Miracle-dz/UniFAR-FTUs huggingface dataset:
A DTN Routing Scheme Based on Publish/Subscribe Model

Delay Tolerant Networking (DTN) is attractive as an effective communication method in unstable network environments where frequent disconnections occur easily. DTN routing is based on the store-carry-forward paradigm. So far, various DTN routing schemes corresponding to the temporal and spatial characteristics of contacts between nodes have been proposed. However, name resolution between a source and a destination is difficult in a network environment that consists of only wireless terminals such as DTN. In this paper, we present a DTN routing scheme based on the publish/subscribe model that enables flexible communication by using topics of information. In the proposed scheme, messages are sorted by the subscription lists and the contact condition of nodes in order to deliver to destinations with a short delay. We compare the performance of the proposed scheme with that of existing schemes through simulations.
Codebook and marker sequence design for synchronization-correcting codes

We propose a construction based on synchronization and error-correcting block codes and a matched marker sequence. The block codes can correct insertion, deletion and substitution errors within each codeword. The marker sequence allows the decoder to maintain synchronization at codeword boundaries even at high error rates. An upper bound is given for the performance of these codes over a channel with random substitutions and synchronization errors. It is shown that the performance is largely dependent on the code's minimum Levenshtein distance. The performance of these codes is verified by simulation and compared to published results. In concatenation with a non-binary outer code we obtain a significant improvement in frame error rate at similar overall code rates.
MLP Neural Network for face recognition based on Gabor Features and Dimensionality Reduction techniques

Face recognition is very used in biometric market for many reasons. Face can be detected at distance without user's implication in enrollment process. Face recognition systems are still expanded in video surveillance areas to control access. This paper presents an experimental study on some proposed face recognition approaches by building systems with different techniques for features extraction and classification. To validate comparison between proposed approaches, we use three face image databases ORL, Caltech Faces and Face94. We demonstrated in this paper that Gabor Features applied with Linear Discriminate analysis to reduce size of dataset classified with MLP Neural Network ranks top the list of proposed approaches as well as many works done in literature.
Adaptive multiuser receivers for DS-CDMA using minimum BER gradient-Newton algorithms

We investigate the use of adaptive minimum bit error rate (MBER) gradient-Newton algorithms in the design of linear multiuser receivers (MUD) for DS-CDMA systems. The proposed algorithms approximate the bit error rate (BER) from training data using linear multiuser detection structures. We carry out a comparative analysis of linear MUDs employing minimum mean squared error (MMSE), previously reported MBER and the proposed MBER algorithms. Computer simulation experiments show that the MBER gradient-Newton approaches outperform other analysed algorithms and can operate with shorter training sequences.
Pipelined Hogenauer CIC filters using field-programmable logic and residue number system

Field-programmable logic (FPL) is on the verge of revolutionizing digital signal processing (DSP) in the manner that programmable DSP microprocessors did nearly two decades ago. While FPL densities and performance have steadily improved to the point where some DSP solutions can be integrated into a single FPL chip, they still have limited use in high-precision high-bandwidth applications. It is shown that in such cases, the residue number system (RNS) can be an enabling technology. The design of a high-decimation rate digital filter is presented which demonstrates the RNS-FPL synergy.
Interactive ray tracing of free-form surfaces

Even though the speed of software ray tracing has recently been increased to interactive performance even on standard PCs, these systems usually only supported triangles as geometric primitives. Directly handling free-form surfaces such as spline or subdivision surfaces instead of first tesselating them offers many advantages such as higher precision results, reduced memory requirements, and faster preprocessing due to less primitives. However, existing algorithms for ray tracing free-form surfaces are much too slow for interactive use. In this paper we present a simple and generic approach for ray tracing free-form surfaces together with specific implementations for cubic Bézier and Loop subdivision surfaces. We show that our approach allows to increase the performance by more than an order of magnitude, requires only constant memory, and is largely independent on the total number of free-form primitives in a scene. Examples demonstrate that even scene with over one hundred thousand free-form surfaces can be rendered interactively on a single processor at video resolution.
The Conscious Brain

Eriksson, J. (2007). The conscious brain: Empirical investigations of the neural correlates of perceptual awareness. Doctoral dissertation from the Department of Psychology, Umea University, S-901 87 Umea, Sweden. ISBN: 978-91-7264-457-1 Although consciousness has been studied since ancient time, how the brain implements consciousness is still considered a great mystery by most. This thesis investigates the neural correlates of consciousness by measuring brain activity with functional magnetic resonance imaging (fMRI) while specific contents of consciousness are defined and maintained in various experimental settings. Study 1 showed that the brain works differently when creating a new conscious percept compared to when maintaining the same percept over time. Specifically, sensory and fronto-parietal regions were activated for both conditions but with different activation patterns within these regions. This distinction between creating and maintaining a conscious percept was further supported by Study 2, which in addition showed that there are both differences and similarities in how the brain works when defining a visual compared to an auditory percept. In particular, frontal cortex was commonly activated while posterior cortical activity was modality specific. Study 3 showed that task difficulty influenced the degree of frontal and parietal cortex involvement, such that fronto-parietal activity decreased as a function of ease of identification. This is interpreted as evidence of the non-necessity of these regions for conscious perception in situations where the stimuli are distinct and apparent. Based on these results a model is proposed where sensory regions interact with controlling regions to enable conscious perception. The amount and type of required interaction depend on stimuli and task characteristics, to the extent that higher-order cortical involvement may not be required at all for easily recognizable stimuli.
Optimized Assays for Human UDP-Glucuronosyltransferase (UGT) Activities: Altered Alamethicin Concentration and Utility to Screen for UGT Inhibitors

The measurement of the effect of new chemical entities on human UDP-glucuronosyltransferase (UGT) marker activities using in vitro experimentation represents an important experimental approach in drug development to guide clinical drug-interaction study designs or support claims that no in vivo interaction will occur. Selective high-performance liquid chromatography-tandem mass spectrometry functional assays of authentic glucuronides for five major hepatic UGT probe substrates were developed: β-estradiol-3-glucuronide (UGT1A1), trifluoperazine-N-glucuronide (UGT1A4), 5-hydroxytryptophol-O-glucuronide (UGT1A6), propofol-O-glucuronide (UGT1A9), and zidovudine-5′-glucuronide (UGT2B7). High analytical sensitivity permitted characterization of enzyme kinetic parameters at low human liver microsomal and recombinant UGT protein concentration (0.025 mg/ml), which led to a new recommended optimal universal alamethicin activation concentration of 10 μg/ml for microsomes. Alamethicin was not required for recombinant UGT incubations. Apparent enzyme kinetic parameters, particularly for UGT1A1 and UGT1A4, were affected by nonspecific binding. Unbound intrinsic clearance for UGT1A9 and UGT2B7 increased significantly after addition of 2% bovine serum albumin, with minimal changes for UGT1A1, UGT1A4, and UGT1A6. Eleven potential UGT and cytochrome P450 inhibitors were evaluated as UGT inhibitors, resulting in observation of nonselective UGT inhibition by chrysin, mefenamic acid, silibinin, tangeretin, ketoconazole, itraconazole, ritonavir, and verapamil. The pan-cytochrome P450 inhibitor, 1-aminobenzotriazole, minimally inhibited UGT activities and may be useful in reaction phenotyping of mixed UGT and cytochrome P450 substrates. These methods should prove useful in the routine assessments of the potential for new drug candidates to elicit pharmacokinetic drug interactions via inhibition of human UGT activities and the identification of UGT enzyme-selective chemical inhibitors.
Development of an advanced manufacturing cloud for machine tool industry based on AVM technology

In this paper, a cloud manufacturing platform, called AMC (Advanced Manufacturing Cloud), is introduced. The AMC provides several manufacturing-related cloud services to facilitate the users to conduct supporting activities for machine tools and offers intelligent devices which can be plugged in various prediction models for performing predictive applications on machine tools. We first describe the architecture design of the AMC and then present methodologies to how to build cloud services and key mechanisms in the AMC. Finally, we construct a paradigm AMC and practically deploy its cloud services and intelligent devices in a public cloud platform and a factory of our cooperative machine tool company, respectively. We also conduct integrated tests to illustrate the efficacy and merits of the AMC.
EST: the new frontier in automatic test-pattern generation

An algorithm, called EST, is presented which is a new combinatorial automatic test-pattern generation (ATPG) branch-and-bound search algorithm, based on the generation of equivalent logic decompositions (search states) at each search decision point. The E-frontier is an efficient representation of a search state and is used with a hashing algorithm to detect equivalent search states. When EST matches an equivalent search state from a prior fault, and both prior and current faults are sensitized, EST completes the current fault test-pattern with values from the prior fault test-pattern and terminates search immediately. A new method of redundant fault analysis is also introduced that uniquely determines signal values for subsequent test-pattern search. Results show that this algorithm accelerates the base ATPG algorithm by a factor of 1.03 to 328 when considering all faults, a factor of 1347:1 for hard-to-test faults and a factor of 200000 for certain redundancy proofs for the test cases shown. <<ETX>>
A Group-Strategyproof Cost Sharing Mechanism for the Steiner Forest Game

We consider a game-theoretical variant of the Steiner forest problem in which each player $j$, out of a set of $k$ players, strives to connect his terminal pair $(s_j, t_j)$ of vertices in an undirected, edge-weighted graph $G$. In this paper we show that a natural adaptation of the primal-dual Steiner forest algorithm of Agrawal, Klein, and Ravi [SIAM J. Comput. , 24 (1995), pp. 445-456] yields a $2$-budget balanced and cross-monotonic cost sharing method for this game. We also present a negative result, arguing that no cross-monotonic cost sharing method can achieve a budget balance factor of less than $2$ for the Steiner tree game. This shows that our result is tight. Our algorithm gives rise to a new linear programming relaxation for the Steiner forest problem which we term the lifted-cut relaxation. We show that this new relaxation is stronger than the standard undirected cut relaxation for the Steiner forest problem.
Managing parameter spaces for multimedia composition

Although the capability to create whole animations by computer has greatly enhanced the artist’s repetoire, it does not by itself address the issue that Whitney [1980] encountered while producing his film, Arabesque, where the “concept was not deeply ‘mined’ for its fullest possibilities. ” Systematic exploration of alternatives is usually costly because it requires “less imagination than patience” [Bertin 1983], and has no guarantee of results. Soft- ware systems aimed at reducing the requirement for patience in the exploration of alternatives have achieved success.
The differential effects of CEO narcissism and hubris on corporate social responsibility

Research Summary: While prior studies have predominantly shown that CEO narcissism and hubris exhibit similar effects on various strategic decisions and outcomes, this study aims to explore the mechanisms underlying how narcissistic versus hubristic CEOs affect their firms differently. Specifically, we investigate how peer influence moderates the CEO narcissism/hubris—corporate social responsibility (CSR). With a sample of SP the negative relationship between CEO hubris and CSR is strengthened when peer firms are engaged in less CSR than a CEO's own firm. Managerial Summary: Some CEOs are more narcissistic while others may be more hubristic, but these two groups of CEOs hold different attitudes toward the extent to which their firms should engage in corporate social responsibility (CSR). Our findings with a large sample of U.S. publically listed firms suggest that narcissistic CEOs care more about CSR, but hubristic CEOs care less. Interestingly, when narcissistic CEOs observe their peer firms engaging in more or less CSR than their own firms, they tend to respond in an opposite manner; in contrast, hubristic CEOs will only engage in even less CSR when their peers also do not emphasize CSR. Our findings point to a fundamental difference between CEO narcissism and hubris in terms of how they affect firms' CSR decisions based on their social comparison with peer firms.
Chronotype, Sleep Behavior, and the Big Five Personality Factors

Chronotype refers to individual differences in sleep timing and in preferences for a given time of day while sleep duration refers to the hours of sleep. Here, we assessed chronotype, sleep duration, and nightmare frequency in relation to the Big Five personality factors. Overall, 2,492 persons (1,437 women, 1,055 men) completed the online survey between March 23, 2015, and April 8, 2015. The mean age of the sample was 47.75 ± 14.41 years. In bivariate correlations, age, extraversion, agreeableness, and conscientiousness were related to morningness, and openness to experience and neuroticism were related to eveningness. In the multiple regression, gender, neuroticism, and agreeableness were not related to chronotype. Morning types slept less at weekends than evening types, and evening types showed longer sleep latencies. Neuroticism showed the strongest effect on nightmare frequency followed by openness to experience. Nightmare frequency declined with age, and there was a small but significant effect of conscientiousness on nightmare frequency; persons with higher conscientiousness scores reported slightly more often nightmares. Chronotype was not associated with nightmare frequency. To conclude, chronotype is associated with personality factors and sleep behavior (sleep duration on weekends and sleep latency).
Information Warfare on Social Media: A Brand Management Perspective

Abstract Employing a perspective informed by brand management, this article aims at understanding information warfare operations in social media. The state, seen as brand, must project an image of itself to both internal and foreign audiences to unite the domestic audience and/or attract global support. However, in constructing a brand, states are vulnerable to ‘sofa warriors’ – ordinary individuals who have been unwittingly recruited by hostile actors to disseminate (over social media or other platforms) a counter-brand, harmful to the state concerned. These new threats are investigated in light of recent tendencies in online branding, elucidating their status as a national security threat, with the potential to significantly disrupt life in political communities.
Dynamic simulation of a hydraulic exoskeleton robot based on virtual prototyping

The exoskeleton robot enhances the wearer's strength and plays an important role in various applications such as disaster relief, battlefield, rehabilitation, etc. The hydraulic system is often used to actuate the locomotion robotics for the advantages of high power-to-mass ratio, large force output, and so on. In this paper, the dynamic simulation of a hydraulic-driven exoskeleton robot is presented. Based on virtual prototyping, the controller and the parameters of the hydraulic system are determined and verified by modeling the driven system in AMESim, while the robot dynamic behavior is analyzed by building the robot dynamic model in ADAMS. The model of the prime mover, an IC engine, is simplified to reflect its torque-speed property rather than the complicated physical and chemical changes in the combustion cycle. In the simulation, the controller is determined first by employing a sufficient constant flow source to replace the engine model and the pump. Then the parameters of the hydraulic system are verified based on the determined controller. Lastly, the dynamic behavior of the exoskeleton robot is predicted by tracking the input reference from the Clinical Gait Analysis (CGA) data. The simulation results indicate that the designed exoskeleton robot can achieve expected working conditions. Experiments are set up on the exoskeleton robot prototype to validate the virtual prototype. The agreement of the results from simulation and experiments confirms that the virtual prototype predicts the dynamic behavior of the exoskeleton robot reliably.
Online optimization for variable selection in data streams

Variable selection for regression is a classical statistical problem, motivated by concerns that too many covariates invite overfitting. Existing approaches notably include a class of convex optimisation techniques, such as the Lasso algorithm. Such techniques are invariably reliant on assumptions that are unrealistic in streaming contexts, namely that the data is available off-line and the correlation structure is static. In this paper, we relax both these constraints, proposing for the first time an online implementation of the Lasso algorithm with exponential forgetting. We also optimise the model dimension and the speed of forgetting in an online manner, resulting in a fully automatic scheme. In simulations our scheme improves on recursive least squares in dynamic environments, while also featuring model discovery and changepoint detection capabilities.
VLSI Implementation of a High-Speed Iterative Sorted MMSE QR Decomposition

The QR decomposition is an important, but often underestimated prerequisite for pseudo- or non-linear detection methods such as successive interference cancellation or sphere decoding for multiple-input multiple-output (MIMO) systems. The ability of concurrent iterative sorting during the QR decomposition introduces a moderate overall latency, but provides the base for an improved layered stream decoding. This paper describes the architecture and results of the first VLSI implementation of an iterative sorted QR decomposition preprocessor for MIMO receivers. The presented architecture performs MIMO channel preprocessing using Givens rotations in order to compute the minimum mean squared error QR decomposition
A Unified Management Model for Data Intensive Storage Clouds

Cloud storage has recently appeared as a promising solution to handle the immense volume of data produced in nowadays' rich and ubiquitous digital environment. Existing approaches, however, do not fully address certain significant issues, such as Service Level Agreements, which tend to be rudimentary, and management of cloud systems, which often lacks sophistication. In this paper, we propose the definition and development of management models that systematically describe the resources, services, usage, and requirements in the context of a cloud storage environment. Furthermore, we introduce content oriented SLA Schemas, which are adapted according to the content term involved in each SLA. Combining all this often heterogeneous information in a smart, structured, and uniform manner can provide significant added value, allowing correlations, links and extraction of useful inferences. We thus propose to incorporate these models in a rich Unified Management Model, which will contribute to optimum decision making, data movement, as well as better resource allocation and energy management, also leading to enhanced Quality of Service. The research presented in this paper is work in progress carried out in the context of the VISION Cloud project.
Dynamic Change Management for Fast-Tracking Construction Projects

Uncertainties make construction dynamic and unstable, mostly by creating non value-adding change iterations among construction processes. Particularly, when a project is fast-tracked without proper planning, those change iterations can cause the disruption of the construction process. For this reason, to effectively handle fast-tracking change iterations involved in fast-tracking need to be identified, and the dynamic behavior of construction resulting from those change iterations must be dealt with in a systematic manner. As an effort to address some of these challenging issues in fast-tracking construction, this research paper identifies different change iteration cycles involved in fast-tracking construction and observes the characteristics and behavior patterns of change. All of research findings are incorporated into a cohesive system dynamics model and the model simulation confirms that managerial decisions on change or rework should be made based on the proper assessment of their tradeoff. In addition, a case study of highway and bridge construction projects shows the potential of how fast-tracking construction can benefit from dynamic change management in real world settings.
The Degradome database: mammalian proteases and diseases of proteolysis

The degradome is defined as the complete set of proteases present in an organism. The recent availability of whole genomic sequences from multiple organisms has led us to predict the contents of the degradomes of several mammalian species. To ensure the fidelity of these predictions, our methods have included manual curation of individual sequences and, when necessary, direct cloning and sequencing experiments. The results of these studies in human, chimpanzee, mouse and rat have been incorporated into the Degradome database, which can be accessed through a web interface at http://degradome.uniovi. es. The annotations about each individual protease can be retrieved by browsing catalytic classes and families or by searching specific terms. This web site also provides detailed information about genetic diseases of proteolysis, a growing field of great importance for multiple users. Finally, the user can find additional information about protease structures, protease inhibitors, ancillary domains of proteases and differences between mammalian degradomes.