Miracle-dz/UniFAR-FTUs huggingface dataset:
Stochastic volatility jump-diffusion models as time-changed Lévy processes

This thesis focuses on applying the time-changed Levy processes technique firstly presented by Carr and Wu (2004) in order to deduce the Bakshi et al. (1997) model with a general jump size distribution. The second goal is reach a full correlation scheme, after reaching the fundamental theorem, where we show how to compute the joint characteristic function of a finite number of time-changed Levy processes under the leverage-neutral measure, we obtain an exact characteristic function for an asset price with stochastic volatility, stochastic interest rates, jumps and a full correlation scheme. As far as we know this is the first time that the exact characteristic function of an model that take into account stochastic volatility, stochastic interest rates, jumps and a full correlation scheme is achieved.
A brain-computer interface for navigation in virtual reality

A Brain-Computer Interface (BCI) decodes the brain signals representing a desire to do something, and transforms those signals into a control command. However, only a limited number of mental tasks have been previously detected and classified. Performing a real or imaginary navigation movement can similarly change the brainwaves over the motor cortex. We used an ERS-BCI to see if we can classify between movements in forward and backward direction offline and then online using different methods. Ten healthy people participated in BCI experiments comprised two-sessions (48 min each) in a virtual environment tunnel. Each session consisted of 320 trials where subjects were asked to imagine themselves moving in the tunnel in a forward or backward motion after a randomly presented (forward versus backward) command on the screen. Three EEG electrodes were mounted bilaterally on the scalp over the motor cortex. Trials were conducted with feedback. In session 1, Band Power method, Time-frequency representation, Autoregressive models and asymmetry ratio were used in the β rhythm range with a LinearDiscriminant-analysis classifier and a Support Vector Machine classifier to discriminate between the two mental tasks. Thresholds for both tasks were computed offline and then used to form control signals that were used online in session 2 to trigger the virtual tunnel to move in the direction requested by the user's brain signals. After 96 min of training, the online band-power biofeedback training achieved an average classification precision of 76 %, whereas the offline classification with asymmetrical ratio and band-power achieved an average classification precision of 80%.
User support system for designing decisional database

The design of a multidimensional schema is usually performed by a specialist (computer scientist). According to data-driven, requirement-driven or hybrid-driven approaches, he determines the facts and axis of analysis. Such an approach assumes that the decision maker expresses, more or less formally, analysis needs and communicate them to the computer scientist. We propose multidimensional schema designing by the decision maker himself following a hybrid-driven approach. Through a process of assistance successively viewing intermediate schemas from sources, the decision maker gradually built his multidimensional schema. As what determined the measures studied, the analysis dimensions and hierarchies within dimensions. A software tool based on this principle has been developed and validated with decision makers
The Effect of Reform-Oriented and Other Mathematics Curricula on Students' College Mathematics Placement Test Scores

This study examined the college mathematics placement exam results of 1,277 students learning from nine secondary mathematics curricula and two Advanced Placement (AP) mathematics programs in 25 different high schools in the United States. The results suggest that students learning from several traditional mathematics programs and AP Calculus significantly outperformed students learning from the reform-oriented mathematics program, Core-Plus Mathematics Project, on algebra manipulation and calculus readiness questions. Prior mathematics achievement, course completion, and gender also significantly influenced mathematics placement scores.
Iterative DataDetection andPilot Symbol Assisted -Channel Estimation forSingle-Parity Check-Product CodedMultiple Antennas System

Maximum aposteriori (MAP)basediterative data detection andpilot symbol assisted channel estimation ofthesingle parity check product coded multiple antenna wireless communication system isdiscussed. Initerative data-detection andchannel-estimation algorithms, the channel estimator andthedatadetector recursively exchange theinformation order toimprove thesystem performance. Theworkinthis paper usesthesingle-parity- checkcode(SPC)as component code,parallel concatenated, ofproduct code (PC). TheSPC-PC codes are high-rate codes whenreasonable block lengths areused. Theyaresimple inbothencoding anddecoding, andare showntoproduce goodperformance whiledecoded iteratively. Bytaking theoutput oftheSPC-PCencoder intotwodefined-interleavers andtransmitting through multiple transmit antennas, will provide space andtime diversity inthesystem. Thisscheme would beBLAST-like system. Pilot-symbol aided channel estimation isusedto measure thechannel impulse response. Following the iteration ofthedecoding process, thechannel impulse response willbeupdated byemploying theextrinsic information output ofthedecoder. Theconvergence ofthis channel impulse response update will investigate.
Scene Segmentation and Understanding for Context-Free Point Clouds

The continuous development of new commodity hardware intended to capture the surface structure of objects is quickly making point cloud data ubiquitous. Scene understanding methods address the problem of determining the objects present in a point cloud which, dependant on sensor capabilities and object occlusions, is normally noisy and incomplete. In this paper, we propose a novel technique which enables automatic identiﬁcation of semantically meaningful structures within point clouds acquired using different sensors on a variety of scenes. The representation model, namely the structure graph, with nodes representing planar surface segments, is computed over these point clouds to help with the identiﬁcation task. In order to accommodate for more complex objects (e.g. chair, couch, cabinet, table), a training process is used to determine and concisely describe, within each object’s structure graph, its important shape characteristics. Results on a variety of point clouds show how our method can quickly discern certain object types.
Learning to remember and to forget: electrophysiological studies on attention-working memory interactions in typical development and ADHD

• A submitted manuscript is the version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers.
MODEL-VIEW-CONTROLLER (MVC) DESIGN PATTERNUNTUK APLIKASI PERANGKAT BERGERAK BERBASIS JAVA

Design pattern merupakan salah satu teknik mendesain komponen perangkat lunak yang bisa digunakan kembali. MVC design pattern merupakan design pattern untuk komponen perangkat lunak yang memisahkan secara tegas antara model data, tampilan, dan kendali perangkat lunak. Artikel ini akan membahas MVC design pattern disertai kesesuaiannya dengan aplikasi perangkat bergerak berbasis Java. Bagian akhir artikel ini menunjukkan bagaimana MVC design pattern untuk aplikasi bergerak berbasis Java. Kata Kunci : MVC, design pattern, aplikasi perangkat bergerak berbasis Java
Analyzing sentiment while accounting for negation scope and strength

Recent developments in automated sentiment analysis show a tendency of accounting for various aspects other than word frequencies. One of these aspects is negation. We compare several approaches to accounting for negation in sentiment analysis, differing in their methods of determining the scope of influence of a negation keyword. On a set of English movie review sentences, the best approach turns out to be to consider the first two words, following a negation keyword, to be negated by that keyword. Additionally, we propose to optimize the sentiment modification in case of negation to a value of ‐1.27 rather than ‐1.
Indexing and path query processing for xml data

XML has emerged as a new standard for information representation and exchange on the Internet. To efficiently process XML data, we propose the extended preorder numbering scheme, which determines the ancestor-descendant relationship between nodes in the hierarchy of XML data in constant time, and adapts to the dynamics of XML data by allocating extra space. Based on this numbering scheme, we propose sort-merge based algorithms, EA -Join and EE -Join, to process ancestor-descendant path expressions. The experimental results showed an order of magnitude performance improvement over conventional methods. We further propose the partition-based algorithms, which can be chosen by a query optimizer according to the characteristics of the input data. For complex path expressions with branches, we propose the Containment B+-tree (CB-tree) index and the IndexTwig algorithm. The CB-tree, which is an extension of the B+-tree, supports both the containment query and the reverse containment query. It is an effective indexing scheme for XML documents with or without a small number of recursions. The proposed IndexTwig algorithm works with any index supporting containment and reverse containment queries, such as the CB-tree. We also introduce a simplified output model, which outputs only the necessary result of a path expression. The output model enables the Fast Existence Test (FET) optimization to skip unnecessary data and avoid generating unwanted results. Also in this dissertation, we introduce techniques to process the predicates in XML path expressions using the EVR-tree. The EVR-tree combines the advantages of indexing on values or elements individually using B+-trees. It utilizes the high value selectivity and/or high structural selectivity, and provides ordered element access by using a priority queue. At the end of the dissertation, we introduce the XISS/R system, which is an implementation of the XML Indexing and Storage System (XISS) on top of a relational database. The XISS/R includes a web-based user interface and a XPath query engine to translate XPath queries into efficient SQL statements.
Investigating Cognitive Rhythms as a New Modality for Continuous Authentication

Abstract : Research performed and results achieved under the DARPA Active Authentication award Investigating Cognitive Rhythms as a New Modality for Continuous Authentication. The research under this project focused on five main tasks: (1) defining and extracting cognitive rhythms (atomic, pausality, linguistic, and revision features) from users' text production data; (2) determining the availability and discriminability of cognitive rhythm features for continuous authentication; (3) determining continuous authentication accuracies of cognitive rhythm features over a large population of users; (4) investigating the impact of non-zero effort forgery attacks against continuous authentication; and (5) prediction of a users' cognitive load levels and demographic information.
Applied Choice Analysis: A Primer

Preface 1. In the beginning 2. Basic notations of statistics 3. Choosing 4. Paradigms of choice data 5. Processes in setting up stated choice experiments 6. Choices in data collection 7. Nlogit for applied choice analysis: a primer 8. Handling choice data 9. Case study: model choice data 10. Getting started modelling: the workhorse - MNL 11. Getting more from your model 12. Practical issues in the application of choice models 13. Allowing for similarity of alternatives 14. Nested logit estimation 15. The mixed logit model 16. Mixed logit estimation Nlogit terms and commands References Index.
Analysis and fast querying of mobility data

Mobility data represents a widely used term to indicate sources of information, possibly structured in many different ways depending on technologies and formats used describing the localization or the movement, in time and space, of sets of entities. Regardless of specific ways through which mobility data is represented, this class of information is nowadays pervasive since it is massively produced, processed and analyzed for many different purposes. The importance of mobility data is going to increase even further in the future, given the ever growing diffusion of the internet of devices and the progressive introduction of the internet of things paradigm. In this thesis we contribute to mobility data research by addressing separately two distinct problems. The first one is related to the on-line processing of streams of mobility data coming from massive amounts of moving objects, where such streams contain location updates and some kind of queries continuously and periodically issued by the objects. This problem is frequently met, nowadays, in the context of Location-Based Services (LBS) or Location-Based Social Networking applications (LBSN), even if one has to observe that the nature of the problem allows it to be possibly found in quite diverse domains, such as massively multiplayer online games, anti-collision detection systems, behavioural simulations and so on. More precisely, we focus on the problem of computing massive range and k-nearest neighbour queries, which represents the time-dominant phase of the whole processing. In order to tackle effectively the problem we exploit the remarkable yet cheap computational power of modern GPUs by introducing novel algorithms and data structures, and we prove the effectiveness of our solutions through an extensive series of experiments. The second problem relates to the domain of mobility data mining. In this context the main goal is to devise novel, off-line analyses able to extract previously unknown and interesting patterns from raw mobility data. This kind of research is, in general, very interesting since it allows to gain new insights on mobility data. We address the problem of detecting avoidance behaviours between moving objects from historical movement traces. To this end, we first introduce a framework which formally defines what is an avoidance behaviour between moving objects; subsequently, on the basis of such framework we provide an algorithm which is able to extract these patterns. Finally, we experimentally prove the effectiveness of our solution with real-world datasets.
Process Coloring: An Information Flow-Preserving Approach to Malware Investigation

Abstract : Process Coloring is an information-preserving, provenance-aware software system for computer malware detection and investigation. By tainting each application process with a distinct color and propagating the color to other processes or system objects along with system call operations, Process Coloring preserves the "provenance" of malware attacks (namely, "Through which process did a malware program infiltrate the system? "). Process Coloring enables three useful malware defense capabilities: (1) color-based malware detection, (2) color-based malware break-in point identification, and (3) color-based log partitioning. Implemented on top of a virtualization platform, Process Coloring achieves strong tamper-resistance as the logs generated by the protected (virtual) machine are stored and processed outside the machine under attack. Finally, Process Coloring can be integrated with techniques that track information flows inside a program. The resultant integrated system achieves better malware detection accuracy by eliminating false positive alerts, especially for client-side environments. This report gives an overview of the Process Coloring project and presents the design, implementation, and evaluation highlights in the research effort.
Method of Automatic Ontology Mapping through Machine Learning and Logic Mining

Ontology mapping is the bottleneck of handling conflicts among heterogeneous ontologies and of implementing reconfiguration or interoperability of legacy systems. We proposed an ontology mapping method by using machine learning, type constraints and logic mining techniques. This method is able to find concept correspondences through instances and the result is optimized by using an error function; it is able to find attribute correspondence between two equivalent concepts and the mapping accuracy is enhanced by combining together instances learning, type constraints and the logic relations that are imbedded in instances; moreover, it solves the most common kind of categorization conflicts. We then proposed a merging algorithm to generate the shared ontology and proposed a reconfigurable architecture for interoperation based on multi agents. The legacy systems are encapsulated as information agents to participate in the integration system. Finally we give a simplified case study.
The performance of DS-CDMA cellular systems with variable-bit-rate traffic

The deployment of third generation (3G) cellular systems is resulting in a transition from cellular systems that predominantly carry constant-bit-rate (CBR) voice traffic to multi-service packet based systems that predominantly carry variable-bit-rate (VBR) traffic. With 3G DS-CDMA cellular systems there is a direct relationship between user traffic and propagation dependent performance as additional traffic causes increased system interference. This thesis investigates the impact of VBR traffic on the propagation dependent performance of DS-CDMA cellular systems that utilise frame-by-frame dynamic resource allocation on the radio channel. A DS-CDMA cellular system model is developed and the downlink performance of both outdoor macro-cellular and indoor pico-cellular systems is evaluated with a variety of traffic types. Both traffic scheduling performance and propagation dependent performance are evaluated as the two are inter-linked. Scenarios are identified where propagation dependent performance is sensitive to the statistical properties of the user traffic streams and it is shown that a significant performance difference potentially exists between different traffic types when the number of users per cell is low. When a significant performance difference does exist, burstier more variable traffic generally results in superior propagation dependent performance. The base transceiver station (BTS) transmitter power mean and variance provides a good indication of the level of propagation dependent performance regardless of the specific traffic type. Traffic scheduling policies that deliberately reduce the variability of user traffic streams are considered and in terms of propagation dependent performance these are shown to have a minimal impact on the performance difference between different traffic types. The implications of VBR traffic on DS-CDMA cellular system design are outlined and it is shown that VBR traffic can be approximated as CBR traffic in many scenarios and this is a convenient approximation as it simplifies system design and detailed traffic models do not need to be developed.
Generalized Scalarizing Problem for Multicriteria Optimization

The paper describes a generalized classification based scalarizing problem of multicriteria optimization. The basic properties of the generalized scalarizing problem are discussed and it is shown that some of the known scalarizing problems of the reference point and the classification based scalarizing problems as well can be obtained from it with the help of different transformations.
A Comparison of Three Combinations of Text and Graphics for Concept Learning. Technical Report 76-16.

Abstract : A study was conducted to determine how verbal instruction could be supplemented by visuals, and in particular, how to take pedagogical advantage of the excellent capabilities of the PLATO 4 computer-based instructional system. Literature research disclosed little previous information of value on the subject. Three versions of a lesson on the sine-ratio concept were prepared, one with verbal text supplemented with animated graphics, one supplemented with still graphics, and one without graphics (text only). Forty-five students from the Basic Electrivity/Electronics School at the Naval Training Center (NTC), San Diego, were randomly assigned to the three versions. A comparison of the pretest and posttest mean scores for each group revealed learning took place in each group, and a questionnaire administered after the posttest revealed that the students gave positive ratings to the instructional materials and presentations. The groups did not differ in time required for training. On the posttest, the animated graphics group had the highest mean performance, but none of the differences between groups were significant. It was concluded that these results are consistent with previous findings suggesting that graphics are more useful for teaching concepts involving time and motion than for concepts involving space, and more useful for tasks involving stimulus identification than for tasks involving terminology or comprehension.
IPsec Implementation in Embedded Systems for Partial Recon gurable Platforms

IPSEC IMPLEMENTATION IN EMBEDDED SYSTEMS FOR PARTIAL RECONFIGURABLE PLATFORMS Ahmad Salman George Mason University, 2011 Thesis Director: Dr. Jens-Peter Kaps Internet Protocol Security (IPsec) provides essential security against attacks on data transmitted over the Internet through different security services provided by cryptographic algorithms like encryption modules and hash functions. Due to the importance of IPsec, it has been implemented in hardware and software with different designs and parameters to suit different platforms and provide better solutions. Among the popular implementations of IPsec in hardware are those that target FPGA platforms because of the flexibility they offer the designer, ease of programming and high speeds that cannot be achieved through software. Due to the fact that FPGAs are resource limited devices, even efficient implementations of IPsec with all the services it provides might not fit on low cost devices or low area devices that are meant for light weight implementations. A solution to this problem can be Partial Reconfiguration which allows some IPsec services to be available in the system and the remaining services can be recalled when needed by an application. Partial Reconfiguration is a configuration method for FPGAs that allows certain portions of the device to be reconfigured during run-time without affecting other portions in the system or their functionality. In this thesis we will investigate the effect of implementing IPsec services using Partial Reconfiguration in terms of speed, area and reconfiguration time. For that, we built an embedded system controlled through an embedded processor to provide self reconfiguration of the system through a software application. We also implemented different versions of the embedded system using Microblaze and PowerPC embedded processors targeting two different platforms (Virtex-4 and Virtex-II-Pro) to perform thorough testing on the proposed design and analyze the results. Chapter 1: Introduction