Miracle-dz/UniFAR-FTUs huggingface dataset:
Autonomic Trust Extraction for Trustworthy Service Discovery in Urban Computing

Trustworthy service discovery against malicious services is an issue in pervasive computing where interactions between user and service occur spontaneously. For trustworthy service selection, reputation based trust model which uses user evaluation to derive the trustworthiness of service behavior is a well known approach. However, it requires voluntary user participation and often has a problem with the lack of gathered data. In general, task based computing provides a task to user which is a composition of services rather than unit services.Therefore, user can’t give direct evaluation on unit service. In this paper, we present an autonomic trust extraction method that trust value of service behavior can be extracted without any user intervention. In our method, the interaction between user and service is monitored, and trust value for a service is automatically determined after each interaction according to the number of recurrent interaction with a service and the fact whether the interacted service is bookmarked or not. We also present simulation results that evaluate the proposed model.The results show that our model captures the degree of trustworthy in service behavior r with about 70% ~ 80% of correlation between the actual trust and the estimated trust when user bookmarking ratio is about over 30%.
Building Secure High-Performance Web Services with OKWS

OKWS is a toolkit for building fast and secure Web services. It provides Web developers with a small set of tools that has proved powerful enough to build complex systems with limited effort. Despite its emphasis on security, OKWS shows performance improvements compared to popular systems: when servicing fully dynamic, non-disk-bound database workloads, OKWS's throughput and responsiveness exceed that of Apache 2 [3], Flash [23] and Haboob [44]. Experience with OKWS in a commercial deployment suggests it can reduce hardware and system management costs, while providing security guarantees absent in current systems.
Development of Functional Genomic Tools in Trematodes: RNA Interference and Luciferase Reporter Gene Activity in Fasciola hepatica

The growing availability of sequence information from diverse parasites through genomic and transcriptomic projects offer new opportunities for the identification of key mediators in the parasite–host interaction. Functional genomics approaches and methods for the manipulation of genes are essential tools for deciphering the roles of genes and to identify new intervention targets in parasites. Exciting advances in functional genomics for parasitic helminths are starting to occur, with transgene expression and RNA interference (RNAi) reported in several species of nematodes, but the area is still in its infancy in flatworms, with reports in just three species. While advancing in model organisms, there is a need to rapidly extend these technologies to other parasites responsible for several chronic diseases of humans and cattle. In order to extend these approaches to less well studied parasitic worms, we developed a test method for the presence of a viable RNAi pathway by silencing the exogenous reporter gene, firefly luciferase (fLUC). We established the method in the human blood fluke Schistosoma mansoni and then confirmed its utility in the liver fluke Fasciola hepatica. We transformed newly excysted juveniles of F. hepatica by electroporation with mRNA of fLUC and three hours later were able to detect luciferase enzyme activity, concentrated mainly in the digestive ceca. Subsequently, we tested the presence of an active RNAi pathway in F. hepatica by knocking down the exogenous luciferase activity by introduction into the transformed parasites of double-stranded RNA (dsRNA) specific for fLUC. In addition, we tested the RNAi pathway targeting an endogenous F. hepatica gene encoding leucine aminopeptidase (FhLAP), and observed a significant reduction in specific mRNA levels. In summary, these studies demonstrated the utility of RNAi targeting reporter fLUC as a reporter gene assay to establish the presence of an intact RNAi pathway in helminth parasites. These could facilitate the study of gene function and the identification of relevant targets for intervention in organisms that are by other means intractable. More specifically, these results open new perspectives for functional genomics of F. hepatica, which hopefully can lead to the development of new interventions for fascioliasis.
Étude de la rhizodéposition chez le maïs : influence de la distribution des photo-assimilats aux racines et de la morphologie racinaire

Nous avons etudie le role de l'allocation de carbone aux racines et de la morphologie racinaire sur la rhizodeposition du mais au stade vegetatif. Une tres forte correlation entre la quantite de rhizodepots retrouves dans le sol et la quantite d'assimilats recents attribues a la fois aux racines et au compartiment souterrain est observee. L'analyse des rhizodepots montre que les composes solubles representent plus de 90 % des composes liberes par les racines. De fortes correlations entre les variables relatives au systeme racinaire et la quantite d'assimilats recents alloues aux racines sont observees. A partir des donnees obtenues, un modele simple de liberation de rhizodepots soluble est propose. Ainsi, cette rhizodeposition est expliquee a plus de 70 % par deux variables: le ratio P A/PR et le nombre d'apex. Il est desormais necessaire de decoupler l'ensemble des variables racinaires et hierarchiser leur importance dans les processus de rhizodeposition.
Visual Object Matching Based on Gradient ICA Feature

Pixel point gradient features represent much of the intrinsic structures of an image and can be used to the description of machine vision object. By ICA technique, pixel gradient data can be projected from a high-dimensional space to a lower-dimensional space, which reduce the redundancy with no image segment based on threshold. A method of visual object matching based on gradient ICA feature is provided in the paper. By training, the gradient ICA features description of both template and object can be acquired. And normalized cross correlation of the gradient ICA feature is adopted as the similar measure for the matching. Matching search can be easily realized from coarse to fine. Matching pulse correlation coefficient is high, and when there is non-uniform illumination or noise, the object can also be clearly recognized, which has be verified by the experiments.
Facilitating meetings with playful feedback

Effective group meetings are important for the productivity of corporations. Various types of meeting facilitators have been developed over the past couple of years. We present a prototype that is unique because it captures both individual and group behaviors and provides real time playful feedback. The portable prototype includes a set of table-top microphones with an audio interface to a laptop PC, where audio data are processed and an avatar-based UI displays the shared state of individual and group behaviors during a meeting. The interface reveals not only level of participation, but also several other meaningful but harder to detect behaviors such as turn taking, interruptions, and group laughter. The presentation's design is deliberately playful to keep participants monitor, self-estimate and improve their meeting behavior.
The importance of the lateral line in nocturnal predation of piscivorous catfish

SUMMARY In a previous study we showed that nocturnal piscivorous catfish track the wake left by a swimming prey fish to locate it, following past locations to detect the present location of the prey. In a wake there are hydrodynamic as well as chemical signatures that both contain information on location and suitability of the prey. In order to determine how these two wake stimuli are utilised in prey tracking, we conducted experiments in catfish in which either the lateral line or the external gustation was ablated. We found that a functional lateral line is indispensable for following the wake of swimming prey. The frequency of attack and capture was greatly diminished and the attacks that did occur were considerably delayed when the lateral line was ablated. In contrast, catfish with ablated external taste still followed the wakes of their prey prior to attacking, albeit their attacks were delayed. The external taste sense, which was reported earlier to be necessary for finding stationary (dead) food, seems to play a minor role in the localisation of moving prey. Our finding suggests that an important function of the lateral line is to mediate wake-tracking in predatory fish.
Protein and lipid sorting from the trans-Golgi network to the plasma membrane in polarized cells.

The targeting of proteins and lipids to the cell surface domains of polarized cells is not a simple bulk flow process but requires sorting into distinct apical and basolateral pathways from the trans-Golgi network. Here, we describe the sorting determinants in the cargo molecules, the cellular sorting machineries responsible for the hierarchical read-out of the signals, and the mechanisms of cargo delivery. Furthermore, we discuss the implications of these findings for protein-lipid interactions in other cellular machineries.
COMPUTER AIDED DIAGNOSIS SYSTEM FOR BRAIN TUMOR DETECTION AND SEGMENTATION

Abnormal cell growth leads to tumor in the brain cells. Earlier detection, diagnosis and proper treatment of brain tumor is essential to prevent human death. An effective brain tumor segmentation of MR image is an essential task in medical field. In this paper, a computer aided development of diagnosis system for brain tumor detection is proposed. The proposed work consists of four stages namely preprocessing, feature extraction, ANFIS Classifier and morphological operations to detect, segment and diagnose the brain tumor regions. Before going to segmentation the preprocessing is carried out since preprocessing makes the image ready for further segmentation. The performance of tumor segmentation are analyzed with the following factors similarity index (SI), extra fraction (EF), overlap fraction (OF) and accuracy, whose values are obtained as 0.78, 0.0098, 0.723 and 99.4% respectively. The results obtained in this paper shows that the proposed work is superior over the other stateofart-techniques.
Work-unit environments of information systems and non-information systems people: implications for end-user computing and distributed processing

This study investigates whether work-unit environments differ for information systems (IS) and non-information systems (non-IS) employees. Within the same occupational level, i.e., within clerical, technical-professional, and managerial level personnel, no differences are discovered in the overall work-unit environments of IS and non-IS employees. Speculation is presented suggesting that (1) the management of end-user personnel need not change as they become more involved in performing information systems tasks and (2) IS and non-IS personnel in distributed processing environments should be managed similarly.
A Workbook for Scaffolding Mentored Undergraduate Research Experiences in the Social and Behavioral Sciences.

Research mentors strive to ensure that undergraduates gain research skills and develop professionally during mentored research experiences in the sciences. We created the SURE (Specialized Undergraduate Research Experience) Workbook, a freely-available, interactive guide to scaffold student learning during this process. The Workbook: (1) identifies mentees’ relevant strengths and areas for improvement, (2) encourages effective long-term goal setting, (3) ensures clear communication to facilitate a positive mentor-mentee working relationship, (4) exposes mentees to all phases of the research process, (5) develops mentees’ autonomy for research and related professional experiences, and (6) offers mentors a concrete assessment tool to evaluate student participation and development over the course of the research experience. Hands-on research experiences can be invaluable and transformative in undergraduates’ professional development, and we predict that the additional structure and standardization provided by the SURE Workbook will help maximize student learning and performance during such experiences. Thinking ahead, mentees who cultivate positive attitudes about research by using the SURE Workbook may be more inclined to pursue research professions and effectively mentor others when they graduate.
Contexts in which Gestures Appear in Service Interactions

This paper is devoted to the study of gestures in a commercial context. It focuses on the contexts in which gestures appear in service interactions. After a short introduction (1) and brief reminder of the theoretical background (2), three types of gestures are identified according to the contexts in which they appear (3): gestures in reaction to a verbal appeal (3.1), gestures in reaction to a non-verbal appeal (3.2) and gestures not coming in reaction to any appeal (3.3). This study allows us to draw conclusions concerning the distribution of tasks between the verbal and non-verbal components and the transactional and relational levels (4).
Noise reductioN iN audio recordiNgs for foreNsic purposes usiNg aN algorithm for short-time spectral aNalysis

Forensic speech to text transcriptions from evidence recordings, which are usually intensively distorted, are carried out in almost every forensic audio analysis. This is connected with a need to correct recordings to improve the quality of the speech signal (forensic audio enhancement). The purpose of this work was to develop our own software to reduce various kinds of noises contained in evidence audio recordings, enabling improvement of speech signal intelligibility. During project implementation, an algorithm for adaptive noise reduction was used with short-time spectral amplitude estimation (MMSe STSa). analyses conducted using the constructed software allowed us to evaluate the effectiveness of the reconstruction of the speech signal for different kinds of noises and SNR values, and define the threshold below which correct transcription is difficult or impossible. The results made it possible to indicate what kind of noise has the most destructive effect on the speech signal and what conditions must be fulfilled by recordings in order to enable a correct transcription. The impact of the applied algorithm on possible distortions of the speech signal after reconstruction was also estimated. The designed and validated software for noise reduction will be a useful tool that allows more effective audio analysis in forensic practice.
In-order pulsed charge recycling in off-chip data buses

This paper presents in-order pulsed charge recycling to reduce energy consumption in an off-chip data bus. The proposed technique performs charge recycling by employing three different steps. At the beginning of an off-chip data bus transaction, i) connect all bus lines that are expected to fall to a common node, ii) connect, one at a time and for a fixed period of time, each of bus lines that are expected to rise to the same common node to enable charge recycling, and finally, iii) resume regular data bus transaction by enabling the tri-state buffers to complete the remaining charging (discharging) of the rising (falling) bus lines. Experimental results in Hspice show that the proposed technique achieves 17.4% average energy savings in a 32 bit-wide data bus implemented in a 0. 13¼m technology with a 1.8V supply voltage.
An advanced traffic management system simulator for intelligent vehicle-highway systems research

This paper provides an overview of an advanced traffic management system (ATMS) simulator developed at Georgia Tech and being used as a research tool to help answer various questions that arise as intelligent vehicle-highway system (IVHS) technology makes its way into tomorrow's advanced traffic management systems. The architecture, capabilities, technical challenges and implementation decisions associated with the development of this simulator are summarized. Brief descriptions of the traffic model, database, displays and associated simulated traffic video coverage are provided.
Adaptive Neural Control for Safe Human-Robot Interaction

The growth of research interest in the area of safe human-robot interaction (sHRI) continues to increase as the industrial, medical and social developments of humanrobotic systems advances. Accordingly, adaptive impedance controls that aim to provide safety and reduce dependency on the precise knowledge of the robot dynamics have increased in importance, especially when the focus of robotic applications shifts from industrial robots to service robots. Motivated by this problem, this thesis focuses on the theoretical development of control algorithms to provide sHRI. The developed controllers can be classified into two main categories: constrained control algorithms, and impedance control algorithms. Based on the rapid progress of sHRI over the past decade, several studies impose hard constraints on robot movements to prevent the potential of human damage during integration with robots. This thesis, inspired by the needs of the safe assistance of neuromuscular patients in robotic rehabilitation, develops two types of constrained control scenarios, namely, position constrained control, and velocity constrained control. The control objective was achieved by employing direct Lyapunov analysis, and further utilizing barrier Lyapunov functions (BLF). By that means, the control Lyapunov function was shaped to bind the joint position and velocity variables of the robots. In this regards, first tangent type time-varying asymmetric BLF were applied to joint position variables to ensure no constraint violation occurred with the robot’s joints. Then, adaptive neural networks were proposed to handle uncertainties in manipulator dynamics and actuator dynamics in addition to the unknown disturbances. To handle the velocity constraints in joint error variables a Lyapunov function was chosen, that was restricted to linear growth, and further, a secant type barrier Lyapunov function was introduced for constraining the joint rate variables. The former was exploited to bind the forward propagation of the position errors, and the latter was utilized to impose hard bounds on the velocity. Also, control input saturation was expressed, and neural networks were employed to tackle the system dynamic uncertainty problems.
MODELING AND RENDERING IN 3 D COORDINATE DEFINED BY TWO CAMERAS FOR SHARED VIRTUAL SPACE COMMUNICATION 1

In this paper, we describe an arbitrary view generation system using reconstructed voxel model in 3D space defined by two cameras. Saito and Kanade have proposed a method to define 3D space by using two camera-rays starting at the image’s center. However, the 3D space was skew because it was generated based on projective geometry. In this paper, we propese a new method to reduce the skewness, so that the reconstructed model can be approximately represented in the Euclidean space without camera calibration. For making the reconstruction faster, we use Shape from Silhouette method with our new octree algorithm. In addition, we introduce an improved background subtraction algorithm by using not only color images but also disparity images to generate silhouette images with few noises. After the reconstruction, we color the model which consists of a set of voxels and render the model for synthesizing an arbitrary view image. Using this method, we build an application that composes two models reconstructed at two remote sites in a shared virtual space and being visualized by arbitrary view image.
Domain-Speci fi c Modeling for Rapid System-Wide Energy Estimation of Recon fi gurable Architectures

Reconfigurable architectures such as FPGAs are flexible alternatives to DSPs or ASICs used in mobile devices for which energy is a key performance metric. Reconfigurable architectures offer several parameters such as operating frequency, precision, amount of memory, number of computation units, etc. These parameters define a large design space that must be explored to find energy efficient solutions. Efficient traversal of such a large design space requires high-level modeling to facilitate rapid estimation of system-wide energy. However, FPGAs do not exhibit a high-level structure like, for example, a RISC processor for which high-level as well as low-level energy models are available. To address this scenario, we propose a domain-specific modeling technique that exploits the knowledge of the algorithm and the target architecture family for a given problem to develop a high-level model. This model captures architecture and algorithm features, parameters affecting power performance, and power estimation functions based on these parameters. A system-wide energy function is derived based on the power functions and cycle specific power state of each building block of the architecture. This model can be used to understand the impact of various parameters on systemwide energy and can be a basis for the design of energy efficient algorithms. Our high-level model can be used to quickly obtain fairly accurate estimate of the system-wide energy of data paths configured using FPGAs. We demonstrate our modeling methodology by applying it to two domains. Keywords– domain modeling, energy estimation, energy optimization
Can a System of Linear Diophantine Equations be Solved in Strongly Polynomial Time ?

We demonstrate that the answer to the question posed in the title is “yes” and “no”: “no” if the set of permissible operations is restricted to {+,−,×,/,mod,<}; “yes” if we are also allowed a gcd-oracle as a permissible operation. It has been shown (see [Sto76, MST91]) that no strongly polynomial algorithm exists for the problem of finding the greatest common divisor (gcd) of two arbitrary integers, a and b. This result precludes the possibility of finding the set of solutions to a system of linear diophantine equations in strongly polynomial time. We show, however, that given an oracle that finds the gcd of two integers a and b and integer multipliers (x0, y0) satisfying ax0 +by0 = gcd(a, b), a system of linear diophantine equations can be solved in strongly polynomial time.
Structured Stochastic Linear Bandits ( DRAFT )

In this paper, we consider the structured stochastic linear bandit problem which is a sequential decision making problem where at each round t the algorithm has to select a p-dimensional vector xt from a convex set after which it observes a loss `t(xt). We assume the loss is a linear function of the vector and an unknown parameter θ∗. We consider the problem when θ∗ is structured which we characterize as having a small value according to some norm, e.g., s-sparse, group-sparse, etc. We precisely characterize how the regret grows for any norm structure in terms of the Gaussian width and show regret bounds which remove a √ p term. Additionally, we provide insight into the problem by introducing a new analysis technique which depends on recent developments in structured estimation.
An analysis of the spontaneous mutation rate measurement in filamentous fungi

Mutations related to gene methG1 of Aspergillus nidulans were analyzed, in order to study a mathematical model for the determination of the mutation rate per nucleus per generation, in filamentous fungi. A replica plating technique was used to inoculate, in a single operation, 26 colonies of the strain, into Petri dishes containing culture medium, and the nine central colonies were analyzed for size and number of conidia in each colony. Using this technique, several central colonies were analyzed with regard to the appearance of mutation, and the number and type of reversions were determined for each colony. The frequencies obtained for each reversion were analyzed, in order to verify if their distribution was in accordance with that of Greenwood and Yule. The data obtained allowed us to conclude that, using the mathematical model studied, it is possible to determine the mutation rate per nucleus, per generation, in filamentous fungi.