Reviewerly/exHarmony huggingface dataset:
Secure Smartphone-Based NFC Payment to Prevent Man-in-the-Middle Attack

Smartphone-based Near-Field Communication (NFC) is considered as a convenient method of payment as there is no additional authentication from the user. However, security threats like man-in-the-middle attack and eavesdropping are inevitable for this payment method, since there are no physical controls that restrict the transmission. Several security protocols have been proposed to mitigate these threats. Still, those protocols require certificates that involve many communications and computational costs, which consumes more resources on client's smartphones. To address this problem, a method was proposed using symmetric cryptography to provide more efficient security protocol against threat in smartphone-based NFC mobile payments. The protocol is originally used on short-range wireless communication.
Designing TinkMate: A Seamless Tinkering Companion for Engineering Design Kits

Tinkering is a successful approach to solving complex engineering design problems. Complexity arises due to constraints from the problem space where the available conceptual knowledge is to be applied to solve the problem. On the other hand, tinkering requires working in the problem space with the available tools and resources to find solutions to the problem at hand. Prior knowledge of affordances of tools and resources available for tinkering through a problem or ability to acquire such information in the time of need is a challenge for an engineer who is a novice at tinkering. Gathering this information from manuals and online resources frequently requires switching context, which inhibits or discourages tinkering with the unknown components. To address this challenge, we propose to build a tinkering companion, TinkMate, using a robot for interaction and augmented reality for providing essential information. From a contextual inquiry in a young engineers robotics workshop, we have found that delivering just in time information about unknown components; and providing triggers on tinkering in a seamless human-like communicative manner, encourages experimentation with components of a kit. We plan to build and test a prototype of TinkMate using an off the shelf robot (COZMO) and features like just in time information (JITI) and just in time triggers for tinkering (JIT3). We would also like to study features that encourage participants and enable reflection, which has emerged on further exploration of this concept.
Literature Recommendation Technology Based on User Characteristics and Semantic Computing

Obtaining the firsthand literature resources related to research is one of the main tasks of intelligence personnel. Different from the open users to whom content recommendation service is oriented, intelligence personnel have a clear professional background and specific research needs. This paper proposes a personalized recommendation algorithm for scientific literature that integrates user characteristics and semantic computing. On the one hand, using the rich background information and scientific research experience of intelligence personnel were used to generate recommendations for static information modeling; on the other hand, user behavior was used to explore the potential semantic relationship between the literatures. Finally, the two methods are combined. Through the effective integration of user static characteristics and user behavior information, the dependence on the user interaction behavior was weakened, and the cold start problem was effectively alleviated. The experimental results showed that the proposed method was significantly improved compared with the traditional method, which proved the feasibility of the method.
Flexible calibration of a stereo vision system by active display

Camera calibration plays a fundamental role for 3D computer vision since it is the first step to recover reliable metric information from 2D images. The calibration of a stereo-vision system is a two-step process: firstly, the calibration of the individual cameras must be carried out, then the two individual calibrations are combined to retrieve the relative placement between the two cameras, and to refine intrinsic and extrinsic parameters. The most commonly adopted calibration methodology uses multiple images of a physical checkerboard pattern. However, the process is time-consuming since the operator must move the calibration target into different positions, typically from 15 to 20. Moreover, the calibration of different optical setups requires the use of calibration boards, which differ for size and number of target points depending on the desired working volume. This paper proposes an innovative approach to the calibration, which is based on the use of a conventional computer screen to actively display the calibration checkerboard. The potential non-planarity of the screen is compensated by an iterative approach, which also estimate the actual screen shape during the calibration process. The use of an active display greatly enhances the flexibility of the stereo-camera calibration process since the same device can be used to calibrate different optical setups by simply varying number and size of the displayed squared patterns.
Research on The Text Emotion of Multinomial Naïve Bayes Integration Algorithm

With the development of the Internet industry, the number of Internet users grows explosively every year. In the Internet era, public opinion can play a decisive role in the process of society. Therefore, the emotional analysis of netizens' comments is particularly important. In this paper, Multinomial Naïve Bayes method, which is widely used in word frequency analysis, is used to generate several weak classifiers, and then AdaBoost method is used to obtain a strong classifier by linear combination of several weak classifiers. Experiments show that the combination algorithm of Multinomial Naïve Bayes and AdaBoost can classify text emotion more accurately.
The Efforts and Verification about Ability Leadership of Vocational Training Instructor

The Polytechnic University (PTU) takes the training of the vocational training instructor, investigation and a research about the vocational ability development. New instructor training course was established and that it was possible to become a vocational instructor widely from 2014. We would like to introduce efforts and the class contents about the leadership training by the vocational training instructor. We implemented research the instructor’s ability evaluation and the degree of the satisfaction and the acquisition after implementing classes. The research result is based, we would like to report verifying whether or not the ability which the vocational training instructor needs was trained up.
Ant Miner

Discovering classification rules from large data is an important task of data mining and is gaining considerable attention. This article presents a novel ant miner for classification rule mining. Our ant miner is inspired by research on the behavior of real ant colonies, simulated annealing, and some data mining concepts as well as principles. Here we present a Michigan style approach for single objective classification rule mining. The algorithm is tested on a few benchmark datasets drawn from UCI repository. Our experimental outcomes confirm that ant miner-HMC (Hybrid Michigan Style Classification) is significantly better than ant-miner-MC (Michigan Style Classification).
Field of experts optimization‐based noisy image retrieval

Summary The value of image retrieval has become more and more prominent in the era of big data. However, large numbers of images are missed from current method since the image retrieval precision largely depends on the high quality of images. By common methodology, when the quality of images decreases a little, the accuracy of retrieval would decrease significantly. In particular, it is difficult to retrieve noisy images effectively by conventional approach. Yet large number of the noisy images could not be ignored at the age of data explosion. Aiming at the problem above, we proposed noisy image retrieval model based on field of experts (FoE) optimization. High‐quality learning images could be selected by sparse coding, which is based on similarity calculation model, and the multioption filter combination model enhances the power of FoE model. We set up a database containing a large numbers of noisy images. Over this database, adequate groups of experiments are conducted. The verification of the method concluded its effectiveness and superiority.
Research on Compression Method of Cement Production Time Series Data Based on Feature Preservation

Under the background of industrial big data era, a large amount of production time series data has been produced in cement enterprises. Mining the law and value behind time series data can grasp and predict the development law and direction of things, which is of great significance for enterprise managers to make correct and scientific decisions. Based on the analysis of the characteristics of production timing data, this paper presents a method of timeseries data compression for cement enterprises based on the problems existing in the application scenarios such as historical trend drawing. By adopting the compression method, the compression ratio of the production time sequence data can be effectively improved, and the compression method plays an indispensable role in trend display and contrast analysis.
Data Mining of Privacy Preserving Based on Secret Sharing Technology

Based on Shamir secret sharing technology, this paper designs a vertical distributed association rule data mining algorithm with privacy-preserving level, and analyses the correctness, complexity and security of the algorithm. At the same time, it points out that under the hypothesis of quasi-honesty attack, the algorithm is not only safe, but also can effectively prevent collusion between participants. This algorithm is suitable for privacy-preserving data mining in relatively small distributed databases.
The Optimal Combination Mode of Three-digit Ciphers Based on Statistical Analysis

At present, brute force tools based on various passwords are emerging one after another, and many encrypted files can be easily cracked. Given the above, we explored the password settings to find the most effective combination of passwords. Here, we start with a three-digit password: First, enumerate nine possible forms based on possible combinations of letters, numbers, and special symbols; secondly, we use Advanced Archive Password Recovery to brute force each of the nine combinations, recording the crack time, average crack speed and hexadecimal password; then, the crack parameters of each kind are analyzed, and the characteristics of each combination are found through the variance method; finally, an optimal combination scheme was sought.
Research and Implementation of RSA IP Core Based on FPGA

In the era of digital economy, users need to transmit key information such as identity, account, password and so on through the network. Once these information is leaked on the Internet, it will cause serious consequences such as economic loss, privacy disclosure and so on. RSA public key cryptography algorithm has been widely used in network security transmission schemes in the world because of its simplicity, security, effectiveness and maturity [1]. In this paper, the important role of asymmetric encryption technology was carefully analyzed, and the algorithm principle of RSA was introduced in detail. In view of the difficulty of division in hardware, Montgomery fast modular multiplication algorithm was adopted as the core part of RSA encryption algorithm. According to the top-down hardware design method, I first distinguished the functions of encryption module, and then used Verilog language to write the modules such as control, inverter, mod and divider. Finally, I simulated the control, mod_exp, inverter in Xilinx Vivado to verify their function. The simulation results showed that the Control module could encrypt and decrypt 256 bits of data in 120 clock cycles. At 500 MHz, the data throughput of the IP core can reach 512 Mbps. After Vivado synthesis, RSA IP core consumes 44 DSPs, LUT 2106 and FF 754 on the FPGA xc7vx485, which saves resources very much. Because the processing speed of IP core of hardware-based RSA algorithm is not as high as that of symmetrical encryption IP core in some key areas [2], finally I proposed four next steps to improve the RSA IP core.
Study of Mammography Medical Imaging Sample Selection Based on CSAL

Medical imaging is widely used in the diagnosis and treatment of clinical practice. At present, medical imaging technology has entered a new era of digitalization. In order to solve the scarcity of medical image standard data sets and the high cost of manual labeling, it is necessary to use active learning methods to select the most valuable data from the vast image data pool for labeling which the purpose is to make the labeling costs lower, reduce the pressure on professional physicians and make clinical decision-making easier. This article focuses on mammography medical imaging, analyzes the structure and characteristics of the images, deals with mammography medical imaging data and trains the model using machine learning model, called CSAL (CNN-Seq2Seq-Attention + Active Learning), in order to reduce the loss of image data sequence after graying, and filter out valuable data from the data pool by active learning. This paper uses two different active learning methods and two different data sets for comparative experiments. The finally experimental results achieved satisfactory effort.
Design and Implementation of Speech Recognition System Based on Gesture Control

Gesture is a basic human characteristic and an indispensable part of interpersonal communication. Gesture recognition voice playback system is designed for deaf and mute people, which can help them communicate with normal people more conveniently. The system is divided into hardware part and software part. The hardware part includes data acquisition and analysis. The raspberry pie system is adopted. The raspberry pie system mainly includes three hardware modules: camera module, wireless network card module and serial communication module. The software part uses Python language to program the raspberry pie, and PyCharm is used as the programming software. The gestures made by deaf-mute people can be converted into text information through this system and displayed on the display screen. At the same time, the voice can be played, so that the normal people and deaf-mute people can understand each other. The experimental results show that the speech recognition system based on gesture control can achieve the function of gesture acquisition, and can play gesture information through loudspeakers, and display gesture information on the screen, which provides a convenient communication between deaf and mute people and normal people.
Identifying Near-Native Protein Structures via Anomaly Detection

Discriminating biologically-active/native tertiary protein structures from non-native ones is an outstanding challenge in computational structural biology. Computationally, the task involves teasing out near-native structures out of several thousands generated in silico. In this paper we build on the concept of anomaly detection in machine learning and propose several methods for discriminating near-native structures. Evaluations on benchmark datasets demonstrate that the proposed methods advance the state of the art and warrant further research on adapting concepts and techniques from machine learning to improve recognition of near-native structures in template-free protein structure prediction.
High Performance Computing in Resource Poor Settings: An Approach based on Volunteer Computing

High Performance Computing (HPC) systems aim to solve complex computing problems (in a short amount of time) that are either too large for standard computers or would take too long.They are used to solve computational problems in many fields such as medical science (for drug discovery, breast cancer detection in images, etc.), climate science, physics, mathematical science, etc. Existing solutions such as HPC Supercomputer, HPC Cluster, HPC Cloud or HPC Grid are not adapted for resource poor settings (mainly for developing countries) because their fees are generally beyond the funding (particularly for academics) and the administrative complexity to access to HPC Grid creates a higher barrier.This paper presents an approach allowing to build a Volunteer Computing system for HPC in resource poor settings.This solution does not require any additional investment in hardware, but relies instead on voluntary machines already owned by the private users.The experiment has been made on the mathematical problem of solving the matrices multiplication using Volunteer Computing system.Given the success of this experiment, the enrollment of other volunteers has already started.The goal being to create a powerful Volunteer Computing system with the maximum number of computers.
Secure multi-party collision resolution protocol for air traffic control

In this paper, we present a protocol for secure resolution of collision between aircraft, while their corresponding trajectories are kept private. For privacy reasons, we assume that each aircraft’s position, heading and velocity are not available to all aircraft involved in the protocol. Our new secure protocol is based on an algorithm, which is for collision resolution of aircraft, without considering the privacy requirement. Our approach is Secure Multi-party Computation. To present our Secure Multi-party Collision Resolution Protocol, we propose a new Secure Sorting Protocol and a Modified Distributed Oblivious Transfer Protocol. We also take advantage of employing a Secure Multi-party Collision Detection Protocol, a Homomorphic Encryption, a Secure Comparison Protocol, and a Secure Maximum Finding Protocol. To prove the security of our proposed protocol and its sub-protocols, we use the Ideal/ Real Simulation Paradigm. The communication complexity of our proposed protocol is in O (n2), and its computation complexity is in O(n). We have also done a simulation for the execution of our proposed protocol for multiple moving aircraft, to show its practicality.
THE USE OF THE CLASSTIME PLATFORM IN THE CONTEXT OF INCLUSION

Relevance: the need to provide equal rights and create opportunities for the education of individuals with different educational needs at all educational levels including higher education as well. It is stated that the issues of realization of education continuity and lifelong learning have resulted the need for scientific, methodological and technical support of the educational process of higher education institutions in the conditions of inclusion. The purpose: the article analyzes the possibilities of the modern Internet resource – Classtime, online plat- form which was created to adapt the process of teaching mathematics according to the individuals’ needs and opportunities of higher education students in the conditions of inclusion. Мethods: analysis, synthesis and generalization. Results. Аfter having used the Classtime platform it has been determined that this service improves the quality of mathematics training for students’ higher education in inclusion and has several benefits for both teachers and students. The resource offers a wide opportunity to analyze each student’s learning activities and achievements, identifies the need for additional explanation and correction by the teacher depending on the actual state of material learning. Classtime platform is claimed to adapt the process of teaching mathematics to specific educational needs and to implement an individual approach to all higher education students by partially compensating for functional limitations caused by certain diseases, for example, for visually impaired people – increasing the size of ... Conclusions. Finally it is stated that scientifically proven and pedagogically aimed usage of modern Internet resources will allow students to fully participate in the educational process and create conditions for the implementation of their individual educational projects. The further perspective is to develop a methodology for mathematics teaching in the conditions of inclusion using information and communication technologies and to provide appropriate educational and methodological support.
STARS

Dynamically Adaptive Systems (DAS) modify their behaviours in response to (sometimes unpredictable) changes in their environment or to the evolution of their own abilities (sensors and actuators). To support adaptation, a reference architecture (such as the MAPE-K model) is paramount. Yet, this is not sufficient as challenges concerning the fine-grained variability management and testability remain. The STARS Ph.D. project aims at developing a variability and context-aware architectural model for DAS that particularly takes into account testability. In particular, we want to adapt tests at runtime in order to assess and prevent the impact of inappropriate adaptations.
Spatio-Temporal Trajectory Features Based Sensitive Relationship Protection

To solve the problem of privacy leakage of sensitive relationships caused by the spatial-temporal trajectory correlation of users in social networks, this paper proposes a privacy protection algorithm for sensitive relationships based on spatial-temporal trajectory features. In this paper, we propose a new measurement model for evaluating users' similarities, the basic idea of which is to calculate the similarity between users' sub-trajectories based on spatial and temporal dimensions. The proposed privacy protection algorithm adopts a heuristic to evaluate the inference contribution and information loss caused by data modification in order to protect sensitive relationship privacy meanwhile maintaining the trajectory data utility. We also provide the security analysis and theoretically prove the availability of the proposed algorithm. Based on the real social network data, the experimental results show that the proposed algorithm is efficient and could achieve high data utility.
Hybrid Teaching of College English Under the Background of Big Data

With the development and popularization of Internet technology, human society has entered a new era of big data from the information age. Big Data is usually used to describe the massive data generated in the era of information explosion, and to name the related technological development and innovation. In big data era, the deep integration of information technology and education will have a far-reaching impact on the relationship between teachers and students, teaching materials, learning environment, as well as teaching testing and evaluation. Based on the author’s study and practical experience, this work first analyzed the concept of big data and the meaning of hybrid teaching, and then summarized the framework of the hybrid teaching model of college English based on big data. Finally, this work proposed the roads to college English hybrid teaching based on big data.
Voting Based System for Robust 3D Hand Pose Estimation and Tracking

Low cost depth cameras and advancements in the field of deep learning have paved the way to precisely estimate 3D hand pose using a single depth camera. However, to accurately estimate the pose one has to detect the hands in the scene and track them over consecutive frames. In this paper, we propose a voting based system to track and estimate the 3D pose of a human hand. Based upon Robot Operating System (ROS), it comprises a hand segmentation stage, a clustering stage, a voting stage, a validation stage and a pose estimation stage. The final output is the 3D pose which is then used by a robot to follow the human hand.