Miracle-dz/UniFAR-FTUs huggingface dataset:
Non-rigid alignment for temporally consistent 3D video.

This thesis presents methods for the temporal alignment of 3D performance capture data. Discussion of sequential tracking is presented along with introduction of a novel approach for non-rigid free-form surfaces which improves on previous approaches by combining geometric and photometric features. This reduces drift and increases reliability of tracking for complex 3D video sequences of people. Subsequently Non-sequential tracking is achieved with the introduction of a novel shape similarity tree representation. This approach combined with the sequential tracking enables alignment of an entire database of multiple 3D video sequences into a consistent mesh structure. This is the first approach to enable alignment across multiple sequences. Non-sequential alignment is also shown to reduce drift and improve reliability of surface alignment overcoming situations where sequential tracking fails. Adopting this approach to representing 3D video sequences provides a number of advantages over previous work in the area. Firstly, with a hierarchical tree representation of a sequence tracking is capable of recovering from even the worst of errors. Secondly, the tree divides the sequence into multiple tracking paths represented by the branches of the tree itself. This allows tracking of long sequences with relatively few sequential alignment steps. The number of sequential alignment steps does not grow linearly with the length of the sequence but instead grows based on the depth of the tree structure. Thirdly, automatic shape matching allows global alignment of multiple sequences of the same character giving the ability to produce databases of temporally consistent 3D video. Temporally consistent 3D performance capture is an essential step in producing an animation framework based on reconstructed video data. Currently reconstruction primarily produces a topologically different representation of each frame. Consequently editing of a sequence requires alteration of each frame within the sequence. A temporally consistent representation would allow automatic propagation of edits with techniques such as space time editing. With a fully consistent database of motions for a character it is possible to parametrise and blend between motions using techniques such as motion graphs. Thus allowing re-animation of the captured character.
Reverse search in electronic dictionaries

In traditional dictionaries (paper dictionaries, digitized dictionaries, humanreadable dictionaries), we can look for information about a word covering the lemmas included in the nomenclature, usually listed alphabetically. After we find the searched word, we can get, in the microstructure, information on: – meanings of the lemma and their definitions; – phonetic transcriptions (or respelling); – grammatical information (morphological, syntactic, semantic, lexical, etc.); – encyclopaedic or cognitive information, specialised technical field, etc.; – pragmatic or rhetorical information; – combinatory possibilities (lexical or syntactic combinations); – examples and citations; – etymological information.
Extending Provenance for Deep Diagnosis of Distributed Systems

Diagnosing and repairing problems in complex distributed systems has always been challenging. A wide variety of problems can happen in distributed systems: routers can be misconfigured, nodes can be hacked, and the control software can have bugs. This is further complicated by the complexity and scale of today’s distributed systems. Provenance is an attractive way to diagnose faults in distributed systems, because it can track the causality from a symptom to a set of root causes. Prior work on network provenance has successfully applied provenance to distributed systems. However, they cannot explain problems beyond the presence of faulty events and offer limited help with finding repairs. In this dissertation, we extend provenance to handle diagnostics problems that require deeper investigations. We propose three different extensions: negative provenance explains not just the presence but also the absence of events (such as missing packets); meta provenance can suggest repairs by tracking causality not only for data but also for code (such as bugs in control plane programs); temporal provenance tracks causality at the temporal level and aims at diagnosing timing-related faults (such as slow requests). Compared to classical network provenance, our approach tracks richer causality at runtime and applies more sophisticated reasoning and post-processing. We apply the above techniques to software-defined networking and the border gateway protocol. Evaluations with real world traffic and topology show that our systems can diagnose and repair practical problems, and that the runtime overhead as well as the query turnarounds are reasonable.
The dictionary structure for effective word search

In the paper some issues connected with indexing documents in the Polish language are discussed. Algorithms for stemming and part of speech tagging, important in the process of text analysis and indexing are shortly described. Next their suitability to the Polish language, which has a very extensive inflection, is discussed. The usefulness for stemming and part of speech tagging of large dictionaries with inflected forms, like WordNet and open-source dictionary of Polish language is also described. Two dictionary structures enabling effective word searching are presented. In the final part, some tests of implemented two dictionary structures are described. Tests were made on the six actual and three crafted artificial texts. At the end conclusions of performed tests are formulated.
Cybernetic automata: An approach for the realization of economical cognition for multi-robot systems

Cybernetic Automata: An Approach for the Realization of Economical Cognition for Multi-Robot Systems. (May 2008) Nebu John Mathai, B.A.Sc. , University of Toronto; M.Eng., University of Toronto Co–Chairs of Advisory Committee: Dr. Deepa Kundur Dr. Takis Zourntos The multi-agent robotics paradigm has attracted much attention due to the variety of pertinent applications that are well-served by the use of a multiplicity of agents (including space robotics, search and rescue, and mobile sensor networks). The use of this paradigm for most applications, however, demands economical, lightweight agent designs for reasons of longer operational life, lower economic cost, faster and easily-verified designs, etc. An important contributing factor to an agent’s cost is its control architecture. Due to the emergence of novel implementation technologies carrying the promise of economical implementation, we consider the development of a technology-independent specification for computational machinery. To that end, the use of cybernetics toolsets (control and dynamical systems theory) is appropriate, enabling a principled specification of robotic control architectures in mathematical terms that could be mapped directly to diverse implementation substrates. This dissertation, hence, addresses the problem of developing a technologyindependent specification for lightweight control architectures to enable robotic agents to serve in a multi-agent scheme. We present the principled design of static and dynamical regulators that elicit useful behaviors, and integrate these within an overall architecture for both single and multi-agent control. Since the use of control theory can be limited in unstructured environments, a major focus of the work is on the
Permissions Based Android Malware Stealing Privacy Data Detection

The large numbers of malwares steal user privacy data in the Android application market, which poses a huge threat to user privacy data. To alleviate the threat, a scheme is proposed in this paper which based on privilege-feature detection. First, we filter sensitive privilege-feature that used to achieve attack out from the built-in permissions of Android. Second, based on sensitive privilege-feature, I design a scoring formula which can used to determine if the application is malicious; Last, I implement a prototype tool base on this method. Using this tool to detect malicious applications, the experimental results show that this method is more effective than the general antivirus engine. Introduction According to the 2016 "China Internet Development Statistics Report" shows that as of June 2016, the number of Chinese mobile Internet users reached 665 million, of which Android mobile phone users accounted for 67.8% [1]. As the Android mobile phone market share and Android operating system open source resulting in Android user privacy data has become a malware of the target [10] [11]. According to the report, the total number of new Android malwares in 2016 intercepted 14.33 million. The number of malwares that steal privacy data accounts for 6.1% of the total. The report counts the number of years of user privacy data, including contacts, text messages, call records, photos. Their number is 1.44 billion, 7.18 billion, 5.15 billion and 252.0 million. To alleviate threat we have done three tasks: (1)Manually analyze malwares that stealing user privacy data, to sort out set of sensitive permissions combinations and sensitive permissions. (2)Based on the set of sensitive permissions database, we designed a lightweight detection method that can detect malwares that steal user privacy data. (3)According to the detection method that has be designed to achieve the tool and use tool to experiment. The experimental results show that the tool can detect malware more effectively than the general antivirus engine. Next, the article introduces the process of detecting the malicious application of Android user privacy data in the first section. The second section describes how to get the sensitive permission characteristics and calculation application points in the detection process; The third section carried out the experiment and analyzed the experimental results. The fourth section introduces related work. The fifth section summarizes the methods used in this paper and the direction of the research in future.
Online Dispute Resolution Algorithm; Artificial Intelligence Model as a Pinnacle

The major principle of Alternative Dispute Resolution is the informality with the process dispute settlement. Online dispute resolution can help to resolving disputes, maintain conventional informality, cost effectiveness and speed through the use of Artificial Intelligence help to streamline dispute processes and the disputants. Online Dispute Resolution referred to processes for dispute resolution that is based on information and connection. The article reveals that Online Dispute Resolution gained popularity by facilitating inexpensive dispute resolution. That Online Dispute Resolution enhanced disputes settlement through Electronic delivered briefs, video conference hearings, and automated online process. The disputants at the Global trend take advantages of ODR are best suited. This makes ODR particularly suited for international commerce and e-commerce, where the disputants are separated geographically and amount involved is minimal. The article posses that Artificial Intelligence in Online Dispute Resolution has been progressing rapidly. It concluded that even if humans can do dispute resolution wrongly; society perhaps still would rather apply human judges than give full control to a machine. Many consider justice to be a uniquely human ideal that may be extremely difficult in Artificial Intelligence to execute no matter its level of sophistication in programming.
An improved sub-word based speech recognizer

The authors describe a system for speaker-dependent speech recognition based on acoustic subword units. Several strategies for automatic generation of an acoustic lexicon are outlined. Preliminary tests have been performed on a small vocabulary. In these tests, the proposed system showed results comparable to those of whole-word-based systems. <<ETX>>
Cooperative control of quadrotors and mobile robots: controller design and experiments

Cooperative control of multi-agent systems (MASs) has been intensively investigated in the past decade. The task is always complicated for an individual agent, but can be achieved by collectively operating a group of agents in a reliable, economic and efficient way. Although a lot of efforts are being spent on improving MAS performances, much progress has yet to be developed on different aspects. This thesis aims to solve problems in the consensus control of multiple quadrotors and/or mobile robots considering irregular sampling controls, heterogeneous agent dynamics and the presence of model uncertainties and disturbances. The thesis proceeds with Chapter 1 by providing the literature review of the state-of-the-art development in the consensus control of MASs. Chapter 2 introduces experimental setups of the laboratory involving two-wheeled mobile robots (2WMRs), quadrotors, positioning systems and inter-vehicle communications. All of the developed theoretical results in Chapters 3-6 are experimentally verified on the platform. Then it is followed by two main parts: Irregular sampling consensus control methods (Chapter 3 and 4) and cooperative control of heterogeneous MASs (Chapter 5 and 6). Chapter 3 focuses on the non-uniform sampling consensus control for a group of 2WMRs, and Chapter 4 studies the event-based rendezvous control for a group of asynchronous robots with time-varying communication delays. Chapter 5
A module-based cell processor simulator

An interesting design alternative to replication-based chip multiprocessors is to create heterogeneous chip multiprocessors composed of several different cores, with one or more of them running the operating system and orchestrating execution, and the others serving as accelerators where parts of the application are off-loaded. We are developing a simulator for this kind of heterogenous architectures, using the Cell Broadband Engine as a first model and the UNISIM modular infrastructure. Thanks to UNISIM, the modules composing the simulator can be easily changed and replaced by others, allowing us to customize the processor and explore the design space for these emerging architectures.
Stemming Influence on Similarity Detection of Abstract Written in Indonesia

In this paper we would like to discuss about stemming effect by using Nazief and Adriani algorithm against similarity detection result of Indonesian written abstract. The contents of the publication abstract similarity detection can be used as an early indication of whether or not the act of plagiarism in a writing. Mostly in processing the text adding a pre-process, one of it which is called a stemming by changing the word into the root word in order to maximize the searching process. The result of stemming process will be changed as a certain word n-gram set then applied an analysis of similarity using Fingerprint Matching to perform similarity matching between text. Based on the F 1 -score which used to balance the precision and recall number, the detection that implements stemming and stopword removal has a better result in detecting similarity between the text with an average is 42%. It is higher comparing to the similarity detection by using only stemming process (31%) or the one that was done without involving the text pre-process (34%) while applying the bigram.
TOWARDS BUILDING AN INTELLIGENT REVISION ASSISTANT FOR ARGUMENTATIVE WRITINGS

Current intelligent writing assistance tools (e.g. Grammarly, Turnitin, etc.) typically work by locating the problems of essays for users (grammar, spelling, argument, etc.) and providing possible solutions. These tools focus on providing feedback on a single draft, while ignoring feedback on an author’s changes between drafts (revision). This thesis argues that it is also important to provide feedback on authors’ revision, as such information can not only improve the quality of the writing but also improve the rewriting skill of the authors. Thus, it is desirable to build an intelligent assistant that focuses on providing feedback to revisions. This thesis presents work from two perspectives towards the building of such an assistant: 1) a study of the revision’s impact on writings, which includes the development of a sentence-level revision schema, the annotation of corpora based on the schema and data analysis on the created corpora; a prototype revision assistant was built to provide revision feedback based on the schema and a user study was conducted to investigate whether the assistant could influence the users’ rewriting behaviors. 2) the development of algorithms for automatic revision identification, which includes the automatic extraction of the revised content and the automatic classification of revision types; we first investigated the two problems separately in a pipeline manner and then explored a joint approach that solves the two problems at the same time.
Controller-pilot communications using a VDL Mode 2 datalink for the NASA runway incursion prevention system

NASA's Runway Incursion Prevention System (RIPS) was tested between September and October 2000 at the Dallas Fort-Worth International Airport (DFW). Controller-Pilot Datalink Communications (CPDLC) represented one component of the RIPS program. Air traffic controllers relayed surface operations instructions to NASA's 757 research aircraft via a Controller Communications and Situational Awareness Terminal (C-CAST). The Onyx mainframe computer aboard the 757 decoded these messages and sent automatic acknowledgements back to the C-CAST. The CPDLC messages were sent over a datalink utilizing the ICAO-defined VHF Digital Link (VDL) Mode 2 protocol. This paper presents implementation and performance details of the datalink. The paper describes the VDL Mode 2 protocol, the overall architecture of the CPDLC system, hardware-software interfacing details, CPDLC message formats, signal coverage data for the DFW airport, and design details of the Airborne Datalink Manager (ADLM) software used for this work.
Summarization of Document using Java

Automatic summarization is the process of reducing a document by a computer program to create summary which retains the important aspects of the original document. As the use of whole document is very tedious task so summary helps identifying the general overview and its importance for us. Generally, there are two approaches of automatic summarization: extraction and abstraction. Extractive methods work by selecting a subset of existing words, phrases, or sentences in the original text to form the summary. Whereas, abstractive methods build an internal semantic representation and then use natural language generation techniques to create a summary that is closer to what a human might generate. Such a summary might contain words not explicitly present in the original. The state-of-the-art abstractive methods are still quite weak, so most research has focused on extractive methods. Each programming language is having its own set of libraries which helps for reading and summarizes the document. This paper presents basic steps of summarization of documents, its challenges and the set of APIs which are available in java and its related technologies.
Leveraging Millimeter Waves for Security

The fact that Millimeter Wave (mmWave) communication needs to be directional is usually perceived as a challenge; in this paper we argue that it enables efficient secret key sharing that are unconditionally secure from passive eavesdroppers, by building on packet erasures. We showcase the potential of our approach in two setups: beam sweeping to align receiver/transmitter pairs, and vehicle platooning. We show that in the first case, we can establish a few hundred secret bits at virtually no additional transmission cost; and in the second case, we can potentially establish keys in the order of tenths of Mbps. These first results are based on some simplifying assumptions, yet we believe they give incentives to further explore such techniques.
Enhancing WWW security through CAPTCHA by leveraging cognitive factors

Many websites use CAPTCHA to defend against malicious automated programs from performing abusive tasks such as illegitimate account registration. CAPTCHA is widely used on commercial websites as a Human Interactive Proofs (HIP) system due to its simplicity of use and effectiveness against attacks. Over the years advances in Optical Character Recognition (OCR) software and techniques developed to break CAPTCHA began to expose flaws and vulnerabilities of these CAPTCHA implementations. CAPTCHA can be improved by adding several levels of complexity but still retain the purpose of CAPTCHA by making it very simple for human users but very difficult for bots to break. In our system multiple different challenge phrases were displayed instead of one like traditional methods. To pass our CAPTCHA challenge questions, users have to graphically interpret the displayed image to determine which challenge phrase to decipher. Based on our methodology, several schemes have been designed and implemented. A particular design was chosen based on the result of surveys conducted on human subjects for the user-friendliness. The result of the surveys shows that our design is preferred by users and helps preventing automated attacks from bots using known methods.
Overseer: SDN-Assisted Bandwidth and Latency Aware Route Optimization based on Application Requirement

Bandwidth and latency are two major factors that contribute the most to network application performance. Between each pair of switches in a network, there may be multiple paths connecting them. Each path has different properties because of multiple factors. Traditional shortest-path routing does not take this knowledge into consideration and may result in sub-optimal performance of applications and underutilization of the network. We propose a concept of “bandwidth and latency aware routing”. The idea is that we could improve overall performance of the network by separating application into bandwidthoriented and latency-oriented application and allocate separate route for each type of application accordingly. We also proposed a design of this network implemented with OpenFlow as well as Overseer, a reference implementation. Routes are calculated based on monitored information using Dijkstra algorithm and its variation. To demonstrate possible application of bandwidth and latency aware network, integration with MPI is employed as an example. To evaluate eligibility, feasibility and practicality of this work, we tested Overseer with emulated environment, controlled virtual environment and real world global-scale environment. Compared with traditional routing, bandwidth and latency aware routing increase overall bandwidth and reduce overall latency significantly in network with congestion. ∗Master’s Thesis, Department of Information Systems, Graduate School of Information Science, Nara Institute of Science and Technology, NAIST-IS-MT1351211, March 12, 2015.
Analyzing Curriculum Mapping Data: Enhancing Student Learning through Curriculum Redesign

This paper includes four examples of data representation from curriculum mapping activities in higher education. The first example shows course outcomes mapped to program-level learning outcomes (PLOs) for one course, and illustrates what one instructor might produce while mapping his or her course. The second example is a bar chart that summarizes the number and depth of course outcomes for identified programlevel learning outcomes when counting all courses in a program. It shows at a glance which program-level learning outcomes are emphasized in the program and to what extent. In the third example, two accompanying charts illustrate how a specific PLO, written communication, is taught and assessed across a program. The fourth example details all required courses within a program and their emphasis on PLOs. This chart shows emphasis and progression of student learning for each PLO throughout a program. Questions to guide the discussion of interpreting the data are included for each one. The end of the paper lists some questions that can be used for discussing and interpreting curriculum mapping data.