Miracle-dz/UniFAR-FTUs huggingface dataset:
Collaborative Intelligent Computing System——Theoretical Model with Its Application

This study is aimed at revealing the view of Collaborative Intelligence derived from the mode of two types of Information Processing,namely computer data and human knowledge,as well as the theoretical model of Collaborative Intelligence Computing System with its application guided by this view.It involves a verifiable method.On the one hand,within the range of n2 matrix,the two basic algorithms,which are enumeration based on divergence equivalent to the way of 2n and search based on convergence equivalent to the way of 1/2n,can be used as tasks of pure digital computing.It is characterized by satisfying the condition that the value-taking of n does not influence computational efficiency of the Indirect Computational Tasks;On the other hand,within the range of n2 matrix corresponding to each grid,Indirect Formalization Processing is used towards single character,which is characterized not only by that single-Zi-syllable,namely Yan,can be calculated indirectly,but also by that two-Zi-syllable and multi-Zi-syllable,namely Yu,can also be calculated indirectly.At the same time,the frequencies of the reuse of Yan and Yu can both be easily counted and calculated indirectly.Thus,this model can not only lead us to revealing the double technique route toward Chinese Information Processing or Natural Language Understanding,but also to verifying the hypothesis of Informatics Basic Laws,which dominate the Indirect Computing Model and Indirect Formalization Method.Eventually,it can be concluded that the previous two verifiable empirical methods are much more than a simple sum of these modes of the two types of Information Processing,namely computer data and human knowledge,but the theoretical model of Collaborate Intelligent Computing System or the third kind of Information Processing Mode with its application generated by Rational Division of labor,highly Collaborative Synergy,such as academic forefront of various journals and conference abstracts home and abroad,answers to Frequent Answered Questions of a variety of software and their Help Files,individual records of Collaborative Intelligent Computing System users,limited symbols of natural language and its limited rules inherent in the diverse combination process or the reuse process and so on,which are the Computer-Aided Analysis of all kinds of Bilingual Information.The main target of such cloud-based computing is the customers who need Computer-Aided Bilingual Knowledge and Information Processing in various types of creative cooperative and productive activities,such as teaching,research,production,learning and using.
MFPSM:efficient algorithm for mining maximum frequent pagesets based on bi-directional constraint

Mining maximum frequent page set is a key to web usage mining applications,since user's traversal patterns and motivation are latent in sessions at some time segment.According to FP-tree,a Frequent Page Tree structure with Dwell Time(abbreviated as FPDT-tree) is designed.Utilizing FPDT-tree to store,compress the session database that is constrained by the bi-directional dwell time,and simplify the configuration of dwell time thresholds in mining.A new algorithm called Maximum Frequent Page Set Mining is presented,which traversals quickly FPDT-tree and discovers maximum frequent page set from the sessions.In the time constraint environment,experimental results show that MFPSM can significantly improve the execution time as long as the decision-maker's(user) gives the appropriate dwell time constraints.
A Hybrid Rate Control Algorithm for Wi-Mesh Network

A new HRC (hybrid rate control) algorithm for Wi-Mesh Network based on ARF protocol and reverse channel estimation mechanism is proposed.In HRC algorithm,the transmission rate would not be raised when the channel state is stable,and could be adjusted under good condition when the channel state changes fast.Thus the system could gain better performance.The simulation results show that HRC protocol could raise the success probability of data-frame sending and improve the efficiency of wireless spectrum as compared with ARF protocol.
HPC Made Easy: Using Docker to Distribute and Test Trilinos

Virtualization is an enticing option for computer science research given its ability to provide repeatble, standardized environments, but traditional virtual machines have too much overhead cost to be practical. Docker, a Linux-based tool for operating-system level virtualization, has been quickly gaining popularity throughout the computer science field by touting a virtualization solution that is easily distributable and more lightweight than virtual machines. This thesis aims to explore if Docker is a viable option for conducting virtualized research by evaluating the results of parallel performance tests using the Trilinos project.
Protected Secret Sharing and its Application to Threshold Cryptography

In the secret reconstruction of Shamir’s (t,n) secret sharing scheme (SS), shares released by shareholders need to be protected otherwise, non-shareholders can also obtain the secret. Key establishment protocol can establish pairwise keys for any pair of shareholders. Then, shareholders can use these pairwise keys to protect shares in the secret reconstruction process. However, adding a key establishment in the secret reconstruction slows down the process significantly. Shamir’s SS is based on a univariate polynomial. Shares generated by a bivariate polynomial enable pairwise keys to be shared between any pair of shareholders. But we proposed a new type of SS, called protected secret sharing scheme (PSS), in which shares of shareholders can not only be used to reconstruct the secret but also be used to protect the secrecy of shares in the secret reconstruction process. Thus, the recovered secret is only available to shareholders but not to non-shareholders. A basic (t,n) PSS based on a bivariate polynomial is proposed. Furthermore, we introduce to use this basic PSS in the applications of threshold cryptography. The PSS is unique since it protects the secrecy of the recovered secret in a very efficient way.
The Optimization Algorithm for CR System Based on Optimal Wavelet Filter

5G network is a heterogeneous large-scale network. Cognitive Radio (CR) technology can be used to realize selection based on the communication time, communication resources, and communication requirement so as to improve the system performance of the whole communication system. Cognitive Radio (CR) system based on wavelet packet owns better flexibility and bandwidth efficiency. The optimal wavelet packet filter optimization algorithm is proposed in the paper for guaranteeing un-licensed user’s (un-LU) data transmission rate and optimizing the performance of system. The intelligent search algorithm is used to obtain the optimal wavelet filter. The simulation results show that the Intercarrier Interference (ICI) and bit error rate (BER) performance of the new optimal wavelet filter algorithm without sacrificing any un-LU’s subcarriers is better than other three masking subcarriers algorithms.
Dynamics of nanoparticle-protein corona: formation, evolution and insight on protein structure

In complex physiological media proteins form transient complexes with nanoparticles (NPs), mediated by competitive binding between proteins and NP surfaces, leading to the formation of a stable (hard) protein corona (HPC). Understanding the formation and the dynamics of this interaction is crucial for designing NP-based therapies, since HPC determines the biological identity of the NPs in vivo. The strong affinity between NPs surfaces and proteins can compensate the destabilization forces that colloidal NPs experience in high ionic strength media, stabilizing them. This interaction is immediate (soft -non stable –PC) and evolves with time (HPC). Nowadays, different studies regarding HPC composition show contradictory results. The complexity of serum composition, being NP size in the same range of proteins, and lack of reliable methods to determine composition of HPC, are behind these controversies. Several underestimated parameters regarding the response of NPs in physiological media (aggregation, dissolution) are critical determinants to be carefully addressed to better understand the formation of the HPC. In this context, it is necessary to develop simple but efficient and reliable protocols to study these processes. In this work, consequences of NP-PC formation providing a simple and reliable approach for determining both composition and physicochemical characterization of the HPC, and the implication for protein structures, is shown. In the first part, the hardening of the PC on 20 nm AuNPs, as a model case of metallic NP widely used in medicine, was monitored over time by UV-Vis spectroscopy, Dynamic Light Scattering and Z-Potential. Results of the process of HPC formation with only albumin or IgG were compared to results of HPC formation in serum. Time evolution of the
Interaction between succinic acid and sulfuric acid–base clusters

Abstract. Dicarboxylic acids likely participate in the formation of pre-nucleation clusters to facilitate new particle formation in the atmosphere, but the detailed mechanism leading to the formation of multicomponent critical nuclei involving organic acids, sulfuric acid (SA), base species, and water remains unclear. In this study, theoretical calculations are performed to elucidate the interactions between succinic acid (SUA) and clusters consisting of SA-ammonia (AM)∕dimethylamine (DMA) in the presence of hydration of up to six water molecules. Formation of the hydrated SUA⚫SA⚫ base clusters is energetically favorable, triggering proton transfer from SA to the base molecule to form new covalent bonds or strengthening the preexisting covalent bonds. The presence of SUA promotes hydration of the SA⚫AM and SA⚫AM⚫DMA clusters but dehydration of the SA⚫DMA clusters. At equilibrium, SUA competes with the second SA molecule for addition to the SA⚫ base clusters at atmospherically relevant concentrations. The clusters containing both the base and organic acid are capable of further binding with acid molecules to promote subsequent growth. Our results indicate that the multicomponent nucleation involving organic acids, sulfuric acid, and base species promotes new particle formation in the atmosphere, particularly under polluted conditions with a high concentration of diverse organic acids.
Modeling and Control of Micro-Grid Powered by Solar and Wind Energies

The number of installations of Micro-Grid or intelligent micro power networks will increase to quadruple by 2020.The purpose is to reduce the cost and the consumption of electricity in transmission and distribution networks, using a hybrid system powered by solar and wind sources, as well as integrating storage devices. This paper reviews and discusses the Micro-Grid Model. It describes various Micro-Grid components and different configurations. It also presents the model of two generation units (Photovoltaic and Wind Turbine). Then, a comparative study of different battery types used for large-scale electricity storage is carried out, followed by a review of control strategies. Full Text: PDF DOI: http://dx.doi. org/10.11591/ijpeds.v8. i1.pp402-416
Privacy-Preserving One-Class Support Vector Machine with Vertically Partitioned Data

We establish a new model of privacy-preserving one-class support vector machine (SVM) based on vertically partitioned data. Every participant holds all the data with a part of attributes. They apply different random matrices to establish their own kernel matrix. By sharing these partial kernel matrices, we construct a global kernel matrix and establish linear and nonlinear privacy-preserving models. Experimental results on benchmark data sets verify the validity of the proposed models.
Tomographic X-ray data of carved cheese

This is the documentation of the tomographic X-ray data of a carved cheese slice. Data are available at www.fips. fi/dataset.php, and can be freely used for scientific purposes with appropriate references to them, and to this document in this http URL The data set consists of (1) the X-ray sinogram of a single 2D slice of the cheese slice with three different resolutions and (2) the corresponding measurement matrices modeling the linear operation of the X-ray transform. Each of these sinograms was obtained from a measured 360-projection fan-beam sinogram by down-sampling and taking logarithms. The original (measured) sinogram is also provided in its original form and resolution.
社交网络影响力传播研究 (Research on influence diffusion in social networks)

With the wide spread of Internet and big data research and applications, influence diffusion research in social networks becomes one of the hot topics in data mining and social networks analysis in recent years. The main results on social influence diffusion research from the field of computer science in the last decade, which covers the three main areas -influence diffusion modeling, influence diffusion learning, and influence diffusion optimization, were summarized. Different techniques, such as stochastic modeling, data mining, algorithmic optimization, and game theory, were demonstrated in their application to influence diffusion research. Finally, some discussions on the current issues, challenges and future directions in influence diffusion research and applications were provided.
Nitrogen-Polar Polarization-Doped Field-Effect Transistor Based on Al0.8Ga0.2N/AlN on SiC With Drain Current Over 100 mA/mm

This letter reports the demonstration of N-polar Al<sub>0.8</sub>Ga<sub>0.2</sub>N/AlN continuously-graded-channel polarization-doped field-effect transistors (PolFETs) on SiC. A PolFET with a source to drain distance of <inline-formula> <tex-math notation="LaTeX">$12~\mu \text{m}$ </tex-math></inline-formula> exhibited a maximum drain current of 62.8 mA/mm and an ON/OFF current ratio of <inline-formula> <tex-math notation="LaTeX">$1.1\times 10^{{4}}$ </tex-math></inline-formula>. The maximum drain current was stable between 20 °C and 250 °C operating temperatures. With the addition of 30-nm-thick Al<sub>2</sub>O<sub>3</sub> gate insulator the maximum drain current increased to 126 mA/mm.
Handling resource intensive hybrid cloud services from iOS devices

Cloud computing and mobile computing domains have advanced rapidly and are promising technologies for the future. As the number of mobile devices continues to grow the applications for them also become more sophisticated. To satisfy the need for processing large amounts of data, developers can benefit from using various cloud resources. Cloud computing becomes mobile when a mobile device tries to access the shared pool of computing resources provided by the cloud, on demand. Mobile applications take advantage of the elasticity of the cloud to remotely process the process intensive tasks at the same time maintaining a soft real time response behavior. To support accessing the cloud services from the mobile phones, Mobile Cloud Middleware (MCM) has been realized by Srirama et al. at UT. MCM mainly handles the interoperability issues for services accessed from multiple clouds. However, when a mobile application needs to perform a task which is expected to be time consuming, as it requires involving intensive data processing and depends on mobile cloud services, it cannot hang the mobile phone until the response arrives. As a solution to address these issues, the thesis incorporated asynchronous notification framework into the MCM, especially for iOS devices.
Data Integration: a Case Study in the Financial Services Industry

Current economic conditions result in banks participating in multiple mergers and acquisitions. This results in banks inheriting silo and heterogeneous systems. For banks to remain competitive, they must create a strategy to integrate data from these acquired systems in a dynamic, efficient, and consumable manner. This research considers a case study of a large financial services company that has successfully integrated data from different sources. In addition this research investigates endeavors that experts in the field have undertaken to develop architectures that address the problems with data integration and appropriate
Exploring Gender, Race, and Sexuality with Social Media Data

We present a full day, hands-on workshop that will provide an opportunity for researchers in our community to explore social media data and ask questions about the intersectionalities of gender, race, and sexuality. We will discuss scholarly questions and methods related to application of social media data analysis and the implications of using, presenting, and communicating results in research contexts. Workshop participants will learn how to access and analyze data using various tools and methods, drawing specifically on a Twitter dataset collected May-June 2014 during the trending hashtag #YesAllWomen. Selected participants will also present their own work to foster opportunities for targeted discussion and continued collaboration. The goals of this workshop are not only to build community but also to enable researchers to begin collecting and analyzing social media data to further their own work. The workshop emphasizes the importance of analyzing social media data ethically, respecting and engaging the sometimes vulnerable and marginalized populations who may have generated the data.
Image transition region extraction and segmentation based on LDC

A novel algorithm for the image transition region extraction and segmentation is presented based on local definition-complexity of the image.At first,the local definition of the original image is calculated to get a definition image,which enhanced the transition region′s grey level.Then the local complexity of the definition image is calculated and transition region extraction threshold is gotten based on the complexity curve.At last,segmentation is made to the original image according to the threshold value obtained from the extracted transition region histogram.Experiment results demonstrate that the proposed algorithm achieves a better transition region extraction and segmentation performance.
Exploring Social Network Analysis in Blended Learning Teacher Training Programs

Learning Analytics is an educational application of web analytics and it is used to analyze the learners’ activities on educational platforms, in order to predict their behaviour. Learning Analytics reflects a field at the intersection of numerous academic disciplines and is using different methods like: statistics, visualizations, data/web mining, and social network analysis. Social network analysis aim is to discover patterns in individual interactions. Network analysis is based on the intuitive notion that these patterns are important attributes of the individuals’ lives. The social network analysis can be made with different software applications and it’s very important to support networked learning. Learning Analytics tools for social network analysis are providing a framework for interpreting and developing an understanding of the observed patterns of exchanges that occur between social actors. The on-line / blended educational programs from the last decades have collected an enormous quantity of data. These data include initial evaluation information, data from the training process and results of the training program. These data can be used to validate the learning analytics theory. Since the definition and purpose of learning analytics is still disputed, comparing the predictions results obtained on the basis of initial data with the final results obtained by learners can contribute to the validation of such applications. This article present the findings and conclusions obtain after analyzing series of forum posts on the educational platforms used in teachers training programs.
Handbook of applied fisheries reproductive biology for stock assessment and management

The handbook is structured in five chapters and additionally, it includes a Glossary with definition of standard terminology commonly used in these types of studies. Chapters are being published online as they are finished. Three of these chapters are already available (see the link below): Chapter 1. Introduction to Fish Reproductive Ecology Chapter 2. Data Collection and Statistics Chapter 3. Maturity (http://hdl.handle.net/10261/87787) Chapter 4. Egg Production (http://hdl.handle.net/10261/87768) Chapter 5. Elasmobranches Reproductive Potential (http://hdl.handle.net/10261/87795) Glossary
Transferring Skin Weights to 3D Scanned Clothes

We present a method for transferring deformation weights of a human character to three‐dimensional (3D) scanned clothes. First, clothing vertices are projected onto a character skin. Their deformation weights are determined from the barycentric coordinates of the projection points. For more complicated parts, such as shoulders and armpits, continuously moving planes are constructed and employed as projection reference planes. Clothing vertices on a plane are projected onto the intersection curve of the plane with a character skin to achieve a smooth weight transfer. The proposed method produces an initial deformation for physically based clothing simulations. We demonstrated the effectiveness of our method through several deformation results for 3D scanned clothes.
Um software de reconhecimento de voz para português brasileiro

This work describes a speech recognition software for Brazilian Portuguese. The main objective is to build a system for large vocabulary continuous speech recognition, able to be used in real-time applications. The concepts, characteristics and all steps needed for the construction of such systems are presented. Several resources were produced and made available: acoustic and language models, new voice and text corpora. The text corpus has been built through the extraction and automatic formatting of text from newspapers on the Internet. In addition, two voice corpora were produced, one based on audiobooks and another specifically developed to simulate real-time tests. This work also proposes the use of speaker adaptation techniques for solving the acoustic mismatch problem between speech corpora. Finally, an application programming interface is presented in order to facilitate using the open-source Julius speech decoder. Performance tests are also presented, comparing the developed system with a commercial software.