A Novel Automated Guided Vehicle (AGV) Remote Path Planning Based on RLACA Algorithm in 5G Environment

Remote control and monitoring will become the future trend. High-quality automated guided vehicle (AGV) path planning through web pages or clients can reduce network data transmission capacity and server resource occupation. Many Remote path planning algorithms in AGV navigation still have blind search, path redundancy, and long calculation time. This paper proposed an RLACA algorithm based on 5G network environment through remote control of AGV. The distribution of pheromone in each iteration of the ant colony algorithm had an impact on the follow-up. RLACA algorithm changed the transfer rules and pheromone distribution of the ant colony algorithm to improve the efficiency of path search and then modify the path to reduce path redundancy. Considering that there may be unknown obstacles in the virtual environment, the path obtained by the improved ant colony algorithm is used as the training data of reinforcement learning to obtain the Q-table. During the movement, the action of each step is selected by the Q-table until the target point is reached. Through experimental simulation, it can be concluded that the enhanced ant colony algorithm can quickly obtain a reasonable and adequate path in a complex environment and effectively avoid unknown obstacles in the environment.

Search for Gamma-Ray Bursts and Gravitational Wave Electromagnetic Counterparts with High Energy X-ray Telescope of Insight-HXMT

The High Energy X-ray telescope (HE) on-board the Hard X-ray Modulation Telescope (Insight-HXMT) can serve as a wide Field of View (FOV) gamma-ray monitor with high time resolution (μs) and large effective area (up to thousands cm2). We developed a pipeline to search for Gamma-Ray Bursts (GRBs), using the traditional signal-to-noise ratio (SNR) method for blind search and the coherent search method for targeted search. By taking into account the location and spectrum of the burst and the detector response, the targeted coherent search is more powerful to unveil weak and sub-threshold bursts, especially those in temporal coincidence with Gravitational Wave (GW) events. Based on the original method in literature, we further improved the coherent search to filter out false triggers caused by spikes in light curves, which are commonly seen in gamma-ray instruments (e.g. Fermi/GBM, POLAR). We show that our improved targeted coherent search method could eliminate almost all false triggers caused by spikes. Based on the first two years of Insight-HXMT/HE data, our targeted search recovered 40 GRBs, which were detected by either Swift/BAT or Fermi/GBM but too weak to be found in our blind search. With this coherent search pipeline, the GRB detection sensitivity of Insight-HXMT/HE is increased to about 1.5E-08 erg cm−2 (200 keV–3 MeV). We also used this targeted coherent method to search Insight-HXMT/HE data for electromagnetic (EM) counterparts of LIGO-Virgo GW events (including O2 and O3a runs). However, we did not find any significant burst associated with GW events.

pChem: a modification-centric assessment tool for the performance of chemoproteomic probes

We report a modification-centric, blind-search tool termed pChem to provide a streamlined pipeline for unbiased assessing of the performance of chemoproteomic probes. The pipeline starts with an experimental setting for isotopically coding probe-derived modifications that can be automatically recognized, accurately calculated and precisely localized by pChem with neither prior knowledge nor manual inspection. Further, pChem exports on-demand reports by scoring the profiling efficiency, modification-homogeneity and proteome-wide residue selectivity of a tested probe. The performance and robustness of pChem were benchmarked by applying it to various bioorthogonal probes, including 15 activity-based protein profiling (ABPP) probes and 3 metabolic labeling probes. Together, pChem is a user-friendly computational tool for probe developers, even those with no experience in informatics, and aims to facilitate the development and optimization of probes for the ever-growing field of chemoproteomics.

More on Symmetric Brothers of a Node in a Perfect Binary Tree

The paper makes an extensive study on the symmetric brothers of a node in a perfect binary tree. Through proving several new properties of the symmetric brothers of a node, it reveals how the symmetric brothers and the symmetric ancestors distribute on the tree and how they are beneficial for designing a searching algorithm of special purpose. Detail mathematical reasoning and proofs are shown together with concrete examples to demonstrate the mathematical traits. The paper is helpful for designing algorithms in blind search related aspects.

Finding Optimal Algorithm in Artificial Intelligence

Present days many artificial intelligence search algorithms are plays a important to figure out the problem of shortest path finding. The paper presents the detailed study of heuristic search and blind search techniques. The paper focus additional in the direction of blind search strategies such as Breadth First Search, Depth First Search, and Uniform Cost Search and informed explore strategies like A*, and Best First Search. The paper consist of effective of search procedure, their qualities, and demerits, where these algorithms are applicable, also at last comparison of search techniques based on complexity, optimality and completeness are presented in tabular structure.

Looking through the photoionisation wake: Vela X−1 at φorb ≈ 0.75 with Chandra/HETG

Context. The supergiant X-ray binary Vela X−1 represents one of the best astrophysical sources to investigate the wind environment of an O/B star irradiated by an accreting neutron star. Previous studies and hydrodynamic simulations of the system have revealed a clumpy environment and the presence of two wakes: an accretion wake surrounding the compact object and a photoionisation wake trailing it along the orbit. Aims. Our goal is to conduct, for the first time, high-resolution spectroscopy on Chandra/HETGS data at the orbital phase φorb ≈ 0.75, when the line of sight is crossing the photoionisation wake. We aim to conduct plasma diagnostics, inferring the structure and the geometry of the wind. Methods. We performed a blind search employing a Bayesian block algorithm to find discrete spectral features and identify them thanks to the most recent laboratory results or through atomic databases. Plasma properties were inferred both with empirical techniques and with photoionisation models within CLOUDY and SPEX. Results. We detect and identify five narrow radiative recombination continua (Mg XI-XII, Ne IX-X, O VIII) and several emission lines from Fe, S, Si, Mg, Ne, Al, and Na, including four He-like triplets (S XV, Si XIII, Mg XI, and Ne IX). Photoionisation models reproduce the overall spectrum well, except for the near-neutral fluorescence lines of Fe, S, and Si. Conclusions. We conclude that the plasma is mainly photoionised, but more than one component is most likely present, which is consistent with a multi-phase plasma scenario, where denser and colder clumps of matter are embedded in the hot, photoionised wind of the companion star. Simulations with the future X-ray satellites Athena and XRISM show that a few hundred seconds of exposure is sufficient to disentangle the lines of the Fe Kα doublet and the He-like Fe XXV, improving, in general, the determination of the plasma parameters.

Reconstruction of EIT Images Using Fish School Search and Non-Blind Search

Breast cancer is the most common type of cancer among women, affecting 2.1 million women per year worldwide. The best strategy for decreasing disease morbidity and mortality is early detection. Mammography is the most used exam for the diagnosis of breast cancer. However, this technique uses ionizing radiation and causes discomfort to the patient. One promising technique that can be used for early detection of breast cancer is electrical impedance tomography (EIT), which is an imaging technique free of ionizing radiation. Yet, its images still have low resolution, making it difficult to use in breast cancer diagnosis. Thus, the development of new reconstruction methods aiming better resolution is necessary. This work evaluates the performance of the reconstruction algorithm based on fish school search with non-blind search in a 3,190 finite element mesh.