Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimized Deep Autoencoder Model for Internet of Things Intruder Detection

The development of an optimized deep learning intruder detection model that could be executed on IoT devices with limited hardware support has several advantages, such as the reduction of communication energy, lowering latency, and protecting data privacy. Motivated by these benefits, this research aims to design a lightweight autoencoder deep model that has a shallow architecture with a small number of input features and a few hidden neurons. To achieve this objective, an efficient two-layer optimizer is used to evolve a lightweight deep autoencoder model by performing simultaneous selection for the input features, the training instances, and the number of hidden neurons. The optimized deep model is constructed guided by both the accuracy of a K-nearest neighbor (KNN) classifier and the complexity of the autoencoder model. To evaluate the performance of the proposed optimized model, it has been applied for the N-baiot intrusion detection dataset. Reported results showed that the proposed model achieved anomaly detection accuracy of 99% with a lightweight autoencoder model with on average input features around 30 and output hidden neurons of 2 only. In addition, the proposed two-layers optimizer was able to outperform several optimizers such as Arithmetic Optimization Algorithm (AOA), Particle Swarm Optimization (PSO), and Reinforcement Learning-based Memetic Particle Swarm Optimization (RLMPSO).
Quantum Circuit for Regression Learning with Backpropagation

This work reports the experiment on building quantum circuit for regression learning using qiskit library. The circuit is based on Watabe's work with some modification based on our interpretation. The parameters and results are stored and used in the quantum circuits. We performed the experiments on fitting the linear function and quadratic function. From the experiment, learning the linear function is more accurate than quadratic function within 120 times of training. The initial parameters effect on the number of rounds of training and the accuracy of the result are investigated.
Image Classification Based On improved VGG Network

Image classification is a fundamental problem in the field of computer vision. In this paper, we propose an improved VGG-16 model suitable for small data sets such as cifar10. The model reduces the fully connected layer, adds batch normalization (BN) and a stronger regularizer (Dropout) as well as improving the loss function. For the cifar10 data set, this paper uses four data augmentation methods: random flip, random translation, random erasure, and mix up to improve the generalization ability of the model. Experimental results show that the training parameters of the improved VGG model are reduced to 10.65% of the original model, and the average classification accuracy rate is increased to 94.43%.
On Comparison of Time Series Models in Modeling and Forecasting Available Bandwidth in Wide Area Networks

We explored modeling and forecasting available bandwidth along an end-to-end paths using four time series models, namely ARIMA (p,d,q), SARIMA (p,d,q) (P,D,Q) [s], FARIMA (p, d (0–0.5),q), and SFARIMA (p, d (0–0.5), d). We employed available bandwidth data set measured over time in 2004 and 2009. The data set was published by Stanford Linear Accelerator Center (SLAC). Our results indicated that we could fit all four models to each time series representing available bandwidth of an end-to-end path measured over time. However, performance of the four models in forecasting future available bandwidth varied. Our results showed that SARIMA outperformed all three counterparts.
Appendix for “Bipartite Formation Tracking for Multi-Agent Systems Using Fully Distributed Dynamic Edge-Event-Triggered Protocol”

Appendix Proof of Theorem 1 ξ̌i = x̄1 i −Hiyi− x̌1 i , i ∈ VF Proof: Denote . Combining (4a) with (5a) gives ̇̌ ξi = (Ǎ11 i +HiǍ 21 i )ξ̌i. (12) Ǎ11 i +HiǍ 21 i limt→∞(x̄ 1 i −Hiyi) = x̌1 i limt→∞ x̂i = xi limt→∞(ζ̄ ε −Hyε) = x̌1 ε limt→∞ ζε = xε (ζ̄1 ε −Hyε − x̌1 ε ) ξi Since is Hurwitz, one has . It is further obtained that . Similarly, we have and . By noting that (8), it is easy to find that is decoupled from . Therefore, the global convergence of (8) is equivalent to the global convergence of the following system:
Automatically Designing CNN Architectures for Acoustic Scene Classification

Deep convolutional neural networks (CNNs) have proven their effectiveness in the acoustic scene classification (ASC) task, becoming the state-of-the-art solution to build pow-erful ASC models. Usually, the architectures of these networks and their hyper-parameters have been manually designed by expert researchers in both the investigated problem and CNN architecture design, which can be a challenging task. In this work, we propose a genetic algorithm (GA) that benefits from the characteristics of state-of-the-art CNN architectures in the field of ASC to specifically optimize CNN architectures for the ASC task, within an acceptable search cost compared to other GAs. After searching for 14 GPU days using a single NVIDIA Tesla K80 GPU on the development dataset of DCASE2020 Task lA, the proposed GA has optimized a CNN architecture that achieved a test accuracy of 68.5 % on the same dataset. The same network has been evaluated on the development dataset of DCASE2018 Task 1A and achieved a classification accuracy of 73.7% without repeating the search process, which demonstrates the generalization capability of the generated CNNs.
New Pattern Underfloor Lifting System for High-speed Train

This paper briefly describes the structure features and maintenance mode of China Railway High-speed(CRH),and compatibility requirements for the CRH maintenance in China.The paper also elaborates the design methodology,technical innovation and novel structure of the DDT-I CRH Synchronous Underfloor Lifting System(UFLS) designed by Beijing Railway Institute of Mechanical Electrical Engineering.The key technical points to solve the compatible requirement of UFLS and safety protection measures are described in detailed,which are instructional for the design of UFLS for subway.
A Novel Compact EBG Structure for Mutual Coupling Reduction in a Patch Array

This paper presents a novel and compact C-shape electromagnetic band-gap (EBG) structure and arrangement for mutual coupling reduction. For the proposed antenna array, the reduction of mutual coupling between the two radiating elements reaches 10dB. The size of the C-shape EBG array is only 0.064‚0 at the operating frequency. Due to the use of EBG structures, the front-back ratio of the antenna is increased by 5.4dB. Simulated and measured results are given to verify the improvement of the performance of the antenna array.
Desarrollo y Validación de la Escala Breve de Satisfacción Laboral

This research aimed to develop and validate an instrument to measure job satisfaction in general. A total of 1,491 employed people who worked at least 20 hours per week and were 21 years of age or older participated in the study. The Job Satisfaction Brief Scale was developed with a total of eight items. Several exploratory factor analyses and several confirmatory factor analyses were performed using structural equation modeling to examine the scale's internal structure. The final version of the scale was composed of four items for which Cronbach's alpha and McDonald's omega coefficients were examined and fluctuated between . 77 to . 78. The results of the factor analyses, especially the confirmatory one, support the one-dimensional internal structure. The new scale appears to be invariance among gender, age, job position, and type of organization. In this way, the results provide evidence of the validity and reliability of the instrument created to measure job satisfaction in general.
Gaps in Information: What Missing Teeth Mean in Bioarchaeology

Previous bioarchaeological analysis of postmortem tooth loss (PMTL) has failed to recognize the potential influence of diseased dental tissue on tooth retention after death. Because tooth loss from a traditional taphonomy prospective is treated simply as missing data, demographic studies are potentially influenced by underestimations of disease prevalence. To investigate the association of tooth loss and dental disease, data on the pathological conditions observed in the tissues were collected on a sample of teeth from 771 individuals. By analyzing the evidence of disease in the bone and dental tissues immediately surrounding empty alveolar sockets suggestive of PMTL, trends in the presence of diseased tissue and retention of a tooth emerged. When compared to teeth retained after death, PMTL sockets were 15.3% less likely to retain neighboring teeth and 21.5% less likely to have neighboring teeth that showed no signs of carious or periapical lesions. The results suggest that the traditional explanation of susceptibility to loss due to the exposure and morphology of single-rooted, anterior teeth does not sufficiently explain the causes of PMTL in many cases. Rather, it would be more accurate to consider PMTL, in part, as an advanced symptom of dental disease when interpreting missing teeth in the bioarchaeological record. *Correspondence to: Laura E. Cirillo Department of Anthropology University of Nevada, Reno E-mail: misslauracirillo@gmail.com This paper was the recipient of the Albert A. Dahlberg prize awarded by the Dental Anthropology Association in 2021.
The impact of COVID-19 outbreak towards the post-pandemic leisure travel intention

There are studies related to COVID-19 pandemic across various sectors, including social, psychology, and specific industries, e.g., tourism. Several countries have imposed travel restrictions to prevent COVID-19 outbreaks and it may lead to travel behaviour changes for their residents. This research contributes to the existing knowledge by providing a new point of view, by extending the Theory of Planned Behaviour (TPB) along with additional determinants of travellers' post-pandemic behavioural intentions, namely cognitive and affective risk perception and non-pharmaceutical interventions. This study focused on Indonesian residents who intended to travel abroad for vacation in 2020, but their plan was postponed due to the COVID-19 pandemic. Data was collected using a convenience sampling technique and analysed using partial least squares structural equation modelling (PLS-SEM). The PLS-SEM enables us to predict the key factors that affect post-pandemic travel intentions. The results show that affective risk perception has a positive relationship with perceived behavioural control and non-pharmaceutical intervention. This research also found significant effects of cognitive risk perception on all variables. Positive significant relationships were found between attitude, subjective norms, perceived behavioural control, and non-pharmaceutical interventions with post-pandemic travel intentions.
Applying an Advocating Student-Environment Lens to Foster Protective Factors: School Counselors’ Role in Buffering ACEs

ABSTRACT Adverse Childhood Experiences (ACEs) have the potential for detrimental effects on students’ mental, emotional, and physical well-being. However, Positive Childhood Experiences (PCE) and Protective Factors (PF) can potentially buffer the impact of ACEs. School counselors can apply an Advocating Student Environment theoretical lens to prioritize constructs that are strong predictors to fostering student success. Thus, school counselors can prioritize evidence-based interventions, organized and offered within this article using two detailed tables, that have been empirically supported to bolster PCE and PFs. These interventions can be delivered through a Multi-Tiered System of Support (MTSS) approach to alter oppressive systems or support student resiliency and success.
Main characteristics of the organized screening program for cervical cancer, breast cancer and colorectal cancer in the Republic of Serbia

The paper aims to provide a descriptive, detailed review of the organized screening programs for cervical cancer, breast cancer and colorectal cancer in the Republic of Serbia. In this research, data from the Regulations on the National Program for Early Detection of Breast Cancer, Cervical Cancer and Colorectal Cancer were used, as well as published and unpublished data from the Institute of Public Health of Serbia. Screening for cervical cancer, breast cancer and colorectal cancer is carried out on the territory of the Republic of Serbia in the form of an organized decentralized program. Cervical cancer screening program encompasses women aged 25-64 years; the breast cancer screening program covers women aged 50-69 years; and the colorectal cancer screening program is offered to men and women aged 50-74 years. All three screening programs aim to cover at least 75% of the target population. The screening cycle for cervical cancer is three years, and for breast cancer and colorectal cancer, two years. The screening test used in the organized cervical cancer screening program is the PAP test; for breast cancer, the screening methodology relies on mammography; and for colorectal cancer, the screening program involves an immunohistochemical FOB test. Organized screening for cervical and breast cancers are offered through gynaecology specialists, while the organized screening for colorectal cancer is provided through the family physician, a medical doctor (or general medicine specialist) at the health centre. Organized cervical cancer, breast cancer and colorectal cancer screening programs represent a key activity at all levels of the healthcare system for early detection, prevention and reduction of mortality from malignant diseases. All programs are a part of continual healthcare activities in the Republic of Serbia, as a highly efficient cancer control strategy.
Stabilization of Switched Linear Neutral Systems With Time-Scheduled Feedback Control Strategy

This article is concerned with the stabilization of continuous-time switched linear neutral systems with tighter bounds on mode-dependent average dwell time. By introducing a novel time-scheduled control strategy, a switching-signal-based multiple discontinuous Lyapunov function (SMDLF) is constructed for continuous-time switched linear neutral systems, where the discontinuous points of the Lyapunov function during each mode-running interval are dynamically adjusted according to the actual system switching signal. First, sufficient criteria are established for global uniform exponential stability (GUES) of switched nonlinear systems. Then, based on the constructed SMDLF, we derive less conservative stability conditions for switched linear neutral systems. Furthermore, a set of time-dependent state feedback controllers are designed to guarantee the GUES of the underlying system. In the end, a simulation example with comparison results is provided to verify the effectiveness and advantages of the presented approach.
Spatial Data Dependence Graph Based Pre-RTL Simulator for Convolutional Neural Network Dataflows

In this paper, a new pre-RTL simulator is proposed to predict the power, performance, and area of convolutional neural network (CNN) dataflows prior to register-transfer-level (RTL) design. In the simulator, a novel approach is adopted to implement a spatial data dependence graph (SDDG), which enables us to model a specific dataflow alongside inter-instruction dependencies by tracking the status of each processing element (PE). In addition, the proposed pre-RTL simulator makes it possible to evaluate the impact of memory constraints such as latency and bandwidth. The latency-insensitive and bandwidth-insensitive PE controllers assumed in the proposed pre-RTL simulator guarantee both operational correctness and maximum performance, regardless of memory constraints. In particular, it is shown that the optimal distribution method of local memory bandwidth can reduce the accelerator performance by up to 37.6% compared with the equal distribution method. For weight stationary (WS) and row stationary (RS) dataflows, the accelerator performance closely depends on memory constraints. The simulation results also show that the relative performances of dataflows depend on the layer shape of the convolutional layer. For example, for an identical hardware area in a standard convolutional layer of AlexNet, WS dataflows do not provide any performance gain over RS dataflows when the memory latency is sufficiently high. In addition, WS dataflows cannot fully reuse the input activation, thereby increasing local memory accesses, since the number of weights loaded at a specific time is limited. Moreover, in a depth-wise convolutional layer of MobileNet, WS dataflows tend to outperform RS dataflows even in the presence of large memory latency.
Polylactic acid and polyhydroxybutyrate coating on hemp fiber: Its effect on hemp fiber reinforced epoxy composites performance

The present research work investigated the influence of biodegradable polymer coatings of hemp fiber on the structural, water absorption, mechanical, and tribological properties of hemp fiber and hemp fiber reinforced epoxy composites (HFREC). Hemp fibers were initially treated with sodium hydrogen carbonate and then coated with biodegradable polymers like polyhydroxybutyrate (PHB) and polylactic acid (PLA). Scanning electron microscopy (SEM) images of the coated fibers showed a visible change in fiber surface and improvement in surface roughness, while; X-Ray diffraction (XRD) analysis indicated the improvement in crystallinity of the coated fibers resulting in enhanced interfacial adhesion between the coated fibers and the epoxy matrix. The experimental results also revealed that both PHB and PLA coatings of the fibers have resulted in improvement of water resistance and mechanical properties such as tensile strength, modulus, and impact strength of coated HFREC. Tribological test results also revealed that the coated HFREC have improved wear and frictional properties in comparison to uncoated HFREC. The best tribological and mechanical properties were exhibited by PLA coated HFREC, which was also confirmed through the SEM images of worn and fractured surfaces of the uncoated and coated hemp fiber composites.
Study of Content Analysis : Trends of Educational Research for Physics Courses in Indonesia

Physics educational research trends are always changing from time to time. This change follows the phenomenon of educational problems that are developing in the field. The current study is a content analysis of research to analyze the trends of physics educational research that was published between the years of 2018 and 2021, visualize physics educational research trends and how Indonesian researchers contribute to physics educational research. This research was reached through the Journal of Research in Science Education (JPPIPA). Data obtained is 48 data and taken with "physics education" as the keyword. It is aimed to guide the researchers who are planning to conduct studies in this particular field by specifying physics education in terms of their methods, subject areas, research titles, data analysis techniques, and sampling types. Based on the results of the research that has been carried out, it can be concluded that the trend of educational research has increased and is in great demand by researchers in 2021. The physics material that is the research trend is wave material. The subject variable that is often studied is research in the cognitive domain. The trend of physics education research tends to be research that uses quantitative research methods with quasi-experimental design and uses data collection instruments in the form of test instruments. The type of sampling used is school students both junior and senior high school. The trend of physics education research also tends to quantitative descriptive research with data analysis techniques using frequencies, percentages, and charts. Number author or authors are becoming a trend in physics education research as much as three and the number of research references are often used as reference only 1-30. The results of this analytical research can be used to guide and provide references for research that will be carried out by further researchers, especially in the field of physics education research
RAD‐tag and mitochondrial DNA sequencing reveal the genetic structure of a widespread and regionally imperiled freshwater mussel, Obovaria olivaria (Bivalvia: Unionidae)

Abstract Obovaria olivaria is a species of freshwater mussel native to the Mississippi River and Laurentian Great Lakes‐St. Lawrence River drainages of North America. This mussel has experienced population declines across large parts of its distribution and is imperiled in many jurisdictions. Obovaria olivaria uses the similarly imperiled Acipenser fulvescens (Lake Sturgeon) as a host for its glochidia. We employed mitochondrial DNA sequencing and restriction site‐associated DNA sequencing (RAD‐seq) to assess patterns of genetic diversity and population structure of O. olivaria from 19 collection locations including the St. Lawrence River drainage, the Great Lakes drainage, the Upper Mississippi River drainage, the Ohioan River drainage, and the Mississippi Embayment. Heterozygosity was highest in Upper Mississippi and Great Lakes populations, followed by a reduction in diversity and relative effective population size in the St. Lawrence populations. Pairwise F ST ranged from 0.00 to 0.20, and analyses of genetic structure revealed two major ancestral populations, one including all St. Lawrence River/Ottawa River sites and the other including remaining sites; however, significant admixture and isolation by river distance across the range were evident. The genetic diversity and structure of O. olivaria is consistent with the existing literature on Acipenser fulvescens and suggests that, although northern and southern O. olivaria populations are genetically distinct, genetic structure in O. olivaria is largely clinal rather than discrete across its range. Conservation and restoration efforts of O. olivaria should prioritize the maintenance and restoration of locations where O. olivaria remain, especially in northern rivers, and to ensure connectivity that will facilitate dispersal of Acipenser fulvescens and movement of encysted glochidia.