Miracle-dz/UniFAR-FTUs huggingface dataset:
Fast color correction for rapid scanning in uncontrolled environment

This work addresses the problem of colorizing correctly time-of-flight 3D scans performed during rapid scanning of a site in natural and uncontrolled lighting conditions. Contrarily to the usual approach correcting high resolution pictures, the proposed method combines all available radiometric information to colorize per vertex the medium resolution depth map. The obtained rendering exhibits no visible artifacts, for models composed of a series of scans. Our solution allows to quickly obtain good visual results within a reasonable time, while allowing to consider various other methods to improve colors and rendering.
Volitional control of neural activity: implications for brain–computer interfaces

Successful operation of brain–computer interfaces (BCI) and brain–machine interfaces (BMI) depends significantly on the degree to which neural activity can be volitionally controlled. This paper reviews evidence for such volitional control in a variety of neural signals, with particular emphasis on the activity of cortical neurons. Some evidence comes from conventional experiments that reveal volitional modulation in neural activity related to behaviours, including real and imagined movements, cognitive imagery and shifts of attention. More direct evidence comes from studies on operant conditioning of neural activity using biofeedback, and from BCI/BMI studies in which neural activity controls cursors or peripheral devices. Limits in the degree of accuracy of control in the latter studies can be attributed to several possible factors. Some of these factors, particularly limited practice time, can be addressed with long‐term implanted BCIs. Preliminary observations with implanted circuits implementing recurrent BCIs are summarized.
In Vitro Translation and Assembly of a Complete T Cell Receptor–CD3 Complex

The T cell receptor for antigen (TCR) is a multisubunit complex that consists of at least seven polypeptides: the clonotypic, disulfide-linked α/β heterodimer that is noncovalently associated with the invariant polypeptides of the CD3 complex (CD3-γ, -δ, -ε) and ζ, a disulfide-linked homodimer. We achieved the complete assembly of the human TCR in an in vitro transcription/translation system supplemented with dog pancreas microsomes by simultaneous translation of the messenger RNAs encoding the TCR-α, -β and CD3-γ, -δ, -ε, and -ζ subunits. CD3-ε, one of the subunits that initiates the assembly of the TCR in living cells, forms misfolded, disulfide-linked homooligomers when translated alone. However, co-translation of one of its first binding partners in the course of assembly, CD3-γ or -δ, led to the expression of mainly monomeric and correctly folded ε subunits, the only form we could detect as part of a properly assembled TCR complex. In the absence of these subunits, the ER-resident chaperone calnexin interacted with oligomeric, i.e. misfolded, structures of CD3-ε in a glycan-independent manner. A glycan-dependent interaction between CD3-ε and calnexin was mediated by CD3-γ and concerned only monomeric CD3-ε complexed with CD3-γ, but was dispensable for proper folding of CD3-ε. We suggest that in addition to its signaling function, CD3-ε serves as a monitor for proper subunit assembly of the TCR.
Emerging Roles for the Immune System in Traumatic Brain Injury

Traumatic brain injury (TBI) affects an ever-growing population of all ages with long-term consequences on health and cognition. Many of the issues that TBI patients face are thought to be mediated by the immune system. Primary brain damage that occurs at the time of injury can be exacerbated and prolonged for months or even years by chronic inflammatory processes, which can ultimately lead to secondary cell death, neurodegeneration, and long-lasting neurological impairment. Researchers have turned to rodent models of TBI in order to understand how inflammatory cells and immunological signaling regulate the post-injury response and recovery mechanisms. In addition, the development of numerous methods to manipulate genes involved in inflammation has recently expanded the possibilities of investigating the immune response in TBI models. As results from these studies accumulate, scientists have started to link cells and signaling pathways to pro- and anti-inflammatory processes that may contribute beneficial or detrimental effects to the injured brain. Moreover, emerging data suggest that targeting aspects of the immune response may offer promising strategies to treat TBI. This review will cover insights gained from studies that approach TBI research from an immunological perspective and will summarize our current understanding of the involvement of specific immune cell types and cytokines in TBI pathogenesis.
Content Recommendation Based on Education-Contextualized Browsing Events for Web-based Personalized Learning

The WWW is now in widespread use for delivering on-line learning content in many large-scale education settings. Given such widespread usage, it is feasible to accumulate data concerning the most useful learning experiences of past students and share them with future students. Browsing events that depict how past students utilized the learning content to accomplish higher levels of achievement are especially valuable. This paper presents a new method for identifying potentially effective browsing events based on a contextualized browsing model built through association mining and statistical techniques. The model annotates browsing events with several contextual factors, including educational ones (group relevance and performance relevance) and non- educational ones (support and confidence). Based on this model, a personalized content recommender was implemented in a Web-based learning content management system, called IDEAL, to deliver personalized learning content based on a student's browsing history. An experiment was conducted to compare the user feedback concerning the recommendations provided through different recommendation models. The results show that students with different levels of achievement prefer different types of contextualization information. Finally, another performance experiment demonstrated that the contextualized browsing model is more effective in improving learning performance than the pure association mining model.
Expansion Through Multiple Unit Franchising

In this article we explore strategic reasons justifying the recent emergence of multiple unit franchising arrangements within Australia from the perspective of the franchisor. Extending resource constraints, efficiency and agency rationales explaining organizational choice, the present study suggests that franchisors encourage franchisee subsystem development as it affords strategic, operational and performance advantages. Dimensions including agency cost minimization, system-wide uniformity, franchise system brand value, reward strategies, and subsystem unit (geographical) proximity and intra-system competition, were found to be important. Less important elements included ownership redirection, system adaptability, local market innovation and franchisee opportunism motives. Given the exploratory nature of this research, in-depth interviews with 23 franchisors were used to collect data.The preliminary research evidence has important implications for franchising theorists and practitioners and, in addition, provides a platform on which future research can be developed to further understand multiple unit franchising arrangements.
Transcriptional Control in the Segmentation Gene Network of Drosophila

The segmentation gene network of Drosophila consists of maternal and zygotic factors that generate, by transcriptional (cross-) regulation, expression patterns of increasing complexity along the anterior-posterior axis of the embryo. Using known binding site information for maternal and zygotic gap transcription factors, the computer algorithm Ahab recovers known segmentation control elements (modules) with excellent success and predicts many novel modules within the network and genome-wide. We show that novel module predictions are highly enriched in the network and typically clustered proximal to the promoter, not only upstream, but also in intronic space and downstream. When placed upstream of a reporter gene, they consistently drive patterned blastoderm expression, in most cases faithfully producing one or more pattern elements of the endogenous gene. Moreover, we demonstrate for the entire set of known and newly validated modules that Ahab's prediction of binding sites correlates well with the expression patterns produced by the modules, revealing basic rules governing their composition. Specifically, we show that maternal factors consistently act as activators and that gap factors act as repressors, except for the bimodal factor Hunchback. Our data suggest a simple context-dependent rule for its switch from repressive to activating function. Overall, the composition of modules appears well fitted to the spatiotemporal distribution of their positive and negative input factors. Finally, by comparing Ahab predictions with different categories of transcription factor input, we confirm the global regulatory structure of the segmentation gene network, but find odd skipped behaving like a primary pair-rule gene. The study expands our knowledge of the segmentation gene network by increasing the number of experimentally tested modules by 50%. For the first time, the entire set of validated modules is analyzed for binding site composition under a uniform set of criteria, permitting the definition of basic composition rules. The study demonstrates that computational methods are a powerful complement to experimental approaches in the analysis of transcription networks.
A similarity-based probability model for latent semantic indexing

A dual probability model is constructed for the La tent Semantic Indexing (LSI) using the cosine simi larity measure. Both the document-document sim ilarity matrix and the term-term similarity matrix naturally arise from the maximum likelihood esti mation of the model parameters, and the optimal solutions are the latent semantic vectors of of LSI. Dimensionality reduction is justified by the statis tical significance of latent semantic vectors as mea sured by the likelihood of the model. This leads to a statistical criterion for the optimal semantic di mensions, answering a critical open question in LSI with practical importance. Thus the model estab lishes a statistical framework for LSI. Ambiguities related to statistical modeling of LSI are clarified.
TCRP: A tree-clustering prototocol for tracking mobile targets in wireless sensor networks

Mobility of nodes and sinks brings new challenges to large-scale sensor networks. In this paper we introduce TCRP, a tree-clustering routing protocol that provides scalable and efficient data delivery to mobile sinks and mobile targets in sensory networks. Each node detecting the presents of the mobile targets proactively constructs a tree structure which enables the mobile sinks to continuously receive data on the move and chases the mobile targets. A sink can move without reporting its location to the tree while receiving data updates successfully The new protocol is very beneficial for data-centric applications such as tracking mobile objects, smart farming, medicine and military applications. We have evaluated the performance of TCRP through simulation experiments. The results of simulation show that TCRP is scalable and energy-efficient. Moreover, TCRP is able to handle/track mobile targets and sinks efficiently compared with other existing protocols.
Frequency response improvement of the two-stage opamp with indirect compensation and large load

This paper presents a further development of an improved frequency compensation method for a two-stage operational amplifier with indirect feedback current, which is beneficial for large capacitive load applications. It describes the case when a nulling resistor is added at the output in such a way that it is residing outside the outer feedback loop of the amplifier. Compared to the case when the nulling resistor is placed outside inner frequency compensation loop but it is inside of the outer feedback loop of the amplifier, the driving capability can be substantially improved or for the same capacitive load it can improve the stability by gaining up to 45 degree of extra phase margin. A prototype has been implemented with the STMicroelectronics 28 nm CMOS technology and simulated with Cadence Virtuoso. Simulations at room temperature show an improvement of the unity gain frequency from 741.57 MHz to 1.047 GHz and an extra phase margin gain of 38 degree. The simulation of the temperature effect showed that the phase margin gain remains for temperature range [-20, 150] °C.
CLONE -BASED MOBILE AGENT ITINERARY PLANNING USING SEPARATE TREES FOR DATA FUSION IN WSN S

Recent studies demonstrate that Mobile Agent (MA) approach could be more effective than conventional client-server model in Wireless Sensor Network (WSN). Particularly, itinerary planning for MAs is a significant aspect of these approaches. Tree-based methods have been widely used for this purpose where many agents are dispatched simultaneously. Most of tree-based methods try to construct an optimal/suboptimal tree in terms of an objective function. In contrast, in this paper we introduce a new approach that tries to separate the MA dispatching and data fusion operations by considering two itinerary trees which results in more flexibility to regulate the itinerary plan. Based on this idea, we propose an algorithm called Two Trees Clone-based Itinerary (TTCI) which constructs two trees, one serves to distribute MA in the network and another to fuse back the sensed data. By experimental results, we demonstrate the performance improvement of TTCI algorithm in terms of overall energy consumption in comparison with the previous schemes. Meanwhile, the TTCI keeps the delay low.
Some Aspects of Rectangular Microstrip Antenna for Mobile Application

We investigate the effects of antenna parameters on the radiation characteristics of a compact size Rectangular Microstrip Antenna suitable for mobile application. In the calculations of antenna parameters, resonant frequency is set at 3 GHz. In our investigations three low cost substrate materials, namely: (a) irradiated poly-guide with relative dielectric constant and loss tangent as 2.32, 0.0005, (b) Glass-Epoxy with and (c) R03006 with are used to simulate the antenna parameters obtained from various models. The simulation results predict that the BW increases with the increase in substrate thickness and decrease in dielectric constant, while directivity strongly depends on width of the patch. Here we will present in details the antenna model, its simulation and the results of our analysis.
Characterizing high-frequency subscriber sessions in cellular data networks

Cellular systems operate under restrictive constraints of resources including radio channel capacity and network processing capability. The tremendous growth in the cellular data network usage brings operators with unprecedented signaling overloads and threatens the stability of the network. Understanding the characteristics of the subscribers who are resource inefficient has an important significance of capacity planning and optimal allocation of resources. In this paper, we perform the first large-scale investigation of session characteristics of a particular category of mobile subscribers, called high-frequency subscribers who access network frequently based on anonymized traces of an city-wide operational 3G network. We fund that high-frequency subscribers can be extremely signaling resource-inefficient. For subscribers who activate more than 10 sessions per hour, they only account for 0.5% of the total subscribers and generate about 1.73% data traffic but roughly 12.6% of the signaling resources consumption. We also propose a novel approach for discovering their session patterns and study the applications that generate such session patterns from semantic level. We observed that the frequency of subscribers' session activation shows positive correlation with the periodicity of session intervals. We also found periodic session activations have a certain correlation with abnormal behaviors, to our best knowledge, we first report that although TCP SYN flooding is detected and blocked by security measures, attackers may still send requests for context activation continuously, which adds unwanted signaling loads. We demonstrate that our findings have significant implications on network optimization.
Bio-Spoof and Anti-Spoofing Detection Based on IQA

in recent years, facial biometric systems have received increased deployment in various applications such as surveillance, access control and forensic investigations. However, one of the limitations of face recognition system is the high possibility of the system being deceived or spoofed by non-real faces such as photograph, video clips or dummy faces. In order the Spoofing and anti-spoofing has become a prevalent topic in the biometrics community. This paper introduces novel and appealing techniques for fake biometric detection using liveness detection based on Image Quality assessment (IQA). The key idea of this approach is to present software based multi-biometric and multi-attack protection method that characterize real but not fake ones. KeywordsImage quality assessment, fake biometrics,
NONTHERMAL γ-RAY AND X-RAY FLASHES FROM SHOCK BREAKOUT IN GAMMA-RAY BURSTS/SUPERNOVAE

Thermal X-ray emission which is simultaneous with the promp t gamma-rays has been detected for the first time from a supernova connected with a gamma-ray burst (GRB) , namely GRB060218/SN2006aj. It has been interpreted as arising from the breakout of a mildly relativ is c, radiation-dominated shock from a dense stellar wind surrounding the progenitor star. There is also evidenc e for the presence of a mildly relativistic ejecta in GRB980425/SN1998bw, based on its X-ray and radio aftergl ow. Here we study the process of repeated bulk Compton scatterings of shock breakout thermal photons by the mildly relativistic ejecta. During the shock breakout process, a fraction of the thermal photons wo uld be repeatedly scattered between the pre-shock material and the shocked material as well as the mildly relat ivistic ejecta and, as a result, the thermal photons get boosted to increasingly higher energies. This bulk motion C mptonization mechanism will produce nonthermal gamma-ray and X-ray flashes, which could account for the prom t gamma-ray burst emission in low-luminosity supernova-connected GRBs, such as GRB060218. A Monte Carlo code has been developed to simulate this repeated scattering process, which confirms that a significa t fr ction of the thermal photons get "accelerated" to form a nonthermal component, with a dominant luminosity. This interpretation for the prompt nonthermal emission of GRB060218 may imply that either the usual intern al shock emission from highly relativistic jets in these low-luminosity GRBs is weak, or alternatively, tha t there are no highly relativistic jets in this peculiar class of bursts. Subject headings: gamma rays: bursts— supernovae: general –shock waves
CBAC – a model for conflict-based access control

II PREFACE . III SUMMARY . IV ACKNOWLEDGEMENTS . V TABLE OF CONTENTS . VII LIST OF FIGURES . X LIST OF TABLES . XI CHAPTER 1: INTRODUCTION ‐ PROBLEM STATEMENT . 1 1.1 INTRODUCTION . 1 1.2 PROBLEM STATEMENT . 2 1.3 RESEARCH QUESTIONS . 4 1.4 RESEARCH HIERARCHY AND METHODOLOGY . 6 1.5 SCOPE AND CONTEXT OF THE STUDY . 7 1.6 TERMINOLOGY USED IN THE THESIS . 7 1.7 LAYOUT OF THESIS . 8 CHAPTER 2: CASE STUDY ‐ DM BANK . 10 2.1 INTRODUCTION . 11 2.2 CASE STUDY . 11 2.2.1 ABC Petrol’s environment . 11 2.2.2 DM Bank’s environment . 13 2.3 ACCESS CONTROL AND THE DATA‐MINING ENVIRONMENT OF DM BANK . 16 CHAPTER 3: EMERGING THEORIES AND PERSPECTIVES RELEVANT TO ACCESS CONTROL AND SECURITY POLICIES . 18 3.1 INTRODUCTION . 19 3.2 ACCESS CONTROL TERMINOLOGY . 19 3.3 SECURITY POLICIES AND ACCESS CONTROL POLICIES . 20 3.4 ACCESS CONTROL MODELS . 21 3.4.1 Access Control Models for Confidentiality . 22 3.4.1.1 Bell‐La Padula Model (BLP) . 22 3.4.1.2 Lampson model; Graham‐Denning model; Harrison‐Ruzzo‐Ullman model . 23 3.4.2 Access Control Models for Conflict . 24 3.4.2.1 Chinese Wall Security Policy Model . 24 3.4.2.2 Aggressive Chinese Wall Security Policy Model . 26 3.4. 3 Access Control Models for a Data‐Mining Environment . 26 3.4. 3.1 Privacy‐Preserving Access Control . 26 3.4. 3.2 Privacy‐Aware Access Control . 27 3.4. 3.3 Privacy‐Enhanced Access Control . 27 3.5 ACCESS CONTROL MODEL SUMMARY . 28 3.6 CONCLUSION . 29 CHAPTER 4: EMERGING THEORIES AND PERSPECTIVES RELEVANT TO ACCESS CONTROL AND DATA MINING . 30 4.1 INTRODUCTION . 31 4.2 THE DATA‐MINING PROCESS . 32 4.2.1 Business‐understanding Step [Daimler‐Benz, et al.] . 33 4.2.1.1 Determine the business objectives . 33 4.2.1.2 Determine and assess the details of the business situation . 34 4.2.1.3 Determine the data‐mining goals . 34 4.2.1.4 Produce a project plan . 34
Are Investors Rational? Choices Among Index Funds

S&P 500 index funds represent one of the simplest vehicles for examining rational behavior. They hold virtually the same securities, yet their returns differ by more than 2 percent per year. Although the relative returns of alternative S&P 500 funds are easily predictable, the relationship between cash flows and performance is weaker than rational behavior would lead us to expect. We show that selecting funds based on low expenses or high past returns outperforms the portfolio of index funds selected by investors. Our results exemplify the fact that, in a market where arbitrage is not possible, dominated products can prosper. Copyright 2004 by The American Finance Association.
Wire-length prediction using statistical techniques

We address the classic wire-length estimation problem and propose a new statistical wire-length estimation approach that captures the probability distribution function of net lengths after placement and before routing. The wire-length prediction model was developed using a combination of parametric and non-parametric statistical techniques. The model predicts not only the length of the net using input parameters extracted from the floorplan of a design, but also probability distributions that a net with given characteristics obtained after placement will have a particular length. The model is validated using both learn-and-test and resubstitution techniques. The model can be used for a variety of purposes, including the generation of a large number of statistically sound and therefore realistic instances of designs. We applied the net models to the probabilistic buffer insertion problem and obtained substantial improvement in net delay after routing.
A post-seismic relief supply allocation model based on risk perception

Post-seismic relief supply allocation based on psychological risk perception is an important yet understudied area in supply chain risk management. This paper is dedicated to build system dynamics model in this range to analyze the system of relief supply allocation based on risk perceptions and behaviors of decision-makers, and verify this model by simulating the Wenchuan earthquake based on field data. The simulation results indicate that a) this model can virtually reflect the actual situation of post-seismic relief supply allocation; and b) decision-makers' risk perception has a significant impact on post-seismic relief supply allocation and relief effects as well as different attitudes of decision-makers' risk perceptions also have different impacts on them.