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2016

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Articles 931 - 960 of 2698

Full-Text Articles in Computer Sciences

Development Of Visualization-Animation Software For Learning Transportation Algorithms, Ivan P. Makohon Jul 2016

Development Of Visualization-Animation Software For Learning Transportation Algorithms, Ivan P. Makohon

Computational Modeling & Simulation Engineering Theses & Dissertations

Recognizing the steady decline in US Science Technology Engineering Mathematics (STEM) interests and enrollments, the National Science Foundation (NSF) and the White House have developed national strategies and provided significant budget resources to STEM education research [1-2] in the past years, with the ultimate goals being to improve both the quality and number of highly trained US educators, student workforce in STEM topics, in today’s highly competitive global markets. With the explosion of the internet’s capability and availability, it is even more critical to effectively train this future USA-STEM work-force and/or to develop effective STEM related teaching tools to reach …

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An Adaptability-Driven Model And Tool For Analysis Of Service Profitability, Eng Lieh Ouh, Jarzabek Stan Jul 2016

An Adaptability-Driven Model And Tool For Analysis Of Service Profitability, Eng Lieh Ouh, Jarzabek Stan

Research Collection School Of Computing and Information Systems

Profitability of adopting Software-as-a-Service (SaaS) solutions forexisting applications is currently analyzed mostly in informal way. Informalanalysis is unreliable because of the many conflicting factors that affect costs andbenefits of offering applications on the cloud. We propose a quantitative economicmodel for evaluating profitability of migrating to SaaS that enables potentialservice providers to evaluate costs and benefits of various migration strategiesand choices of target service architectures. In previous work, we presented arudimentary conceptual SaaS economic model enumerating factors that have todo with service profitability, and defining qualitative relations among them. Aquantitative economic model presented in this paper extends the conceptualmodel with equations …

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Build Emotion Lexicon From The Mood Of Crowd Via Topic-Assisted Joint Non-Negative Matrix Factorization, Kaisong Song, Wei Gao, Ling Chen, Shi Feng, Daling Wang, Chengqi Zhang Jul 2016

Build Emotion Lexicon From The Mood Of Crowd Via Topic-Assisted Joint Non-Negative Matrix Factorization, Kaisong Song, Wei Gao, Ling Chen, Shi Feng, Daling Wang, Chengqi Zhang

Research Collection School Of Computing and Information Systems

Kaisong Song, Wei Gao, Ling Chen, Shi Feng, Daling Wang, and Chengqi Zhang. (2016). . In , pages 773–776, Pisa, Italy. ACM Press. https://doi.org/10.1145/2911451.2914759

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From Offline To Online: How Health Insurance Policies Drive The Demand For Online Healthcare Service?, Yue Yu, Qiu-Yan Mei, Qiu-Hong Wang Jul 2016

From Offline To Online: How Health Insurance Policies Drive The Demand For Online Healthcare Service?, Yue Yu, Qiu-Yan Mei, Qiu-Hong Wang

Research Collection School Of Computing and Information Systems

Online healthcare service has gradually become a significant part of healthcare services, especially in emerging economy with shortage in medical resources and wide coverage in the Internet usage. This paper studies how health insurance policies affect the demand for online healthcare consultation by using longitudinal online healthcare and offline medical services datasets of a major city in China. The two policies we study are the integration of health insurance systems in urban and rural regions and the integration of health insurance systems between pairwise-cities. The empirical results show that both policies significantly affected the demand for online consultation. Our study …

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Generic Anonymous Identity-Based Broadcast Encryption With Chosen-Ciphertext Security, Kai He, Jian Weng, Man Ho Au, Yijun Mao, Deng, Robert H. Jul 2016

Generic Anonymous Identity-Based Broadcast Encryption With Chosen-Ciphertext Security, Kai He, Jian Weng, Man Ho Au, Yijun Mao, Deng, Robert H.

Research Collection School Of Computing and Information Systems

In a broadcast encryption system, a broadcaster can encrypt a message to a group of authorized receivers S and each authorized receiver can use his/her own private key to correctly decrypt the broadcast ciphertext, while the users outside S cannot. Identity-based broadcast encryption (IBBE) system is a variant of broadcast encryption system where any string representing the user’s identity (e.g., email address) can be used as his/her public key. IBBE has found many applications in real life, such as pay-TV systems, distribution of copyrighted materials, satellite radio communications. When employing an IBBE system, it is very important to protect the …

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Word Clouds With Latent Variable Analysis For Visual Comparison Of Documents, Tuan M. V. Le, Hady W. Lauw Jul 2016

Word Clouds With Latent Variable Analysis For Visual Comparison Of Documents, Tuan M. V. Le, Hady W. Lauw

Research Collection School Of Computing and Information Systems

Word cloud is a visualization form for text that is recognized for its aesthetic, social, and analytical values. Here, we are concerned with deepening its analytical value for visual comparison of documents. To aid comparative analysis of two or more documents, users need to be able to perceive similarities and differences among documents through their word clouds. However, as we are dealing with text, approaches that treat words independently may impede accurate discernment of similarities among word clouds containing different words of related meanings. We therefore motivate the principle of displaying related words in a coherent manner, and propose to …

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A Feasible No-Root Approach On Android, Yao Cheng, Yingjiu Li, Robert H. Deng Jul 2016

A Feasible No-Root Approach On Android, Yao Cheng, Yingjiu Li, Robert H. Deng

Research Collection School Of Computing and Information Systems

Root is the administrative privilege on Android, which is however inaccessible on stock Android devices. Due to the desire for privileged functionalities and the reluctance of rooting their devices, Android users seek for no-root approaches, which provide users with part of root privileges without rooting their devices. In this paper, we newly discover a feasible no-root approach based on the ADB loopback. To ensure such no-root approach is not misused proactively, we examine its dark side, including privacy leakage via logs and user input inference. Finally, we discuss the solutions and suggestions from different perspectives.

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Robust Median Reversion Strategy For Online Portfolio Selection, Dingjiang Huang, Junlong Zhou, Bin Li, Hoi, Steven C. H., Shuigeng Zhou Jul 2016

Robust Median Reversion Strategy For Online Portfolio Selection, Dingjiang Huang, Junlong Zhou, Bin Li, Hoi, Steven C. H., Shuigeng Zhou

Research Collection School Of Computing and Information Systems

On-line portfolio selection has been attracting increasing interests from artificial intelligence community in recent decades. Mean reversion, as one most frequent pattern in financial markets, plays an important role in some state-of-the-art strategies. Though successful in certain datasets, existing mean reversion strategies do not fully consider noises and outliers in the data, leading to estimation error and thus non-optimal portfolios, which results in poor performance in practice. To overcome the limitation, we propose to exploit the reversion phenomenon by robust L1-median estimator, and design a novel on-line portfolio selection strategy named "Robust Median Reversion" (RMR), which makes optimal portfolios based …

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On Effective Personalized Music Retrieval Via Exploring Online User Behaviors, Zhiyong Cheng, Jialie Shen, Steven C. H. Hoi Jul 2016

On Effective Personalized Music Retrieval Via Exploring Online User Behaviors, Zhiyong Cheng, Jialie Shen, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

In this paper, we study the problem of personalized text based music retrieval which takes users' music preferences on songs into account via the analysis of online listening behaviours and social tags. Towards the goal, a novel Dual-Layer Music Preference Topic Model (DL-MPTM) is proposed to construct latent music interest space and characterize the correlations among (user, song, term). Based on the DL-MPTM, we further develop an effective personalized music retrieval system. To evaluate the system's performance, extensive experimental studies have been conducted over two test collections to compare the proposed method with the state-of-the-art music retrieval methods. The results …

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A Learning-To-Rank Based Fault Localization Approach Using Likely Invariants, Tien-Duy B. Le, David Lo, Claire Le Goues, Lars Grunske Jul 2016

A Learning-To-Rank Based Fault Localization Approach Using Likely Invariants, Tien-Duy B. Le, David Lo, Claire Le Goues, Lars Grunske

Research Collection School Of Computing and Information Systems

Debugging is a costly process that consumes much of developer time and energy. To help reduce debugging effort, many studies have proposed various fault localization approaches. These approaches take as input a set of test cases (some failing, some passing) and produce a ranked list of program elements that are likely to be the root cause of the failures (i.e., failing test cases). In this work, we propose Savant, a new fault localization approach that employs a learning-to-rank strategy, using likely invariant diffs and suspiciousness scores as features, to rank methods based on their likelihood to be a root cause …

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Robust Repositioning To Counter Unpredictable Demand In Bike Sharing Systems, Supriyo Ghosh, Michael Trick, Pradeep Varakantham Jul 2016

Robust Repositioning To Counter Unpredictable Demand In Bike Sharing Systems, Supriyo Ghosh, Michael Trick, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

Bike Sharing Systems (BSSs) experience a significant loss in customer demand due to starvation (empty base stations precluding bike pickup) or congestion (full base stations precluding bike return). Therefore, BSSs operators reposition bikes between stations with the help of carrier vehicles. Due to unpredictable and dynamically changing nature of the demand, myopic reasoning typically provides a below par performance. We propose an online and robust repositioning approach to minimise the loss in customer demand while considering the possible uncertainty in future demand. Specifically, we develop a scenario generation approach based on an iterative two player game to compute a strategy …

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On Very Large Scale Test Collection For Landmark Image Search Benchmarking, Zhiyong Cheng, Jialie Shen Jul 2016

On Very Large Scale Test Collection For Landmark Image Search Benchmarking, Zhiyong Cheng, Jialie Shen

Research Collection School Of Computing and Information Systems

High quality test collections have been becoming more and more important for the technological advancement in geo-referenced image retrieval and analytics. In this paper, we present a large scale test collection to support robust performance evaluation of landmark image search and corresponding construction methodology. Using the approach, we develop a very large scale test collection consisting of three key components: (1) 355,141 images of 128 landmarks in five cities across three continents crawled from Flickr; (2) different kinds of textual features for each image, including surrounding text (e.g. tags), contextual data (e.g. geo-location and upload time), and metadata (e.g. uploader …

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Which Information Sources Are More Effective And Reliable In Video Search, Cheng Zhiyong, Xuanchong Li, Jialie Shen, Alexander G. Hauptmann Jul 2016

Which Information Sources Are More Effective And Reliable In Video Search, Cheng Zhiyong, Xuanchong Li, Jialie Shen, Alexander G. Hauptmann

Research Collection School Of Computing and Information Systems

It is common that users are interested in finding video segments, which contain further information about the video contents in a segment of interest. To facilitate users to find and browse related video contents, video hyperlinking aims at constructing links among video segments with relevant information in a large video collection. In this study, we explore the effectiveness of various video features on the performance of video hyperlinking, including subtitle, metadata, content features (i.e., audio and visual), surrounding context, as well as the combinations of those features. Besides, we also test different search strategies over different types of queries, which …

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A Survey On Future Internet Security Architectures, Wenxiu Ding, Zheng Yan, Robert H. Deng Jul 2016

A Survey On Future Internet Security Architectures, Wenxiu Ding, Zheng Yan, Robert H. Deng

Research Collection School Of Computing and Information Systems

Current host-centric Internet Protocol (IP) networks are facing unprecedented challenges, such as network attacks and the exhaustion of IP addresses. Motivated by emerging demands for security, mobility, and distributed networking, many research projects have been initiated to design the future Internet from a clean slate. In order to obtain a thorough knowledge of security in future Internet architecture, we review a number of well-known projects, including named data networking, Content Aware Searching Retrieval and sTreaming, MobilityFirst Future Internet Architecture Project (MobilityFirst), eXpressive Internet Architecture, and scalability, control, and isolation on next-generation network. These projects aim to move away from the …

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Practitioners' Expectations On Automated Fault Localization, Pavneet Singh Kochhar, Xin Xia, David Lo, Shanping Li Jul 2016

Practitioners' Expectations On Automated Fault Localization, Pavneet Singh Kochhar, Xin Xia, David Lo, Shanping Li

Research Collection School Of Computing and Information Systems

Software engineering practitioners often spend significant amount of time and effort to debug. To help practitioners perform this crucial task, hundreds of papers have proposed various fault localization techniques. Fault localization helps practitioners to find the location of a defect given its symptoms (e.g., program failures). These localization techniques have pinpointed the locations of bugs of various systems of diverse sizes, with varying degrees of success, and for various usage scenarios. Unfortunately, it is unclear whether practitioners appreciate this line of research. To fill this gap, we performed an empirical study by surveying 386 practitioners from more than 30 countries …

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Cross-Modal Self-Taught Hashing For Large-Scale Image Retrieval, Liang Xie, Lei Zhu, Peng Pan, Yansheng Lu Jul 2016

Cross-Modal Self-Taught Hashing For Large-Scale Image Retrieval, Liang Xie, Lei Zhu, Peng Pan, Yansheng Lu

Research Collection School Of Computing and Information Systems

Cross-modal hashing integrates the advantages of traditional cross-modal retrieval and hashing, it can solve large-scale cross-modal retrieval effectively and efficiently. However, existing cross-modal hashing methods rely on either labeled training data, or lack semantic analysis. In this paper, we propose Cross-Modal Self-Taught Hashing (CMSTH) for large-scale cross-modal and unimodal image retrieval. CMSTH can effectively capture the semantic correlation from unlabeled training data. Its learning process contains three steps: first we propose Hierarchical Multi-Modal Topic Learning (HMMTL) to detect multi-modal topics with semantic information. Then we use Robust Matrix Factorization (RMF) to transfer the multi-modal topics to hash codes which are …

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Scalable Greedy Algorithms For Task/Resource Constrained Multi-Agent Stochastic Planning, Pritee Agrawal, Pradeep Varakantham, William Yeoh Jul 2016

Scalable Greedy Algorithms For Task/Resource Constrained Multi-Agent Stochastic Planning, Pritee Agrawal, Pradeep Varakantham, William Yeoh

Research Collection School Of Computing and Information Systems

Synergistic interactions between task/resource allocation and stochastic planning exist in many environments such as transportation and logistics, UAV task assignment and disaster rescue. Existing research in exploiting these synergistic interactions between the two problems have either only considered domains where tasks/resources are completely independent of each other or have focussed on approaches with limited scalability. In this paper, we address these two limitations by introducing a generic model for task/resource constrained multi-agent stochastic planning, referred to as TasC-MDPs. We provide two scalable greedy algorithms, one of which provides posterior quality guarantees. Finally, we illustrate the high scalability and solution performance …

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Satisfiability Modulo Heap-Based Programs, Quang Loc Le, Jun Sun, Wei-Ngan Chin Jul 2016

Satisfiability Modulo Heap-Based Programs, Quang Loc Le, Jun Sun, Wei-Ngan Chin

Research Collection School Of Computing and Information Systems

In this work, we present a semi-decision procedure for a fragment of separation logic with user-defined predicates and Presburger arithmetic. To check the satisfiability of a formula, our procedure iteratively unfolds the formula and examines the derived disjuncts. In each iteration, it searches for a proof of either satisfiability or unsatisfiability. Our procedure is further enhanced with automatically inferred invariants as well as detection of cyclic proof. We also identify a syntactically restricted fragment of the logic for which our procedure is terminating and thus complete. This decidable fragment is relatively expressive as it can capture a range of sophisticated …

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Self-Regulated Incremental Clustering With Focused Preferences, Di Wang, Ah-Hwee Tan Jul 2016

Self-Regulated Incremental Clustering With Focused Preferences, Di Wang, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Due to their online learning nature, incremental clustering techniques can handle a continuous stream of data. In particular, various incremental clustering techniques based on Adaptive Resonance Theory (ART) have been shown to have low computational complexity in adaptive learning and are less sensitive to noisy information. However, parameter regularization in existing ART clustering techniques is applied either on different features or on different clusters exclusively. In this paper, we introduce Interest-Focused Clustering based on Adaptive Resonance Theory (IFC-ART), which self-regulates the vigilance parameter associated with each feature and each cluster. As such, we can incorporate the domain knowledge of the …

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The Impact Of Nasd Rule 2711 And Nyse Rule 472 On Analyst Behavior: The Strategic Timing Of Recommendations Issued On Weekends, Yi Dong, Nan Hu Jul 2016

The Impact Of Nasd Rule 2711 And Nyse Rule 472 On Analyst Behavior: The Strategic Timing Of Recommendations Issued On Weekends, Yi Dong, Nan Hu

Research Collection School Of Computing and Information Systems

Amendments to NASD Rule 2711 and NYSE Rule 472, enacted in May 2002, mandate that sell-side analysts disclose the distribution of their security recommendations by buy, hold and sell category. This regulation enhances the transparency of analysts' information and mitigates the long-recognized optimistic bias in their recommendations. However, we find that analysts are more likely to issue sell recommendations or downgrade revisions on weekends when investors have limited attention after these rule changes. This pattern is more pronounced for prestigious analysts, who are more likely to influence stock prices. Market reaction tests reveal an incomplete immediate response and a greater …

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Real-Time Salient Object Detection With A Minimum Spanning Tree, Wei-Chih Tu, Shengfeng He, Qingxiong Yang, Shao-Yi Chien Jul 2016

Real-Time Salient Object Detection With A Minimum Spanning Tree, Wei-Chih Tu, Shengfeng He, Qingxiong Yang, Shao-Yi Chien

Research Collection School Of Computing and Information Systems

In this paper, we present a real-time salient object detection system based on the minimum spanning tree. Due to the fact that background regions are typically connected to the image boundaries, salient objects can be extracted by computing the distances to the boundaries. However, measuring the image boundary connectivity efficiently is a challenging problem. Existing methods either rely on superpixel representation to reduce the processing units or approximate the distance transform. Instead, we propose an exact and iteration free solution on a minimum spanning tree. The minimum spanning tree representation of an image inherently reveals the object geometry information in …

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Outlier Detection In Complex Categorical Data By Modeling The Feature Value Couplings, Guansong Pang, Longbing Cao, Ling Chen Jul 2016

Outlier Detection In Complex Categorical Data By Modeling The Feature Value Couplings, Guansong Pang, Longbing Cao, Ling Chen

Research Collection School Of Computing and Information Systems

This paper introduces a novel unsupervised outlier detection method, namely Coupled Biased Random Walks (CBRW), for identifying outliers in categorical data with diversified frequency distributions and many noisy features. Existing pattern-based outlier detection methods are ineffective in handling such complex scenarios, as they misfit such data. CBRW estimates outlier scores of feature values by modelling feature value level couplings, which carry intrinsic data characteristics, via biased random walks to handle this complex data. The outlier scores of feature values can either measure the outlierness of an object or facilitate the existing methods as a feature weighting and selection indicator. Substantial …

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Linear Encryption With Keyword Search, Shiwei Zhang, Guomin Yang, Yi Mu Jul 2016

Linear Encryption With Keyword Search, Shiwei Zhang, Guomin Yang, Yi Mu

Research Collection School Of Computing and Information Systems

Nowadays an increasing amount of data stored in the public cloud need to be searched remotely for fast accessing. For the sake of privacy, the remote files are usually encrypted, which makes them difficult to be searched by remote servers. It is also harder to efficiently share encrypted data in the cloud than those in plaintext. In this paper, we develop a searchable encryption framework called Linear Encryption with Keyword Search (LEKS) that can semi-generically convert some existing encryption schemes meeting our Linear Encryption Template (LET) to be searchable without re-encrypting all the data. For allowing easy data sharing, we …

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Automatic Hookworm Detection In Wireless Capsule Endoscopy Images, Xiao Wu, Honghan Chen, Tao Gan, Junzhou Chen, Chong-Wah Ngo, Qiang Peng Jul 2016

Automatic Hookworm Detection In Wireless Capsule Endoscopy Images, Xiao Wu, Honghan Chen, Tao Gan, Junzhou Chen, Chong-Wah Ngo, Qiang Peng

Research Collection School Of Computing and Information Systems

Wireless capsule endoscopy (WCE) has become a widely used diagnostic technique to examine inflammatory bowel diseases and disorders. As one of the most common human helminths, hookworm is a kind of small tubular structure with grayish white or pinkish semi-transparent body, which is with a number of 600 million people infection around the world. Automatic hookworm detection is a challenging task due to poor quality of images, presence of extraneous matters, complex structure of gastrointestinal, and diverse appearances in terms of color and texture. This is the first few works to comprehensively explore the automatic hookworm detection for WCE images. …

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Fine-Grained Detection Of Programming Students’ Frustration Using Keystrokes, Mouse Clicks And Interaction Logs, Hua Leong Fwa Jul 2016

Fine-Grained Detection Of Programming Students’ Frustration Using Keystrokes, Mouse Clicks And Interaction Logs, Hua Leong Fwa

Research Collection School Of Computing and Information Systems

Prolonged frustration leads to loss of confidence and eventual disinterest in the learning itself. The modelling of frustration in learning is thus important as it informs on the appropriate time to intervene to sustain the interest and motivation of students. To automatically detect learner’s frustration in a naturalistic learning environment, the novel use of keystrokes, mouse clicks and interaction patterns of students captured within the context of a tutoring system was proposed. The modelling approach was described and a comparison was made between the proposed model using Bayesian Network and the baseline Naïve Bayes model. With the formulation of an …

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Hci Testing In Laboratory Or Field Settings, Chuan-Hoo Tan, Austin Silva, Rich Lee, Kanliang Wang, Fiona Fui-Hoon Nah Jul 2016

Hci Testing In Laboratory Or Field Settings, Chuan-Hoo Tan, Austin Silva, Rich Lee, Kanliang Wang, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

This paper presents perspectives from both academia and practice on how an HCI testing is to be conducted and the deliberations that go into the testing. HCI testing can be conducted in closed-door laboratory or in a field setting. While there is an increased interest in field testing of an HCI artifact, there is always an enduring concern over how to administer a field testing given that the testers will have less control over the course of testing. In this paper, we cover HCI testing deliberation as well as the operational issues of field testing, and conclude the paper with …

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Aviation And Cybersecurity: Opportunities For Applied Research, Jon Haass, Radhakrishna Sampigethaya, Vincent Capezzuto Jul 2016

Aviation And Cybersecurity: Opportunities For Applied Research, Jon Haass, Radhakrishna Sampigethaya, Vincent Capezzuto

Publications

Aviation connects the global community and is moving more people and payloads faster than ever. The next decade will experience an increase in manned and unmanned aircraft and systems with new features and unprecedented applications. Cybertechnologies—including software, computer networks, and information technology—are critical and fundamental to these advances in meeting the needs of the aviation ecosystem of aircraft, pilots, personnel, passengers, stakeholders, and society. This article discusses current and evolving threats as well as opportunities for applied research to improve the global cybersecurity stance in the aviation and connected transportation industry of tomorrow.

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Deep Semantic Image Interpolation, Joshua D. Little Jul 2016

Deep Semantic Image Interpolation, Joshua D. Little

McKelvey School of Engineering Graduate Student Theses & Dissertations

Image datasets often live on a continuum: Images from an outdoor scene vary from day to night, across different weather conditions, and over the course of seasons. Faces age and exhibit different expressions. We consider the problem of taking individual images from these datasets and explicitly manipulating those images to change where they lie on the continuum. We focus on a version of this problem that requires as little input as possible, and we build off of previous work using CNN features to construct an intermediate image manifold on which to manipulate the images. We also investigate a novel way …

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A Simulation-Based Layered Framework Framework For The Development Of Collaborative Autonomous Systems, Ioannis Sakiotis Jul 2016

A Simulation-Based Layered Framework Framework For The Development Of Collaborative Autonomous Systems, Ioannis Sakiotis

Computational Modeling & Simulation Engineering Theses & Dissertations

The purpose of this thesis is to introduce a simulation-based software framework that facilitates the development of collaborative autonomous systems. Significant commonalities exist in the design approaches of both collaborative and autonomous systems, mirroring the sense, plan, act paradigm, and mostly adopting layered architectures. Unfortunately, the development of such systems is intricate and requires low-level interfacing which significantly detracts from development time. Frameworks for the development of collaborative and autonomous systems have been developed but are not flexible and center on narrow ranges of applications and platforms. The proposed framework utilizes an expandable layered structure that allows developers to define …

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A Computational Framework For Learning From Complex Data: Formulations, Algorithms, And Applications, Wenlu Zhang Jul 2016

A Computational Framework For Learning From Complex Data: Formulations, Algorithms, And Applications, Wenlu Zhang

Computer Science Theses & Dissertations

Many real-world processes are dynamically changing over time. As a consequence, the observed complex data generated by these processes also evolve smoothly. For example, in computational biology, the expression data matrices are evolving, since gene expression controls are deployed sequentially during development in many biological processes. Investigations into the spatial and temporal gene expression dynamics are essential for understanding the regulatory biology governing development. In this dissertation, I mainly focus on two types of complex data: genome-wide spatial gene expression patterns in the model organism fruit fly and Allen Brain Atlas mouse brain data. I provide a framework to explore …

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