bluuebunny/crossref_metadata_2025_split huggingface dataset:
Improve medical IoT based on DFC algorithm and machine learning
Authors: Shao Wei , Ding Yihang , Wen Jinghao , Zhu Pengxu , Luo Meng , Ou Lisong 
Published: December 2022

Abstract
With the rapid development of IoT technology, medical IoT is one of the current research focuses and hotspots. In the practical application of medical IoT, achieving accurate localization and effective data fusion is conducive to improving the operational efficiency of medical IoT and reducing the power consumption of the network. Therefore, this paper uses SVM and KNN algorithms to improve the localization accuracy, and proposes an event-driven cluster-tree data fusion algorithm DFC based on the special characteristics of data in medical IoT.The DFC algorithm uses a combined cluster-tree topology to dynamically partition clusters and decide the decision range of the corresponding cluster based on the severity of the event, and then constructs the data fusion within the cluster from the current cluster head The data propagation along the fusion tree can improve the accuracy of the data and extend the lifetime of the network. In this paper, we analyze the fusion delay problem in the network and propose a minimum fusion delay method by calculating the fusion waiting time of nodes. Experiments demonstrate that the DFC algorithm has better accuracy and fusion through machine learning, an improvement of the medical IoT. This is of great importance in real-life applications
Accurate Management of Public Services Based on Big Data
Authors: Xu Jiamuzi 
Published: December 2022

Abstract
With the support of national policies, information technology and resource aggregation are increasing day by day. Large-scale data mining is a large scientific and practical area of "digital gold". This is not only a challenge of the times, but also requires vigorous development of public services. Therefore, this paper was driven by big data to analyze the current situation of public services, and then used the fuzzy evaluation method to analyze the precise management. Finally, the public service management was optimized, and the realization path of the accurate management of the whole process of public service driven by big data was designed. Through fuzzy comprehensive evaluation, it was known that the model value and information entropy of public services were constantly increasing; the average value of the model value of precise management of public services was about 4.35, and the average value of information entropy was about 0.98. Moreover, the management efficiency and comprehensive efficiency of precision management of social public welfare activities based on big data were better than that of traditional precision management of public services; the management benefits were 7% higher than the traditional ones, and the overall efficiency was 9% higher than the traditional ones.
Generalization of Beckmann’s Transformation for Traffic Assignment Models With Asymmetric Cost Functions
Authors: Marechal Matthieu , Grange Louis 
Published: December 2022

Abstract
An optimization model is developed to solve the deterministic traffic assignment problem under congested transport networks with cost functions that have an asymmetric Jacobian. The proposed formulation is a generalization of Beckmann’s transformation that can incorporate network links with multivariate vector cost functions to capture the asymmetric interactions between the flows and costs of the different links. The objective function is built around a line integral that generalizes the simple definite integral in Beckmann’s transformation and is parameterised to ensure the solution of the new problem satisfies Wardrop’s first principle of network equilibrium. It is shown that this method is equivalent to the variational inequality approach.
Research on Autonomous Behavior Decision of UAV Cluster with Limited Communication Bandwidth
Authors: Ting-Ting Zhang , Jun-Yun Jin , Liu Yun-Ping , Yun Lin , Ai-Guo Song , Yu-Shi Lan 
Published: December 2022

Abstract
Communication is the basis of UAV(Unmanned Aerial Vehicle,UAV) cluster cooperative decision control. In the battlefield environment with scarce communication resources, it is of great significance to realize the efficient communication of UAV cluster. At present, Multi-Agent Reinforcement learning method is widely used in the research of Autonomous Cooperation Strategy of UAV cluster, but most methods do not consider the impact of limited communication resources. Based on the partial observable Markov decision process, a communication based autonomous behavior decision model of UAV cluster is proposed; Based on the research hypothesis and information theory, a reward strategy based on bandwidth utilization is designed. The reward value under this strategy is adjusted with the change of available bandwidth, which can guide the UAV whether to send messages at each step in real time; In the process of model training and execution, the long-term and short-term memory network is used as the memory unit to ensure the effectiveness of UAV cooperative decision-making. The effectiveness of the proposed method is verified by air confrontation simulation experiment, which provides a method reference for autonomous cooperative decision-making of UAV cluster in bandwidth limited combat scenario.
Volatile Kernel Rootkit Hidden Process Detection in Cloud Computing
Authors: S Suresh kumar , SudalaiMuthu T 
Published: December 2022

Abstract
Malware assaults on kernel rootkits have grown increasingly nuanced and difficult to detect, giving them control over the functionality of the kernel. It can be difficult to detect the presence of these kernel rootkits within the victim system since they use stolen techniques to conceal the system tasks, kernel modules, and various management structures. The majority of the current rootkit detection methods are system-specific and supported by traditional sources, making them ineffectual for new, obscure, and undiscovered rootkits. In order to identify such rootkits by their distinctive hidden processes, this study suggests a VKRHPDV system. This detection method uses a cross-view, clean-boot-based approach and defines a process-watching framework that continuously keeps track of all running processes and can identify any rumoured or unidentified rootkit with the least amount of performance overhead. The linguistics gap is filled by VKRHPDV, which monitors the kernel while extremely discretely intercepting call events of the tainted package to reconstruct a semantic-level method information structure. The results of an in-depth performance analysis performed on sixty-four rootkit datasets in a cloud environment for each UNIX and Windows kernel show that VKRHPDV can detect process hiding habits in all datasets in the shortest amount of time.
Studies on Ablative Performance of silicone low density ablative material
Authors: Maddu Sujatha , Srivast Tanu , Katari Naresh Kumar , Merugu Karuna , Gundla Rambabu , S Krishna Mohan 
Published: December 2022

Abstract

In the present studies silicon based low density ablative material has been studied for its ablative performance to protect flight hardware from temperature raised due to aerodynamic forces for longer duration. Ablative properties are estimated by oxyacetylene flame test at 100-120 W/m2 heat flux. The time duration for the flame test is taken 200 sec. The material shows low mass and linear ablation rate with high ablative effectiveness. The degradation kinetics of silicon ablator is studied by Thermo Gravimetric Analysis (TGA) method. Non-isothermal TGA is performed in the temperature range of 30 °C to 900 °C at various heating rates viz. 5, 10, 15 and 20 oC/ min. Knowledge of the kinetic parameters of thermal decomposition is used to predict degradation kinetics of the material at high heating rates which the ablator faces during aerospace applications. During ablation the silicone ablative material consist of a virgin zone, reaction zone and char zone. These are explained by kinetic parameters which are determined with help of free software called Kinetic Calculation.
Avapritinib is Effective for Treatment of Minimal Residual Disease in Acute Myeloid Leukemia with t (8;21) and KIT mutation Failing to Immunotherapy After Allogeneic Hematopoietic Stem Cell Transplantation
Authors: Wang Yu , Kong Jun , Zheng Feng-Mei , zhidong wang , Zhang Yuan-Yuan , Yifei Cheng , fu haixia , Lv Meng , Chen Huan , Xu Lan-Ping , Zhang Xiao-hui , Huang Xiao-Jun 
Published: December 2022

Abstract
In patients with t(8;21) acute myeloid leukemia (AML) with recurrent minimal residual disease (MRD) after allogeneic hematopoietic stem cell transplantation (allo-HSCT), pre-emptive interferon-α therapy and donor lymphocyte infusion are noneffective in 30–50% of patients. Avapritinib is a novel tyrosine kinase inhibitor targeting KIT mutations. We report about 20 patients with t(8;21) AML and KIT mutations treated with avapritinib after allo-HSCT with MRD and most failing to respond to immunotherapy. Reduction of RUNX1-RUNX1T1 transcripts after 1 month of treatment was ≥ 1 log in 12 patients (60%), which became negative in 4 patients (20%). In 13 patients who received avapritinib for ≥ 3 months, the reduction was ≥ 1 log in all patients, which became negative in 7 patients (53.8%). The median follow-up time was 5.5 (2.0–10.0) months from avapritinib initiation to the last follow-up. Three patients underwent hematologic relapse and survived. Among all 20 patients, RUNX1-RUNX1T1 transcripts turned negative in 9 patients (45%). The efficacy did not differ significantly between D816 and non-D816 KIT mutation groups. The main adverse effect was hematological toxicity, which could generally be tolerated. In summary, avapritinib was effective for MRD treatment in patients with t(8;21) AML with KIT mutations failing to respond to immunotherapy after allo-HSCT.
Seismic response characteristics and whiplash effect mechanism of continuous rigid-frame bridges subjected to near-fault ground motions
Authors: Li Jun , Xu Long-He 
Published: December 2022

Abstract
Continuous rigid-frame bridge (CRFB) is widely constructed in western China with high seismicity areas. To investigate the seismic response characteristics and whiplash effect mechanism of CRFBs under near-fault ground motions, this study selects a long-span CRFB with high piers as the prototype bridge and develops the nonlinear finite element model based on OpenSees. In this work, three groups of near-fault ground motions having forward directivity pulse, fling-step pulse and non-pulse are selected as seismic inputs. These records are intercepted using significant duration index and scaled to 0.2 g, 0.4 g, and 0.64 g, representing basic ground motions, frequent ground motions and rare ground motions, respectively. The study analyzes the seismic response characteristics of CRFBs and discusses the effects of bearing constraints, ground motion components and vertical excitations on the seismic responses. The numerical results show that the longitudinal vibration, transverse whiplash effect and vertical uplift behavior of main girder are main deformation characteristics of CRFBs. Compared with non-pulse earthquakes, the structural displacements, lateral drift angles, bearing deformations, internal forces and pounding effects all significantly increase under pulse-like earthquakes. There are spatial torsional effects in mid-span girder and main piers and pounding effects between girder ends and transition pier top. The perfectly-free and fixed bearings in transverse direction are not recommended for the seismic design of CRFBs. An optimal stiffness ratio in friction pendulum systems may exist that can minimize bending degree of the main girder. Furthermore, the side-span girder under pure longitudinal excitations can uplift that is closely related to the pier-girder consolidation form and rotation of the main piers. The main piers may be tensioned under strong vertical excitations, which is an uncommon problem worthy of attentions.
Estimation of uncertainty from duplicate measurements: new quantification procedure in the case of concentration-dependent precision
Authors: Synek Václav , Kříženecká Sylvie 
Published: December 2022

Abstract
In many analytical measurements, the analyte concentration in the test samples varies over a wide range. In such cases, the standard deviation (SD) quantifying the imprecision of the measurement should be expressed as a function of the analyte concentration, c: \({s}_{c}=\sqrt{{\text{s}}_{0}^{2}+{ s}_{r}^{2}{c}^{2}}\), where s0 represents a nonzero SD at zero concentration and sr represents a near-constant relative SD at very high concentrations. These parameters can be estimated from the differences in the values measured in duplicate on test samples; datasets with a high number of duplicate results can be obtained within the internal quality control. The procedures recommended for parameter estimation published so far are based on statistically demanding weighted regression. This article proposes a statistically less demanding procedure that estimates s0 and sr separately by processing the differences between the duplicates from areas with lower and higher concentration levels, where the terms \({ s}_{r}^{2}{c}^{2}\) and \({\text{s}}_{0}^{2}\)do not represent the dominant components of \({ s}_{c}^{2}\), respectively. The parameter estimates are calculated by using the root mean square of the differences, with an addition correction for the interfering effect of second, less significant term. This procedure was verified on Monte Carlo simulated datasets. The variability of the parameter estimates obtained by this simpler procedure was similar to or slightly worse than that of the estimates obtained by the best but statistically demanding regression procedure, but better than the variability of the estimates obtained by the other tested regression procedures.
Partition of Omega facility in two configurations of 24 and 36 laser beams to improve implosion performance
Authors: Temporal Mauro , Piriz A. R. , Canaud B. , Ramis R. 
Published: December 2022

Abstract
The OMEGA installation is separated into two independent sub-configurations with 24 and 36 laser beams each one minimising direct drive illumination non-uniformity. Two different laser focal spots associated one to each configuration are proposed to apply the zooming technique in order to increase the laser-target coupling efficiency. This approach is used by 1D hydrodynamics simulations of the implosion of a direct-drive capsule characterised by a relatively large aspect ratio A = 7 and an optimized laser pulse shape delivering a maximum of 30 TW and 30 kJ. It is shown that zooming allows for a 1D-thermonuclear energy gain greater than one while without zooming the thermonuclear gain remains largely below one.
Determination of some heavy metals concentrations in urban soils using pollution indices and multivariate analysis -A case study of Tripoli city, Libya
Authors: Salem Mansour , Alzarqah Ali , Alnaas Afiyah , Sharif Omar , Nassar Yasser , Assad Mamdouh El Haj 
Published: December 2022

Abstract
Forty-six samples of urban topsoil were collected from Tripoli at a depth of 0–15 cm to determine the concentration of nine heavy metals, including Cd, Pb, Zn, Cu, Ni, Co, Fe, Mn, and Cr. The study aimed to quantify and identify their likely sources of environmental contamination indices and assess their ecological risk to humans. The mean concentrations of these metals were 3.943, 38.317, 170.941, 29.669, 19.699, 30.371, 27444.515, 235.812, and 195.92 mg.kg-1, respectively. These values are higher than the virgin soil background values and permissible limits set forth by WHO. The pollution index (PI) varied from 1.152 for Ni and 2.518 for Cr. The geoaccumulation index (Igeo) averaged 0.824 for Mn and 1.679 for Cr, the contamination factor (CF) averaged 1.28 for Mn and 2.686 for Cr, and the enrichment factor (EF) averaged 0.968 for Mn and 1.893 for Cr, respectively. Pollution indicators such as the Pollution Load Index (PLI), Contamination Degree (Cdeg), and Potential Ecological Risk (RI) suggest that the research region is moderately contaminated, with values ranging from 1.233–1.923, 12.099–18.469, and 47.241–145.067, respectively. Principal component analysis (PCA), correlation coefficient, and hierarchical cluster analysis (HCA) had used to identify the studied metals' possible sources. The results revealed that three sources of heavy metals were determined as indicated by a strong positive correlation between Cd, Pb, Cu, Cr, and Co, which suggested that the sources of these metals are mainly anthropogenic, such as agricultural practices, industrial activities, and vehicle emissions. While the possible sources of Mn, Fe, and Ni mainly originate from natural sources (parent rocks). The heavy metals' potential ecological risk was determined to be moderate. The RI ranged from 65 to 130.
Temporal word embedding with predictive capability
Authors: Farhan Ahnaf , Barranco Roberto Camacho , Akbar Monika , Hossain M. Shahriar 
Published: December 2022

Abstract
Semantics in natural language processing is largely dependent on contextual relationships between words and entities in a document collection. The context of a word may evolve. For example, the word ``apple'' currently has two contexts -- a fruit and a technology company. The changes in the context of words or entities in text data such as scientific publications, and news articles can help us understand the evolution of innovation or events of interest. In this work, we present a new diffusion-based temporal word embedding model that can capture short and long-term changes in the semantics of entities in different domains. Our model captures how the context of each entity shifts over time. Existing temporal word embeddings capture semantic evolution at a discrete/granular level, aiming to study how a language developed over a long period. Unlike existing temporal embedding methods, our approach provides temporally smooth embeddings, facilitating prediction and trend analysis better than those of existing models. Extensive evaluations demonstrate that our proposed temporal embedding model performs better in sense-making and predicting relationships between entities in the future compared to other existing models.
Design, construction and characterisation of a diode-pumped, three-element, 1-GHz Kerr-lens-modelocked Ti:sapphire oscillator
Authors: Ostapenko Hanna , Mitchell Toby , Castro-Marin Pablo , Reid Derryck T. 
Published: December 2022

Abstract
We report a 1-GHz repetition rate Ti:sapphire laser pumped with a single green pump diode, producing 111-fs pulses and exhibiting self-starting Kerr-lens modelocking at pump powers above 850 mW. At 1.1W of pump power, the average output of the laser is over 116 mW, and the slope efficiency of the laser is measured to be 13%. The optimisation of the cavity dispersion has demonstrated a possible shortening of the pulses up to 87 fs with an average power of 108 mW. The relative intensity noise of the laser was measured to be 0.06%, and the phase error of the repetition rate after locking to a reference has been measured to be 1.7 mrad, corresponding to timing jitter of 270 fs.
Determining equations governing multibody dynamic systems through joint kinematics and kinematic chain effects in closed-form mechanisms
Authors: Mohammadi Yousef , Fatouraee Nasser , Bostanshirin Mehdi 
Published: December 2022

Abstract

In this study, the governing equations of dynamic systems were derived using a novel method that integrated the kinematic properties of joints and the complex kinematic chains of multibody systems into a set of governing equations. The governing equations of multibody systems were then transformed into ODE using the calculus of matrix-valued functions. This algorithm can efficiently obtain recursive differential equations of motion for multibody systems. Consequently, the computational cost of the simulation was reduced successfully. Andrew’s squeezing and carpet scraping mechanisms were utilized with kinematic constraints to validate the proposed method. Results indicated that the proposed method was 4.2 and 5.4 times faster than the other methods based on algebraic differential equations in Andrew’s squeezing and carpet scraping mechanism, respectively.
Implementation Of Two-Fold DNA Cryptography Based On Amino Acid Table In Cloud Computing And Using Socket Programming
Authors: Kumar Abhay , singh Manmohan 
Published: December 2022

Abstract

Worldwide, organizations are migrating their IT infrastructure to public clouds. One of the biggest challenges during this transition is the implementation of appropriate security techniques to withstand cyber attacks. Unfortunately, this process is still ambiguous for many organizations and data are exposed to different threats and vulnerabilities during this migration.To address this, there are several approaches applied worldwide to strengthen security of the stored data on cloud computing. The two-fold DNA Cryptography is one such data security techniques.The existing technique focuses only on the ASCII character set, ignoring the non-English user of the cloud computing. Thus, proposing two-fold DNA Cryptography using the Unicode characters so that it can be used for non-English users also.
Electronic structural and lattice thermodynamic properties of MAlO2 and M5AlO4 (M=Li, Na, K) sorbents for CO2 capture applications
Authors: Duan Yuhua 
Published: December 2022

Abstract
The electronic properties and thermal stabilities of MAlO2 and M5AlO4 (M=Li, Na, K) are investigated by the density functional theory and lattice phonon dynamics. Based on the calculated electronic and lattice thermodynamic properties, their abilities to capture CO2 as solid sorbents are analyzed. The calculated electronic structural properties of MAlO2 and M5AlO4 indicate that all of these alkali aluminates are semiconductors with bandgap range of 2.4~6.4 eV. The 1st valence bands of these alkali aluminates are located in 0~-6 eV under Fermi levels and are mainly contributed by p orbitals of O, s and p orbitals of Al and M. The phonon vibrational frequencies of M5AlO4 spread at lower frequency range compared to their MAlO2 phases. With increasing temperature, the calculated phonon free energies of M5AlO4 decrease faster than their corresponding MAlO2 while their entropies have opposite trends. The reaction 2MAlO2 + CO2 = M2CO3 + Al2O3 has higher reaction heat and Gibbs free energy change than those of corresponding reaction 2/5M5AlO4 + CO2 = M2CO3 + 1/5Al2O3, which shows the former reaction possesses lower turnover temperature. Among these alkali aluminates studied, the β-NaAlO2, lt-KAlO2, and γ-LiAlO2 are better candidates that could be applied for CO2 capture technologies.