Vkse-Mo: Verifiable Keyword Search Over Encrypted Data In Multi-Owner Settings, 2017 Xidian University
Vkse-Mo: Verifiable Keyword Search Over Encrypted Data In Multi-Owner Settings, Yinbin Miao, Jianfeng Ma, Ximeng Liu, Junwei Zhang, Zhiquan Liu
Research Collection School Of Information Systems
Searchable encryption (SE) techniques allow cloud clients to easily store data and search encrypted data in a privacy-preserving manner, where most of SE schemes treat the cloud server as honest-but-curious. However, in practice, the cloud server is a semi-honest-but-curious third-party, which only executes a fraction of search operations and returns a fraction of false search results to save its computational and bandwidth resources. Thus, it is important to provide a results verification method to guarantee the correctness of the search results. Existing SE schemes allow multiple data owners to upload different records to the cloud server, but these schemes have ...
Fast On-Line Kernel Density Estimation For Active Object Localization, 2017 Portland State University
Fast On-Line Kernel Density Estimation For Active Object Localization, Anthony D. Rhodes, Max H. Quinn, Melanie Mitchell
Computer Science Faculty Publications and Presentations
A major goal of computer vision is to enable computers to interpret visual situations—abstract concepts (e.g., “a person walking a dog,” “a crowd waiting for a bus,” “a picnic”) whose image instantiations are linked more by their common spatial and semantic structure than by low-level visual similarity. In this paper, we propose a novel method for prior learning and active object localization for this kind of knowledge-driven search in static images. In our system, prior situation knowledge is captured by a set of flexible, kernel-based density estimations— a situation model—that represent the expected spatial structure of the ...
Supporting Trajectory Udf Queries And Indexes On Postgis, 2017 Turbo Soft Inc.
Supporting Trajectory Udf Queries And Indexes On Postgis, Pyoung Woo Yang, Kwang Woo Nam
Free and Open Source Software for Geospatial (FOSS4G) Conference Proceedings
In this paper, we propose a system model for querying and indexing the GPS trajectory of moving objects on PostGIS/PostgreSQL. We developed moving object data types including MPoint(moving point), MDouble(moving double) for GPS trajectories. Also, various moving objects UDFs(user-defined functions) are implemented for moving objects queries. For efficient query processing, r-tree index is extended for trajectory, and pre-materialization techniques are proposed for fast UDF processing. Experimental results show that the pre-materialization techniques are about 1.2 times faster than naïve query processing using r-tree index.
Analyzing The Performance Of Nosql Vs. Sql Databases For Spatial And Aggregate Queries, 2017 International Institute of Information Technology Hyderabad Gachibowli, Hyderabad, India
Analyzing The Performance Of Nosql Vs. Sql Databases For Spatial And Aggregate Queries, Sarthak Agarwal, Ks Rajan
Free and Open Source Software for Geospatial (FOSS4G) Conference Proceedings
Relational databases have been around for a long time and spatial databases have exploited this feature for close to two decades. The recent past has seen the development of NoSQL non-relational databases, which are now being adopted for spatial object storage and handling, too. While SQL databases face scalability and agility challenges and fail to take the advantage of the cheap memory and processing power available these days, NoSQL databases can handle the rise in the data storage and frequency at which it is accessed and processed - which are essential features needed in geospatial scenarios, which do not deal with ...
Reveiw Paper.Docx, 2017 International Islamic University Chittagong (IIUC)
Reveiw Paper.Docx, Shahariar Rifat
No abstract provided.
Developing Grounded Goals Through Instant Replay Learning, 2017 Swarthmore College
Developing Grounded Goals Through Instant Replay Learning, Lisa Meeden, Douglas S. Blank
Computer Science Faculty Research and Scholarship
This paper describes and tests a developmental architecture that enables a robot to explore its world, to find and remember interesting states, to associate these states with grounded goal representations, and to generate action sequences so that it can re-visit these states of interest. The model is composed of feed-forward neural networks that learn to make predictions at two levels through a dual mechanism of motor babbling for discovering the interesting goal states and instant replay learning for developing the grounded goal representations. We compare the performance of the model with grounded goal representations versus random goal representations, and find ...
When Big Data Gets Too Big, 2017 Vocational Training Council
When Big Data Gets Too Big
SIGNED: The Magazine of The Hong Kong Design Institute
Computer modelling has long been used as a design tool, and big data is a massive resource on which to build these models. But when the datasets get too big for computers to handle, innovative design solutions are needed. And the urge to play has driven technology forward
Data Predictive Control Using Regression Trees And Ensemble Learning, 2017 University of Pennsylvania
Data Predictive Control Using Regression Trees And Ensemble Learning, Achin Jain, Francesco Smarra, Rahul Mangharam
Real-Time and Embedded Systems Lab (mLAB)
Decisions on how to best operate large complex plants such as natural gas processing, oil refineries, and energy efficient buildings are becoming ever so complex that model-based predictive control (MPC) algorithms must play an important role. However, a key factor prohibiting the widespread adoption of MPC, is the cost, time, and effort associated with learning first-principles dynamical models of the underlying physical system. An alternative approach is to employ learning algorithms to build black-box models which rely only on real-time data from the sensors. Machine learning is widely used for regression and classification, but thus far data-driven models have not ...
Comparing And Improving Facial Recognition Method, 2017 California State University – San Bernardino
Comparing And Improving Facial Recognition Method, Brandon Luis Sierra
Electronic Theses, Projects, and Dissertations
Facial recognition is the process in which a sample face can be correctly identified by a machine amongst a group of different faces. With the never-ending need for improvement in the fields of security, surveillance, and identification, facial recognition is becoming increasingly important. Considering this importance, it is imperative that the correct faces are recognized and the error rate is as minimal as possible. Despite the wide variety of current methods for facial recognition, there is no clear cut best method. This project reviews and examines three different methods for facial recognition: Eigenfaces, Fisherfaces, and Local Binary Patterns to determine ...
Natural Language Processing Based Generator Of Testing Instruments, 2017 California State University, San Bernardino
Natural Language Processing Based Generator Of Testing Instruments, Qianqian Wang
Electronic Theses, Projects, and Dissertations
Natural Language Processing (NLP) is the field of study that focuses on the interactions between human language and computers. By “natural language” we mean a language that is used for everyday communication by humans. Different from programming languages, natural languages are hard to be defined with accurate rules. NLP is developing rapidly and it has been widely used in different industries. Technologies based on NLP are becoming increasingly widespread, for example, Siri or Alexa are intelligent personal assistants using NLP build in an algorithm to communicate with people. “Natural Language Processing Based Generator of Testing Instruments” is a stand-alone program ...
Probabilistic Graphical Models Follow Directly From Maximum Entropy, 2017 Banking University of Ho Chi Minh City
Probabilistic Graphical Models Follow Directly From Maximum Entropy, Anh H. Ly, Francisco Zapata, Olac Fuentes, Vladik Kreinovich
Departmental Technical Reports (CS)
Probabilistic graphical models are a very efficient machine learning technique. However, their only known justification is based on heuristic ideas, ideas that do not explain why exactly these models are empirically successful. It is therefore desirable to come up with a theoretical explanation for these models' empirical efficiency. At present, the only such explanation is that these models naturally emerge if we maximize the relative entropy; however, why the relative entropy should be maximized is not clear. In this paper, we show that these models can also be obtained from a more natural -- and well-justified -- idea of maximizing (absolute) entropy.
In Search Of Homo Sociologicus, 2017 The Graduate Center, City University of New York
In Search Of Homo Sociologicus, Yunqi Xue
All Graduate Works by Year: Dissertations, Theses, and Capstone Projects
The subject of this dissertation is to build an epistemic logic system that is able to show the spreading of knowledge and beliefs in a social network that contains multiple subgroups. Epistemic logic is the study of logical systems that express mathematical properties of knowledge and belief. In recent years, there have been increasing number of new epistemic logic systems that are focused on community properties such as knowledge and belief adoption among friends.
We are interested in revisable and actionable social knowledge/belief that leads to a large group action. Instead of centralized coordination, bottom-up approach is our focus ...
Distributed Database Fragmentation System Without Reading Empirical Data, 2017 International Islamic University Chittagong (IIUC)
Distributed Database Fragmentation System Without Reading Empirical Data, Bilawal Alam
Review Paper On Development Of National Health Data Warehouse Bangladesh: Privacy Issues And Practical Solution And Similarity Analysis Of Patients’ Data: Bangladesh Perspective., 2017 International Islamic University Chittagong (IIUC)
Review Paper On Development Of National Health Data Warehouse Bangladesh: Privacy Issues And Practical Solution And Similarity Analysis Of Patients’ Data: Bangladesh Perspective., Kalyan Brata Chakraborty
Kalyan Brata Chakraborty
No abstract provided.
Forensic State Acquisition From Internet Of Things (Fsaiot): A General Framework And Practical Approach For Iot Forensics Through Iot Device State Acquisition, Christopher S. Meffert, Devon R. Clark, Ibrahim Baggili, Frank Breitinger
Electrical & Computer Engineering and Computer Science Faculty Publications
IoT device forensics is a difficult problem given that manufactured IoT devices are not standardized, many store little to no historical data, and are always connected; making them extremely volatile. The goal of this paper was to address these challenges by presenting a primary account for a general framework and practical approach we term Forensic State Acquisition from Internet of Things (FSAIoT). We argue that by leveraging the acquisition of the state of IoT devices (e.g. if an IoT lock is open or locked), it becomes possible to paint a clear picture of events that have occurred. To this ...
Bim+Blockchain: A Solution To The Trust Problem In Collaboration?, 2017 Dublin Institute of Technology
Bim+Blockchain: A Solution To The Trust Problem In Collaboration?, Malachy Mathews, Dan Robles, Brian Bowe
This paper provides an overview of historic and current organizational limitations emerging in the Architecture, Engineering, Construction, Building Owner / Operations (AECOO) Industry. It then provides an overview of new technologies that attempt to mitigate these limitations. However, these technologies, taken together, appear to be converging and creating entirely new organizational structures in the AEC industries. This may be characterized by the emergence of what is called the Network Effect and it’s related calculus. This paper culminates with an introduction to Blockchain Technology (BT) and it’s integration with the emergence of groundbreaking technologies such as Internet of Things (IoT ...
Lmproving Microcontroller And Computer Architecture Education Through Software Simulation, 2017 The University of Western Ontario
Lmproving Microcontroller And Computer Architecture Education Through Software Simulation, Kevin Brightwell
Electronic Thesis and Dissertation Repository
In this thesis, we aim to improve the outcomes of students learning Computer Architecture and Embedded Systems topics within Software and Computer Engineering programs. We develop a simulation of processors that attempts to improve the visibility of hardware within the simulation environment and replace existing solutions in use within the classroom. We designate a series of requirements of a successful simulation suite based on current state-of-the-art simulations within literature. Provided these requirements, we build a quantitative rating of the same set of simulations. Additionally, we rate our previously implemented tool, hc12sim, with current solutions. Using the gaps in implementations from ...
Regulating Robo Advice Across The Financial Services Industry, 2017 University of Pennsylvania Law School
Regulating Robo Advice Across The Financial Services Industry, Tom Baker, Benedict G. C. Dellaert
Automated financial product advisors – “robo advisors” – are emerging across the financial services industry, helping consumers choose investments, banking products, and insurance policies. Robo advisors have the potential to lower the cost and increase the quality and transparency of financial advice for consumers. But they also pose significant new challenges for regulators who are accustomed to assessing human intermediaries. A well-designed robo advisor will be honest and competent, and it will recommend only suitable products. Because humans design and implement robo advisors, however, honesty, competence, and suitability cannot simply be assumed. Moreover, robo advisors pose new scale risks that are different ...
Parallel Computation Using Mems Oscillator-Based Computing System, 2017 Purdue University
Parallel Computation Using Mems Oscillator-Based Computing System, Xinrui Wang, Ilias Bilionis, Salar Safarkhani
The Summer Undergraduate Research Fellowship (SURF) Symposium
In recent years, parallel computing systems such as artificial neural networks (ANNs) have been of great interest. In these systems which emulate the behavior of human brains, the processing is carried out simultaneously. However, it is still a challenging engineering problem to design highly efficient hardware for parallel computing systems. We will study the properties of networks of Microelectromechanical System (MEMS) oscillators to explore their capabilities as parallel computing infrastructure. Furthermore, we simulate the time-variant states of MEMS oscillators network under various initial conditions and performance of certain tasks. Recent theoretical results show that networks of MEMS oscillators have some ...
The Practicality Of Cloud Computing, 2017 Sacred Heart University
The Practicality Of Cloud Computing, Xiaohua (Cindy) Li
Since its inception, cloud computing has become the current paradigm. Organizations of different size and type have embraced the concept because of its both technological and economic advantages. Sacred Heart University Library has recently published its newly designed website on the cloud. For a small academic library, what does it mean to put their online data on the cloud? This paper will analyze and discuss the advantages of cloud computing, and some potential obstacles created by it through the author’s observations. This paper hopes the uniqueness of the case will contribute to the improvement of cloud computing experience of ...