Miracle-dz/UniFAR-FTUs huggingface dataset:
Perceptual Criteria on Image Compression

Nowadays, digital images are used in many areas in everyday life, but they tend to be big. This increases amount of information leads us to the problem of image data storage. For example, it is common to have a representation a color pixel as a 24-bit number, where the channels red, green, and blue employ 8 bits each. In consequence, this kind of color pixel can specify one of 2 ≈ 16.78 million colors. Therefore, an image at a resolution of 512 × 512 that allocates 24 bits per pixel, occupies 786,432 bytes. That is why image compression is important. An important feature of image compression is that it can be lossy or lossless. A compressed image is acceptable provided these losses of image information are not perceived by the eye. It is possible to assume that a portion of this information is redundant. Lossless Image Compression is defined as to mathematically decode the same image which was encoded. In Lossy Image Compression needs to identify two features inside the image: the redundancy and the irrelevancy of information. Thus, lossy compression modifies the image data in such a way when they are encoded and decoded, the recovered image is similar enough to the original one. How similar is the recovered image in comparison to the original image is defined prior to the compression process, and it depends on the implementation to be performed. In lossy compression, current image compression schemes remove information considered irrelevant by using mathematical criteria. One of the problems of these schemes is that although the numerical quality of the compressed image is low, it shows a high visual image quality, e.g. it does not show a lot of visible artifacts. It is because these mathematical criteria, used to remove information, do not take into account if the viewed information is perceived by the Human Visual System. Therefore, the aim of an image compression scheme designed to obtain images that do not show artifacts although their numerical quality can be low, is to eliminate the information that is not visible by the Human Visual System. Hence, this Ph.D. thesis proposes to exploit the visual redundancy existing in an image by reducing those features that can be unperceivable for the Human Visual System. First, we define an image quality assessment, which is highly correlated with the psychophysical experiments performed by human observers. The proposed CwPSNR metrics weights the
A Dialogue System with Emotion Estimation and Knowledge Acquisition Functions

In this paper, we propose a dialogue system with emotion estimation and knowledge acquisition functions. In the emotion estimation part, 9-emotions are treated in the proposed bimodal approach using voice and natural language processing. In the voice processing part, 396-dimensional features are extracted from the voice data, and they are used in learning of Stacked Denoising AutoEncoder. In the natural language processing part, two methods are proposed. The first one is to consider the implications of the relationship between emotional expression dictionary and input sentence’s words. The second one is to consider the co-occurrence frequency of the emotion words in emotion dictionary. In the knowledge acquisition part, the relationship patterns from the input sentences are extracted. In the evaluation experiments, we can confirm that the proposed dialogue system obtains higher score than the existing system in term of the adequacy of the feeling estimation and the variety of response sentences.
Architecture Based Design Of Multi Agent Systems

In this age of modern era, the use of internet must be maximized. Yeah, internet will help us very much not only for important thing but also for daily activities. Many people now, from any level can use internet. The sources of internet connection can also be enjoyed in many places. As one of the benefits is to get the on-line architecture based design of multi agent systems book, as the world window, as many people suggest.
ICMPv6-Based DoS and DDoS Attacks and Defense Mechanisms: Review

ABSTRACT The number of internet users and devices that are in need for more IP addresses to be assigned to them is rapidly increasing. A new protocol named IPv6 was developed in 1998 to overcome the addressing issue and to improve network communications in general. IPv6 is an improved protocol compared to IPv4 in terms of security since it provides built-in security mechanisms, such as IPSec. In addition, it brought new functionalities, such as Neighbour Discovery Protocol (NDP) procedure, which depends on Internet Control Message Protocol version 6 (ICMPv6) protocol messages. However, IPv6 inherited a number of attacks from IPv4 in addition to new attacks it brought within its new features. One of the most common attacks is the Denial of Service (DoS) attack due to its ease of being launched in different ways. A more serious DoS attack can be launched from many hosts called Distributed Denial of Service (DDoS). DoS and DDoS attacks are thorny and a grave problem of today's internet, resulting in economic damages for organizations and individuals. Therefore, this paper is created to study the properties of DoS and DDoS attacks against IPv6 networks using ICMPv6 messages. Additionally, it analyzes the various existing detection and prevention approaches that are proposed to tackle ICMPv6-based DoS and DDoS attacks. Moreover, it explains the existing tools that might be used for performing these attacks.
Periodic Intermittently Connected-Based Data Delivery in Opportunistic Networks

This paper propos a periodic intermittently connected-based data delivery in opportunistic networks(PICD). By effectively utilizing periodic intermittent connectivity between any two nodes,PICD can improve data delivery: First,for a certain node,based on its periodic intermittently-connected paths to the sink and its data delay tolerance,PICD establishes the delay probability model by means of random dynamic programming.Next,PICD will calculate the node's periodic delay probability distribution matrix by the function space iteration.Next,according to the node's distribution matrix,the current data delivery probability can be calculated by specifying period and tolerable delay,and this will become the key-player of the next-hop choosing.In short,the probability forwarding mechanism is delay-relevant and can increase data delivery probability within a tolerable amount of delay.Simulation shows that compared with existing algorithms,which only take advantage of single-hop delivery probability,PICD is better at data delivery and can also lower delay.
Reduction of low-frequency output voltage ripple for isolated high-power-factor AC–DC converter

ABSTRACT In the article, an isolated high-power-factor AC-DC converter, combining the buck-boost and flyback converters, is developed based on only one switch. With a suitable design of the voltage across the output capacitor of the buck-boost converter in the proposed circuit, the low-frequency output voltage ripple can be reduced. Therefore, the proposed converter possesses a smaller low-frequency output voltage ripple than the traditional AC–DC flyback converter does. In addition, the voltage stress on the output capacitor of the buck-boost converter in the proposed circuit can be varied by the turns ratio of the transformer so as to increase design elasticity. And, some experimental results are provided to verify the effectiveness of the proposed circuit.
Implementation of 14 bits floating point numbers of calculating units for neural network hardware development

An important aspect of modern automation is machine learning. Specifically, neural networks are used for environment analysis and decision making based on available data. This article covers the most frequently performed operations on floating-point numbers in artificial neural networks. Also, a selection of the optimum value of the bit to 14-bit floating-point numbers for implementation on FPGAs was submitted based on the modern architecture of integrated circuits. The description of the floating-point multiplication (multiplier) algorithm was presented. In addition, features of the addition (adder) and subtraction (subtractor) operations were described in the article. Furthermore, operations for such variety of neural networks as a convolution network - mathematical comparison of a floating point (‘less than’ and ‘greater than or equal’) were presented. In conclusion, the comparison with calculating units of Atlera was made.
Research on the Algorithm Optimization of Improved Ant Colony Algorithm- LSACA

The ant colony algorithm is an algorithm which is used to find the optimal path. As a kind of bionic evolutionary algorithm, the ant colony algorithm is inspired by the real ant colony foraging mechanisms. Firstly, this paper introduces the basic model of the ant colony algorithm. Then, aiming at the shortcomings of the ant colony algorithm, we propose a new probability formula of the optimal path and the new formula of the pheromone update. In addition, we combine the traditional ant colony algorithm with the local search algorithm and propose the improved ant colony algorithm. It is the LSACA algorithm. In the experimental analysis, we set and analyze the parameters of the algorithm. Then, we compare with the traditional algorithm to prove the feasibility and the effectiveness of the algorithm.
Facile synthesis of hollow microspherical YPO 4 : Eu 3+ /Tb 3+ using polystyrene spheres as sacrificial template and its photoluminescent properties

Monodisperse hollow microspherical YPO4:Ln3+ (Ln3+ = Eu3+/Tb3+) with diameters of around 2.5 µm have been successfully synthesised by combining a convenient homogeneous precipitation method, an ion exchange method, and a calcination process for the first time. X-ray diffraction, Fourier transform infrared, thermogravimetric analysis, scanning electron microscopy, transmission electron microscopy, and photoluminescence spectra were used to characterise the samples. Upon ultraviolet excitation, Eu3+- and Tb3+-doped microspherical YPO4 showed typical red and green emission, respectively, which provide potential applications in bioanalysis, future colour displays, light-emitting devices, and so on.
Sixty-Four Curves of Degree Six

ABSTRACT We present a computational study of smooth curves of degree six in the real projective plane. In the Rokhlin–Nikulin classification, there are 56 topological types, refined into 64 rigid isotopy classes. We developed software that determines the topological type of a given sextic and used it to compute empirical probability distributions on the various types. We list 64 explicit representatives with integer coefficients, and we perturb these to draw many samples from each class. This allows us to explore how many of the bitangents, inflection points, and tensor eigenvectors are real. We also study the real tensor rank, the construction of quartic surfaces with prescribed topology, and the avoidance locus, which is the locus of all real lines that do not meet a given sextic. This is a union of up to 46 convex regions, bounded by the dual curve.
A Resource-Efficient System Architecture for Processing Various Sensor Data in Smart home Environment

The Internet of Things (IoT) technology is gaining vast popularity and it is expected to become ubiquitous in the near future. It envisions the idea of a fully connected network of smart objects, enabling cooperative and intelligent distributed functionalities. Especially, smart homes provide innovative, automated and interactive services for residential customers through distributed and collaborative operations. In this paper the challenge of processing large amounts of sensor data at network gateways with limited memory and computing power is described. A resource-efficient system to process various heterogeneous data is introduced.
On the relationship between indenation hardness and modulus, and the damage resistance of biological materials

The remarkable mechanical performance of biological materials is based on intricate structure-function relationships. Nanoindentation has become the primary tool for characterising biological materials, as it allows to relate structural changes to variations in mechanical properties on small scales. However, the respective theoretical background and associated interpretation of the parameters measured via indentation derives largely from research on ‘traditional’ engineering materials such as metals or ceramics. Here, we discuss the functional relevance of indentation hardness in biological materials by presenting a meta-analysis of its relationship with indentation modulus. Across seven orders of magnitude, indentation hardness was directly proportional to indentation modulus, illustrating that hardness is not an independent material property. Using a lumped parameter model to deconvolute indentation hardness into components arising from reversible and irreversible deformation, we establish criteria which allow to interpret differences in indentation hardness across or within biological materials. The ratio between hardness and modulus arises as a key parameter, which is a proxy for the ratio between irreversible and reversible deformation during indentation, and the material’s yield strength. Indentation hardness generally increases upon material dehydration, however to a larger extend than expected from accompanying changes in indentation modulus, indicating that water acts as a ‘plasticiser’. A detailed discussion of the role of indentation hardness, modulus and toughness in damage control during sharp or blunt indentation yields comprehensive guidelines for a performance-based ranking of biological materials, and suggests that quasi-plastic deformation is a frequent yet poorly understood damage mode, highlighting an important area of future research.
Every zero-dimensional homogeneous space is strongly homogeneous under determinacy

All spaces are assumed to be separable and metrizable. We show that, assuming the Axiom of Determinacy, every zero-dimensional homogeneous space is strongly homogeneous (i.e. all its non-empty clopen subspaces are homeomorphic), with the trivial exception of locally compact spaces. In fact, we obtain a more general result on the uniqueness of zero-dimensional homogeneous spaces which generate a given Wadge class. This extends work of van Engelen (who obtained the corresponding results for Borel spaces), complements a result of van Douwen, and gives partial answers to questions of Terada and Medvedev.
A Test Purpose and Test Case Generation Approach for SOAP Web

—SOA Web services are now supported by most of major software development companies and industry. To be reliable, these ones require to be developed with respect to a complete software development life cycle and, in particular, they need to be tested. Test purpose-based methods are black box testing techniques which take advantage of reducing the time required for test derivation in comparison with exhaustive methods. Nevertheless, test purposes must be constructed manually. This paper proposes some test purpose generation methods for SOAP Web services, modelled by Symbolic Transition Systems (STS). Prior to generate test purposes, we augment the speciﬁcation with the SOAP environment, to beneﬁt from the messages generated by SOAP processors which give new information about the operations and the faults received. Then, we describe the test case generation from test purposes by synchronizing them with the speciﬁcation. Test cases are ﬁnally translated into XML to be used later by the Soapui tool.
Perturbation Analysis Of Optimization Problems

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A Novel Approach Of Privacy Preserving Data With Anonymizing Tree Structure

Data anonymization techniques have been proposed in order to allow processing of personal data without compromising user’s privacy. the data management community is facing a big challenge to protect personal information of individuals from attackers who try to disclose the information. So data anonymization strategies have been proposed so as to permit handling of individual information without compromising user’s privacy. Data anonymization is a type of information sanitization whose intent is privacy protection. It is the process of either encrypting or removing personally identifiable information from data sets, so that the people whom the data describe remain anonymous. We are presenting k(m;n)-anonymity privacy guarantee which addresses background knowledge of both value and structure using improved and automatic greedy algorithm. (k (m,n) - obscurity ensure) A tree database D is considered k (m,n) - unknown if any assailant who has foundation information of m hub names and n auxiliary relations between them (ancestor descendant), is not ready to utilize this learning to distinguish not as much as k records in D. A tree dataset D can be transformed to a dataset D0 which complies to k (m,n) - anonymity, by a series of transformations.The key idea is to replace rare values with a common generalized value and to remove ancestor descendant relations when they might lead to privacy breaches.
Security camera video authentication

The ability to authenticate images captured by a security camera, and localise any tampered areas, will increase the value of these images as evidence in a court of law. This paper outlines the challenges in security camera video authentication, and discusses the reasons why fingerprinting, a robust type of digital signature, provides a solution preferable to semi-fragile watermarking. A fingerprint based upon block DC differences is described, and the tamper detection performance is assessed both theoretically and experimentally, the latter using an automated method of 'tampering' images.
Cosmology, initial conditions, and the measurement problem

The assumption that a complete description of an early state of the universe does not privilege any position or direction in space leads to a unified account of probability in cosmology, macroscopic physics, and quantum mechanics. Such a description has a statistical character. Deterministic laws link it to statistical descriptions of the cosmic medium at later times, and because these laws do not privilege any position or direction in space, the same must be true of these descriptions. If the universe is infinite, we can identify the probability that the energy density at a particular instant and a particular point in space (relative to a system of spacetime coordinates in which the postulated spatial symmetries are manifest) lies in a given range with the fractional volume occupied by points where the energy density lies in this range; and similarly with all other probabilities that figure in the statistical description. The probabilities that figure in a complete description of the cosmic medium at any given moment thus have an exact and objective physical interpretation. The statistical entropy and the information associated with each cosmological probability distribution are likewise objective properties of the universe, defined in terms of relative frequencies or spatial averages.
A NOVEL BASED APPROACH TO INVESTIGATE DISTINCTIVE REGION OF BRAIN CONNECTIVITY USING NEURAL MAPS

Introduce two-dimensional neural maps for exploring connectivity in the brain. Main goal, which are primarily in the field of tractography visualization. First Objectives is a 2D path representation of tractography data sets that, in contrast to the previously used 2D point representation. Main objective is to achieve abstraction and filtration, can help users overcome the difficulties of visual complexity. While abstraction involves simplification and generalization, filtration here entails clustering and hierarchization. To obtain a hierarchy of 2D neural diagrams from a whole-brain tractogram, these can be considered immersions of neural paths in the plane and link the 2D neural maps with the 3D stream tube representations. The human brain is massive interconnected organ, consisting tens of millions of nerve fibers grouped into hundreds of major tracts. While the ultimate goal of neuroscience is to understand how it works, you may not be aware that understanding the brain's structure is also an important goal in itself. The brain's structure is very unpredictable, with nerve fiber clusters much of the time weaving together in hard-to-predict pathways. A basic test that neuroscientists face is the manner by which to scan and break down the unpredictable pathway. The central core part of the brain known as the white matter, includes moderately huge fiber tracts that intervene correspondence between neurons at broadly differentiated areas. Information about these white matter associations may as well upgrade
Cognitive Analysis of Metaphor Domains of Spatial Dimensionality Words "high/low" in Children's Literary Language

Based on the theories of Lexical Semantics and Metaphor of Cognitive Linguistics,using the views and methods of cognitivism,this paper analyzes the appearance time,orders and the frequency of seven spatial dimensionality words in the compositions which were almost 1.25 million words,and which were written by primary and middle school students.Especially it analyzes the metaphor domains of the "high/low" to probe into the relationship between the development of abstract and space conceptions.
Trust and reputation evaluation for Web services based on user experience

Trust and reputation are important to Web services. Short of trust and reputation evaluation, service providers and customers may not benefit from Web services. However, evaluation often puts emphasis on QoS. Actually, the factors of influencing service trust and reputation should include QoS and degree of customer satisfaction. Based on the consideration, the paper put forward trust and reputation evaluation system, which collected user feedback and computed meeting ratio of QoS. To avoid QoS cheating, QoS should be mended by results of QoS statistics. The simulation results indicate that it can make a reasonable evaluation of trust and reputation even on the conditions of fake services disturbance and QoS distortion.
Mixed key management scheme based on domain for wireless sensor network

Concerning the existing problems in the current key management strategies, lower connectivity, higher storage consumption and communication cost, this paper proposed a mixed key management scheme based on domain for Wireless Sensor Network( WSN). The scheme divided the deployment area into a number of square areas, which consisted of member nodes and head nodes. According to their pre-distribution key space information, any pair of nodes in the same area could find a session key, but the nodes in different areas could only communicate with each other through head nodes. The eigenvalues and eigenvectors of the multiple asymmetric quadratic form polynomials were computed, and then the orthogonal diagonalization information was got, by which the head nodes could achieve identification and generate the session key between its neighbor nodes. The analysis of performance shows that compared with the existing key management schemes, this scheme has full connectivity and a bigger improvement in terms of communication overhead, storage consumption and safety.