Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive Critic Based Control of Aircraft with Atmospheric Disturbance

The design of fight control is full of challenges because of the complex model and the complicated fight entironment. The traditional control methods no longer ensure the demand in the many fight modes. Recently, advanced control methods attract more and more researchers to make application research in this field. Adaptive critic design (ACD) is an effective control method to learn the optimal control online. The performance of fight control with atomospheric disturance needs to be improved using active control or robust control. This paper presents adaptive critic based controller design of aircraft with atmospheric disturbance. The controller does not rely on the parameters of the aircraft, and it can learn online very well. When there are atmospheric disturbances, such as random turbulence, discrete gust and wind shear, adaptive critic based controller can resist the disturbances effectively, and shows the good robust performance. Finally, the simulation proves the validity of the adaptive critic based controller for aircraft with atmospheric disturbance.
Connecting Educational Leadership with Multi-Level Assessment Reform.

Renewed calls for greater accountability within schools have led to a rapid expansion of standardsbased reforms across the Western world. Establishing and raising standards, and measuring the attainment of those standards, are intended to encourage excellence in our schools. Yet concern is increasing about the fairness of external testing and the undue pressure it places on students and teachers. This paper discusses the impact of recent standards-based reforms and proposes a framework to connect educational leadership with timely assessment reforms at the provincial/state governance, university, district, and school level. The proposed multi-level reforms are grounded in the belief that coherent, well integrated assessment policies are essential for promoting improved teaching practice and student learning.
Internet of things using publish and subscribe method cloud-based application to NFT-based hydroponic system

The integration Internet of Things (IoT) generally identical with Cloud computing. IoT aims to connect the heterogeneous objects/devices with each other, in order to communicate or exchange data/information. Development of the Cloud IoT system, have challenges to achieve these objectives, such as middleware, interoperability and scalability of system. In this paper, we will discuss the solution of the challenges, by applying the publish and subscriber method, using MQTT protocol. This paper, proposed of architecture model design, which is implemented in the form of system topology. This topology apply to monitor and control the provision of nutrition hydroponics, accessible as a Cloud SaaS. From the test results, average node response time needed to connect and communicate with IoT Cloud system (online) is 7.21 seconds. The time required to declare offline state of a node is 21.55 seconds. The test results of Cloud IoT (broker), obtained that number of nodes for each level QoS, affecting resource usage of CPU and throughput. The highest resource usage of CPU is 19% of 2.0GHz and throughput TX/RX is 34.68KBps/49.4KBps. This result obtained from 1000 nodes scheme testing with 1 messages/node, by using simulation application, on QoS level 2. The average of minimum bandwidth used is ± 0.90Kbps by 1 publisher, to send 1 message with 115 Bytes of payload size, on each 3 levels of QoS MQTT, and approximately ± 0.04Kbps on subscriber to receive that message.
Dependency Parse Reranking with Rich Subtree Features

In pursuing machine understanding of human language, highly accurate syntactic analysis is a crucial step. In this work, we focus on dependency grammar, which models syntax by encoding transparent predicate-argument structures. Recent advances in dependency parsing have shown that employing higher-order subtree structures in graph-based parsers can substantially improve the parsing accuracy. However, the inefficiency of this approach increases with the order of the subtrees. This work explores a new reranking approach for dependency parsing that can utilize complex subtree representations by applying efficient subtree selection methods. We demonstrate the effectiveness of the approach in experiments conducted on the Penn Treebank and the Chinese Treebank. Our system achieves the best performance among known supervised systems evaluated on these datasets, improving the baseline accuracy from 91.88% to 93.42% for English, and from 87.39% to 89.25% for Chinese.
Learning image representations equivariant to ego-motion ( Supplementary material )

Some sample images from KITTI and SUN are shown in Fig 1. As they show, these datasets have substantial domain differences. In KITTI, the camera faces the road and has a fixed field of view and camera pitch, and the content is entirely street scenes around Karlsruhe. In SUN, the images are downloaded from the internet, and belong to 397 diverse indoor and outdoor scene categories—most of which have nothing to do with roads.
Multiscale difference equation signal modeling and analysis techniques

A novel signal modeling technique in which an arbitrary sequence of data points is represented as samples of the solution to a multiscale difference equation is proposed. Such a model completely characterizes a number of higher derivatives of the signal as well as the signal itself. It provides a recursive signal interpolation mechanism as a function of scale. It also leads to multigrid type signal filtering, detection and estimation algorithms. The existence and uniqueness of L/sub 1/ and L/sub 2/ solutions to the multiscale difference equation are first investigated. The paper generalizes the results obtained for the two scale difference equation. Next, we provide conditions for the existence of unique solution to such an equation. Finally, techniques for modeling an arbitrary set of data samples as samples of the solution to a multiscale difference equation are presented. Specifically, we describe the encoding and decoding steps in these techniques. We also prevent audio signal modeling examples to illustrate multiscale difference equation models. <<ETX>>
Taiwan's Ban on Corporal Punishment: Educator Perceptions of Impact and Meaning

On the basis of interviews of a sample of teachers and administrators, we examine Taiwan's 2006 legislative ban on school corporal punishment, seeking to understand why the practice persists within the nation's junior high schools. Results suggest that while teachers reject harsher forms of corporal punishment, many continue to view its moderate use as a practical, acceptable tool for pupil control. This appears to result from schools’ traditional reliance on informal, discretionary forms of punishment and the high-stakes testing environment. Our study illustrates how conflict between macro and local environmental structures, needs, and values can delay and limit broad reform efforts.
Combining Spatial-Temporal and Phylogenetic Analysis Approaches for Improved Understanding on Global H5N1 Transmission

Background Since late 2003, the highly pathogenic influenza A H5N1 had initiated several outbreak waves that swept across the Eurasia and Africa continents. Getting prepared for reassortment or mutation of H5N1 viruses has become a global priority. Although the spreading mechanism of H5N1 has been studied from different perspectives, its main transmission agents and spread route problems remain unsolved. Methodology/Principal Findings Based on a compilation of the time and location of global H5N1 outbreaks from November 2003 to December 2006, we report an interdisciplinary effort that combines the geospatial informatics approach with a bioinformatics approach to form an improved understanding on the transmission mechanisms of H5N1 virus. Through a spherical coordinate based analysis, which is not conventionally done in geographical analyses, we reveal obvious spatial and temporal clusters of global H5N1 cases on different scales, which we consider to be associated with two different transmission modes of H5N1 viruses. Then through an interdisciplinary study of both geographic and phylogenetic analysis, we obtain a H5N1 spreading route map. Our results provide insight on competing hypotheses as to which avian hosts are responsible for the spread of H5N1. Conclusions/Significance We found that although South China and Southeast Asia may be the virus pool of avian flu, East Siberia may be the source of the H5N1 epidemic. The concentration of migratory birds from different places increases the possibility of gene mutation. Special attention should be paid to East Siberia, Middle Siberia and South China for improved surveillance of H5N1 viruses and monitoring of migratory birds.
Letters in the forest: global precedence effect disappears for letters but not for non-letters under reading-like conditions

Normally skilled reading involves special processing strategies for letters, which are habitually funneled into an abstract letter code. On the basis of previous studies we argue that this habit leads to the preferred usage of an analytic strategy for the processing of letters, while non-letters are preferably processed via a holistic strategy. The well-known global precedence effect (GPE) seems to contradict to this assumption, since, with compound, hierarchical figures, including letter items, faster responses are observed to the global than to the local level of the figure, as well as an asymmetric interference effect from global to local level. We argue that with letters these effects depend on presentation conditions; only when they elicit the processing strategies automatized for reading, an analytic strategy for letters in contrast to non-letters is to be expected. We compared the GPE for letters and non-letters in central viewing, with the global stimulus size close to the functional visual field in whole word reading (6.5° of visual angle) and local stimuli close to the critical size for fluent reading of individual letters (0.5° of visual angle). Under these conditions, the GPE remained robust for non-letters. For letters, however, it disappeared: letters showed no overall response time advantage for the global level and symmetric congruence effects (local-to-global as well as global-to-local interference). We interpret these results as according to the view that reading is based on resident analytic visual processing strategies for letters.
Data Dissemination With Side Information and Feedback

Index coding (IC), which can be regarded as a special class of network coding, deals with the problem of sending a number of packets to a group of receivers, each of which requests one packet and may have some other packets in its cache. This paper generalizes the IC problem in that both the packet requested by a receiver and the packets in its cache can be linear combinations of the packets. To minimize the number of transmissions required, a heuristic algorithm based on the idea of partitioning the users into coding groups is designed. To realize this idea, a polynomial time algorithm to determine whether a set of users form a coding group over the binary field or a field with a size larger than the number of users is constructed. For users that form a coding group, the corresponding encoding vector can be also found. A lower bound is derived in order to evaluate the performance of the heuristic algorithm. Numerical results show that the number of transmissions required by the heuristic algorithm and the lower bound both grow roughly linearly with the number of users, and the heuristic algorithm outperforms some benchmark algorithms.
NMDA But Not Non-NMDA Excitotoxicity is Mediated by Poly(ADP-Ribose) Polymerase

Poly(ADP-ribose) polymerase (PARP-1), a nuclear enzyme that facilitates DNA repair, may be instrumental in acute neuronal cell death in a variety of insults including, cerebral ischemia,1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine-induced parkinsonism, and CNS trauma. Excitotoxicity is thought to underlie these and other toxic models of neuronal death. Different glutamate agonists may trigger different downstream pathways toward neurotoxicity. We examine the role of PARP-1 in NMDA- and non-NMDA-mediated excitotoxicity. NMDA and non-NMDA agonists were stereotactically delivered into the striatum of mice lacking PARP-1 and control mice in acute (48 hr) and chronic (3 week) toxicity paradigms. Mice lacking PARP-1 are highly resistant to the excitoxicity induced by NMDA but are as equally susceptible to AMPA excitotoxicity as wild-type mice. Restoring PARP-1 protein in mice lacking PARP-1 by viral transfection restored susceptibility to NMDA, supporting the requirement of PARP-1 in NMDA neurotoxicity. Furthermore, Western blot analyses demonstrate that PARP-1 is activated after NMDA delivery but not after AMPA administration. Consistent with the theory that nitric oxide (NO) and peroxynitrite are prominent in NMDA-induced neurotoxicity, PARP-1 was not activated in mice lacking the gene for neuronal NO synthase after NMDA administration. These results suggest a selective role of PARP-1 in glutamate excitoxicity, and strategies of inhibiting PARP-1 in NMDA-mediated neurotoxicity may offer substantial acute and chronic neuroprotection.
Measuring Unobserved Expected Inflation

The aim of this study is to develop an eclectic but robust model that allows for a better measure of expected inflation and allows testing for all sorts of biases. Improving the measure of expected inflation is of critical importance for conducting monetary policy. In many circumstances, indicators of expected inflation move in opposite directions, and this divergence may be critical for the setting of the interest rate. The model is estimated for a special set of Israeli data via the Kalman filter methodology. We test for systematic biases, for a better normalization of the model, for liquidity problems, and for inflation risk - all possibly present in current measures of expected inflation.
A Life Span Developmental Perspective on Psychosocial Development in Midlife

The fields of life span human development and counseling share the goal of empowering diverse individuals and families in living healthy, satisfying, and meaningful lives (Geidner, 2009; Kaplan, Tarvydas, & Gladding, 2014). The life span developmental perspective studies patterns of development from conception to death to foster positive adaptation and resilience in people of all ages (Overton, 2015). Although middle adulthood (ages 40 to 65 years) spans about one third of the life span, it is little researched relative to childhood and older adulthood (Lachman, 2015). Myths about midlife abound, and it is often portrayed colloquially as a time of crisis and loss. Research instead suggests that middle adulthood is a time of stability, discovery, and growth (Lachman, 2015). This article provides an overview of the life span developmental perspective and its application in understanding midlife adults’ sense of self and aging, developmental tasks, and immersion in a system of contexts. An understanding of psychosocial development in middle adulthood can aid counselors in their work with middle-aged adults as clients and family members.
Hybrid crossover operators with multiple descendents for real‐coded genetic algorithms: Combining neighborhood‐based crossover operators

Most real‐coded genetic algorithm research has focused on developing effective crossover operators, and as a result, many different types of crossover operators have been proposed. Some forms of crossover operators are more suitable to tackle certain problems than others, even at the different stages of the genetic process in the same problem. For this reason, techniques that combine multiple crossovers, called hybrid crossover operators, have been suggested as alternative schemes to the common practice of applying only one crossover model to all the elements in the population. On the other hand, there are operators with multiple offsprings, more than two descendants from two parents, which present a better behavior than the operators with only two descendants, and achieve a good balance between exploration and exploitation. © 2009 Wiley Periodicals, Inc.
Maestro : Direct Manipulation Through Gesture Alone

Past research suggests a number of benefits to using hand-based interaction when interacting with electronic presentations. This paper introduces Maestro, a computer-vision based presentation system that uses hand gestures to allow fine-grained interaction with the contents of a projected slideshow. Maestro employs a single web camera and no other physical mediators. The contributions of this paper lie in robustly solving the gesture segmentation problem inherent in using only computer vision as input, and in a set of feedback mechanisms designed to scaffold use of the recognition system without interfering with the visual presentation of content. Specifically, Maestro employs bimanual cues, spatial and contentbased context, hand roles, and, in some case, dwell time to segment gestures. These strong segmentation cues are robust with respect to false positives and allow the actual gestures themselves to more directly match the action to be performed. They also result in a direct manipulation-style interface built on gestures alone. To assist with use, Maestro introduces a feedback comet, an augmented cursor that provides mnemonics for gestures and feedback to help govern gesture speeds to those conducive to gesture recognition. We present the design of the system and lessons learned from user evaluations.
Sequence-aware Intrusion Detection in Industrial Control Systems

Nowadays, several threats endanger cyber-physical systems. Among these systems, industrial control systems (ICS) operating on critical infrastructures have been proven to be an attractive target for attackers. The case of Stuxnet has not only showed that ICSs are vulnerable to cyber-attacks, but also that some of these attacks rely on understanding the processes beyond the employed systems and using such knowledge to maximize the damage. This concept is commonly known as "semantic attack". Our paper discusses a specific type of semantic attack involving "sequences of events". Common network intrusion detection systems (NIDS) generally search for single, unusual or "not permitted" operations. In our case, rather than a malicious event, we show how a specific series of "permitted" operations can elude standard intrusion detection systems and still damage an infrastructure. Moreover, we present a possible approach to the development of a sequence-aware intrusion detection system (S-IDS). We propose a S-IDS reference architecture and we discuss all the steps through its implementations. Finally, we test the S-IDS on real ICS traffic samples captured from a water treatment and purification facility.
Recent improvements in speech recognition performance on large vocabulary conversational speech (voicemail and switchboard)

In this paper we report recent improvements in word error performance on a voicemail transcription task. Last year, the speaker independent word error rate (WER) on the dev test set of the Voicemail Transcription task was reported at 35.45% [1]. This year, we report a relative 20% gain over this number. The improvements were obtained using several new algorithms and an increased amount of training data. In addition to benchmarking the performance of these algorithms on the Voicemail task, we have also evaluated them on the Switchboard task, and we report these results here as well. Finally, we also present the result of cross-domain experiments to evaluate the domain-independence of the constructed systems.
An Improved Algorithm for Blind Reverberation Time Estimation

An improved algorithm for the estimation of the reverberation time (RT) from reverberant speech signals is presented. This blind estimation of the RT is based on a simple statistical model for the sound decay such that the RT can be estimated by means of a maximum-likelihood (ML) estimator. The proposed algorithm has a significantly lower computational complexity than previous ML-based algorithms for RT estimation. This is achieved by a downsampling operation and a simple pre-selection of possible sound decays. The new algorithm is more suitable to track time-varying RTs than related approaches. In addition, it can also estimate the RT in the presence of (moderate) background noise. The proposed algorithm can be employed to measure the RT of rooms from sound recordings without using a dedicated measurement setup. Another possible application is its use within speech dereverberation systems for hands-free devices or digital hearing aids.
Tracking control of a giant magnetostrictive actuator with stress-dependent hysteresis compensation

Effective employment of giant magnetostrictive actuator (GMA) is limited in trajectory-tracking applications due to hysteresis nonlinearity, especially it is stress-dependent. In this paper, the properties of stress-dependent hysteresis for GMA are studied and a stress-dependent hysteresis model is given by extending modified Prandtl-Ishlinskii model to describe hysteresis effects. The identification method of this model is given and constraint conditions are also discussed to guarantee the unique existence of its analytical inverse, which is attractive to real-time control. Subsequently, the inverse stress-dependent hysteresis model is applied to cancel the hysteresis of GMA for the real-time microposition tracking control. A comparison is made between control with stress-dependent hysteresis compensation and control with stress-independent hysteresis compensation. Experimental results show that RMS tracking errors are reduced by if the rate-dependent hysteresis compensation is added. In order to improve control accuracy, a PID feedback controller is incorporated with a feedforward loop. Experimental results show that tracking results are improved greatly by augmenting the feedback loop with hysteresis compensation in the feedforward loop.
Best practices for motor control center protection and control

Low-voltage motor control centers (MCCs) are numerous and consume a large portion of maintenance and operator interaction in an industrial power distribution system. The extensive human interaction with these low-voltage (less than 1,000 V) circuits makes a low-voltage MCC a location of significant potential hazard. The large number of low-voltage MCC circuits results in significantly more human interface time with low-voltage MCC equipment than with medium-voltage MCCs and switchgear. Modern protection and control systems derived from medium-voltage (1,000 V to 38 kV) and high-voltage (38 to 765 kV) power systems have much to offer low-voltage MCC systems. Proactive maintenance indicators based on load characteristics, motor start characteristics, and thermal measurements are described. Time synchronization, modern Ethernet-based protocols, sequence of events records, oscillography (COMTRADE), monitoring and alarming for protection functions, and other previously standard features in medium- and high-voltage protective relays are available in modern low-voltage MCC protective relays. Increased safety in the form of advanced protection elements and arc-flash detection are now also available. This paper focuses on the philosophy of a comprehensive low-voltage MCC protection and control system.