Miracle-dz/UniFAR-FTUs huggingface dataset:
Revisiting Conditional R enyi Entropies and Generalizing Shannon's Bounds in Information Theoretically Secure Encryption ?

Information theoretic cryptography is discussed based on conditional Renyi en- tropies. Our discussion focuses not only on cryptography but also on the denitions of con- ditional Renyi entropies and the related information theoretic inequalities. First, we revisit conditional Renyi entropies, and clarify what kind of properties are required and actually satised. Then, we propose security criteria based on Renyi entropies, which suggests us deep relations between (conditional) Renyi entropies and error probabilities by using sev- eral guessing strategies. Based on these results, unied proof of impossibility, namely, the lower bounds of key sizes is derived based on conditional Renyi entropies. Our model and lower bounds include the Shannon's perfect secrecy, and the min-entropy based encryption presented by Dodis, and Alimomeni and Safavi-Naini. Finally, a new optimal symmetric key encryption is proposed which achieve our lower bounds.
Computer Algorithms for Discriminating Protein Folds and Predicting Protein Folding Rates Based on Contact Information

Inter-residue interactions play an important role in governing the folding and stability of protein structures. In this work, we have analyzed the contacts between amino acid residues in different folding types of globular proteins and various ranges of folding rates. Based on amino acid contacts a novel parameter, multiple contact index has been developed for understanding protein folding rates. We have computed short, medium and long-range contacts in proteins of different folding types and rates from their sequences and structures. Utilizing the information, we have developed models for recognizing protein folds and predicting their folding rates, using machine learning techniques. Our methods showed an accuracy of 55% for discriminating 1612 globular proteins belonging to 30 different folds and an accuracy of 96% to distinguish the fast and slow folding proteins using 5-fold cross-validation method.
Approximating geometric coverage problems

We present the first study on the approximability of geometric versions of the unique coverage problem and the minimum membership set cover problem. In the former problem, one is given a family of sets of elements from some universe and aims to select sets that maximize the number of elements contained in precisely one selected set. Unique Coverage has important applications in wireless networks and it is thus natural to consider it in a geometric setting. We use the well-known (unit) disk model for wireless networks and show that Unique Coverage remains NP-hard in this case and present a polynomial-time 1/18-approximation algorithm. This algorithm is extended to the budgeted low-coverage problem, where covering can element multiple times yields less profit and we have a fixed budget to 'buy' sets. We give an asymptotic FPTAS in case the disks have arbitrary size, but bounded ply. For the case that the geometric objects are arbitrary fat objects, we show that these problems are as hard to approximate as in the general case. In the minimum membership set cover problem, the goal is to cover all elements while minimizing the maximum number of sets in which any element is contained. For unit squares and unit disks, we show that the problem remains NP-hard and does not admit a polynomial-time approximation algorithm with ratio smaller than 2 unless P=NP. For unit squares, we give a 5-approximation algorithm for instances where the optimum objective value is bounded by a constant.
Automatic generation of portrait

In this paper, an algorithm which can generate a portrait automatically from an input face image is proposed. In our approach, we adopt integral project method to distill the feather of the face, find the main organspsila location, then segment each organspsila area using an adaptive threshold, in order to present a hand paint effect, we combine the image after segmentation with the image which has been processed through neon method, This method can get a portrait of the input image automatically, and it is easy to be realized. Experimental results demonstrate the effectiveness of our techniques.
Distributed predictive control for power balancing in electric distribution networks

One of the efficient control method is the model predictive control (MPC) that calculates appropriate inputs corresponding to desired output by an optimization method and predicting future output based on related model. Then the first step of calculated input is applied to system. An important application of this control method is for controlling load-frequency and power balancing in power grids. It preserves transition power and network frequency as one of important parameters of power quality within admissible range by controlling generation. Considering the complicity of calculations in centralized architecture in large scale systems, in this paper a cooperative distributed predictive control is used that makes the calculations faster and easier and also offers good performance. However in the not too distant future, with development of smart grids, Exploitation of distributed generation in demand side and electric distribution network will be usual and it will be necessary to replace traditional control methods by smart and advanced methods. In this regard, results of the discussed control method are compared with those of the classical control of load-frequency and its proper performance is shown against load variation disturbance, with considering a power grid with 4 control zones that each zone has local generation and load.
Qualitative Researches in the Last Decade:: Review of the Journal of Educational Sociology

The purpose of this paper is to review the qualitative researches that have been carried out in the last decade, in the field of sociology of education. First, we explore the studies in the new field of “sociology of education”, which focus on the educational processes in school where students assimilate cultures under social control. These studies reveal demonstratively, for example, how a ʻmacro-levelʼ educational idea takes shape in a ʻmicro-levelʼ classroom, or how a change in the ʻmacro-levelʼ educational situation is related to a change in the ʻmicro-levelʼ classroom. Then, we examine the studies of education for the new comers, which area of study has been expanding and deepening recently. The new-comer students in Japan have been treated as minority, and researchers have applied the qualitative methods to look into the reality of the situation. Empirical researches, as well as critical ones, have led to the new studies which evaluate the educational practice theoretically. It must be noted that constructionism has played an important role on the development of qualitative researches. Social constructionists deal with educational discourse, deviant behavior and social problems, adopting observations of participants, interviews, and/ or ethnographies. And, they apply the methodology to the problems specific to educational practice. Lastly, we consider relationship between the researcher and the subject, and raise
Two quasi orthogonal space-time block codes with better performance and low complexity decoder

This paper presents two new space time block codes (STBCs) with quasi orthogonal structure for an open loop multi-input single-output (MISO) systems. These two codes have been designed to transmit from three or four antennas at the transmitter and be given to one antenna at the receiver. In this paper first, the proposed codes are introduced and their structures are investigated. This is followed by the demonstration of how the decoder decodes half of transmitted symbols independent of the other half. The last part of this paper discusses the simulation results, makes performance comparison against other popular approaches and concludes that the proposed solutions offer superiority.
Automatic extraction of text regions from document images by multilevel thresholding and k-means clustering

Textual data plays an important role in a number of applications such as image database indexing, document understanding, and image-based web searching. The target of automatic real-life text extracting in document images without character recognition module is to identify image regions that contain only text. These textual regions can then be either input of optical character recognition application or highlighted for user focusing. In this paper we propose a method which consists of three stages-preprocessing which improves contrast of grayscale image, multi-level thresholding for separating textual region from non-textual object such as graphics, pictures, and complex background, and heuristic filter, recursive filter for text localizing in textual region. In many of these applications, it is not necessary to identify all the text regions, therefor we emphasize on identifying important text region with relatively large size and high contrast. Experimental results on real-life dataset images demonstrate that the proposed method is effective in identifying textual region with various illuminations, size and font from various types of background.
Context Sensitive Spoken Language Understanding using Role Dependent LSTM layers

Neural network models have become a recent focus of investigation in spoken language understanding (SLU). To understand speaker intentions accurately in a dialog, it is important to consider the sentence in the context of the surrounding sequence of dialog turns. In this study, we use long short-term memory (LSTM) recurrent neural networks (RNNs) to train a context sensitive model to predict sequences of dialog concepts from the spoken word sequences. In this model, words of each utterance are input one at a time, and concept tags are output at the end of each utterance. The model is trained from human-to-human dialog data annotated with concept tags representing client and agent intentions for a hotel reservation task. The LSTM layers jointly represent both the context within each utterance, and the context within the dialog. The diﬀerent roles of client and agent are modeled by switching between role-dependent layers. To evaluate the performance of our models, we compared label accuracies using Logistic Regression (LR) and LSTMs. The results show 70.8% for LR, 72.4% for LR w/ word2vec, 78.8% for context sensitive LSTMs, and 84.0% for role dependent LSTMs. We conﬁrmed signiﬁcant improvement by using context sensitive role dependent LSTMs.
Homography-Based Extrinsic Self-Calibration for Cameras in Automotive Applications

In this paper we present a method to calibrate the extrinsic parameters of a monocular camera on a moving vehicle. The method is based on a homography which describes the image motion on the road between two camera shots. Therefore, only the road surface has to be visible in the pair of images. A reasonable definition of the world coordinate system in combination with the use of epipolar geometry and odometric data enables the parameterization of the homography matrix with a single parameter. A measure is introduced which evaluates how well the image motion matches to motion described by the homography. The minimization of this one-dimensional error measure finally lead to the extrinsic parameters.
TSHC: Trusted Scheme for Hadoop Cluster

Hadoop is a Apache project, which has be used at many fields, such online media companies including Facebook, Yahoo, educational service, government. However, there are some security risks or untrust risks in the Hadoop cluster. In the paper, a Trusted Scheme for Hadoop cluster (TSHC) to protect data security with Trusted Computing and cryptography technology is proposed. We first propose the trusted architecture framework for Hadoop cluster with Trusted Computing Base. And then some protocols, which are key management, node trusted management protocol, client access management protocol, node access management protocol, job executing management and data storage and update management, are developed. Moreover, the security analysis proves that the TSHC can efficiently meet the security requirement of Hadoop.
An efficient method for the unmanned aerial vehicle image denoising

An efficient method for the unmanned aerial vehicle (UAV) image denoising is proposed by combining an adaptive wavelet thresholding denoising and the image enhancement method in this paper. This method is aimed at improving the effect of the wavelet thresholding denoising method and enhancing the edge of the image. An adaptive threshold value which changes with the change of the decomposition scale and the direction of the subband is selected for denoising. After wavelet denoising, the image enhancement method is used for enhancing the edge of the image. Experimental results show that, compared with the other methods, the proposed method yields bigger peak signal-to-noise ratio and superior visual image quality-measured by universal image quality index. It also retains more edges and details of the image.
Design and Implementation of Interactive TPEG-UCM Application Service Using T-DMB

In Korea, the T-DMB (terrestrial-digital multimedia broadcasting) commercial service was successfully launched. However, T-DMB service providers are very weak for beneficial business because T-DMB A/V services have been started free of charge. Therefore, they want to have pay services like data services. Among these data services, the TTI (Traffic and Travel Information) service based on TPEG (Transport Protocol Experts Group) is proposed as a killer application to overcome financial limitations. At present, the TPEG service is not much popular as it fails to satisfy the users’ demands in various aspects. Therefore, to overcome a lack of variety and unidirectional of the existing TPEG application services, in this paper, it is proposed a novel TPEG-UCM (User Created Message) application service. The proposed service uses individual bidirectional media which is initiated and interacted by users. Also, the proposed service is integrated well into the existing TPEG service systems. The usability and the operability of the proposed method are verified through the experiment. KeywordsTPEG; TTI; DMB; Interactive; Bidirectional
IJESRT INTERNATIONAL JOURNA Video Shot Cut Boundary Detection using Histogram

In this paper we will be discussing about Video shot boundary detection using histogram differences. We can use color histogram as well as gray scale histogram. This technique is able to differentiate abrupt shot boundary detection. The aim of this method is to provide a simple and fast algorithm to work in real time with high performance in video indexing tool. In this pap Introduction Shot Boundary Detection (SBD) appeared in the 1990's. It has been deeply studied in recent years and has found applications in many domains such as video indexing, video compression, video access and others. It is a basic task of video temporal segmentation. It is closely related to the video making method. It is a way to divide video in many different parts, which are easy to manage. Video Shot Boundary Detection algorithms have to challenge the difficulty of finding shot boundaries in the presence of camera, motion of the objects and illumination variation. Moreover, different shot boundaries may present very different appearances like abrupt temporal changes or smooth temporal transitions. Shot Boundary Detection has been an area of active research. Many automatic techniques have been developed to detect frame transition in video sequences. There are all together many ways of detecting shot boundary detection. The simplest way is by comparing the pixel values of 2 corresponding frames [1]. The way alternate to pixel matching is using a gray-scale or color histogram [2]. Another way of detecting shot boundary is by edge change [3]. Other methods use predefined models, objects, regions or spatio-temporal sub-sampling to detect camera breaks [4]. In this paper we present a simple and a fast method for detecting video shot boundary based on gray-scale and color histogram. The algorithm detects abrupt shot changes both using gray-scale as well color frames. The simplicity of this method is due to its low complexity of computation and that all the further analysis is based on 1D signal. Abstract In this paper we will be discussing about Video shot boundary detection using histogram differences. We stogram as well as gray scale histogram. This technique is able to differentiate abrupt shot boundary detection. The aim of this method is to provide a simple and fast algorithm to work in real time with high performance in video indexing tool. In this paper we give the overview of our approach and summary of the result. Shot Boundary Detection (SBD) …
Long-Acting Injectable Antipsychotics for Prevention of Relapse in Bipolar Disorder: A Systematic Review and Meta-Analyses of Randomized Controlled Trials

Background: This meta-analysis of randomized controlled trials aimed to examine the advantages of long-acting injectable antipsychotics over placebo or oral medications regarding efficacy and safety for patients with bipolar disorder. Methods: Two categorical meta-analyses of randomized controlled trials were performed to compare study-defined relapse rate (primary), discontinuation rates, and individual adverse events: (1) risperidone-long-acting injectable vs placebo, and (2) long-acting injectable antipsychotics vs oral medications. Results: We identified 7 randomized controlled trials (n=1016; long-acting injectable antipsychotics [flupenthixol (1 randomized controlled trial) and risperidone (6 randomized controlled trials)=449]; oral medications [mood stabilizers, antidepressants, antipsychotic, or any combination of these agents=283]; and placebo=284). Risperidone-long-acting injectable antipsychotic was superior to placebo for study-defined relapse rate (risk ratio=0.63, P<.0001), relapse of manic symptoms (risk ratio=0.42, P<.00001), and all-cause discontinuation (risk ratio=0.75, P=.007). Risperidone-long-acting injectable was associated with higher incidence of prolactin-related adverse events (risk ratio=4.82, P=.001) and weight gain (risk ratio=3.80, P<.0001) than placebo. The pooled long-acting injectable antipsychotics did not outperform oral medications regarding primary outcome but with significant heterogeneity (I2=74%). Sensitivity analysis, including only studies with rapid cycling or high frequency of relapse patients, revealed that long-acting injectable antipsychotics were superior compared to oral medications (I2=0%, RR=0.58, P=.0004). However, the comparators in this sensitivity analysis did not include second-generation antipsychotic monotherapy. In sensitivity analysis, including only studies with second-generation antipsychotic monotherapy as the comparator, long-acting injectable antipsychotics did not outperform second-generation antipsychotic monotherapy. Risperidone-long-acting injectable was also associated with higher incidence of prolactin-related adverse events than oral medications (RR=2.66, P=.03). Conclusions: Long-acting injectable antipsychotics appear beneficial for relapse prevention in patients with rapid cycling. Furthermore, randomized controlled trials comparing long-acting injectable antipsychotics and oral second-generation antipsychotic using larger samples of rapid cycling patients are warranted.
The Frequency of Binary Stars in the Core of 47 Tucanae

Differential time series photometry has been derived for 46,422 main-sequence stars in the core of 47 Tucanae. The observations consisted of near-continuous 160 s exposures alternating between the F555W and F814W filters for 8.3 days in 1999 July with the Wide Field Planetary Camera 2 on the Hubble Space Telescope. Using Fourier and other search methods, 11 detached eclipsing binaries and 15 W Ursa Majoris stars have been discovered plus an additional 10 contact or near-contact noneclipsing systems. After correction for nonuniform area coverage of the survey, the observed frequencies of detached eclipsing binaries and W UMa stars within 90'' of the cluster center are 0.022% and 0.031%, respectively. The observed detached eclipsing binary frequency, the assumptions of a flat binary distribution with log period, and assuming that the eclipsing binaries with periods longer than about 4 days have essentially their primordial periods imply an overall binary frequency of 13% ± 6%. The observed W UMa frequency and the additional assumptions that W UMa stars have evolved to contact according to tidal circularization and angular momentum loss theory and that the contact binary lifetime is 109 yr imply an overall binary frequency of 14% ± 4%. An additional 71 variables with periods from 0.4 to 10 days have been found, which are likely to be BY Draconis stars in binary systems. The radial distribution of these stars is the same as that of the eclipsing binaries and W UMa stars and is more centrally concentrated than average stars but less so than the blue straggler stars. A distinct subset of six of these stars falls in an unexpected domain of the color-magnitude diagram, comprising what we propose to call red stragglers.
On the logic of theory change: Partial meet contraction and revision functions

Abstract This paper extends earlier work by its authors on formal aspects of the processes of contracting a theory to eliminate a proposition and revising a theory to introduce a proposition. In the course of the earlier work, Gärdenfors developed general postulates of a more or less equational nature for such processes, whilst Alchourrón and Makinson studied the particular case of contraction functions that are maximal, in the sense of yielding a maximal subset of the theory (or alternatively, of one of its axiomatic bases), that fails to imply the proposition being eliminated. In the present paper, the authors study a broader class, including contraction functions that may be less than maximal. Specifically, they investigate “partial meet contraction functions”, which are defined to yield the intersection of some nonempty family of maximal subsets of the theory that fail to imply the proposition being eliminated. Basic properties of these functions are established: it is shown in particular that they satisfy the Gärdenfors postulates, and moreover that they are sufficiently general to provide a representation theorem for those postulates. Some special classes of partial meet contraction functions, notably those that are “relational” and “transitively relational”, are studied in detail, and their connections with certain “supplementary postulates” of Gàrdenfors investigated, with a further representation theorem established.
Intelligent Detection of Cracks in Metallic Surfaces Using a Waveguide Sensor Loaded with Metamaterial Elements

This work presents a real-life experiment implementing an artificial intelligence model for detecting sub-millimeter cracks in metallic surfaces on a dataset obtained from a waveguide sensor loaded with metamaterial elements. Crack detection using microwave sensors is typically based on human observation of change in the sensor's signal (pattern) depicted on a high-resolution screen of the test equipment. However, as demonstrated in this work, implementing artificial intelligence to classify cracked from non-cracked surfaces has appreciable impacts in terms of sensing sensitivity, cost, and automation. Furthermore, applying artificial intelligence for post-processing the data collected from microwave sensors is a cornerstone for handheld test equipment that can outperform rack equipment with large screens and sophisticated plotting features. The proposed method was tested on a metallic plate with different cracks, and the experimental results showed good crack classification accuracy rates.