Miracle-dz/UniFAR-FTUs huggingface dataset:
Fast motion estimation algorithm for HEVC video encoder

Video compression is required in applications like video network communications, video conference, broadcasting, live streaming and video storage. H.265/HEVC is the latest video compression standard, jointly developed by JCT-VC that provides the highest compression efficiency without significant loss in original video source quality. Among all the tools in HEVC encoder, Motion Estimation (ME) is one of the most complex tasks. The present paper analyses the ME algorithm present in HEVC standard reference software and proposes two improvements to the algorithm. Our results show a decrease on the computational complexity by almost 30% with negligible loss in the video quality. Keywords—Video Compression; HEVC; Motion Estimation
Aeroelastic Assessments and Functional Hazard Analysis of a Regional Aircraft Equipped with Morphing Winglets

The application of morphing wing devices can bring several benefits in terms of aircraft performance, as the current literature shows. Within the scope of Clean Sky 2 AirGreen 2 European project, the authors provided a safety-driven design of an adaptive winglet, through the examination of potential hazards resulting from operational faults, such as actuation chain jamming or links structural fails. The main goal of this study was to verify whether the morphing winglet systems could comply with the standard civil flight safety regulations and airworthiness requirements (EASA CS25). Systems functions were firstly performed from a quality point of view at both aircraft and subsystem levels to detect potential design, crew and maintenance faults, as well as risks due to the external environment. The severity of the hazard effects was thus identified and then sorted in specific classes, representative of the maximum acceptable probability of occurrence for a single event, in association with safety design objectives. Fault trees were finally developed to assess the compliance of the system structures to the quantitative safety requirements deriving from the Fault and Hazard Analyses (FHAs). The same failure scenarios studied through FHAs have been simulated in flutter analyses performed to verify the aeroelastic effects due to the loss of the actuators or structural links at aircraft level. Obtained results were used to suggest a design solution to be implemented in the next loop of design of the morphing winglet.
Data Bundle Transmission for Remote System in Duty Cycle Utilizing 3-D Discrete-Time Markov Chain

: The Duty cycle is the standout amongst the most well-known systems for information parcel transmission for remote system. In this strategy some bundle misfortune may happening and parcel size may vary from source to goal information voyaging time. Procedure utilized as the protection of vitality in remote systems by keeping the hubs at the same time wake up and rest deliberately. A solitary bundle transmission (SPT) happens per cycle, prompting perhaps long suspension. With aggregated parcel transmission (APT), hubs transmit a clump of bundles in a solitary cycle. The potential advantages brought by an APT plan incorporate shorter postponement, higher throughput, and higher vitality proficiency. In the writing, diverse logical models have been proposed to assess the execution of SPT plans. Be that as it may, no logical models for the APT mode on synchronous DC medium access control (MAC) systems exist. In this procedure, let’s build up a 3-D discrete-time Markov chain (DTMC) model to assess the execution of an APT plan with bundle retransmission empowered. The recommended model catches the elements of the condition of the line of hubs and the retransmission status and the development of the quantity of dynamic hubs in the system, i.e., hubs with a nonempty line. After that consider the quantity of retransmissions expected to transmit a bundle effectively. In view of the examination, build up another less-mind boggling DTMC show with boundless retransmissions, which epitomizes just two measurements . Along with, expand the 3-D demonstrate into a 4-D display by considering blunder inclined channel conditions. The prescribed models are embraced to decide parcel delay, bundle misfortune, vitality utilization, and vitality productivity. Also, the expository models are approved through discrete-occasion based reproductions. Numerical outcomes demonstrate that an APT plan accomplishes considerably preferable execution over its SPT partner regarding delay, throughput, parcel misfortune, and vitality effectiveness and that the created logical models uncover accurately the conduct of the APT plan.
Evaluation of Approximate Memories using Bit Dropping in Motion Estimation for Video Coding

Approximate Computing is a design paradigm that can be employed in situations where results of computation do not have to be exact – applications that can tolerate a certain amount of approximation errors and still produce useful outputs for the end-user, especially for perceptual signals processing. Approximate memories are a digital hardware design technique that brings these approximations to the data storage level. This paradigm is usually explored in Error-Tolerant Applications (ETAs), which include image and video processing, artificial neural networks, computer vision, web searches, machine learning, etc. This work proposes the use of Approximate Memories for High Efficiency Video Coding (HEVC or H.265), with the development of a methodology to evaluate the impact of the introduction of such approximations on the quality of the compressed video and the energy consumption. The memory access patterns of the HEVC encoder are recorded as memory traces and used to extract power results. The quality degradation produced by the approximations is evaluated with objective metrics used in the video coding literature, such as Peak Signal-to-Noise Ratio (PSNR) and Bjøntegaard delta bit-rate (BD-BR).
Acceptance of payment systems from the perspective of merchants

To date, the problem of acceptance of payment systems and technology from the consumer's perspective has been intensively investigated. Dahlberg et al. [1, 2] indicated diminishing need for additional research on the acceptance of payment systems by consumers. On the contrary, evaluation of adoption of payment systems by other participants of the market in the e-commerce ecosystem, in particular merchants, is still missing. This paper attempts to fill the existing gap. The objective of this paper is to propose determinants that merchants use as guidance in accepting or not a payment system. The main factors influencing the acceptance of payment systems by merchants have been defined basing on the commercially available “eXpay” system [8], as well as the TAM and UTAUT models. On this basis, a new model containing intention constructs and moderators significant from the merchants' perspective has been proposed. In the paper, the components of the model and possibilities of its application in further research are discussed.
Impact Evaluation of Malicious Control Commands in Cyber-Physical Smart Grids

The Smart Grid is vulnerable to cyber-attacks due to its integration with a variety of information, communication, and control technologies. If undetected by deployed security systems, cyber-attacks could damage critical power system infrastructure and disrupt services to a very large number of energy customers. In particular, cyber attackers could hijack the smart grid by injecting malicious commands. To provide insight into these concerns, we propose an approach that develops a new tool for the real-time Cyber-Physical Security Assessment (CPSA) of malicious control commands that target physical smart grid components. The tool is able to detect and protect the system against known Trojans (such as BlackEnergy). It also efficiently and effectively monitors the health of the power system in real-time and detects the presence of malicious commands. The security analysis of our approach includes a look at three system-generated metrics: system susceptibility, access points, and threat capability. The performance analysis includes a look at the system overhead, scalability, accuracy, robustness, and execution and response times. Our proposed approach was tested on a 42-bus power system with 24 substations. The developed tool could be extended and used by power system operators to assess and mitigate the impact of cyber-attacks on the smart grid.
A Novel Approach of Development of Web Pattern by Focusing on Web Structure Mining Techniques

The World Wide Web is a very useful and interactive resource of information like hypertext, multimedia etc. When we search any information on the Google, there are many URL’s has been opened. The bulk amount of information becomes very difficult for the users to find, extract and filter the relevant information, so that some techniques are used to solve these problems. The objective of current manuscript is focus on processing of structured and unstructured data mining. With the tremendous growth in website, web portal to provide downloaded data to the user. The semantic web is about machine-understandable web pages to make the web more intelligent and able to provide useful services to the users. The data structure definition and recognition is to estimate the accurate page ranking and to produce better result while searching operation with web data.
A Data Transmission Protocol for Wireless Sensor Networks: A Priority Approach

Recent development in the field of a wireless sensor network has shown the significant improvement and has emerged as a new energy efficient wireless technology for low data rate applications. Handling different types of event data altogether is a crucial task in the sensor networks. This paper presents the solution to the problem of heterogeneous data transmission of long distance prioritised nodes in low data rate wireless sensor networks (LR-WSNs). The solution comprises three main algorithms, namely data reporting, traffic scheduling, and centralised reporting rate mechanism. The data reporting algorithm reports the demanded data in each specified decision window size with variable reporting rate. The traffic aware packet scheduling algorithm performs the packet reprioritisation and scheduling. The priority assignment is designed based on the data priority and hop count. It serves transient traffic against newly sensed packets, or less hop distance travelled packets. As a result, it minimises the chances of dying earlier than its deadline. The third algorithm presents the flexible data gathering approach based on the level of the buffer either sensed by its own or recently received information from hop node. It uses a decision interval window for managing the frequency of data delivery. This centralised decision approach makes the sink node more adaptive for data gathering and controlling the active source nodes. This multi-tier framework functions over CSMA/CA due to its unique feature of energy saving, especially for LR-WSNs. The reported work is simulated and examined over various scenarios in the multi-hop wireless sensor networks. Moreover, the performance of the scheduler proves better data transmission rate for prioritybased traffic over regular traffic flows; approximately 7% over First-Come-First-Served (FCFS) and 5% against Precedence Control Scheme (PCS) mechanism using theoretical analysis and computer simulations.
A Review of Bow-Tie Antennas for GPR Applications

ABSTRACT Ground penetrating radar (GPR) is a special type of radar, which uses electromagnetic (EM) wave to detect the buried objects in the shallow subsurface. The overall efficiency and performance of the GPR system significantly depend on the quality of the acquired data and hence on the antenna and transceiver electronics sensor used in GPR surveying. Bow-tie antennas are widely used for GPR applications, as they possess a set of stringent antenna performances such as a low frequency of operation, ultra-wideband performance, minimal ringing, compact, planner, and lightweight. In this article, a comprehensive review of the bow-tie antennas used for GPR applications is presented. A brief review of the theoretical analysis of the bow-tie antennas indicates the advantageous features of this type of antennas with elliptical structures over the traditional triangular shapes. A comparative analysis of popularly used feed networks confirms that there is a requirement of a balun (balanced to unbalanced) which is used to convert the unbalanced current flow of the coaxial cable to the balanced current flow of two symmetrical lines used for exciting a balanced antenna. A comparative analysis of design techniques used to improve the traditional bow-tie antennas to overcome the various limitations, such as end-fire reflections, narrow bandwidth, dispersion characteristics, low efficiency, and gain, is presented. There is ample scope to propose a novel bow-tie antenna or to improve the existing Bow-tie antennas to achieve compactness, lightweight, reduced end-fire reflections, dispersionless characteristics, better gain and directivity, high radiation efficiency, and so on.
Built-In Test for Hidden Delay Faults

Marginal hardware introduces severe reliability threats throughout the life cycle of a system. Although marginalities may not affect the functionality of a circuit immediately after manufacturing, they can degrade into hard failures and must be screened out during manufacturing test to prevent early life failures. Furthermore, their evolution in the field must be proactively monitored by periodic tests before actual failures occur. In recent years, small delay faults (SDFs) have gained increasing attention as possible indicators of marginal hardware. However, SDFs on short paths may be undetectable even with advanced timing aware ATPG. Faster-than-at-speed test (FAST) can detect such hidden delay faults (HDFs), but so far FAST has mainly been restricted to manufacturing test. This paper presents a fully autonomous built-in self-test approach for FAST, which supports in-field testing by appropriate strategies for test generation and response compaction. In particular, the required test frequencies for HDF detection are selected, such that hardware overhead and test time are minimized. Furthermore, test response compaction handles the large number of unknowns ( ${X}$ -values) on long paths by storing intermediate MISR-signatures in a small on-chip memory for later analysis using ${X}$ -canceling transformations. A comprehensive experimental study demonstrates the effectiveness of the presented approach. In particular, the impact of the considered fault size is studied in detail.
Advantages and limitations of high-speed digital imaging in studying the singing voice: A critical look

It may be argued that singing requires a greater precision and control of timing and coordination of onset and offset mechanisms, as dictated by the musical score. Another important difference between sung and spoken phonation is the greater frequency range of phonation and control/precision necessary for smoother transition among registers in singing. HSDI has applied advantages in vocal pedagogy, by providing a direct visual example to help better understand the vocal fold (VF) vibratory mechanism during singing. It may also be used as a delayed visual feedback tool.
Transfer learning for bimodal biometrics recognition

Biometrics recognition aims to identify and predict new personal identities based on their existing knowledge. As the use of multiple biometric traits of the individual may enables more information to be used for recognition, it has been proved that multi-biometrics can produce higher accuracy than single biometrics. However, a common problem with traditional machine learning is that the training and test data should be in the same feature space, and have the same underlying distribution. If the distributions and features are different between training and future data, the model performance often drops. In this paper, we propose a transfer learning method for face recognition on bimodal biometrics. The training and test samples of bimodal biometric images are composed of the visible light face images and the infrared face images. Our algorithm transfers the knowledge across feature spaces, relaxing the assumption of same feature space as well as same underlying distribution by automatically learning a mapping between two different but somewhat similar face images. According to the experiments in the face images, the results show that the accuracy of face recognition has been greatly improved by the proposed method compared with the other previous methods. It demonstrates the effectiveness and robustness of our method.
Trading off Network Density with Frequency Spectrum for Resource Optimization in 5G Ultra-Dense Networks

To effectively increase the capacity in 5G wireless networks requires more spectrum and denser network deployments. However, due to the increasing network density, the coordination of network and spectrum management becomes a challenging task both within a single operator’s network and among multiple operators’ networks. In this article, we develop new radio resource management (RRM) algorithms for adapting the frequency spectrum and the density of active access nodes in 5G ultra-dense networks (UDNs) to the traffic load and the user density in different geographical areas of the network. To this end, we formulate a network optimization problem where the allocation of spectrum bandwidth and the density of active access nodes are optimized to minimize a joint cost function, and we exploit Lagrange duality techniques to develop provably optimal network-scheduling algorithms. In particular, we develop density algorithms for two application scenarios. The first scenario solves the resource management problem for an operator of an ultra-dense network with exclusive access to a pool of frequency resources, while the second scenario applies to the management of the network density of collocated UDNs that belong to multiple operators sharing the same frequency spectrum. Simulation results demonstrate how effectively the algorithms can adapt the allocation of the spectrum allocation and the density of active access nodes over space and time.
Backscattering enhancements due to retroreflection of ultrasonic leaky Rayleigh waves at corners of solid elastic cubes in water

Backscattering enhancements can be important for interpreting acoustical images of scatterers. Experiments were performed on a solid stainless steel cube in water in order to investigate a significant mechanism for producing a large backscattered signal. Enhanced high-frequency backscattering is observed when the block is rotated such that the incident acoustic wave strikes one of its flat surfaces in the vicinity of the coupling angle for launching a leaky Rayleigh wave at the steel–water interface. This enhancement can be explained as a retroreflection of the leaky wave at a corner of the block, which results in a reversal of the incident wave vector and thus produces a large backscattered signal. The magnitude of the peak backscattered pressure is approximated using a convolution formulation [P. L. Marston, J. Acoust. Soc. Am. 97, 34–41 (1995)]. Observed backscattering enhancements support the validity of the convolution formulation to approximate the general magnitude of the peak pressure, as well as .
eDOI: Exploratory Degree of Interest Exploration of Multilayer Networks Based on User Interest

The " zoom and filter " operations dear to the Shneiderman mantra are in reality not well specified in a data exploration context. There is a need to support users and suggest potential directions for exploration , and automatically selects a subset of nodes of interest based on a minimum initial user input. Filtering the data additionally avoids visual cluttering, especially overplotting, often resulting from laying out large networks. This paper explores how the multilayer properties of networks can be used to design a DOI (Degree of Interest) approach. Layers in a multilayer network bring nuances and must not be considered on an equal basis. We propose a method for extracting, expanding and displaying a sequence of sub-networks to guide users when exploring a multilayer network. Nodes and edges are selected based on an interest score computed for each node specifically taking the layer structure into account.
Advancing Discovery Science with FAIR Data Stewardship: Findable, Accessible, Interoperable, Reusable

ABSTRACT This report summarizes a presentation by Dr. Michel Dumontier. It reviews innovative scientific research methods created by data science, and the need to develop infrastructure, methodologies, and user communities to advance data science. Stakeholders have proposed a set of principles to make digital resources findable, accessible, interoperable, and reusable—FAIR. FAIR principles provide guidelines, do not require specific technologies, and allow communities of stakeholders to define specific FAIR standards and develop metrics to quantify them. Libraries can be part of the new data ecosystem by providing education, data stewardship, and infrastructure.
Rationale for the timing of the first oral evaluation.

The oral health of children living in industrialized countries has improved remarkably in the last 20 years, but many children still suffer from oral disease including caries, gingival infection, and malocclusion. Many studies report risk factors associated with the development of oral disease in children. While none provides a formula to determine accurately at birth the infant who will have the greatest risk of oral disease later in life, some studies strongly support early identification and management of contributing factors. Today, health supervision for children younger than 3 years of age remains the purview of primary care physicians, with preventive counseling and early identification of disease in their hands (AAP Recommendations for Preventive Pediatric Health Care, 1995).