Miracle-dz/UniFAR-FTUs huggingface dataset:
Fixed-Time Actuator Fault Accommodation Applied to Hypersonic Gliding Vehicles

This article presents a fixed-time accommodation strategy of actuator faults for hypersonic gliding vehicles (HGVs). The approach against actuator faults is incorporated by sliding mode control (SMC), bilimit homogeneity, and adaptive techniques, with consideration of practical constraints and model uncertainties. The resulting fault-tolerant attitude control law allows the fault compensation to be completed in a fixed time, in view of the limited time available for recovery of a faulty HGV. The effectiveness of the presented scheme is validated by comparing it to the finite-time fault accommodation scheme. Note to Practitioners—Hypersonic vehicles have drawn significant interests due to the features of super-fast and flexible maneuverability. The use of advanced fault-tolerant control (FTC) techniques is expected to guarantee safety during hypersonic vehicle operation. A challenging problem is how to counteract actuator faults promptly and effectively in the presence of practical constraints and model uncertainties. This article presents a fixed-time FTC algorithm for a hypersonic gliding vehicle.
Motivations for Entrepreneurship of Students in Vietnam

Entrepreneurship, as an engine for economic growth, has drawn much attention in these recent decades worldwide. Numerous studies have examined factors affecting entrepreneurial attitudes and intention in a variety of geographical contexts. However, a few studies use Maslow’s hierarchy of needs theory as a theoretical background to explain the motivations for entrepreneurship. Therefore, this paper fills in the gap in the existing literature of motivations and entrepreneurship. A research model was adapted from related work to test the influence of deficiency-need motivations and growth-need motivation on the entrepreneurial intention of Vietnamese young people. Based on the data from a self-administered survey with 600 Vietnamese students, research results confirmed the positive relationship between entrepreneurial intention and deficiency needs, such as physiological needs, safety needs, and belongingness needs. More interestingly, gender plays a controlling role in the mentioned relationship between motivations and entrepreneurial intention. These findings suggest solutions for policymakers and universities to promote entrepreneurship among young people.
Resource Allocation for Enhancing Offloading Security in NOMA-Enabled MEC Networks

This paper studies an uplink nonorthogonal multiple access (NOMA)-enabled mobile-edge computing network. Specifically, we focus on the practical design of secure offloading without knowing the eavesdropper's channel state information. The aim is to maximize the minimum antieavesdropping ability (AEA) for uplink NOMA users subject to the worst-case secrecy rate requirements and limited transmission power budgets. The formulated problem is nonconvex and difficult to be solved directly. In order to tackle this issue, we propose an efficient iterative algorithm by jointly designing the secrecy rate, local computing bits, and power allocation. The local computing bits and the power allocation are derived in closed form. Numerical results are provided to demonstrate the efficiency of our proposed scheme in terms of AEA.
Low-Cost and Confidentiality-Preserving Multi-Image Compressed Acquisition and Separate Reconstruction for Internet of Multimedia Things

Internet of Multimedia Things (IoMT) is facing how to achieve low-cost compression and acquisition of multimedia big data at the resource-constrained side while preserving the confidentiality of the data. In this article, we propose a low-cost and confidentiality-preserving multi-image compressed acquisition model and provide separate image reconstruction. We group a series of image sets and randomly sample them with compressive sensing in each group. It is noteworthy that we harness the sigmoid sequence to fuse the measurement of each group to alleviate the uneven distribution of the measurement. The experiment verifies that the proposed method avoids the energy information leakage of the original signal from the measurement. Subsequently, we assemble the sampling result of each group into a big master image with a suitable size and further encrypt it. The encrypted master image is transmitted to the cloud for storage and decryption service. The cloud performs a separate reconstruction of images. It provides different image reconstruction services for a fused measurement according to realistic demands, which reduces unnecessary resource consumption. Simulation results show the effectiveness and security of our acquisition scheme, which indicates the proposal can have a potential application to IoMT.
Barriers for Cervical Cancer Screening in Women Living with HIV: A Systematic Review

Cervical cancer is a prominent cancer in U.S. women caused primarily by the human papilloma virus and its incidence and mortality rates have decreased through screening programs. Certain barriers are perceived to be affecting the rates of cervical cancer screening among women living with HIV (WLWH). A systematic review was conducted to identify and summarize these barriers among WLWH nationwide. There is a need to increase awareness and education among WLWH. Public health programs and community-based interventions should target women of low SES and minority status while assessing the barriers among this population to improve cervical cancer screening rates.
Artificial Intelligence Usage Opportunities in Smart City Data Management

2020. ABSTRACT In our current study, we are aiming to explore data management methods in Smart City systems. In data management, Artificial Intelligence can be used as well. Solutions for the usage of Artificial Intelligence and integration into Smart City concept will be researched as well. Main motivation of the study is to draw attention to one of the most important element of Smart Cities, to the flow of data. Our study provides a possible solution for managing data and keep data up-to-date in such systems with the usage of newest technology possibilities. While explaining the solution, we will give all the necessary details about the data flow model between the Artificial Intelligence based system and humans who are using the Smart City. For managing the dataflow, we would like to use Big Data methods extended with other required methods. We are using the term of Big Data as a technology maximizing computation power and algorithmic accuracy to gather, analyse, link, and compare large data sets [1] connecting with Artificial Intelligence
Uplink Resource Allocation for NOMA-Based Hybrid Spectrum Access in 6G-Enabled Cognitive Internet of Things

Sixth generation (6G)-enabled Internet of Things (IoT) needs sufficient spectrum resources to provide spectrum access for massive IoT’s terminals. However, traditional orthogonal multiple access restricts the full use of limited spectrum resources. In this article, a nonorthogonal multiple access (NOMA)-based hybrid spectrum access scheme is proposed for 6G-enabled cognitive IoT (CIoT), where the CIoT may access both the idle and busy spectrum via NOMA regardless of the primary user’s (PU) state. The uplink resource allocations for the CIoT are optimized in the decoding-PU-last and decoding-PU-first schemes, respectively, which seek to maximize the average total transmission rate of CIoT while ensuring the minimum transmission rates for PU and each CIoT node. Then, a clustering NOMA-based CIoT is presented to decrease the interuser interference, where the nodes in each cluster use NOMA to transmit in the allocated subchannel. The simulation results have shown the performance advantages for the NOMA-based hybrid spectrum access and better rate guarantee for the clustering NOMA-based CIoT.
Steady-State Characteristics Study of a Power Split Hydraulic Transmission

The steady-state characteristics of a power split hydraulic transmission were carefully studied in this article. The hydraulic transmission is an alternative power split device for power split hydraulic hybrid drivetrain. It was built from a balanced vane pump, where an output shaft is added and coupled to its floating ring. The internal friction torques due to the relative motion between floating ring and vanes help to drive the output shaft. This improves the mechanical transfer efficiency from input to output shaft, making it more competitive than conventional hydrostatic transmission. The steady-state characteristics of the hydraulic transmission were investigated through both theoretical analysis and experimental studies. Mathematical models of the input and output shaft torques, and the outlet flow rate of the hydraulic transmission were developed. Studies show that the input and output shaft torques are not only dependent on outlet pressure, but also dependent on differential shaft speed. The outlet flow rate is proportional to the differential shaft speed. Finally, a hydro-mechanical transmission based on power split hydraulic transmission was introduced. The characteristics and system application of the hydro-mechanical transmission were given.
MEDIA PEMBELAJARAN BERBASIS TEKNOLOGI SEBAGAI INOVASI PEMBELAJARAN ERA REVOLUSI INDUSTRI 4.0

Era revolusi industri 4.0 merupakan era dimana hampir semua dikendalikan oleh teknologi termasuk dalam dunia pendidikan. Dampak dari era revolusi industri 4.0 dalam dunia pendidikan adalah terbukti semakin banyak media pembelajaran berbasis teknologi yang memudahkan pengajar menyampaikan materi bahkan tidak harus dengan tatap muka. Media pembelajaran berbasis teknologi ini memudahkan proses pembelajaran dari segi efektivitas dan efisiensi. Ada beberapa media pembelajaran berbasis teknologi yang daat digunakan untuk menunjang proses pembelajaran. Media tersebut antara lain Media Audio, Media Visual, dan Media Audio Visual. Media pembelajaran tersebut dapat diimplementasikan dalam semua materi yang ada, selain itu, dapat diimplementasikan di dalam semua jenjang pendidikan, tentunya pengajar dituntut untuk terus berinovasi dengan media pembelajaran yang akan digunakan. Banyak manfaat yang dapat dirasakan dengan adanya media pembelajaran berbasis teknologi, selain dapat menarik minat belajar peserta didik juga dapat meningkatkan hasil prestasi belajar. Oleh karena media pembelajaran berbasis teknologi sangat diharapkan untuk dimanfaatkan di dalam proses pembelajaran.
Determining Changes in the Covariance Structure of Gaussian Processes

Time series data is everywhere, such as stock data in finance market, the sensor data in factories, or the temperature data in everyday life. Time series data have been studied for a long time to analyze and predict the future behavior. While it is tractable when the sequential data behave as stationary, it becomes difficult to model and predict non-stationary time series. Change point detection is a problem that identify non-stationarity which has been investigated for decades in many different names. Change point detection is a challenging problem because defining a change point decisively and objectively is difficult in nature. In this thesis we are trying to define and find a change point using hypothesis tests based on statistics. Specifically we focus on structural breaks in the covariance structure of Gaussian Processes. Further we propose an online change point detection algorithm, called Confirmatory Bayesian Online Change Point Detection, by leveraging the devised hypothesis tests into the conventional Bayesian online change point detection algorithm.
Identification of Novel Genes and Variations Associated to Glycolytic Potential Based on Pig Model

In livestock, glycolytic potential (GP) is a critical indicator for evaluating the meat quality. To date, two major genes protein kinase AMP-activated γ3 non-catalytic subunit gene (PRKAG3) and phosphorylase kinase catalytic subunit gamma 1(PHKG1), and corresponding cause mutations influencing GP have been confirmed in pigs. Therefore, the aim of this study to identify the novel candidate genes and variations related to GP-related traits using a four-hybrid pig model [Pietrain (P)× Duroc (D)] ×[(Landrace) ×(Yorkshire)]. We totally constructed six RNA-seq libraries using longissimus dorsi (LD) muscles, and each library contained two higher GP (H) or two lower GP (L) individuals. A total of 525, 698 and 135 differentially expressed genes (DEGs) were identified between H11 vs L11, H9 vs L9, and H5 vs L5 groups using PossionDis method, respectively. Notably, we found 97 non-redundant DEGs were mapped to GP related QTLs from three paired comparison groups. Moreover, 69 DEGs were identified between H (H11, H9 and H5) and L (L11, L9 and L5) groups using NOIseq method. Additionally, 1,076 potential specific SNPs were figured out between H and L groups, and approximately 40 large Indels with a length ≥ 5bp were identified in each sequencing library. In conclusion, our data provide foundation for further confirming the key genes and the functional mutations affecting GP-related traits in pigs, and also pave the way for elucidating the underling molecular regulatory mechanisms of glycogen metabolism in future study. Moreover, this study might provide valuable information for study on human glycogen storage diseases.
In-memory Learning with Analog Resistive Switching Memory: A Review and Perspective

In this article, we review the existing analog resistive switching memory (RSM) devices and their hardware technologies for in-memory learning, as well as their challenges and prospects. Since the characteristics of the devices are different for in-memory learning and digital memory applications, it is important to have an in-depth understanding across different layers from devices and circuits to architectures and algorithms. First, based on a top-down view from architecture to devices for analog computing, we define the main figures of merit (FoMs) and perform a comprehensive analysis of analog RSM hardware including the basic device characteristics, hardware algorithms, and the corresponding mapping methods for device arrays, as well as the architecture and circuit design considerations for neural networks. Second, we classify the FoMs of analog RSM devices into two levels. Level 1 FoMs are essential for achieving the functionality of a system (e.g., linearity, symmetry, dynamic range, level numbers, fluctuation, variability, and yield). Level 2 FoMs are those that make a functional system more efficient and reliable (e.g., area, operational voltage, energy consumption, speed, endurance, retention, and compatibility with back-end-of-line processing). By constructing a device-to-application simulation framework, we perform an in-depth analysis of how these FoMs influence in-memory learning and give a target list of the device requirements. Lastly, we evaluate the main FoMs of most existing devices with analog characteristics and review optimization methods from programming schemes to materials and device structures. The key challenges and prospects from the device to system level for analog RSM devices are discussed.
Applying Stack Bidirectional LSTM Model to Intrusion Detection

Nowadays, Internet has become an indispensable part of daily life and is used in many fields. Due to the large amount of Internet traffic, computers are subject to various security threats, which may cause serious economic losses and even endanger national security. It is hoped that an effective security method can systematically classify intrusion data in order to avoid leakage of important data or misuse of data. As machine learning technology matures, deep learning is widely used in various industries. Combining deep learning with network security and intrusion detection is the current trend. In this paper, the problem of data classification in intrusion detection system is studied. We propose an intrusion detection model based on stack bidirectional long shortterm memory (LSTM), introduce stack bidirectional LSTM into the field of intrusion detection and apply it to the intrusion detection. In order to determine the appropriate parameters and structure of stack bidirectional LSTM network, we have carried out experiments on various network structures and parameters and analyzed the experimental results. The classic KDD Cup’1999 dataset was selected for experiments so that we can obtain convincing and comparable results. Experimental results derived from the KDD Cup’1999 dataset show that the network with three hidden layers containing 80 LSTM cells is superior to other algorithms in computational cost and detection performance due to stack bidirectional LSTM model’s ability to review time and correlate with connected records continuously. The experiment shows the effectiveness of stack bidirectional LSTM network in intrusion detection.
Signal Reconstruction With Semidefinite Relaxation Optimization in Uplink Massive MIMO Systems

In this letter, we consider a single group massive MIMO (Multi-Input Multi-Output) system, which consists of one receiver deployed with large number of antennas and multiple users with each having single antenna. In the uplink transmissions from users to base station, we focus on the efficient signal reconstruction of all the users’ transmitted symbols. We build a statistic decision matrix based on the received signals, whose eigenvectors and eigenvalues constitute the key components of our signal reconstruction algorithm. Then, an optimization problem is formulated and we convert this problem to obtaining the optimal weights by solving Semidefinite Relaxation (SDR) optimization and obtaining the optimal rotation phases. Finally, an iterative algorithm framework is proposed for multi-user signal reconstruction. Numerical results are carried out to verify the bit-error-ratio (BER) performance compared with several coherent detection and noncoherent transmission schemes.
Introduced population of ring-necked parakeets Psittacula krameri in Madeira Island, Portugal – Call for early action

Alien invasive species are major drivers of ecological change worldwide, being especially detrimental in oceanic islands, where they constitute one of the greatest threats to the survival of native species. Ring-necked parakeets Psittacula krameri (Scopoli, 1769) are popular pets and individuals escaped from captivity have formed multiple self-sustainable populations outside their native range. For over ten years, free-ranging ring-necked parakeets have regularly been observed in Madeira Island (Portugal) and strong evidence suggests that they have breed multiple times in Funchal, the capital of the island. Herein, we assess the current status of Psittacula krameri in Madeira and discuss the possible ecological and economic impacts of established populations of this non-native parakeet. Given the initial stage of the incursion, we advocate for a “rapid response” intervention aimed at preventing the spread of this potential invader.
Should Banks Create Money

The paper compares the welfare properties of two competing organi- zations of the monetary system: The current fractional reserve banking system versus a narrow banking system where inside money is fully backed by outside money issued by the central bank. Using a New Monetarist model, the analysis shows that fractional reserve banking is bene cial because of the interest payments on inside money. Since inside money funds loans, it pays interest, compensating the agents for the in ation tax and thus reducing the welfare costs of in ation. Since narrow banking provides no such compensation fractional reserve banking typically domi- nates narrow banking in terms of welfare. This also holds if outside money pays interest. Only if fractional reserve banking is suciently constrained, narrow banking can yield higher welfare.
Complete mitochondrial genome of the Blotched snake, Elaphe sauromates (Pallas, 1814)

Abstract Here, we present the complete mitochondrial genome of the Blotched snake, Elaphe sauromates (Pallas, 1814). Mitogenome complete sequence is 17,187 bp long and consists of 13 protein-coding genes (PCGs), two rRNA genes, and 22 tRNA genes and two control regions. The species mitochondrial genome has the same gene order as other mitogenomes of Elaphe spp. Their analysed genome has base composition as: 34.8% (A), 26.8% (C), 25.7% (T), and 12.7% (G), with an A + T bias (60.5%). Presented mitogenome will provide new data for phylogenetic analysis within the genus Elaphe.
Multiresidue Determination of Endocrine Disrupting Compounds in Sewage Treatment Plants (SPE-HPLC-DAD)

This work focuses on the validation and application of solid phase extraction followed by high-performance liquid chromatography (SPE-HPLC) analysis of important endocrine disruptors compounds (EDC) from different classes in highly complex wastewater matrix. The endocrine disruptors investigated included three different categories: pharmaceuticals (sulfamethoxazole (SMZ), trimethoprim (TMP) and diclofenac (DCF)), hormones (estrone (E1), 17α-ethinylestradiol (EE2) and 17β-estradiol (E2)) and plastic materials (bisphenol A (BPA)). The method involves pre-concentration by SPE using Strata-X extraction cartridges followed by HPLC coupled with diode array detector (DAD). As the assumption of homoscedasticity was met for analytical data, ordinary linear regression procedure was applied to the data. The method was considered validated for 7 EDC after consistent evaluation of the key analytical parameters. Recoveries were ranged from 52.3 to 179.6%. Limits of quantification were in the range 6.0-0.4 μg L. The described method was applied to evaluate the occurrence and removal efficiency of EDC in two biological sewage treatment plants (STPs). The influent mean concentrations of E1, E2 and EE2 hormones were 79.54; 175.09 and 102.19 μg L, respectively, while for SMZ, TMP, DCF and BPA were 215.17; 187.01; 218.97 and 87.12 μg L for STP A, respectively. The efficiencies for the removal of EDCs ranged from 0 to 79.4%.
Automatic Optimization of the Compensation Networks of a Wireless Power Transfer System

This paper addresses the optimization of the compensation networks of a wireless power transfer system. Optimization is performed by means of a genetic algorithm that looks for the reactances of the elements of the compensation networks that maximize the power transfer efficiency and the power transferred to the load. In addition, the algorithm selects the solutions that are less sensitive to the difference between the theoretical and actual reactances. The last part of the paper describes the prototypal setup used for the tests and supports the theoretical findings by reporting experimental results.