Miracle-dz/UniFAR-FTUs huggingface dataset:
Bayesian Estimation of the Diffusion Tensor from diffusion weighted MRI data

of a thesis presented to the Faculty (Abstract) Diffusion tensor imaging is a method of magnetic resonance imaging which allows observation of diffusion and thus makes it possible to characterize microscopic properties of biological tissue. First research on the scalar self-diffusivity D in isotropic media was done in 1965. Today it is well known that a scalar value is not sufficient for describing diffusion in non-isotropic media like biological tissue. A tensor formalism is needed to describe the directional dependency. From the diffusion tensor, rotational invariants such as the trace or anisotropy indices are calculated to characterize abnormal diffusion in the brain due to diseases like stroke or schizophrenia. The diffusion tensor can also be used for investigation of fiber orientation in the brain (tractography). Constrained and unconstrained linear and nonlinear least squares methods are commonly used to determine the diffusion tensor from diffusion weighted magnetic resonance images. This work reviews these methods and extends them by using Bayesian parameter estimation to incorporate the true noise characteristic of magnitude MR images which is given by the Rice distribution. The precision and accuracy of this new technique is compared to previous methods using simulated data sets. The shape of the posterior is examined to determine which optimization algorithm is adequate for this problem. The Jacobian and the Hessian matrices of the posterior are derived. They can be used for optimization algorithms on the one hand and to derive error estimates for the best fit parameters on the other hand. The error estimates are tested on simulated data and shown to be valid. Acknowledgements It is a pleasure to thank the many people who made this thesis possible. I would like to gratefully acknowledge the supervision of Dr. Kevin H. Knuth. Without his hints and ideas, this work had not been possible. I also would like to thank him for all the opportunities he offered me, such as a visit to an observatory, attending Maxent 2007 and many others which made my stay abroad even more interesting. Knuth for their great lectures and the personal discussions from which I have benefited a lot. I would like to express my thanks to Dr. Babak Ardekani from the Nathan Kline Institute, who supported my work with ideas, papers and data. I also like to thank Cheng Guan Koay from the National Institute of Health for answering many questions about DTI and for sending me …
Privacy-preserving frequent itemset mining in outsourced transaction databases

Cloud computing has ushered a new interest in a paradigm called Datamining-as-a-service. This paradigm is aimed at organizations that lack the technical expertise or the computational resources enabling them to outsource their data mining tasks to a third party service provider. One of the main issues in this regard is the confidentiality of the valuable data at the server which the data owner considers as private. In this work, we study the problem of privacy preserving frequent itemset mining in outsourced transaction databases. We propose a novel hybrid method to achieve k-support anonymity based on statistical observations on the datasets. Our comprehensive experiments on real as well as synthetic datasets show that our techniques are effective and provide moderate privacy.
International Journal of Innovative Research in Computer and Communication Engineering a Countermeasure Circuit for Secure Aes Engine against Differential Power Analysis

— In cryptography, the Advanced Encryption Standard (AES) is one of the most popular algorithms used in symmetric key cryptography. It is available in many different encryption packages. AES is a 128 bit Symmetric block cipher which is based on a design principle known as a Substitution permutation network. Power analysis is a form of side channel attack in which the attacker studies the power consumption of a cryptographic hardware device (such as a smart card, tamper-resistant "black box", or integrated circuit). The attack can non-invasively extract cryptographic keys and other secret information from the device. Differential power analysis (DPA) is a side-channel attack which involves statistically analyzing power consumption from a cryptosystem. Several methods have been proposed in literatures to resist the DPA attack in cryptographic device, but they largely increase the hardware cost and severely degrade the throughput. In existing system, the security problem is resolved by a new architecture with self-generated true random sequence. DPA countermeasure circuit can effectively reduce the area overhead and throughput degradation.
Protocol Synthesis using Dialogue Structure Theory

Inspired by computational linguistic approaches to annotate the structures that occur in human dialogue, this paper describes a technique which encodes these structures as transformations applied to a protocol language. Agents can have a controlled mechanism to synthesise their interaction protocol during their participation in a multiagent system. This is in contrast to the approach typified by electronic institutions where agents must subscribe to a fixed protocol and relinquish control over an interaction that may not satisfy the agent’s dialogical needs.
Development of a stepped frequency GPR prototype

Ground penetrating radar systems and through the wall radars are important research areas which are frequently studied on due to their civilian and military applications. Development of penetrating radar systems using microwave frequencies is primary in that point. In this work, a stepped frequency continuous wave (SFCW) GPR prototype is developed. The system is working between 700MHz-6GHz frequency range and is controlled through user interface. The measured data and the detection results are shown through the same user interface in real time. The system can be used either for through the wall or subsurface applications. Initial experimental data results are shown.
Application of MVP Architecture in Reengineering of Legacy Financial System

As the progress of information technology, some financial systems used for long time can no longer meet the requirement of customers in both user interface and business process, and need reengineering imminently. In order to save the human resource and financial effort, this article raises a reengineering approach by encapsulating the back-end data access code of legacy system and only refactoring the front-end user interface and business logic. In the reengineering work, this article uses MVP (Model-View-Presenter) Architecture. By extracting screen logic into Presenters, the display code in View is independent from logic code in Presenter. Also, the introduction of MVP Architecture greatly enhances the reusability and the testability of business logic code, and finally improves the efficiency of development and test work significantly.
THE MUTUAL VARIATION OF WIND, SHEAR, AND BAROCLINICITY IN THE CUMULUS CONVECTIVE ATMOSPHERE OF THE HURRICANE

Abstract The enhanced cumulus convection in tropical disturbances acts in two opposing ways. In one sense the condensation heat from the cumuli acts to warm the inner portions of the disturbance and induce vertical shear of the horizontal wind through the thermal wind relationship. In the opposite sense the cumuli also act to suppress vertical wind shear by transfer of horizontal momentum within their up- and downdrafts. The operation of this dual or “paradox” role of the cumulus cloud is of fundamental importance for understanding the steady-state dynamics of the hurricane's inner core region and is also hypothesized to be of basic importance in the development of tropical storms and generation of easterly waves. Observational information and calculations on the radial distribution of baroclinicity and vertical shear collected on 102 individual flight legs (on 19 flight levels) into hurricanes flown by the Research Flight Facility of the U.S. Weather Bureau are presented. The measured baroclinicity in th.
A Phylogenetically Informed Comparison of GH1 Hydrolases between Arabidopsis and Rice Response to Stressors

Glycoside hydrolases Family 1 (GH1) comprises enzymes that can hydrolyze β-O-glycosidic bond from a carbohydrate moiety. The plant GH1 hydrolases participate in a number of developmental processes and stress responses, including cell wall modification, plant hormone activation or deactivation and herbivore resistance. A large number of members has been observed in this family, suggesting their potential redundant functions in various biological processes. In this study, we have used 304 sequences of plant GH1 hydrolases to study the evolution of this gene family in plant lineage. Gene duplication was found to be a common phenomenon in this gene family. Although many members of GH1 hydrolases showed a high degree of similarity in Arabidopsis and rice, they showed substantial tissue specificity and differential responses to various stress treatments. This differential regulation implies each enzyme may play a distinct role in plants. Furthermore, some of salt-responsive Arabidopsis GH1 hydrolases were selected to test their genetic involvement in salt responses. The knockout mutants of AtBGLU1 and AtBGLU19 were observed to be less-sensitive during NaCl treatment in comparison to the wild type seedlings, indicating their participation in salt stress response. In summary, Arabidopsis and rice GH1 glycoside hydrolases showed distinct features in their evolutionary path, transcriptional regulation and genetic functions.
Managing Green Datacenters Powered by Hybrid Renewable Energy Systems

The rapidly growing server energy expenditure and the warning of climate change have forced the IT industry to look at datacenters powered by renewable energy. Existing proposals on this issue yield sub-optimal performance as they typically assume certain specific type of renewable energy sources and overlook the benefits of cross-source coordination. This paper takes the first step toward exploring green datacenters powered by hybrid renewable energy systems that include baseload power supply, intermittent power supply, and backup energy storage. We propose GreenWorks, a power management framework for green high-performance computing datacenters powered by renewable energy mix. Specifically, GreenWorks features a hierarchical power coordination scheme tailored to the timing and capacity of different renewable energy sources. Using real datacenter workload traces and renewable power generation data, we show that our scheme allows green datacenters to achieve better design trade-offs.
Model driven reverse engineering: Graph modeling for mobiles platforms

In this paper, we describe a model driven reverse engineering approach [1] that focuses on graph modeling. This method allows to represent different views of a mobile development platform (physical, technological and semantic) as a graph model format. We expose this concise method: its strengths side meta-modeling and transformation between model graphs. Moreover, we explain especially about Semantic Extraction component illustrated with a case study of reverse engineering from iOS platform to Android platform.
Stroke detection and reconstruction of characters pressed on metal label

In order to detect features of protuberant characters, a novel stroke detection method based on Gabor filters is proposed. First, the gray images of protuberant characters were preprocessed using morphological algorithm. Next, a set of Gabor filters is used to break down an image of protuberant characters into four directional images, which contain the stroke information of four directions. Then, a reconstruction experiment is carried out with the Gabor characters. The results show that the Gabor representation has strong reconstruction power. Finally, A BP neural network is introduced to classify the Gabor features and the experiment results tell that the Gabor features have good separate capability. All of the above proves that the proposed method can be reliably used for feature extraction of pressed characters in low-quality images.
Personal Mesh: A Design of Flexible and Seamless Internet Access for Personal Area Network

SUMMARY With the proliferation of various types of computing and networking resources in ubiquitous computing environments, an architecture allowing mobile users to flexibly access these resources is desirable. We have focused our attention on the access link resources of devices surrounding users. Our framework named Personal Mesh allows personal devices to seamlessly access the Internet via appropriate access links available in a personal area network. The Personal Mesh deals with two technical issues: access link selection management and a PAN mobility support mechanism. In this paper, we describe the design and implementation of
Replication location decisions

In this paper we focus on a replication decision model. Using an extensible decision model a distributed file system will be able to take the best action to prevent or to properly address disaster situations. BBUFs is a decentralized peer-to-peer distributed file system used here as case study. The file system is designed for ordinary Unix machines that are IPv6 capable.
APPLICATION OF NITROGEN INJECTION DISPLACEMENT FOR FIRE EXTINGUISHMENT

According to statistics, the coal spontaneous combustion fire accounted for more than 94% of the total number of coal mine fire, of which 60% occur in gob [1]. With the mining depth increasing, coal pillar become so easy to be crushed that coal spontaneous combustion is easier to occur. The fire’s occurrence and development not only affect the safety in production and the surrounding environment, but also easily lead to explosion of gas or coal dust [2]. Therefore, the research of new technology and new method on the coal spontaneous combustion fire prevention and control are of great significance. Professor Zhang Guoshu presented a new method of nitrogen injection for fire extinguishment in sealed gob. Practice has proved that this method is effective. The article applied this technology in coal mine, and then verified the results through numerical simulation, and then presented some new views in specific implementation of nitrogen injection displacement for fire extinguishment.
Random Forest Classification for Training a Brain Computer Interface ( BCI )

1 Brain–computer interfaces (BCIs) aim at providing a non-muscular channel 2 for sending commands to the external world using brain activity. Most 3 existing BCIs detect specific mental activity in a so-called synchronous 4 paradigm. Unlike synchronous systems that are operational at specific 5 system-defined periods, self-paced interfaces have the advantage of being 6 operational at all times. Existing BCI systems rely on feature extraction 7 followed by a classification scheme to detect intentions from the brain 8 signal. In this paper, we propose a novel self-paced BCI system that 9 employs Random Forest (RF) algorithm for the classification of brain 10 signal. Unlike the conventional BCI systems, the proposed system does not 11 have a feature extraction step and tries to implicitly learn features from the 12 raw brain signals. We also employ a Bayesian optimization framework to 13 tune the parameters of the RF algorithm and the BCI system. The 14 performances of the proposed novel BCI system and a grid search method 15 are compared on dataset I of BCI competition IV. On the calibration data 16 our optimization method outperformed the grid search method by at least 17 11% accuracy. As expected, the results of both methods on the evaluation 18 dataset were not promising as the brain signal recordings in the calibration 19 and evaluation sessions followed two different paradigms 20
A model for usability testing in challenging environments

Remote software usability testing has been studied for over two decades. Yet, many of the existing testing methods are not ideal for field testing in challenging environments typical to military and emergency operations and contexts. In this paper we introduce a model and a messaging framework that allow remote usability tests to be run easily in the real work context of the users. We also introduce a proof-of-concept implementation of the model and show how the model can be integrated to an existing user interface of a military communication system. To verify our model, we pilot the test set-up on real end users of the system.
Environment Recognition Using Selected MPEG-7 Audio Features and Mel-Frequency Cepstral Coefficients

In this paper, we propose a system for environment recognition using selected MPEG-7 audio low level descriptors together with conventional mel-frequency cepstral coefficients (MFCC). The MPEG-7 descriptors are first ranked based on Fisher’s discriminant ratio. Then principal component analysis is applied on top ranked 30 MPEG-7 descriptors to obtain 13 features. These 13 features are appended with MFCC features to complete the feature set of the proposed system. Gaussian mixture models (GMMs) are used as classifier. The system is evaluated using ten different environment sounds. The experimental results show a significant improvement in recognition performance of the proposed system over MFCC or full MPEG-7 descriptor based systems. For example, the best performance is achieved in Restaurant environment where MFCC, full MPEG-7, and the proposed method give 90%, 94%, and 96% accuracy, respectively.
Multi-media Communication with Emotion-driven \believable Agents"

The AAective Reasoner is a real-time simulation platform which supports multiple agents. These agents are capable of simple \emotional" reactions to situations that arise in the simulation, including those generated by interaction with the user. The platform has developed over time and currently includes, besides the underlying emotion engine, a speech recognition package which is able to discriminate at least some broad categories of emotion content ; a music indexing and playback mechanism allowing virtually instant access to hundreds of hours of midi format music to aid in the expression of emotion ; a schematic representation of approximately 70 emotion faces; and a text-to-speech module for expressing dynamically constructed text including a minimal amount of emotion innection. In this paper we discuss the multi-media environment being constructed for the AAective Reasoner, followed by some brief comments on personality, interestingness of automated agents, and the merits of a \believ-able agent" approach. Lastly we discuss the design of three proposed applications: aaective user mod-eling, a sympathetic computer, and an automated poker player with \emotions. "
Opportunistic Spectrum Access for Cognitive Radio in the Presence of Reactive Primary Users

Opportunistic spectrum access (OSA) is a key technique for the secondary user (SU) in a Cognitive Radio network to transmit over the "spectrum holes" unoccupied by the primary user (PU). Most existing work on the design of OSA has assumed a non-reactive (NR) PU model, i.e., the PU transmission on-off status is independent of the SU access policy, which may not be practical. In this paper, we propose a new Reactive Primary User (RPU) model for the study of OSA, where the PU's access probability over a particular channel is related to the SU's past access history. We model the channel occupancy of the RPU as a 4-state memoryless Markov chain, as opposed to the conventional 2-state (on/off) counterpart, where the expanded state space and state transition probabilities are used to model the reactions of the PU subject to the SU transmit collision. Under this model, we formulate the optimal OSA design for the SU's throughput maximization as a finite-horizon partially observable Markov decision process (POMDP) problem, subject to a conditional collision probability constraint for protecting the PU. Because of the high complexity of the proposed problem, we further propose a separation principle to obtain the optimal policy for the SU with implementable complexity. Numerical results show the new tradeoff between the SU's and the PU's throughput under the RPU model, as compared to the conventional NRPU model.
THE EFFECT OF INSTITUTIONAL VARIABLES ON FDI INFLOWS: EVIDENCE FROM UPPER

For two decades, the relationship between institutions and foreign direct investment (FDI) is receiving a growing attention as a result of increasing economic globalization and international tr world. This paper economic and political, on foreign direct investment inflows into 54 upper income developing countries applying panel data regressions 2011. The findings suggest that the institutional variables have significant effect on FDI inflows but their impact is weaker than macoreconomic variables. Especially, the market size indicators, population growth rate, global competit international country risk play a major role in attracting FDI.
uPA dependent and independent mechanisms of wound healing by C-phycocyanin

Wound repair requires both recruitment and well co‐ordinated actions of many cell types including inflammatory cells, endothelial cells, epithelial cells and importantly fibroblast cells. Urokinase‐type plasminogen activator (uPA) system plays a vital role in wound healing phenomenon. We have previously demonstrated that C‐phycocyanin (C‐pc), a biliprotein from blue‐green algae, transcriptionally regulates uPA through cAMP‐dependent protein kinase A (PKA) pathway. To date, a role for C‐pc in wound‐healing scenario is not elucidated. This study was designed to examine the wound‐healing property of C‐pc in relation to fibroblast proliferation and migration. C‐pc increased fibroblast proliferation in a dose‐dependent manner. It also enhanced G1 phase of cell cycle and increased the expressions of cyclin‐dependent kinases 1 and 2, which facilitate cell cycle progression, in a uPA‐independent manner. In vitro wound healing and migration assays revealed the pro‐migratory properties of C‐pc. Short‐interference RNA studies demonstrated that uPA was necessary for C‐pc‐induced fibroblast migration. C‐pc also significantly elevated the expressions of chemokines (MDC, RANTES, Eotaxin, GRO α, ENA78 and TARC) and Rho‐GTPases (Cdc 42 and Rac 1) in a uPA‐dependent manner. Pre‐treatment of C‐pc‐stimulated cells with pharmacological inhibitor of PI‐3K (LY294002) annulled the expression of GTPases implying that Rac 1 and Cdc 42 were induced through PI‐3K pathway. C‐pc‐induced cellular migration towards wounded area was also negatively affected by PI‐3K inhibition. In vivo wound‐healing experiments in mice validated our finding that C‐pc accelerates wound healing. Our data provides conclusive evidence of a novel therapeutic usage for C‐pc as a wound‐healing agent. C‐pc is a food and drug administration (FDA)‐approved health supplement. We believe this compound can also be beneficial in healing of internal wounds, such as ulcers.
An ontology-based framework for Semantic Web Content Mining

The voluminous amount of information available in the Web makes information retrieval a challenging task. Most of the surfers' time is wasted in following different links ranked by search engines. Moreover, manual integration of information available in different Web pages is difficult and inefficient. So, to ease the process of information retrieval and to provide the surfer with more relevant information, Semantic Web could be employed. The metadata information available in the Semantic Web in the form of ontology helps in the retrieval of relevant information. In this paper, an Ontology-Based framework for Semantic Web Content Mining has been proposed. This framework is a semi-automatic process which suits many application domain like Education, Medicine and Tourism. The proposed framework is implemented in JAVA and ontology engineering is done using the ontology language, RDF (Resource Description Framework). The screen shots are designed using Net Beans IDE. The efficiency of the framework is measured in terms of precision, average precision and relevance score.