input weights and bias are randomly assigned and not adjusted, the ELMs model shows an instability if we repeat the experiments many times. Such instability makes the ELMs less reliable than other computational intelligence models. In our investigation, we try to solve this problem by using the Random Production in the first layer of the ELMs. Thus, we can reduce the chance of using random weight assignment in ELMs by removing the bias in the hidden layer. Experiment son different data sets demonstrate that the proposed model has higher stability and reliability than the classical ELMs.

关键词： Accuracy Neurons Training Data models Optimization Analytical models Artificial neural networks

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Animated geooral clusters for exploratory search in event data document collections 18

Animated geooral clusters for exploratory search in event da...

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2014 18th International Conference on Information Visualisation: Visualisation, BioMedical Visualization, Visualisation on Built and Rural Environments and Geometric Modelling and Imaging, IV 2014

作者： Craig, Paul Seiler, Nena Roa Cervantes, Ana Delia Olvera Department of Computer Science and Software Engineering Xi'An Jiaotong-Liverpool University Suzhou China School of Computing Edinburgh Napier University Edinburgh United Kingdom Instituto de Física y Matemáticas Universidad Tecnológica de la Mixteca Huajuapan de-León Mexico

ISBN: (纸本)9781479941032

This paper presents a novel visual analytics technique developed to support exploratory search tasks for event data document collections. The technique supports discovery and exploration by clustering results and overlaying cluster summaries onto coordinated timeline and map views. Users can also explore and interact with search results by selecting clusters to filter and re-cluster the data with animation used to smooth the transition between views. The technique demonstrates a number of advantages over alternative methods for displaying and exploring geo-referenced search results and spatiooral data. Firstly, cluster summaries can be presented in a manner that makes them easy to read and scan. Listing representative events from each cluster also helps the process of discovery by preserving the diversity of results. Also, clicking on visual representations of geooral clusters provides a quick and intuitive way to navigate across space and time simultaneously. This removes the need to overload users with the display of too many event labels at any one time. The technique was evaluated with a group of nineteen users and compared with an equivalent text based exploratory search engine. © 2014 IEEE.

关键词： Search engines

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Using Chou's Amphiphilic Pseudo-amino Acid Composition and Extreme Learning Machine for Prediction of Protein-protein Interactions

Using Chou's Amphiphilic Pseudo-amino Acid Composition and E...

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International Joint Conference on Neural Networks

作者： Qiao-Ying Huang Zhu-Hong You Shuai Li Zexuan Zhu School of Computer Science and Technology Harbin Institute of Technology Shenzhen Graduate School College of Computer Science and Software Engineering Shenzhen University Department of Computing The Hong Kong Polytechnic University

ISBN: (纸本)9781479914821

Protein-protein interactions (PPIs) play crucial roles in the execution of various cellular processes. Almost every cellular process relies on transient or permanent physical bindings of proteins. Unfortunately, the experimental methods for identifying PPIs are both time-consuming and expensive. Therefore, it is important to develop computational approaches for predicting PPIs. In this study, a novel approach is presented to predict PPIs using only the information of protein sequences. This method is developed based on learning algorithm-Extreme Learning Machine (ELM) combined with the concept of Chous Pseudo-Amino Acid Composition (PseAAC) composition. PseAAC is a combination of a set of discrete sequence correlation factors and the 20 components of the conventional amino acid composition, so this method can observe a remarkable improvement in prediction quality. ELM classifier is selected as prediction engine, which is a kind of accurate and fast-learning innovative classification method based on the random generation of the input-to-hidden-units weights followed by the resolution of the linear equations to obtain the hidden-to-output weights. When performed on the PPIs data of Saccharomyces cerevisiae, the proposed method achieved 79.66% prediction accuracy with 79.16% sensitivity at the precision of 79.96%. Extensive experiments are performed to compare our method with state-of-the-art techniques Support Vector Machine (SVM). Achieved results show that the proposed approach is very promising for predicting PPIs, and it can be a helpful supplement for PPIs prediction.

关键词： Extreme Learning Machine (ELM) Pseudo-amino Acid Composition Protein-protein Interactions Support Vector Machine (SVM)

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FACIAL ACTION UNIT RECOGNITION BY RELATION MODELING FROM BOTH QUALITATIVE KNOWLEDGE AND QUANTITATIVE DATA

FACIAL ACTION UNIT RECOGNITION BY RELATION MODELING FROM BOT...

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IEEE International Conference on Multimedia and Expo Workshops

作者： Zhen Gao Shangfei Wang Chongliang Wu Jun Wang Qiang Ji Key Lab of Computing and Communication Software of Anhui Province School of Computer Science and Technology University of Science and Technology of China Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute

ISBN: (纸本)9781479947164

In this paper, we propose to capture Action Unit (AU) relations existing in both qualitative knowledge and quantitative data through Credal Networks (CN). Each node of the CN represents an AU label, and the links and probability intervals capture the probabilistic dependencies among multiple AUs. The structure of CN is designed based on prior knowledge. The parameters of CN are learned from both knowledge and ground-truth AU labels. The AU preliminary estimations are obtained by an existing image-driven recognition method. With the learned credal network, we infer the true AU labels by combining the relationships among labels with the previous obtained estimations. Experimental results on the CK+ database and MMI database demonstrate that with complete AU labels, our CN model is slightly better than the Bayesian Network (BN) model, demonstrating that credal sets learned from data can capture uncertainty more reliably;With incomplete and error-prone AU annotations, our CN model outperforms the BN model, indicating that credal sets can successfully capture qualitative knowledge.

关键词： Prior knowledge Credal network AU recognition

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A Calculus for Transportation Systems

A Calculus for Transportation Systems

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IEEE Annual Computer software and Applications Conference Workshops (COMPSACW)

作者： Moonkun Lee Jungrhan Choi Department of Computer Science and Engineering Chonbuk National University Jeonju Jeonbuk Republic of Korea Cloud Computing Research Department BigData Software Research Laboratory ETRI Daejun Republic of Korea

This paper presents a new formal method, called Calculus of Real-Time Distribution, Mobility, and Interaction (CaRDMI), to specify and verify spatial and temporal behaviors of transportation systems. For specification, CaRDMI defines a map, consisting of nodes and edges with spatial and temporal constraints. The movement of a carrier or agent in the system is represented by a path on the map. Interactive constraints among carriers are represented by synchronization modes on objects at nodes, which are distinguishable features of CaRDMI from other methods. Especially, n-to-n timed synchronization constraints are noticeable. For verification, CaRDMI presents the spatial, temporal and interactive deduction rules and the spatial and temporal equivalence relations. With the rules and relations, it can be measured how two carriers or agents are temporally and/or spatially equivalent. It is another distinguishable feature of CaRDMI.

关键词： Mobile agents Synchronization Semantics Transportation Calculus Real-time systems

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An efficient visual loop closure detection method in a map of 20 million key locations

An efficient visual loop closure detection method in a map o...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Junjun Wu Hong Zhang Yisheng Guan Department of Software Guangdong Food and Drug Vocational College Guangzhou China Department of Computing Science University of Alberta Edmonton Canada School of Electro-mechanical Engineering Guangdong University of Technology Guangzhou China

An important problem in robot simultaneous localization and mapping (SLAM) is loop closure detection. Recent studies of the problem have led to successful development of methods that are based on images captured by the robot. These methods tackle the issue of efficiency through data structures such as indexing and hierarchical (tree) organization of the image data that represent the robot map. In this paper, we offer an alternative approach and present a novel method for visual loop-closure detection. Our approach uses an extremely simple image representation, namely, a down-sampled binarized version of the original image, combined with a highly efficient image similarity measure - mutual information. As a result, our method is able to perform loop closure detection in a map with 20 million key locations in about 2.38 seconds on a commodity computer. The excellent performance of our method in terms of its low complexity and accuracy in experiments establishes it as a promising solution to loop closure detection in large-scale robot maps.

关键词： Visualization Simultaneous localization and mapping Educational institutions Histograms Complexity theory Joints

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Intactness verification in anonymous RFID systems

Intactness verification in anonymous RFID systems

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International Conference on Parallel and Distributed Systems (ICPADS)

作者： Kai Bu Jia Liu Bin Xiao Xuan Liu Shigeng Zhang College Computer Science and Technology Zhejiang University State Key Laboratory for Novel Software Technology Nanjing University Department of Computing The Hong Kong Polytechnic University School of Information Science and Engineering Central South University

Radio-Frequency Identification (RFID) technology has fostered many object monitoring systems. Along with this trend, tagged objects' value and privacy become a primary concern. A corresponding important problem is to verify the intactness of a set of tagged objects without leaking tag identifiers (IDs). However, existing solutions necessitate the knowledge of tag IDs. Without tag IDs as a priori, this paper studies intactness verification in anonymous RFID systems. We identify three critical solution requirements, that is, deterministic verification, anonymity preservation, and scalability. We propose Cardiff and Divar, two crypto-free, lightweight protocols that isolate tag IDs from intactness verification and satisfy solution requirements. Cardiff explores tag cardinality as intactness proof while Divar leverages Direct-Sequence Spread Spectrum (DSSS) enabled RFID. Both analytical and simulation results demonstrate that Cardiff and Divar can satisfy the requirements of accuracy, privacy, and scalability.

关键词： Radiofrequency identification Spread spectrum communication Servers Scalability Protocols Monitoring Privacy

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Understanding the tradeoffs between software-managed vs. hardware-managed caches in GPUs

Understanding the tradeoffs between software-managed vs. har...

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IEEE International Symposium on Performance Analysis of Systems and software

作者： Chao Li Yi Yang Hongwen Dai Shengen Yan Frank Mueller Huiyang Zhou Department of Electrical and Computer Engineering North Carolina State University Department of Computing Systems Architecture NEC Laboratories America Institute of Software North Carolina State University Department of Computer Science North Carolina State University

On-chip caches are commonly used in computer systems to hide long off-chip memory access latencies. To manage on-chip caches, either software-managed or hardware-managed schemes can be employed. State-of-art accelerators, such as the NVIDIA Fermi or Kepler GPUs and Intel's forthcoming MIC “Knights Landing” (KNL), support both software-managed caches, aka. shared memory (GPUs) or near memory (KNL), and hardware-managed L1 data caches (D-caches). Furthermore, shared memory and the L1 D-cache on a GPU utilize the same physical storage and their capacity can be configured at runtime (same for KNL). In this paper, we present an in-depth study to reveal interesting and sometimes unexpected tradeoffs between shared memory and the hardware-managed L1 D- caches in GPU architecture. In our study, the kernels utilizing the L1 D-caches are generated from those leveraging shared memory to ensure that the same optimizations such as tiling are applied equally in both versions. Our detailed analyses reveal that rather than cache hit rates, the following tradeoffs often have more profound performance impacts. On one hand, the kernels utilizing the L1 caches may support higher degrees of thread-level parallelism, offer more opportunities for data to be allocated in registers, and sometimes result in lower dynamic instruction counts. On the other hand, the applications utilizing shared memory enable more coalesced accesses and tend to achieve higher degrees of memory-level parallelism. Overall, our results show that most benchmarks perform significantly better with shared memory than the L1 D-caches due to the high impact of memory-level parallelism and memory coalescing.

关键词： Graphics processing units Tiles Kernel Prefetching Computer architecture Parallel processing

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Cloudsme: Developing a cloud computing-based platform for simulation in manufacturing and engineering

Cloudsme: Developing a cloud computing-based platform for si...

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2014 Operational Research Society Simulation Workshop, SW 2014

作者： Taylor, Simon J. E. Kiss, Tamas Kacsuk, Peter Terstyanszky, Gabor Nicola, Fantini Department of Information Systems and Computing Brunel University Uxbridge MiddlesexUB8 3PH United Kingdom Centre for Parallel Computing Department of Business Information Systems University of Westminster 115 New Cavendish St LondonW1W 6UW United Kingdom MTA SZTAKI Victor Hugo u. 18-22 Budapest1132 Hungary Department of Computer Science and Software Engineering Faculty of Science and Technology University of Westminster LondonW1W 6UW United Kingdom Huobstrasse 10 Pfäffikon8808 Switzerland

There is a demand from simulation users for speed, the ability to obtain quickly results from simulation runs. Cloud computing offers the potential for scalable, on-demand access to resources that can be used to speed up simulation. However, developing cloud computing solutions for industry is difficult without appropriate expertise. This paper introduces the CloudSME project that is dedicated to developing cloud computing solutions for simulation in industry and presents an overview of the CloudSME Simulation Platform that is being used to support an initial set of Cloud-based versions of Simul8's discrete-event simulation environment, Ascomp's TransAT computational fluid dynamics application, Ingecon's 3D Scan Insole Designer tool and 2MORO's Bfly software for aircraft maintenance logistics. The paper presents an overview of cloud computing, the CloudSME project, the architecture of the CloudSME Simulation Platform and its two key elements: gUse and CloudBroker.

关键词： Discrete event simulation

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