Miracle-dz/UniFAR-FTUs huggingface dataset:
Program behavior model based on system call and time interval

The automaton of program behavior based on system call is often used to model program behavior. The automaton of program behavior based on system call and time interval is proposed, which overcomes one of drawbacks of traditional automaton of program behavior based on system call: inability to monitor the program behavior between adjacent system calls. The method of quantifying time intervals between adjacent system calls is presented. Through monitoring the deviation degree of time intervals between adjacent system calls, the model can decide whether to deviate from normal program behavior between adjacent system calls to some extent. The experimental results show that the automaton of program behavior based on system call and time interval can model program behavior more accurately and has better detection ability of program behavior than traditional models.
Spatio-activity based object detection

We present the SAMMI lightweight object detection method which has a high level of accuracy and robustness, and which is able to operate in an environment with a large number of cameras. Background modeling is based on DCT coefficients provided by cameras. Foreground detection uses similarity in temporal characteristics of adjacent blocks of pixels, which is a computationally inexpensive way to make use of object coherence. Scene model updating uses the approximated median method for improved performance. Evaluation at pixel level and application level shows that SAMMI object detection performs better and faster than the conventional Mixture of Gaussians method.
Learning Image Manifolds from Local Features

Visual recognition is a fundamental yet challenging computer vision task. In the recent years there have been tremendous interest in investigating the use of local features and parts in generic object recognition-related problems such as, object categorization, localization, discovering object categories, recognizing objects from different views, etc. In this Chapter we present a framework for visual recognition that emphasizes the role of local features, the role of geometry and the role of manifold learning. The framework learns an image manifold embedding from local features and their spatial arrangement. Based on that embedding several recognition-related problems can be solved, such as object categorization, category discovery, feature matching, regression, etc. We start by discussing the role of local features, geometry and manifold learning; and follow that by discussing the challenges in learning image manifolds from local features.
Generating random spanning trees

The author describes a probabilistic algorithm that, given a connected, undirected graph G with n vertices, produces a spanning tree of G chosen uniformly at random among the spanning trees of G. The expected running time is O(n log n) per generated tree for almost all graphs, and O(n/sup 3/) for the worst graphs. Previously known deterministic algorithms are much more complicated and require O(n/sup 3/) time per generated tree. A Markov chain is called rapidly mixing if it gets close to the limit distribution in time polynomial in the log of the number of states. Starting from the analysis of the above algorithm, it is shown that the Markov chain on the space of all spanning trees of a given graph where the basic step is an edge swap is rapidly mixing. <<ETX>>
FDI spillovers over time in an emerging market: : The roles of entry tenure and barriers to imitation

In this study, we examine how foreign direct investment (FDI) spillovers to domestic firms in an emerging market occur over time. From the organizational learning perspective, we propose that, as entry tenure of foreign firms in an industry increases, domestic firms can learn from the foreign firms over time and improve their productivity. We further build upon the competitor imitation argument to propose that this effect will be stronger when barriers to imitation faced by the domestic firms are lower. Based upon a comprehensive panel dataset on manufacturing firms in China in 1998–2007, our findings strongly support these arguments. We find that entry tenure of foreign firms in an industry has a positive relationship with the productivity of individual domestic firms in the same industry, albeit at a diminishing rate. We also find that this positive relationship is stronger when the foreign firms have lower export intensity, lower intangible asset intensity, and have followed a more rhythmic (i.e., less irregular) entry pattern—situations characterizing lower barriers to imitation.
Performance Analysis of UKF for Nonlinear Problems

Unscented Kalman filter (UKF) is a class of nonlinear filtering methods based on unscented transform within the Kalman filter framework. It is in light of the intuition that to approximate a probability distribution by a set of deterministic samples is easier than to approximate an arbitrary nonlinear transform. The key factors of UKF—the scalar, the state variable dimensions and the noises involved in nonlinear system, besides the probability distribution, should be synthetically analyzed. The mean square error is adopted to evaluate the effect of these factors on the performance of UKF. The simulation results show that the factors above mentioned more or less affect the performance of UKF, in which the state noise plays the most important role.
A Method to Detect Machine Generated Domain Names Based on Random Forest Algorithm

In this paper, we proposed a method to detect machine generated domain names. Differences between the white list and the black list were analyzed to build a feature template from the angle of lexicology and linguistics. In contrast to the method based on the similarity, we adopted random forest algorithm to meet the demand of actual detection system by improving the generalization ability. Experimental results show that the method can not only achieve good performance in the efficiency and accuracy of detection, but also provide effective information support for security incidents.
Assessing the impacts of ICT A participatory evaluation process to overcome the eGovernment paradox

This paper builds on an extensive review of literature and practice analysing the barriers hindering the adoptions of eGovernment services (Savoldelli, Codagnone and Misuraca, 2012), and on the measurement and evaluation of ICT impact in general and of selected public eServices, including eGovernment (Misuraca, Codagnone and Rossel, 2012). From these analyses it emerges that one of the critical factors for implementing successful eGovernment services seems to be the presence of a transparent and trustworthy policy-making process. Moreover, the lack of a structured evaluation methodology to assess the impact of eGovernment services hampers the possibility of designing and implementing valid measurement models, highlighting the need to test concepts and hypotheses underlying them at a more granular and micro level. In order to overcome such limitations, this paper provides first a comparison between selected eGovernment evaluation methodologies, and discusses their limitations with regard to the capability to capture and assess the impacts of ICT-enabled services with specific regard to the relationships with the policy-making process. Building on the findings from this comparison, the paper proposes a comprehensive methodological approach, the eGEP-2.0 model, to assess the impacts of ICT-enabled services in the public sector, describing how an eGovernment evaluation framework should be organized, which should be its key components and which could be the political, managerial and organizational implications for the policy-making process. Finally, in order to validate the findings of the analysis and the proposed methodological framework, the paper discusses the results of the application of such framework to the x ante evaluation process of the eGovernment Information and Telecommunication Programme of the RegioneEmilia-Romagna in Italy, for the period 2011-2013, where more than 30 eGovernment services have been assessed and are being implemented following the proposed evaluation methodology. The paper concludes with some indications on how to further apply and develop the proposed framework and methodology.
Resolved motion control of a humanoid robot for coordinated manipulation

When applied for some tasks, such as payload handling, assemble, repairing, and so on, the two arms of a humanoid robot will form closed kinematic chain. It makes the motion planning and control for dual-arm coordination very complex and difficult. In this paper, we presented two types of resolved motion control methods for a humanoid robot during coordinated manipulation. They are respectively position-level and velocity-level resolved motion control method. For the former, the position-level trajectory of the payload is firstly planned. Then the desired pose (position and attitude) of the two arms are simultaneously determined by resolving the constraints on their end-effectors. For the latter, the velocity of the payload is planned. Then, the each end-effectors' velocities are resolved according to the constraints on the closed-chain system. The joint variables of each arm are then calculated using the inverse kinematics equations, at position-level or velocity-level corresponding to the two cases above. Finally, a dynamic modeling and simulation platform is established based on ADAMS. The proposed methods are verified by typical cases.
Distributed Security System for Intelligent Building Based on Wireless Communication Network

A distributed security system based on wireless communication technology is presented in this paper. The system adopts distributed structure, which consists of detect sensors, intelligent terminal, alarm devices and wireless communication network. The intelligent terminal which designed based on embedded system is used to realize acquisition information submitted from detect sensors, control the alarm devices and communicate the information to the host or police. The alarm information and control signals transmitted between the detect sensors and intelligent terminal by dint of wireless communication network. A real-time routing protocol of wireless communication network is described. The protocol provides a predictable upper bound for the end-to-end delivery delay. The real-time end-to-end guarantee was achieved by geographic forwarding, periodic message exchange between neighbour nodes, and stateless one-hop delay guarantee. A lower power-consuming encoding arithmetic is detailed moreover. The security system which is digital, networked, wireless and moveable have abroad application foreground.
Detecting and Correcting the Lies That Data Tell

Because of the way in which data are typically analyzed and interpreted, they frequently lie to researchers, leading to conclusions that are not only false but more complex than the underlying reality. The several examples of this presented in this article illustrate the possibility that although data may appear to indicate complex phenomena at the surface structure level, the phenomena may be quite simple at the deep structure level, suggesting the possibility of applying Occam’s razor to achieve the scientific goal of parsimony. The approaches to data analysis described in this article may also lead to a solution to the serious problem of construct proliferation in psychology by demonstrating that many constructs are redundant with other existing constructs. The major obstacles to these outcomes are researchers' continued reliance on the use of statistical significance testing in data analysis and interpretation and the failure to correct for the distorting effects of sampling error, measurement error, and other artifacts. Some of these problems have been addressed by the now widespread use of meta-analysis, but examination of the meta-analyses appearing in Psychological Bulletin from 1978 to 2006 shows that most employ a statistically inappropriate model for meta-analysis (the fixed effects model) and that 90% do not correct for the biasing effects of measurement error. Hence, there is still a long way to go in the improvement of data analysis and interpretation methods.
Autocorrelation Function of the Soft X-Ray Background Produced by Warm-Hot Gas in Dark Halos

We calculate the angular two-point autocorrelation function (ACF) of the soft X-ray background (SXRB) produced by the warm-hot intergalactic medium (WHIM) associated with dark halos, motivated primarily by searching for missing baryons and distinguishing different physical processes of the WHIM in dark halos. We employ a purely analytic model for the halo population that is completely determined by the universal density profile and the Press-Schechter mass function. We then adopt a phenomenological approach to nongravitational processes of the WHIM such as preheating and radiative cooling. It shows that the power spectra of the SXRB predicted by three WHIM models, namely, the self-similar model, preheating model, and cooling model, demonstrate remarkably different signatures in both amplitude and shape, with the peak locations moving from l ≈ 4 × 104 for the self-similar model to a smaller value of l ≈ (3-5) × 103 when nongravitational processes are taken into account. The corresponding ACFs for preheating and cooling models become shallower too as compared to the prediction of the self-similar model. This may permit an effective probe of the physical processes of the WHIM in massive halos in conjunction with the observationally determined power spectrum or ACF of the SXRB from diffuse WHIM. However, a direct comparison of our theoretical predictions with existing data (e.g., the ACF determined from ROSAT observations) is still difficult because of the dominant contribution of active galactic nuclei in the soft X-ray sky. We discuss briefly the implications of our results for resolving the missing baryon problem in the local universe.
Fine‐scale genetic structure and flowering output of the seagrass Enhalus acoroides undergoing disturbance

Abstract Seagrass are under great stress in the tropical coast of Asia, where Enhalus acoroides is frequently the dominant species with a large food web. Here, we investigate the question of the fine‐scale genetic structure of this ecologically important foundation species, subject to severe anthropogenic disturbance in China. The genetic structure will illuminate potential mechanisms for population dynamics and sustainability, which are critical for preservation of biodiversity and for decision‐making in management and restoration. We evaluated the fine‐scale spatial genetic structure (SGS) and flowering output of E. acoroides, and indirectly estimated the relative importance of sexual versus asexual reproduction for population persistence using spatial autocorrelation analysis. Results reveal high clonal diversity for this species, as predicted from its high sexual reproduction output. The stronger Sp statistic at the ramet‐level compared with genet‐level indicates that clonality increases the SGS pattern for E. acoroides. Significant SGS at the genet‐level may be explained by the aggregated dispersal of seed/pollen cohorts. The estimated gene dispersal variance suggests that dispersal mediated by sexual reproduction is more important than clonal growth in this study area. The ongoing anthropogenic disturbance will negatively affect the mating pattern and the SGS patterns in the future due to massive death of shoots, and less frequency of sexual reproduction.
Notice of RetractionFuzzy PID Sliding Mode Controller Design for the Position Control of a DC Motor

In this paper, sliding mode control method is studied for controlling DC motor because of its robustness against model uncertainties and external disturbances, and also its ability in controlling nonlinear and MIMO systems. In this method, using high control gain to overcome uncertainties lead to occur chattering phenomena in control law which can excite unmodeled dynamics and maybe harm the plant. Different approaches, such as intelligent methods, are used to abate these drawbacks. In order to enhancement the sliding mode controller performance, we have used fuzzy logic. For this purpose, we have used a PID outer loop in the control law then the gains of the sliding term and PID term are tuned on-line by a fuzzy system, so the chattering is avoided and response of the system is improved against external load here. Presented simulation results confirm the above claims and demonstrate the performance improvement in this case.
Speech Recognition and Synthesis Algorithm for Digital Hearing Aids under Background Noise

The difficulty of speech comprehension under background noise greatly influenced the use of hearing aids. To address this problem, this paper proposes a new hearing aids algorithm based on speech recognition and synthesis. This method is based on the pure speech to build a parameters database. Under the real noisy scene, implement speech recognition for the input speech, and then extract the corresponding parameters according to the results of the recognition and synthesize the pure speech. To improve the noise robustness of speech recognition system, we use a newly proposed kernel power flow orientation coefficients (KPOCs) as the characteristic parameters for training and testing. Because the speech synthesis is based on the parameters of pure speech, the output speech almost does not contain noise, and the difficulty of speech comprehension has great improvement.
Single phase multilevel string inverter for solar applications

The proposed study deals with modeling and implementation of a multilevel string inverter with non-isolated dc-dc converter design. The modeled system is intended to be used for solar applications that the photovoltaic panels are connected in string structure. However, the dc-dc converter and multilevel inverter are capable to be used in distributed energy generation applications owing to the proposed control infrastructure. The entire design includes dual buck converter at the dc coupling input where both of the converters simultaneously operate to regulate photovoltaic string voltages. Each dc converter is capable to manage a string comprised of two photovoltaic arrays at the input. The maximum power of each solar array is allowed to be 1.2 kWp while the maximum value of total input power is limited to 4.8 kWp regarding to the related international standards such as AS4777-2013, IEC62109, and IEC61727. The output voltages of dc converters are set to 120V by the proportional-integral controller and are coupled over dc busbar to supply 9-level string inverter. The multilevel string inverter is comprised of two H-bridges in symmetrical topology where it is arranged according to regular 5-level symmetrical inverter. Furthermore, the regular sinusoidal pulse width modulator is enhanced to increase voltage level of inverter to nine instead of regular 5-level output. The inverter provides unity power factor with 0.63% total harmonic distortion ratio.
Wrist joint proprioceptive acuity assessment using inertial and magnetic measurement systems

Human wrist proprioception is particularly important due to its role in manual dexterity and associated tasks of daily living. Most studies have focused on testing single degree of freedom joints or were only capable of displacing or moving a joint in a single plane, such as flexion/extension of the wrist. The purpose of this study was to examine the effects of both direction and angular level on the accuracy of human wrist position reproduction error. Sixty subjects (all males) without a history of wrist pathology were recruited from a university campus. Subjects performed a position reproduction task in eight directions at three angular levels. The results showed that wrist position reproduction error depends on direction and angular level. Comparable reliability for the intra-observer measurements for wrist range of motion and joint position sense. The orientation of the joint position sense production ellipse is similar to the orientation of the range of motion ellipse, indicating that subjects generated the most accurate in directions where it is easy to generate more range of motion and the lowest accurate in directions where it is not easy to generate more range of motion. Joint position sense decreased in accuracy as the joint angle increased. The position reproduction error depends on the angular level, and subjects overshoot the target angle for the low angular levels (25% range of motion) and undershoot the target angle for high angular levels (75% range of motion). Mapping the human wrist joint position sense ellipse contributes to our understanding of the comprehensive proprioceptive function of the wrist. This technique offers the opportunity to assess all of the directions of proprioceptive function, which in turn may aid in improving therapeutic approaches.
Recent advancements in stimulated-Brillouin-scattering slow light

espanolEn la presente revision se exponen los resultados obtenidos por nuestro grupo en luz lenta via scattering Brillouin estimulado (SBS por sus siglas en ingles). En ella describimos los fundamentos de los fenomenos de luz lenta y como el proceso de scattering Brillouin estimulado puede ser utilizado para obtener retardos sintonizables en fibras opticas. Posteriormente expondremos los mecanismos utilizados para superar las limitaciones impuestas por el estrecho ancho de banda de la resonancia Brillouin y para optimizar los resultados a tasas de datos correspondientes a las redes de telecomunicaciones actuales. A continuacion tambien describimos el proceso de almacenamiento coherente de la luz en fibras opticas basado en SBS, con aplicaciones en buffers completamente opticos. Finalmente, se comentan las perspectivas futuras de este excitante campo de investigacion. EnglishA review on the work performed by our group on slow light via Stimulating Brillouin scattering (SBS) is presented. We describe the fundamentals of the slow-light phenomena and how SBS can be used to obtain tunable optical delays in optical fibers. We then review the mechanisms to overcome the limitations imposed by the narrow SBS resonance bandwidth and to optimize the slow-light performance for data rates used in modern telecommunication networks. We also describe the process of coherent light storage in optical fibers based on SBS which paves the way to optical buffering applications. Finally, future perspectives of this exciting field of research are discussed.
Phoneme-level speech and natural language intergration for agglutinative languages

A new tightly coupled speech and natural language integration model is presented for a TDNN-based large vocabulary continuous speech recognition system. Unlike the popular n-best techniques developed for integrating mainly HMM-based speech and natural language systems in word level, which is obviously inadequate for the morphologically complex agglutinative languages, our model constructs a spoken language system based on the phoneme-level integration. The TDNN-CYK spoken language architecture is designed and implemented using the TDNN-based diphone recognition module integrated with the table-driven phonological/morphological co-analysis. Our integration model provides a seamless integration of speech and natural language for connectionist speech recognition systems especially for morphologically complex languages such as Korean. Our experiment results show that the speaker-dependent continuous Eojeol (word) recognition can be integrated with the morphological analysis with over 80\% morphological analysis success rate directly from the speech input for the middle-level vocabularies.