From a Chinese kindergarten: A personal journey

How do Chinese kindergarten teachers understand their teaching practices? How are these influenced by cultural, political and economic forces? What do their classrooms look like from the perspective of a Chinese New Zealander

Swing Leg Motion Strategy for Heavy-load Legged Robot Based on Force Sensing

The heavy-load legged robot has strong load carrying capacity and can adapt to various unstructured terrains. But the large weight results in higher requirements for motion stability and environmental perception ability. In order to utilize force sensing information to improve its motion performance, in this paper, we propose a finite state machine model for the swing leg in the static gait by imitating the movement of the elephant. Based on the presence or absence of additional terrain information, different trajectory planning strategies are provided for the swing leg to enhance the success rate of stepping and save energy. The experimental results on a novel quadruped robot show that our method has strong robustness and can enable heavy-load legged robots to pass through various complex terrains autonomously and smoothly

Erkennung und Vermeidung von Fehlverhalten in fahrzeugbasierten DTNs

Delay- and Disruption-Tolerant Networks (DTNs) are a suitable technology for many applications when the network suffers from intermittent connections and significant delays. In current vehicular networks, due to the high mobility of vehicles, the connectivity in vehicular networks can be highly unstable, links may change or break soon after they have been established and the network topology varies significantly depending on time and location. When the density of networked vehicles is low, connectivity is intermittent and with only a few transmission opportunities. This makes forwarding packets very difficult. For the next years, until a high penetration of networked vehicles is realized, delay-tolerant methods are a necessity in vehicular networks, leading to Vehicular DTNs (VDTNs). By implementing a store-carry-forward paradigm, VDTNs can make sure that even under difficult conditions, the network can be used by applications. However, we cannot assume that all vehicles are altruistic in VDTNs. Attackers can penetrate the communication systems of vehicles trying their best to destroy the network. Especially if multiple attackers collude to disrupt the network, the characteristics of VDTNs, without continuous connectivity, make most traditional strategies of detecting attackers infeasible. Additionally, selfish nodes may be reluctant to cooperate considering their profit, and due to hard- or software errors some vehicles cannot send or forward data. Hence, efficient mechanisms to detect malicious nodes in VDTNs are imperative. In this thesis, two classes of Misbehavior Detection Systems (MDSs) are proposed to defend VDTNs against malicious nodes. Both MDSs use encounter records (ERs) as proof to document nodes' behavior during previous contacts. By collecting and securely exchanging ERs, depending on different strategies in different classes of MDSs, a reputation system is built in order to punish bad behavior while encouraging cooperative behavior in the network. With independently operating nodes and asynchronous exchange of observations through ERs, both systems are very well suited for VDTNs, where there will be no continuous, ubiquitous network in the foreseeable future. By evaluating our methods through extensive simulations using different DTN routing protocols and different realistic scenarios, we find that both MDS classes are able to efficiently protect the system with low overhead and prevent malicious nodes from further disrupting the network.In Netzwerken mit zeitweisen Unterbrechungen oder langen Verzögerungen sind Delay- and Disruption-Tolerant Networks (DTNs) eine geeignete Technologie für viele Anwendungen. Die Konnektivität in Fahrzeugnetzen ist bedingt durch die hohe Mobilität und die geringe Verbreitung von netzwerkfähigen Fahrzeugen oft instabil. Bis zur flächendeckenden Verbreitung von netzwerkfähigen Fahrzeugen ist es daher zwingend notwendig auf Methoden des Delay Tolerant Networking zurückzugreifen um die bestmögliche Kommunikation zu gewährleisten. In diesem Zusammenhang wird von Vehicular Delay Tolerant Networks (VDTNs) gesprochen. Durch das Store-Carry-Forward-Prinzip kann ein VDTN Kommunikation für Anwendungen ermöglichen. Allerdings ist davon auszugehen, dass sich nicht alle Fahrzeuge altruistisch verhalten: Angreifer können Fahrzeuge übernehmen und das Netzwerk attackieren oder Knoten sind aus egoistischen Motiven oder auf Grund von Defekten unkooperativ. Verfahren, die Fehlverhalten in stabilen Netzen durch direkte Beobachtung erkennen können, sind in VDTNs nicht anwendbar. Daher sind Methoden, die Fehlverhalten in VDTNs nachweisen können, zwingend erforderlich. In dieser Arbeit werden zwei Klassen von Misbehavior Detection Systems (MDSs) vorgestellt. Beide Systeme basieren auf Encounter Records (ERs): Nach einem Kontakt tauschen zwei Knoten kryptografisch signierte Meta-Informationen zu den erfolgten Datentransfers aus. Diese ERs dienen bei darauffolgenden Kontakten mit anderen Netzwerkteilnehmern als vertrauenswürdiger Nachweis für das Verhalten eines Knotens in der Vergangenheit. Basierend auf der Auswertung gesammelter ERs wird ein Reputationssystem entwickelt, das kooperatives Verhalten belohnt und unkooperatives Verhalten bestraft. Dauerhaft unkooperative Knoten werden aus dem Netzwerk ausgeschlossen. Durch den asynchronen Austausch von Informationen kann jeder Knoten das Verhalten seiner Nachbarn selbstständig und unabhängig evaluieren. Dadurch sind die vorgestellten MDS-Varianten sehr gut für den Einsatz in einem VDTN geeignet. Durch umfangreiche Evaluationen wird gezeigt, dass sich die entwickelten MDS-Verfahren für verschiedene Routingprotokolle und in unterschiedlichen Szenarien anwenden lassen. In allen Fällen ist das MDS in der Lage das System mit geringem Overhead gegen Angreifer zu verteidigen und eine hohe Servicequalität im Netzwerk zu gewährleisten

Fine-Grained Access Control Systems Suitable for Resource-Constrained Users in Cloud Computing

For the sake of practicability of cloud computing, fine-grained data access is frequently required in the sense that users with different attributes should be granted different levels of access privileges. However, most of existing access control solutions are not suitable for resource-constrained users because of large computation costs, which linearly increase with the complexity of access policies. In this paper, we present an access control system based on ciphertext-policy attribute-based encryption. The proposed access control system enjoys constant computation cost and is proven secure in the random oracle model under the decision Bilinear Diffie-Hellman Exponent assumption. Our access control system supports AND-gate access policies with multiple values and wildcards, and it can efficiently support direct user revocation. Performance comparisons indicate that the proposed solution is suitable for resource-constrained environment

Genome-wide analysis of CCCH zinc finger family in Arabidopsis and rice

<p>Abstract</p> <p>Background</p> <p>Genes in the CCCH family encode zinc finger proteins containing the motif with three cysteines and one histidine residues. They have been known to play important roles in RNA processing as RNA-binding proteins in animals. To date, few plant CCCH proteins have been studied functionally.</p> <p>Results</p> <p>In this study, a comprehensive computational analysis identified 68 and 67 CCCH family genes in Arabidopsis and rice, respectively. A complete overview of this gene family in Arabidopsis was presented, including the gene structures, phylogeny, protein motifs, and chromosome locations. In addition, a comparative analysis between these genes in Arabidopsis and rice was performed. These results revealed that the CCCH families in Arabidopsis and rice were divided into 11 and 8 subfamilies, respectively. The gene duplication contributed to the expansion of the CCCH gene family in Arabidopsis genome. Expression studies indicated that CCCH proteins exhibit a variety of expression patterns, suggesting diverse functions. Finally, evolutionary analysis showed that one subfamily is higher plant specific. The expression profile indicated that most members of this subfamily are regulated by abiotic or biotic stresses, suggesting that they could have an effective role in stress tolerance.</p> <p>Conclusion</p> <p>Our comparative genomics analysis of CCCH genes and encoded proteins in two model plant species provides the first step towards the functional dissection of this emerging family of potential RNA-binding proteins.</p

First realization of macroscopic Fourier ptychography for hundred-meter distance sub-diffraction imaging

Fourier ptychography (FP) imaging, drawing on the idea of synthetic aperture, has been demonstrated as a potential approach for remote sub-diffraction-limited imaging. Nevertheless, the farthest imaging distance is still limited around 10 m even though there has been a significant improvement in macroscopic FP. The most severely issue in increasing the imaging distance is FoV limitation caused by far-field condition for diffraction. Here, we propose to modify the Fourier far-field condition for rough reflective objects, aiming to overcome the small FoV limitation by using a divergent beam to illuminate objects. A joint optimization of pupil function and target image is utilized to attain the aberration-free image while estimating the pupil function simultaneously. Benefiting from the optimized reconstruction algorithm which effectively expands the camera's effective aperture, we experimentally implement several FP systems suited for imaging distance of 12 m, 90 m, and 170 m with the maximum synthetic aperture of 200 mm. The maximum imaging distance and synthetic aperture are thus improved by more than one order of magnitude of the state-of-the-art works with a fourfold improvement in the resolution. Our findings demonstrate significant potential for advancing the field of macroscopic FP, propelling it into a new stage of development

Two-Stream Retentive Long Short-Term Memory Network for Dense Action Anticipation

Analyzing and understanding human actions in long-range videos has promising applications, such as video surveillance, automatic driving, and efficient human-computer interaction. Most researches focus on short-range videos that predict a single action in an ongoing video or forecast an action several seconds earlier before it occurs. In this work, a novel method is proposed to forecast a series of actions and their durations after observing a partial video. This method extracts features from both frame sequences and label sequences. A retentive memory module is introduced to richly extract features at salient time steps and pivotal channels. Extensive experiments are conducted on the Breakfast data set and 50 Salads data set. Compared to the state-of-the-art methods, the method achieves comparable performance in most cases

Highly Stable Gully-Network Co3O4 Nanowire Arrays as Battery-Type Electrode for Outstanding Supercapacitor Performance

3D transition metal oxides, especially constructed from the interconnected nanowires directly grown on conductive current collectors, are considered to be the most promising electrode material candidates for advanced supercapacitors because 3D network could simultaneously enhance the mechanical and electrochemical performance. The work about design, fabrication, and characterization of 3D gully-network Co3O4 nanowire arrays directly grown on Ni foam using a facile hydrothermal procedure followed by calcination treatment will be introduced. When evaluated as a binder-free battery-type electrode for supercapacitor, a high specific capacity of 582.8 C g−1 at a current density of 1 A g−1, a desirable rate capability with capacity retention about 84.8% at 20 A g−1, and an outstanding cycle performance of 93.1% capacity retention after 25,000 cycles can be achieved. More remarkably, an energy density of 33.8 W h kg−1 at a power density of 224 W kg−1 and wonderful cycling stability with 74% capacity retention after 10,000 cycles can be delivered based on the hybrid-supercapacitor with the as-prepared Co3O4 nanowire arrays as a positive electrode and active carbon as negative electrode. All the unexceptionable supercapacitive behaviors illustrates that our unique 3D gully-network structure Co3O4 nanowire arrays hold a great promise for constructing high-performance energy storage devices