On the Burness-Giudici Conjecture

Let $G$ be a permutation group on a set $\Omega$. A subset of $\Omega$ is a base for $G$ if its pointwise stabilizer in $G$ is trivial. By $b(G)$ we denote the size of the smallest base of $G$. Every permutation group with $b(G)=2$ contains some regular suborbits. It is conjectured by Burness-Giudici in [4] that every primitive permutation group $G$ with $b(G)=2$ has the property that if $\alpha^g\not\in \Gamma$ then $\Gamma \cap \Gamma^g\neq \emptyset$, where $\Gamma$ is the union of all regular suborbits of $G$ relative to $\alpha$. An affirmative answer of the conjecture has been shown for many sporadic simple groups and some alternative groups in [4], but it is still open for simple groups of Lie-type. The first candidate of infinite family of simple groups of Lie-type we should work on might be $PSL(2,q)$, where $q\geq 5$. In this manuscript, we show the correctness of the conjecture for all the primitive groups with socle $PSL(2,q)$, see Theorem $1.3$

Tactical Trajectory Planning for Stealth Unmanned Aerial Vehicle to Win the Radar Game

In this paper, problem of planning tactical trajectory for stealth unmanned aerial vehicle (UAV) to win the radar game is studied. Three principles of how to win the radar game are presented, and their utilizations for stealth UAV to evade radar tracking are analysed. The problem is formulated by integrating the model of stealth UAV, the constraints of radar detecting and the multi-objectives of the game. The pseudospectral multi-phase optimal control based trajectory planning algorithm is developed to solve the formulated problem. Pseudospectral method is employed to seek the optimal solution with satisfying convergence speed. The results of experiments show that the proposed method is feasible and effective. By following the planned trajectory with several times of switches between exposure and stealth, stealth UAV could win the radar game triumphantly.Defence Science Journal, 2012, 62(6), pp.375-381, DOI:http://dx.doi.org/10.14429/dsj.62.268

A polynomial time optimal algorithm for robot-human search under uncertainty

This paper studies a search problem involving a robot that is searching for a certain item in an uncertain environment (e.g., searching minerals on Moon) that allows only limited interaction with humans. The uncertainty of the environment comes from the rewards of undiscovered items and the availability of costly human help. The goal of the robot is to maximize the reward of the items found while minimising the search costs. We show that this search problem is polynomially solvable with a novel integration of the human help, which has not been studied in the literature before. Furthermore, we empirically evaluate our solution with simulations and show that it significantly outperforms several benchmark approaches

Adonis: Practical and Efficient Control Flow Recovery through OS-Level Traces

Control flow recovery is critical to promise the software quality, especially for large-scale software in production environment. However, the efficiency of most current control flow recovery techniques is compromised due to their runtime overheads along with deployment and development costs. To tackle this problem, we propose a novel solution, Adonis, which harnesses OS-level traces, such as dynamic library calls and system call traces, to efficiently and safely recover control flows in practice. Adonis operates in two steps: it first identifies the call-sites of trace entries, then it executes a pair-wise symbolic execution to recover valid execution paths. This technique has several advantages. First, Adonis does not require the insertion of any probes into existing applications, thereby minimizing runtime cost. Second, given that OS-level traces are hardware-independent, Adonis can be implemented across various hardware configurations without the need for hardware-specific engineering efforts, thus reducing deployment cost. Third, as Adonis is fully automated and does not depend on manually created logs, it circumvents additional development cost. We conducted an evaluation of Adonis on representative desktop applications and real-world IoT applications. Adonis can faithfully recover the control flow with 86.8% recall and 81.7% precision. Compared to the state-of-the-art log-based approach, Adonis can not only cover all the execution paths recovered, but also recover 74.9% of statements that cannot be covered. In addition, the runtime cost of Adonis is 18.3× lower than the instrument-based approach; the analysis time and storage cost (indicative of the deployment cost) of Adonis is 50× smaller and 443× smaller than the hardware-based approach, respectively. To facilitate future replication and extension of this work, we have made the code and data publicly available

Passively Q-switched erbium-doped fiber laser using evanescent field interaction with gold-nanosphere based saturable absorber

We demonstrate an all-fiber passively Q-switched erbiumdoped fiber laser (EDFL) using a gold-nanosphere (GNS) based saturable absorber (SA) with evanescent field interaction. Using the interaction of evanescent field for fabricating SAs, long nonlinear interaction length of evanescent wave and GNSs can be achieved. The GNSs are synthesized from mixing solution of chloroauricacid (HAuCl4) and sodium citrate by the heating effects of the microfiber's evanescent field radiation. The proposed passively Q-switched EDFL could give output pulses at 1562 nm with pulse width of 1.78 μs, a repetition rate of 58.1 kHz, a pulse energy of 133 nJ and a output power of 7.7 mWwhen pumped by a 980 nm laser diode of 237 mW

Describe, Explain, Plan and Select: Interactive Planning with Large Language Models Enables Open-World Multi-Task Agents

We investigate the challenge of task planning for multi-task embodied agents in open-world environments. Two main difficulties are identified: 1) executing plans in an open-world environment (e.g., Minecraft) necessitates accurate and multi-step reasoning due to the long-term nature of tasks, and 2) as vanilla planners do not consider how easy the current agent can achieve a given sub-task when ordering parallel sub-goals within a complicated plan, the resulting plan could be inefficient or even infeasible. To this end, we propose "$\underline{D}$escribe, $\underline{E}$xplain, $\underline{P}$lan and $\underline{S}$elect" ($\textbf{DEPS}$), an interactive planning approach based on Large Language Models (LLMs). DEPS facilitates better error correction on initial LLM-generated $\textit{plan}$ by integrating $\textit{description}$ of the plan execution process and providing self-$\textit{explanation}$ of feedback when encountering failures during the extended planning phases. Furthermore, it includes a goal $\textit{selector}$, which is a trainable module that ranks parallel candidate sub-goals based on the estimated steps of completion, consequently refining the initial plan. Our experiments mark the milestone of the first zero-shot multi-task agent that can robustly accomplish 70+ Minecraft tasks and nearly double the overall performances. Further testing reveals our method's general effectiveness in popularly adopted non-open-ended domains as well (i.e., ALFWorld and tabletop manipulation). The ablation and exploratory studies detail how our design beats the counterparts and provide a promising update on the $\texttt{ObtainDiamond}$ grand challenge with our approach. The code is released at https://github.com/CraftJarvis/MC-Planner.Comment: NeurIPS 202

An Integrated Multicriterion hp

Pseudospectral methods (PMs) for solving general optimal control problems (OCPs) attract an increasing amount of research and application in engineering. It is challenging to improve the convergence rate, the solution accuracy, and the applicability of PMs, especially for nonsmooth problems. Existing hp-adaptive PMs consider only one heuristic criterion, which cannot produce satisfactory performance in many cases. In this paper, we propose a novel method which integrates multicriterion to hp-adaptive PM, in order to further improve the performance. For this purpose, we first devise an OCP solving framework of hp-adaptive PM. We then design a multicriterion hp-adaptive strategy which introduces prior knowledge, intermediate error and curvature as useful criterions for adaptive refinement. We last present an iterative procedure for solving general nonlinear OCPs. Results from two examples show that our method significantly outperforms competitors on the convergence rate and the solution accuracy. The method is practical and effective for direct solving of various OCPs in a broad range of engineering

Simulación de la demanda de calor y energía de un edifico y abastecimiento por medio de diferentes tipos de generadores y acumuladores

El trabajo realizado en el presente estudio consta fundamentalmente de 4 partes. La primera de ellas consiste en la descripción y modelización de un edificio particular, situado en la localidad de Soller (Mallorca). Se pretende tener un conocimiento de los materiales, distribución y propiedades de los cerramientos a fin de poder establecer correctamente los balances térmicos entre el interior y el exterior del edificio. La segunda parte del trabajo consiste en el cálculo de las necesidades de energía del edificio para abastecerlo completamente de calefacción, aire acondicionado, suministro eléctrico y agua caliente sanitaria (en adelante, ACS), y de acuerdo con los parámetros establecidos en la normativa española respecto a las condiciones de diseño interior de los edificios. Para ello se han tenido en cuenta los datos climáticos de la localidad durante cada hora del año, obtenidos a partir del programa informático METEONORM versión 6. Se ha aplicado el método de las diferencias finitas según el esquema de Crank-Nicholson a toda la envolvente térmica del edificio, con la ayuda del programa de cálculo y simulación MATLAB 2007. Se incluyen, anexos a este trabajo, el código implementado y un manual explicativo. Como resultado de esta parte se ha obtenido la evolución de la temperatura interior del edificio, el consumo eléctrico y el consumo energético para el ACS, la calefacción y el aire acondicionado, a lo largo de todo el año. En la tercera parte del proyecto se plantean y simulan dos posibles instalaciones, basadas en tecnologías solares, capaces de abastecer el edificio. La primera de ellas, recogida en lo que en adelante llamaremos “caso 1”, consiste en la instalación en el tejado del edificio de un colector solar plano para suministrar ACS. El resto de superficie disponible del tejado se utiliza para instalar un campo de paneles fotovoltaicos que proporcionan el suministro eléctrico para alimentar una bomba de calor reversible y para el consumo normal del edificio. La bomba de calor climatiza el edificio todo el año. La segunda instalación propuesta, recogida en el “caso 2”, consiste en la instalación en el tejado de un campo de colectores solares planos que proporcionan ACS todo el año y agua caliente para calefacción en invierno. En verano se realiza la climatización del edificio mediante una máquina de refrigeración solar por adsorción, alimentada mediante el agua caliente procedente de los colectores. Tanto en el caso 1 como en el caso 2, se contempla el uso de electricidad de la red general como fuente auxiliar para abastecer al edificio de energía en los casos en que los recursos solares sean escasos. La última parte del proyecto consiste en la comparación de las instalaciones de los casos 1 y 2, en base a criterios energéticos, de eficiencia y económicos, y apuntando posibles mejoras que permitan una mejor consecución de los objetivos propuestos

Fatigue Analysis of Hybrid Wind Turbine Towers

Fatigue analysis of hybrid wind turbine towers between cut in wind speed and cut out wind speed are demonstrated. Nominal stress method and miner liner accumulated damage theory are adopted. Through the analysis of the results, comparative research on effect of parameters of aspect ratio, height ratio and unequal legs for fatigue properties of hybrid wind turbine towers. The results show that the optimal range of aspect ratio of hybrid towers is 1/6~1/4, the optimal range of height ratio of hybrid towers is 0.60~0.67. Fatigue analysis of hybrid towers, should select the right junction of leeward towers and the S-N curve from EN 1993-1-9.The effect of unequal legs for fatigue properties of hybrid towers can be neglected