Miracle-dz/UniFAR-FTUs huggingface dataset:
Non-linear Similarity Learning for Semantic Compositionality

The notion of semantic similarity between text data (e.g., words, phrases, sentences, and documents) plays an important role in natural language processing (NLP) applications such as information retrieval, classification, and extraction. Recently, word vector spaces using distributional and distributed models have become popular. Although word vectors provide good similarity measures between words, phrasal and sentential similarities derived from composition of individual words remain as a difficult problem. To solve the problem, we focus on representing and learning the semantic similarity of sentences in a space that has a higher representational power than the underlying word vector space. In this paper, we propose a new method of non-linear similarity learning for compositionality. With this method, word representations are learned through the similarity learning of sentences in a high-dimensional space with implicit kernel functions, and we can obtain new word representations inexpensively without explicit computation of sentence vectors in the high-dimensional space. In addition, note that our approach differs from that of deep learning such as recursive neural networks (RNNs) and long short-term memory (LSTM). Our aim is to design a word representation learning which combines the embedding sentence structures in a low-dimensional space (i.e., neural networks) with non-linear similarity learning for the sentence semantics in a high-dimensional space (i.e., kernel methods). On the task of predicting the semantic similarity of two sentences (SemEval 2014, task 1), our method outperforms linear baselines, feature engineering approaches, RNNs, and achieve competitive results with various LSTM models.
Recognition of convoys with airborne adaptive monopulse radar

A technique for recognition of extended targets on the ground, in particular convoys, by air- or space-based radar is presented. The technique is based on adaptive monopulse in conjunction with space-time adaptive processing for clutter and interference rejection. It is demonstrated that the standard deviation of the azimuth and radial target velocity estimates of the space-time adaptive monopulse can be exploited to recognise a potential spatial extension of a moving target. (5 pages)
Review Paper on Two Factor Authentication Using Mobile Phone (Android)

In this paper we describe the methods for implementing connectionless approach for stronger authentication. This connectionless approach includes the two factor authentication using mobile phone (Android). The main purpose of this method is to provide the stronger authentication in online transaction. Mobile phone is used for the purpose of generation of OTP. It improves the security of Internet payments by providing an additional password to the user. Using the password the user can successfully make his payment. Online card transactions over Internet need enhanced security. Secure processing system facilitates additional security by way of a cardholder-chosen password, which is known only to the cardholder. Dynamic password authentication is one solution that uses the added security of credit cards to offer better protection against online fraud. The primary benefit of this system is the reduction in disputed transactions and the resultant exception handling expense and losses. Thus the proposed system is adding an extra layer of security at the point where you enter information online. The service helps to prevent unauthorized online use before it happens by confirming your identity with an additional password.
Trust Quantitative Model with Multiple Decision Factors in Trusted Network

In a trustworthy network system,trust model is one of the most complex concepts in social relationships,and it also is an abstract psychological cognitive process,involving assumptions,expectations,behavior and the environment,and other factors.So,it is very difficult to quantify and forecast trust-ship accurately.In this paper,a novel dynamic trust quantization model with multiple decision factors based on information entropy is proposed,in which multiple decision factors,including direct trust,trust risk function,feedback trust,incentive function and active degree,are incorporated to reflect trust relationship's complexity and uncertainty in various angles.Also,the weight of classification is set up by information entropy theory for these decision factors,which overcomes the shortage of traditional method,in which the weight is set up by subjective manners,and makes the model has a better rationality and a higher practicability.Simulation's results show that,compared to the existing trust quantization metrics,the model in this paper is more robust on trust dynamic adaptability,has remarkable enhancements in the system's security.
Introducing Experiential Exercises to Inexperienced Faculty Members

This paper describes a simulation of a case study that was presented to a group of faculty members who had little or no previous experience with interactive learning techniques. A case study was created that covered topics of interest to faculty. Two groups were chosen to present the case, and each was subjected to a different style of interaction from the instructor. Participants were able to experience various aspects of interactive learning and see how different techniques can create different results from a common theme.
“Altered CD8+ T cell associated aging gene signature in the peripheral blood of patients with Alzheimer’s disease”

INTRODUCTION Effector memory (EM) CD8+ T cells have been associated with poor cognition in Alzheimer’s disease (AD). Our lab recently discovered an age-associated gene expression signature of IL-7 receptor alpha (IL-7Rα)low EM CD8+ T cells. We hypothesized that individuals with AD have altered levels of this IL-7Rαlow aging gene expression. METHODS Forty genes associated with IL-7Rαlow EM CD8+ T cells, AD, or memory, were analyzed in peripheral blood of participants with normal cognition, mild cognitive impairment, and dementia by qPCR. RESULTS Of the eight genes that were found to be differentially expressed based on clinical diagnosis, 5 genes (62.5%) were IL-7Rαlow aging genes. Principal component analysis revealed 3 clusters of participants with dementia which had distinct expression levels of IL-7Rαlow aging genes and cognitive function. DISCUSSION Our findings support the possible relationship of the IL-7Rαlow EM CD8+ T cell aging signature with cognition in individuals with dementia due to AD.
Detecting and managing operational, transactional and auditing risk using data analytics

Companies depend on timely and accurate financial information. Businesses and investors both need current and reliable information for making the decisions that must be made every day. Much of the information that companies, investors and the government receives and incorporates in their long term business decisions is provided by a third party known as independent auditors and the process they undertake is called data analysis used for preventing and identifying risks. This paper explores the basic concepts and techniques of the set of tools used to detect and manage operational, transactional and auditing risk. It provides insights of the internal control evaluations that take place to ensure the accuracy of the information being audited and the reports that are drafted to summarize the audit findings. It also includes the reports and findings of that audit of the company and how the company can recognize the operational, transactional and auditing risks. This will help leading organizations and audit departments in leveraging data analytics for auditing purposes.
Know Thy Player: An Integrated Model of Player Experience for Digital Games Research

Digital games are among the most complex forms of media entertainment. They contain a large variety of multimodal sensory stimuli, from vivid three-dimensional graphics to engaging sound effects and background music, elaborate narratives, and absorbing virtual worlds. Games are also highly dynamic, meaning that they usually do not follow a linear structure. This chapter provides an overview of research on player experience and its different methodological approaches. It discusses the concept of integrated model of player experience (IMP) as a framework to describe the dimensions of player experience and organize the research that investigates it. The IMP distinguishes between three main elements comprising the gaming experience: context, player, and game. Effects and influences of these levels occur in three consecutive phases: pregame phase, game phase and postgame phase.
From craftsmen to laborers: A history of carpet making in Republican China

Beijing and Tianjin hand-woven carpets were once a major export item of Republican China. These carpets were mainly bound for the Western markets, especially the United States. In the late Qing dynasty, Chinese carpets found their way into the collections of wealthy connoisseurs and then, increasingly throughout the 1920s, into the homes of America’s rising middle class. This paper shows that by pursuing a strategy of export maximization, the Republican Chinese carpet industry submitted itself to technical standards set by the American market, as well as to the shifting tastes of American homemakers. This resulted in the valorization of knowledge about foreign market and devalorization of traditional Chinese artisanal knowledge. Eventually, entrepreneurs with direct connections to the foreign market came to dominate the carpet production; weavers were reduced to manual laborers.
Secure key distribution applications of chaotic lasers

Chaotic semiconductor laser is a good candidate for secure communication and high-speed true random bit generator, for its characteristics of broad bandwidth and prominent unpredictability. Based on the synchronization property and true random bit generation characteristic of chaotic semiconductor lasers, physical secure key distribution is available. In this work, we majorly show three key distribution schemes stemming from synchronized chaotic semiconductor lasers or chaos-based key exchange protocol. The numerical results demonstrate that the security of the chaos-synchronization-based key distribution scheme can be physically enhanced by adopting dynamic synchronization scheme or encrypted key generation, and that of key distribution with chaos-based key exchange protocol is dependent on the security of the exchange protocol and finally determined by the difficulty of regeneration the chaos system accurately.
Quantification of information

Information is a complex phenomenon rarely focused as a whole. The objective of science, said Galileo, is «to measure what is measurable and to make measurable what it is not». Very few aspects of information are currently subject to quantification studies; citations and book titles published are among the handful considered in modern information studies. This paper gives a summary presentation of a three-year old project and its forthcoming book/report, aiming at the quantification of every item included under the broad term «information»: maps, gravestones, slides, advertissements, sound recordings, video recordings, dissertations, periodicals, papyri, ostraca, chritmas cards, and several scores more
Line extraction via phase congruency with a novel adaptive scale selection for poisson noisy images

In this paper we address the problem of extracting curvilinear structures from images in the presence of Poisson-distributed noise that is typically found in low-quality, low-contrast data, as well as in numerous medical imaging modalities. A contrast-robust phase congruency estimation method is proposed such that the optimal range of scales is selected in an adaptive manner for each location in the image. The adaptive regime is driven by a statistically well-principled variance test statistic which is based upon a local measure of the dispersion index. Experimental validation confirms that the adaptive scheme delivers superior line extraction results on mammographic imagery when compared to other recent attempts including the non-adaptive phase congruency.
New Algorithms on IP Network Topology Discovery and Its Implement

In this paper,we present two novel algorithms,one for discovery logical topology,the other one for discovering physical topology in heterogeneous IP networks.The algorithm for logical network,which adopt heurism\greedy algorithms,can be applied to large scale IP network.For the algorithm can self deduce IP addresses,adjust the search domain,it has strong adaptabilities.Another novel algorithm is presented for physical topology which includes switches,hosts and hubs.At the same time,a new data structure named Treelike-Graphics for topology discovery is presented with precise mathematic definition,relationship set and proprietary operation on this data structure.The algorithm,which we present in this paper,does no base on the STP protocol to get the information of topology.So,there are few preconditions to the algorithm.We have implemented the algorithm presented in this paper in Perl in Tsinghua University own research network.The experimental results clearly validate our algorithm,demonstrating that our algorithm can consistently discover the accurate physical network topology with reasonably small running-time requirements.
Navigational programming: toward structured distributed parallel programming

As distributed-memory cluster computers become less expensive and increasingly available, our ability to program this new generation of supercomputers is lagging behind demand. Achieving scalability and ease of programming simultaneously is a grand challenge. The state of the art for implementing large-scale high-performance scientific and engineering applications has been message passing (MP), despite the fact that MP is widely considered hard to use. Studies reveal that the two operations at the heart of MP---Send() and Recv ()--change the code similar to the goto statements, thus making structured programming problematic. This is reminiscent of the software crisis of the 1960s that led to Dijkstra's recommendation that goto statements be abolished. This dissertation introduces a new methodology, called Navigational Programming (NavP), that is based on the use of self-migrating computations. NavP is philosophically different from message passing because it describes the quantity of interest---a distributed computation---following the movement of its locus. In contrast, all other approaches use the SPMD (Single Program Multiple Data) view to describe computations at stationary locations. Program transformations in NavP involves the insertion of migration statements ( hop()), which, unlike the Send() and Recv(), does not change code structure. NavP puts an end to the use of "goto " statements and it enables scalable structured distributed parallel programming. This dissertation develops the NavP methodology with steps for its programmers to follow. Case studies using real-world examples demonstrate how efficient, scalable, and elegant NavP programs can be developed in an incremental fashion using the NavP methodology. We show how the NavP methodology yields parallel implementations of algorithms that are difficult to parallelize, and that on the surface appear unparallelizable, using MP. Performance data shows that for several important and non-trivial real-world applications, NavP programs are as fast as or faster than the corresponding MPI programs. NavP exploits both fine-grained parallelism using shared variables and multithreading, and coarse-grained parallelism using pipelined tasks in a uniform fashion. NavP holds the promise of allowing scientists and engineers to use the most advanced computers without being overwhelmed by the complexity of rewriting their codes with each new generation of architectures.
Turning mathematics for the senior secondary level into a dynamic and attractive science by exploring the hidden mathematics in modern science and technology

In our talk, we consider the complete secondary level of teaching as consisting of six years of courses, normally starting at the age of twelve and finishing at the age of eighteen; by the senior secondary level we mean the last two years (students age: 16 to 18). At that level, there are different finalities for the students. Our concern in what follows is with the kind of mathematics that may be offered to the students that are choosing the general formation finality (which in some sense may be considered as preparing for continued studies at a higher level) with a sufficient quantity of mathematics in their programme (since the amount of mathematics at the senior level is usually determined by some choosen option).
T cell kinetics reveal expansion of distinct lung T cell subsets in acute versus in resolved influenza virus infection

Influenza virus infection is restricted to airway-associated tissues and elicits both cellular and humoral responses ultimately resulting in generation of memory cells able to initiate a rapid immune response against re-infections. Resident memory T cells confer protection at the site of infection where lung-resident memory T cells are important for protecting the host against homologous and heterologous influenza virus infections. Mapping kinetics of local and systemic T cell memory formation is needed to better understand the role different T cells have in viral control and protection. After infecting BALB/c mice with influenza virus strain A/Puerto Rico/8/1934 H1N1 the main proportion of activated T cells and B cells expressing the early activation marker CD69 was detected in lungs and lung-draining mediastinal lymph nodes. Increased frequencies of activated cells were also observed in the peripheral lymphoid organs spleen, inguinal lymph nodes and mesenteric lymph nodes. Likewise, antigen-specific T cells were most abundant in lungs and mediastinal lymph nodes but present in all organs studied. CD8+CD103-CD49a+ lung-resident T cells expanded simultaneously with timing of viral clearance whereas CD8+CD103+CD49a+ lung-resident T cells was the most abundant subset after resolution of infection and antigen-specific, lung-resident T cells were detected up to seven months after infection. In conclusion, the results in this detailed kinetic study demonstrate that influenza virus infection elicits adaptive immune responses mainly in respiratory tract-associated tissues and that distinct subsets of lung-resident T cells expand at different time points during infection. These findings contribute to the understanding of the adaptive immune response locally and systemically following influenza virus infection and call for further studies on the roles of the lung-resident T cell subsets.
LS Channel Estimation in Multicell Multiuser MIMO OFDM with Zadoff Chu Sequence as Pilots

High spectral efficiency and the ability to combat multipath fading are the key requirements of future wireless communication systems. Multiple-input multiple-output (MIMO) combined with orthogonal frequency- division multiplexing (OFDM) has been widely considered to be a promising candidate. Moreover Multi user MIMO OFDM can provide good spatial multiplexing with single antenna for each user. In the case of multicell multiuser MIMO OFDM system main challenge is to acquire the channel state information. In order to get the channel state information, channel estimation is to be done. Here pilot aided LS channel estimation is used to obtain the estimates. For multi cell multi user MIMO OFDM, channel estimation using pilot subcarriers causes pilot contamination. This is due to the reuse of pilot subcarriers in different cells. In order to reduce the impact of pilot contamination, pilot sequences must select properly. Here Zadoff Chu sequences are used for the design of pilots in different cells.
QoS weighted scheduling: real-time streaming of multi-resolution video

In this work, we propose novel packet scheduling algorithm for real-time streaming of multi-resolution video. Our scheduling algorithm targets towards the situation where there exists relatively large fluctuation in bandwidth availability and the short queue depth in the receiver's end. The proposed algorithm determines which packets to send and when to send them. We develop QoS significance metric to represent the importance of a packet. QoS significance incorporates the composite transitive dependency in multi-resolution video. We develop QoS weighted traffic smoothing to determine the transmission schedule. We found that when the receiver has short queue length, e.g. mobile terminal, packet loss is very sensitive to the packet interval distribution. In determining the packet transmission schedule, we consider not only the bandwidth process of the packet traffic but also the importance of the individual packets. We introduce more slack for more important packet. We found that QoS weighted traffic smoothing makes the resulting bandwidth process burstier and entails more packet losses. However, it greatly enhances the user perceivable QoS. The simulation results show that the our scheme not only maximizes user perceivable QoS but also minimizes resource requirements.
An Algorithm of Video Scene Segmentation Based on Semantics

The scene segmentation is a high-level temporal video segment.This paper presents a method of scene segmentation based on semantics.At first,the video clips are segmented into shots and the shot key frames are extracted.Then the features of color histogram and MPEG-7 edge histogram of each key frame are computed and the feature vectors of shot key frames are formed.The support vector machines(SVM) are trained by these feature vectors and 7 binary classifiers in accordance with difference semantic concepts are constructed.These binary classifiers are used to classify the shot key frames of the video clips based on the features of the color and the texture and the semantics concepts of shot key frames can be obtained.The semantic concept vectors of shot key frames are formed by the semantic concepts contained in the key frames.The shot key frames are clustered by the semantic concept vectors and the video scene can be constructed.The shot select function is defined to extract the scene key frame based on the value of function.The experimental results shown that the recall and the precision of this algorithm are higher than those of the Hanjalic's method about 34.7% and 9.1%,respectively.
The Way to Go: A Thorough Introduction to the Go Programming Language

This book provides the reader with a comprehensive overview of the new open source programming language Go (in its first stable and maintained release Go 1) from Google. The language is devised with Java / C#-like syntax so as to feel familiar to the bulk of programmers today, but Go code is much cleaner and simpler to read, thus increasing the productivity of developers. You will see how Go: simplifies programming with slices, maps, structs and interfaces incorporates functional programming makes error-handling easy and secure simplifies concurrent and parallel programming with goroutines and channels And you will learn how to: make use of Go's excellent standard library program Go the idiomatic way using patterns and best practices in over 225 working examples and 135 exercises This book focuses on the aspects that the reader needs to take part in the coming software revolution using Go.