Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigation on the digital image correlation and charge trap characteristics of Al/epoxy nanocomposites

The influence of nanofiller on the tensile and surface charge properties of Al/Epoxy nanocomposite materials is investigated with respect to their structural composition. The formation of conductive network nearing the percolation limit with the addition of nanofiller has strongly influenced the mechanical and electrical characteristics of nanocomposites. The digital image correlation technique is employed to acquire the strain variation at the distinct locations on the tensile specimen. The load-displacement, as well as shape deformation, were analysed for the various nano filled composites. The improved tensile characteristics were achieved up to certain wt% of filler addition, beyond which the load and time required for the material fracture were reduced drastically. Likewise, the addition of filler up to 5 wt% has shown the improved charge decay characteristics viz. quicker charge decay and enhancement in shallow energy states under the applied DC voltage. The direct analogy in mechanical and electrical characteristics was formulated in terms of structural composition (defects, additives and filler) of respective materials.
A Survey on the Internet of Things (IoT) Forensics: Challenges, Approaches, and Open Issues

Today is the era of the Internet of Things (IoT). The recent advances in hardware and information technology have accelerated the deployment of billions of interconnected, smart and adaptive devices in critical infrastructures like health, transportation, environmental control, and home automation. Transferring data over a network without requiring any kind of human-to-computer or human-to-human interaction, brings reliability and convenience to consumers, but also opens a new world of opportunity for intruders, and introduces a whole set of unique and complicated questions to the field of Digital Forensics. Although IoT data could be a rich source of evidence, forensics professionals cope with diverse problems, starting from the huge variety of IoT devices and non-standard formats, to the multi-tenant cloud infrastructure and the resulting multi-jurisdictional litigations. A further challenge is the end-to-end encryption which represents a trade-off between users’ right to privacy and the success of the forensics investigation. Due to its volatile nature, digital evidence has to be acquired and analyzed using validated tools and techniques that ensure the maintenance of the Chain of Custody. Therefore, the purpose of this paper is to identify and discuss the main issues involved in the complex process of IoT-based investigations, particularly all legal, privacy and cloud security challenges. Furthermore, this work provides an overview of the past and current theoretical models in the digital forensics science. Special attention is paid to frameworks that aim to extract data in a privacy-preserving manner or secure the evidence integrity using decentralized blockchain-based solutions. In addition, the present paper addresses the ongoing Forensics-as-a-Service (FaaS) paradigm, as well as some promising cross-cutting data reduction and forensics intelligence techniques. Finally, several other research trends and open issues are presented, with emphasis on the need for proactive Forensics Readiness strategies and generally agreed-upon standards.
Profit Optimization for Mileage-Based Pricing of Electric Vehicle Lease

Electric vehicles (EVs) are now widely acknowledged as ideal means of transportation in future, in terms of energy conservation and environmental protection for urban governance. EV lease service is an effective measure to promote the use of EVs and has gained the support of many countries. In this article, a comprehensive pricing scheme is developed to optimize the annual operations profit for EV lease service based on mileage-based pricing (MBP), where the profit is defined as the revenue subtracted by the maintenance cost. Different from the traditional MBP for vehicle lease service, our model characterizes how the grade level of EVs affects the maintenance cost after each failure. Moreover, the lease service is modeled as a queuing system where each consumer has the probability choosing the MBP by comparing the service value and his expense. An enumerative algorithm is developed to find the optimal pricing as well as analyze the influence of parameters on the optimal profit. The algorithm is implemented in the pricing of an EV lease company in China. The results show that the optimal pricing will increase with service rate, consumer arrival rate, and the service value from lessor, but decrease with waiting cost of consumers. Differential pricing strategies are also proposed to resolve the conflict goals of lessors and consumers, which can further boost lessors’ profit and raise consumers’ satisfaction level. The results show that MBP with differential pricing strategies will increase profit between 2.3% and 69.8%, comparing with cases without differential pricing strategies.
Optimizing Motheye Nanostructures and Achieving 100% Transmission

Nanostructured Antireflections Layers (NALs) are a promising substitute for conventional antireflection layers. In the nature, such structures have long existed on insects’ eyes. Here, we have derived a general form of mathematical relation that generates a profile close to that of surface of a Moth’s eye. By properly designing NALs over dielectric, light has been efficiently transmitted through our high index nanostructures with minimal reflection. The parameters determining the transmission efficiency are the pitch and the profile of the periodic nanostructures. By optimizing the profile, we have designed NALs with transmission reaching 100%. Our periodic structures have minimal dependence on the pitch. This makes it possible to fabricate NALs with the very broadband transmission, without inducing diffraction to lower wavelengths of the transmitted light. Also, our periodic NALs make it possible to transmit laser lights without scattering.
Prehistoric human activity and its environmental background in Lake Donggi Cona basin, northeastern Tibetan Plateau

Lake Donggi Cona is a key area for the exploration of the prehistoric settlement of the inner Tibetan Plateau because of its location in the joint of the higher inner Tibetan Plateau and the upper Yellow River valley. Here, we carried out archeological investigation on the lake basin, and a total of 256 pieces of stone artifacts were collected from the surface of the DJCN 3-2-2 site on the northern shore terraces of the lake. In addition, AMS14C and OSL dating were performed on hearths and section (DJCN 3-2-2), respectively; meanwhile environmental proxies, including grain size, charcoal, magnetic susceptibility, fungal spore, and pollen, were analyzed. The results indicate that the AMS14C ages of the charcoal range between ~5.4 and 5.0 cal. ka BP, consistent with OSL dating from the charcoal layers in the DJCN 3-2-2 section (~5.5 ka BP). The functional analysis of the stone artifacts and dating results showed that the site was a seasonal, relative long-term, and central camp which was used for processing of stone artifacts, cutting and consuming food and the production of daily necessities. Charcoal, magnetic susceptibility, and fungal spores from the DJCN 3-2-2 section revealed that prehistoric human activities began at ~5.8 ka BP and significantly intensified during the period of ~5.6–5.5 ka BP and then gradually weakened. Pollen assemblages indicated that the vegetation was dominated by alpine steppe during the period of ~5.8–5.0 ka BP, indicative of a relatively warmer and wetter climatic condition during this period. Taken together, we infer that under the impact of the Neolithic culture in lower altitude of upper Yellow River valley and Microlithic culture in the higher altitude inner Plateau, a Neolithic-Zongri culture had emerged in the transitional region between these two cultures during middle Holocene.
Design of an Access Control System Based on Face Recognition

This paper studies design of an access control system based on face recognition for the major purpose of programming face recognition and access systems for embedded equipment. The access control system studied in this paper has functions regarding security, access control, personnel management, travel logs and time management. In this paper, face recognition algorithms are theoretically analyzed and derived. Based on face recognition algorithms, access control systems, particularly including face recognition algorithms, image processing and software, are designed and realized. Overall systematic debugging practices prove that aforementioned algorithms and software designs are correct and effective.
Deep Spatial–Temporal Model Based Cross-Scene Action Recognition Using Commodity WiFi

With the popularization of Internet-of-Things (IoT) systems, passive action recognition on channel state information (CSI) has attracted much attention. Most conventional work under the machine-learning framework utilizes handcrafted features (e.g., statistic features) that are unable to sufficiently describe the sequence data and heavily rely on designers’ experiences. Therefore, how to automatically learn abundant spatial–temporal information from CSI data is a topic worthy of study. In this article, we propose a deep learning framework that integrates spatial features learned from the convolutional neural network (CNN) into the temporal model multilayer bidirectional long short-term memory (Bi-LSTM). Specifically, CSI streams are segmented into a series of patches, from which spatial features are extracted by our designed CNN structure. Considering long-term dependencies between adjacent sequences, the fully connected layer of CNN for each patch is taken as the Bi-LSTM sequential input to further capture temporal features. Our model is appealing in that it can simultaneously learn temporal dynamics and convolutional perceptual representations. To the best of our knowledge, this is the first work to explore deep spatial–temporal features for CSI-based action recognition. Furthermore, in order to solve the problem that the trained model fully fails with environmental changes, we use the off-the-shelf model as the pretrained model and fine-tune it in the new scenario. The transfer method is able to realize cross-scene action recognition with low computational consumption and satisfactory accuracy. We carry out experiments on indoor data and the experimental results validate the effectiveness of our algorithm.
Air pollution, pulmonary oxidative stress, and the endothelin system in the development of cardiovascular injury.

s Natasha DeJarnett, Ray Yeager, Daniel Conklin, Timothy O’Toole, James McCracken, Wesley Abplanalp, Daniel Riggs, Ihab Hamzeh, Stephen Wagner, Atul Chugh, Andrew DeFilippis, Tiffany Ciszewski, Bradley Wyatt, Carrie Becher, Deirdre Hidgon, Jordan Finch, Imtiaz Ismail, David J. Tollerud, Shesh Rai, Jasmit Shah, Nagma Zafar, Stahya Krishmasamy, Sumanth Prabhu, Aruni Bhatnagar. Air Pollution and Tobacco Smoke Differentially Depress Circulating Angiogenic 90 Cells in Humans. American Public Health Association Annual Meeting, Chicago, IL, 2015.
THE INFLUENCE OF SCHOOL ENVIRONMENT ON STUDENTS’INTEREST IN ENGLISH SUBJECT(A Case at SMP IT Assalam Boarding School Pekalongan in the Academic Yearof 2018/2019)

School environment and students’ interest are important factors to support the development of students’ learning process. School environment includes all the components that contribute to create an environment in teaching-learning process both physical and non-physical. The objectives of this study are to find the influences, if any, of school environment on students’ interest in English subject and to determine, if any, how significant school environment influences students’ interest in English subject. The design of this research was Ex Post Facto which the researcher could not control and manipulate the independent variable in the study, because the independent variable already existed naturally. The population of this study was students at SMP IT Assalam Boarding School Pekalongan in the academic year of 2018/2019. The researcher selected 60 students as samples of the study by applying Random Sampling Technique. The data were obtained by distributing questionnaires about school environment and students’ interest to the selected students. The result of the study revealed that there was a significant influence of school environment on students’ interest in English subject. It was concluded from the computation of Pearson’s Product Moment that school environment influences students’ interest in high category with significance 0.649. If R-value is higher than R-table, there is a significant influence between the two variables. In this study, Rvalue (0.649) was higher than R-table (0.254). It means that H0 was rejected and H1 which was stated “There is a significant influence of school environment on students’ interest in English subject at SMP IT Assalam Boarding School Pekalongan” was accepted.
Design and Validation of a Fall Detection Application for iOS

Despite significant preventative efforts, falls continue to be a major source of morbidity and mortality among the elderly. Additionally, the fear of falling can be a major obstacle to independent living for otherwise self-sufficient individuals. This fear is significantly heightened in individuals who have sustained a fall and often results in self-imposed restrictions on mobility and exercise, causing weakening in these individuals and further exacerbating the danger. Much time has been spent developing alert systems in an attempt to mitigate these problems. Unfortunately these systems typically involve dedicated monitoring centers and therefore often come with substantial upfront and recurring costs. This thesis proposes a solution to these problems by implementing fall detection and alert capabilities on a smartphone, devices that are quickly becoming ubiquitous in today's society. This solution has the potential to quell the fears of many elderly people and their families, while allowing them to maintain their independence at little expense. Detailed herein is the process of designing, developing, and validating this fall detection application. The final application was written in Objective-C for iOS and tested on an iPhone. Figure Page Figure 1 – The abstraction layers of iOS; the top corresponds to the highest level of abstraction, with the bottom being the lowest level of Figure 6 – Graph of accelerations in each axis, during three simulated falls with a punching bag, in the backward direction and an update interval of 0. Figure 8 – Graph of accelerations in each axis, during three simulated falls with a punching bag, in the backward direction and an update Figure 9 – Graph of accelerations in each axis, during three simulated falls with a punching bag, in the backward direction and an update Figure 10 – Graph of accelerations in each axis, during three simulated falls with a punching bag, in the backward direction and an update Figure 11 – Graph of accelerations in each axis, during three simulated falls with a punching bag, in the sideways direction and an update speed of 40Hz. Included in yellow are the sums of the Figure 12 – Graph of accelerations in each axis, during three simulated falls with a punching bag, in the sideways direction and an update speed of 40Hz. Included in black are the sums of the absolute accelerations in the three axes.
GaSe/MoS2 Heterostructure with Ohmic‐Contact Electrodes for Fast, Broadband Photoresponse, and Self‐Driven Photodetectors

In this letter, the vertically‐stacked GaSe/MoS2 heterostructures with indium tin oxide (ITO) and Ni/Au as contact electrodes are successfully fabricated, respectively. The GaSe/MoS2 heterostructure exhibits a broadband photoresponse covering the range of visible to near‐infrared spectra at room temperature without external bias voltage. When ITO serves as contact electrodes, a high rectification ratio, i.e., 1.5 × 104 at VDS = ±1 V, and an excellent photoelectric performance, i.e., responsivity of ≈0.67 A W‐1, specific detectivity of ≈2.3 × 1011 cm Hz1/2 W‐1 and external quantum efficiency of ≈160% at the wavelength of 520 nm is achieved. Moreover, the GaSe/MoS2 heterostructure with Ohmic‐contact ITO electrodes demonstrates a faster response time of 155 µs, which is 4 times faster than the GaSe/MoS2 heterostructure with Ni/Au electrodes and about 300 times faster than previous reports. These results reveal the presence of an abrupt p–n junction between GaSe and MoS2 and significant role of electrode‐contact mode in determining the photoelectric properties of GaSe/MoS2 heterostructure.
A Short Note On Comparative Analysis Of Acetylcholinesterase Genes In Mosquito Genome

Ace ty l cho l i nese rase genes con fe r t he organophosphate and carbamate resistance mechanism. A total of 46 acetylcholineserase genes in the 24 mosquito genomes were identified. In this study, all the analysed mosquito genomes have the two acetylcholinesterase genes (ace-1 and ace-2) except Aedes albopictus and Anopheles sinensissinensis strain. Phylogenetic tree showed the divergence of acetylcholinesterase genes among the mosquito genome. Phylogenetic tree confirmed that the ace-1 and ace-2 genes of each species were structurally different and they form the different clades. This provided data on acetylcholinesterase gene organization for 24 mosquito genome is possibly a first time and will be a starting point for the molecular characterization of the acetylcholinesterase genes wh ich fu r the r he lps to unders tand the organophosphate and carbamate resistance mechanism.
Analisis Perbandingan Metode Naïve Bayes dan PNN Dalam Mendeteksi Denial of Service

Abstrak Denial of Service (DoS) adalah serangan dimana penyerang menghabiskan sumber daya jaringan komputer. Dampak dari serangan DoS menyebabkan komputer tidak dapat berfungsi dengan normal. Intrusion Detection System (IDS) berperan sebagai pendeteksi berbagai jenis serangan pada jaringan komputer termasuk DoS. IDS mengidentifikasi serangan berdasarkan klasifikasi data jaringan. Metode Intrusion Detection System (IDS) nonmachine learning saat ini tidak terlalu akurat, sehingga diperlukan metode IDS dengan machine learning yang lebih akurat dalam mendeteksi serangan. Untuk mengatasi permasalahan ini, penelitian ini membandingkan metode Naive Bayes dan Probabilistic Neural Network (PNN) untuk mendeteksi serangan DoS secara optimal. Pada penelitian ini, implementasi menggunakan metode Naive Bayes dan PNN dalam mendeteksi serangan DoS menggunakan NSL-KDD dataset dengan 13 fitur dari 41 fitur. Hasil dari penelitian ini yaitu Naive Bayes memiliki akurasi lebih tinggi dengan nilai akurasi 100% daripada PNN yang hanya mempunyai nilai akurasi sebesar 91,93% dalam mendeteksi serangan DoS. Kata kunci : Keamanan Jaringan Komputer, Naive Bayes, Probabilistic Neural Network (PNN), Denial of Service. Abstract Denial of Service (DoS) is attack where an attacker spends computer network resources. The impact of a DoS attack causes the computer not to function normally. Intrusion Detection System (IDS) serves as a detection of various types of attacks on computer networks including DoS. IDS identifies attacks based on network data classification. Non-machine learning Intrusion Detection System (IDS) methods are currently not very accurate, so the IDS method with machine learning is more accurate in detecting attacks. To address this problem, the study compares the Naive Bayes and Probabilistic Neural Network (PNN) methods to optimally detect DoS attacks. In this study, implementations used Naive Bayes and PNN methods in detecting DoS attacks using NSL-KDD datasets with 13 features from 41 features. The result of this study is that Naive Bayes has higher accuracy with an accuracy value of 100% than that of PNN which only has an accuracy value of 91,93% in detecting DoS attacks. Keywords : Computer Network Security, Naive Bayes, Probabilistic Neural Network (PNN), Denial of Service.
‘I can’t sit here and cry with you, I have to play’. Strategies by very young children in refugee collective accommodation

ABSTRACT Little is known about the everyday life of very young children in refugee collective accommodation centres, hosted together with their parents. Access to high-quality provision of early education and care is not implemented. Against this background, the paper explores young children’s everyday life practices in these specific centres. This paper presents findings from an explorative ethnographic research project in refugee accommodation centres in Germany. Researchers accompanied 12 children aged three to seven years old in their daily play and family activities through participant observation in different refugee centres. Against the constraints of their life circumstances, refugee children’s activities are discussed as children’s unique ways of appropriation, demonstrating social actor-ship. In outlook, the paper highlights co-operative work with refugee parents and the use of ethnographic research findings to inform programmes in Early Childhood Education and Care.
Phytophthora pathogens threaten rare habitats and conservation plantings

Phytophthora pathogens are damaging native wildland vegetation including plants in restoration areas and botanic gardens. The infestations threaten some plants already designated as endangered and degrade high-value habitats. Pathogens are being introduced primarily via container plant nursery stock and, once established, they can spread to adjacent areas where plant species not previously exposed to pathogens may become infected. We review epidemics in California – caused by the sudden oak death pathogen Phytophthoraramorum Werres, De Cock & Man in ‘t Veld and the first USA detections of P. tentaculata Kröber & Marwitz, which occurred in native plant nurseries and restoration areas – as examples to illustrate these threats to conservation plantings.
Fully Actuated Multirotor UAVs: A Literature Review

In the last decade, the aerial robotics community has witnessed an increased interest in fully actuated multirotor unmanned aerial vehicles (UAVs) that have more capabilities than conventional underactuated multirotors. This article collects the different UAV designs having fully actuated aerodynamic wrench generation proposed in the literature to date. The work includes a systematic derivation of the control-allocation matrix for all of the concepts as well as a discussion of the different quantitative criteria used for optimizing UAV designs.
The Atlantic Meridional Overturning Circulation in High‐Resolution Models

The Atlantic meridional overturning circulation (AMOC) represents the zonally integrated stream function of meridional volume transport in the Atlantic Basin. The AMOC plays an important role in transporting heat meridionally in the climate system. Observations suggest a heat transport by the AMOC of 1.3 PW at 26°N-a latitude which is close to where the Atlantic northward heat transport is thought to reach its maximum. This shapes the climate of the North Atlantic region as we know it today. In recent years there has been significant progress both in our ability to observe the AMOC in nature and to simulate it in numerical models. Most previous modeling investigations of the AMOC and its impact on climate have relied on models with horizontal resolution that does not resolve ocean mesoscale eddies and the dynamics of the Gulf Stream/North Atlantic Current system. As a result of recent increases in computing power, models are now being run that are able to represent mesoscale ocean dynamics and the circulation features that rely on them. The aim of this review is to describe new insights into the AMOC provided by high-resolution models. Furthermore, we will describe how high-resolution model simulations can help resolve outstanding challenges in our understanding of the AMOC.