Reviewerly/exHarmony huggingface dataset:
Retrieve the Hidden Leaves in the Forest: Prevent Voting Spamming in Zhihu

Nowadays, more and more people start posting their opinions on online social networks, such as commercial product evaluation websites, forums, and crowdsourcing $$ Q \& A$$ websites. In practice, most majority vote schemes cannot reveal the true distribution of opinions, due to the spam problem. Many public relationship companies can recruit people or use automatic commenting machines to promote target products and ruin the reputation of their opponents. In such a sense, the opinions on these websites may not be reliable. In the literature, there are a lot of studies contributed to detect such spams, based on the characteristics of posted content, social relationship, user activity, posting time, etc. We find that most spam detection schemes rely heavily on the experience and preference of experts. This is dangerously as it can lead to bias and dictatorship. In this work, we take Zhihu - one popular Chinese $$ Q \& A$$ website as a case study, and propose a time diversity based voting scheme to reduce the impact of voting spamming. We illustrate that, our proposed opinion tolerant system can maintain a good balance in the appearance of different opinions.
Wield Blockchain TechnologyTo Fortify Smart Wallet

Considering security as a potential disadvantage to an e-wallet application, we propose a three level of security screening in order to login to the application. This application will help to secure the wallet from the hackers.Anumeric passcode, which will only be known by the user. After the passcode has been successfully validated, a fingerprint recognition will be prompted for the user. On successful validation of the user's fingerprint pattern, the user's fingerprint pattern, the user will be prompted for the `face login', which they might have already provided while registering on the application. If and only if the user has provided the required security information correctly will be available for use. In case, the user provides an incorrect information in any of the 3 levels of security logins, an alert will be generated and sent to the user's registered e-mail id. Then the user will be alerted if any one tries to access his/her account. A `twoway handshake' acknowledgement connection will be set between the user and the payment recipient/store in the form of an OTP. Once the user initiates a transaction, an OTP will be sent to both the user and the recipient. Only if the recipient acknowledges the receipt of the OTP, the transaction will be completed. Near field communication technique, such as a `QR' code verification can also be used to make a payment, when the user Is on store purchase.
Design and Simulation of a Quantum Key Distribution Protocol Based on Single-Particle and EPR Entanglement

Based the idea of original “Ping-pong” protocol, an improved “Ping-pong” protocol based on single-particle and Einstein-Podolsky-Rosen (EPR) entanglement is presented. The EPR entanglement is used to detect the eavesdropping and the single particle is used to transmit the information. During the protocol, the sender Alice transmits an EPR entanglement pairs and a single particle to the receiver Bob at the same time. The bit error is caused by the random position of the single particle. In our security analysis, an eavesdropping will cause at least a bit error rate of 16.7%, and the probability of detecting eavesdropping with bit error rate is 50.0%. We also give a simulation which is based on law of large numbers and Monte Carlo method. In our simulation, we use mean square error (the value is $$1.8115\times 10^{-5}$$ ) to indicate that the simulation data is approach to the theoretical value. Compared with the original “Ping-pong” protocol, the presented protocol doesn’t need the control mode, and it doesn’t need to store the quantum state.
High pass filter based on curvelet transform coefficients

High pass filter are widely used in image processing for different purpose, due to that use many researchers provide this field with so many type for those filters with different techniques. This research provide a new approach to design high pass filter by adopting the properties of the curvelet transformation coefficients (fine, coarse and detail). Studying the effect of that coefficient by dropping some of them, then reconstructed the image from the remaining coefficients. The proposed technique applied on different type of images, which hold different amount of frequencies, dropping one level of high frequencies starting from level two up to last level of image decomposition. The result shows that dropping cells at last level will produce fine edges and thicker edges can be got by dropping cells at level 2. The benefits that were appear from the approach that this type of high frequency does not need kernel to reject low pass frequencies but depend upon the image itself. Using different images with different high frequencies support users to get wild field in using edge detection.
Enhancing online security using selective DOM approach to counter phishing attacks

Summary Today's computer era has paved the way for innovations like self‐driving cars, quantum computing, and other ingenious advancements. As technology advances at a rapid pace, some issues yet remain unresolved. One of the issues is phishing, which dates back to the 1980s. Phishing is an art used by cybercriminals from the 1980s until to date targeting online users to harvest financial, confidential, and other sensitive information. The art and the methodologies used by cybercriminals have not evolved much from the AOL (American online) heydays. However, the counter mechanisms to defeat phishing have undergone considerable changes over the past two decades. Although sophisticated antiphishing systems are in place, statistics shows that phishing is a major threat. Our practical research proves that one of the state‐of‐the‐art antiphishing systems can be bypassed using simple techniques. The research further demonstrates why today's antiphishing mechanisms fail and the need for a novel mechanism that will identify the authenticity of the website. In this manuscript, an antiphishing algorithm, PhishSec (PH‐Sec), is introduced. PhishSec will not consider the URL of the website as the primary factor to determine the authenticity, rather take a reverse approach where the URL of the website is derived by analyzing the content of the visited website to establish its authenticity. To accomplish this, the HTML DOM (document object model) of a given web page on load is considered. This manuscript quotes the research results of the analysis of a state‐of‐the‐art antiphishing system along with the introduced algorithm to counter‐attack phishing. The introduced system detects phishing attacks with 99.21% of accuracy.
Study the Preprocessing Effect on RNN Based Online Uyghur Handwriting Word Recognition

There is little work done on unconstrained handwritten Uyghur word recognition by implementing deep neural networks. This paper carries out a comparative study to see the preprocessing effect on training a neural network based online handwriting Uyghur word recognition system. Bidirectional recurrent neural network with connectionist temporal classification is implemented for unconstrained handwriting word recognition experiments on a dataset of 23400 Uyghur word samples. The results are directly obtained from model output without any lexicon or language model. Experiments showed that proper preprocessing can improve the training speed very effectively. The comparative study conducted in this paper can be good reference for later studies.
Construction of Modern University Library Website (CMULW) Based on User Needs

Abstract The construction of modern university library website (CMULW) adapts to the changes of the times, and it will extend the scope and content of library services, which is of great significance to the development of universities. This article will be presented to describes the CMULW must follow the user needs from three aspects, including basic function needs, safety and security needs and humanistic respect needs. The website safety and security needs will be used in the website security system to introduce. The CMULW conforms to the requirements of the current era of social information technology development and provides users with better network information services. The modern university library website (MULW) needs not only to enhance its own practicability, and it needs to satisfy the user omni-directional demand to improve the user experience. Only constantly to find and meet the needs of users and improve service capability and the quality of service, is the basic attitude and development path of the modern university library website construction (MULWC).
Simulation Model Selection Method Based on Semantic Search in Cloud Environment

Search and selection of simulation model is an important process of building simulation application of complex system based on model composition in cloud architecture environment. This paper aims to solve the problem of lacking model correlation search and quality of service (QoS) weighted selection. The knowledge graph is used to describe the simulation models and their correlations. According to the model attributes (such as model name, domain, type, time scale, model granularity, etc.) and the model correlation (such as equipment model carrying relationship, etc.) set by users, the initial set of simulation models satisfying the requirements is found based on semantic search. Then, an optimization selection mechanism based on QoS is proposed to support users in customizing the weights of the QoS indices. The optimally ordered model candidate set is provided for selecting according to the weighting comparison of QoS indices. The experimental results show that the proposed method based on semantic search can support the effective selection of simulation models in cloud environment and the composite modeling of complex systems.
Breast Lesion Discrimination Using Saliency Features from MRI Sequences and MKL-Based Classification

Breast MRI interpretation requires that radiologists examine several images, depending on the acquisition protocol that is managed in the health institution, a very subjective and time-consuming process that reports large variability, which affects the final diagnosis and prognosis of the patient. In this paper, we present a computational method for classifying lesions detected in breast MRI studies, which aims to reduce physician subjectivity. The proposed approach take advantage of the ability of the Multiple Kernel Learning (MKL) strategy for optimally fusing the features extracted from the different image sequences that compose a breast MRI Study, which describe the grey level distribution of the original image and its saliency map, computed using the Graph-based Visual Saliency (GBVS) algorithm. Breast lesions were classified as positive and negative findings with an accuracy of $$85.5\%$$ and $$84.8\%$$ when nine and five sequences were used, respectively.
A Huber based Unscented Kalman Filter Terrain Matching Algorithm for Underwater Autonomous Vehicle

Underwater autonomous vehicles(AUV) are effective tools for marine surveys and military applications. As the energy of the electromagnetic signal will decay rapidly in seawater, most land navigation methods cannot be implemented on underwater vehicles. Underwater terrain matching navigation is an emerging high-precision passive navigation method. It compares the measured underwater terrain data with the digital map and obtains its own position. The unscented Kalman filter(UKF) based underwater terrain matching algorithm has the advantage of high position accuracy and good engineering feasibility. However, the UKF adopts Kalman filtering as the basic framework, which leads to a weaker robustness. When there is a deviation from the actual parameters, the estimation results will be greatly affected. Therefore, based on the above reasons, this paper studies the feasibility of UKF in the AUV underwater terrain matching problem and introduces the Huber method into the UKF, and obtains a framework of underwater terrain matching algorithm based on Huber method, which effectively improves the robustness of the algorithm and makes the algorithm more suitable for AUV different works.
ASSESSMENT OF LEVEL OF INFORMATION-PSYCHOLOGICAL IMPACTS OF VARIOUS SOURCES OF INFORMATION ON YOUNG PERSONALITY

The article considers current information and information-psychological impact as a means of education and training as well as a tool for forming attitudes to the events, phenomena, processes, subjects. Nowadays, the state has the most developed structure of information and communication technologies, but there are growing alternative sources of information. There has been studied the degree of the 19-25 age group’s confidence in different sources of information, ideology of the young of today is actively developing. To conduct the research there was made a questionnaire including questions about the degree of trust of respondents to the main sources of information (parents, environment, research literature, fiction, etc.) and their reference frequency. Statistical data have been collected, according to the results of processing the questionnaires. They allowed evaluating the data obtained. The conclusion on the impact of various information sources on the age group under study has been made. There has been revealed a tendency towards the increasing appeal for information, including unverified information, in the Internet, which makes its own contribution (not always positive) to development of ideological and personal qualities of an individual. There have been analyzed the data on the degree of trust of respondents to various sources of information and its usefulness. Having singled out a particular source of information as the main source affecting the perception, one can use the source for learning as well as for promoting certain products or services. But this approach can also be used by perpetrators for information and psychological impact.
Effect of shapes of activation functions on predictability in the echo state network

We investigate prediction accuracy for time series of Echo state networks with respect to several kinds of activation functions. As a result, we found that some kinds of activation functions with an appropriate nonlinearity show high performance compared to the conventional sigmoid function.
Cloud-Supported Internet of Things Data Security and Access Control in Smart Grid

The cloud-supported Internet of Things (Cloud-IoT) has been widely used in smart grid. The amount of data related to the power grid is huge and sensitive. In order to improve the security of data storage and achieve fine-grained access control with flexibility, a multi-authorization center and fixed-length ciphertext policy attribute encryption access control scheme with attribute revocation is proposed in this paper. The multi-attribute authority is introduced to generate keys to defend against collusion attack, and partial decryption is delegated to the proxy server to reduce user's computing cost. In addition, user revocation updates and attribute revocation updates are used to improve system flexibility. The security of the scheme is proved by Diffie-Hellman hypothesis, and comparative analysis is carried out. The results show that the scheme effectively improve the speed of encryption and decryption, as well as reduce time cost of the system.
Constructive Proofs of Negated Statements

In constructive proofs of negated statements, case distinctions are permitted. We illustrate the strength of this well-known and useful fact in the context of automatic continuity in convex analysis. This sheds light on the level of logic needed to deduce some prominent results and thus fits in well with the concept of Proof Theory as Mathesis Universalis.
Reciprocal Teaching Based Augmented Reality for Enhancing English Novel Reading Skills among Secondary Students

This research aimed to enhance secondary students’ reading comprehension and critical reading skills within the narrative text of the assigned novel. The research design was two group pre and post-test experimental design. The participants were 72 1st year secondary school students from an Egyptian public governmental school in Ismailia governorate. They were divided into two groups: Experimental group of 36 students and Control group of 36 students. Chapters five and six in Charles Dickens’ novel (Oliver Twist) assigned for the 1st grade of the secondary stage, were introduced in the second term to the experimental group via reciprocal teaching based augmented reality in order to determine how far it had a positive impact on enhancing the novel reading skills of the experimental group. A novel reading test that was designed by the researcher and validated as a paper-and-pencil test for assessing the 1st year secondary students’ novel reading comprehension and critical reading skills. It was divided into two parts: part one for reading comprehension skills and part two for critical reading skills. The findings revealed that reciprocal teaching based augmented reality had a significant positive effect on the 1st year secondary school students’ target novel reading skills. Consequently, reciprocal teaching based augmented reality was proved to be successful when teaching reading within a narrative context.
Framework for Construction and Incremental Maintenance of High-Quality Linked Data Mashup

Due to the Linked Data initiative, previously isolated datasets are published as linked data. This enables the creation of applications that consume data from multiple Linked Data sources. Applications are confronted with the challenge of obtaining a homogenized view of this global data space, called a Linked Data Mashup view. This work proposes a framework to perform the fusion of Linked Data and quality assessment of Linked Data Mashup. Quality assessment of Linked Data mashup is computed based on the result of the data fusion. We also propose the implementation of a platform for creation and incremental maintenance of mashup views.
LBS and Multidimensional Scoring Based Recommendation Algorithm

With the rapid development of the national economy, China's car ownership is increasing, so the demand and value of the automobile after-service market are constantly rising. How to integrate the existing automobile maintenance and repair services to provide fast and convenient environment for car owners has become a difficult problem. Firstly, in view of the sparsity of user-store scoring matrix, this paper proposes geolocation-based matrix partition to reduce the running time. Then demographic-based recommendation algorithm is employed to solve the 'cold start' problem existed in user-based collaborative filtering recommendation algorithm. Finally, in terms of different users' concerns, a dynamic multidimensional scoring model is proposed. The experiment is conducted on the Meituan data, and the results show that the proposed method achieves good performance in recommendation efficiency, precision and recall. Meanwhile, this method also brings light to the future automobile after-service market.
Clinical Test on Treatment of Paraplegia by Supreme Rehabilitation Act after Spinal Cord Injured

This study aims to integrate the traditional supreme training methods into the treatment and rehabilitation ofparaplegia after spinal cord injured. Through research, this paper holds that supreme rehabilitation method is akind of treatment and rehabilitation method with Chinese characteristics which integrates traditional martial arts.The main purpose of this paper is to explore the effect of this treatment and rehabilitation method. In terms ofresearch methods, 32 cases of this type of patients were divided into two groups randomly, among which thefirst group consisted of 17 people, who were treated and rehabilitated by supreme rehabilitation. Another groupof 15 patients were treated and rehabilitated using traditional methods of exercise rehabilitation. Through 12months of rehabilitation treatment and training, the core indexes of daily living ability, motor ability and sensoryability of the two groups of patients were compared, and the therapeutic and rehabilitation effects of the twogroups of patients were evaluated. In the evaluation process, Adopted the Scoring criteria for recovery of spinalcord injured developed by the German Spinal Cord Injury and Rehabilitation Association in 2013, Judged by thethe ASIA sensory index, ASIA motor function index and ASIA self-care function index of the two groups’patients. The research results showed that the ASIA motor function index of the first group using supremerehabilitation was significantly better than that of the second group using traditional exercise rehabilitation,which indicated that supreme rehabilitation was more beneficial to the rehabilitation of patients’ motor function.The ASIA sensory index score of supreme rehabilitation group was higher than that of traditional rehabilitationexercise training group, which indicated that supreme rehabilitation method was more beneficial to patients’sensory function recovery. The ASIA self-care function index score of supreme rehabilitation group members isalso better than that of traditional rehabilitation exercise training group, which indicates that patients’ self-careability can also be better restored through the treatment and recovery of supreme rehabilitation method.Therefore, this paper concludes that supreme rehabilitation can improve patients’ motor function, sensoryfunction and self-care ability significantly in the rehabilitation of paraplegia after spinal cord injured.
Analyzing the Detectability of Harmful Postures for Patient with Hip Prosthesis Based on a Single Accelerometer in Mobile Phone

This research studies the use of a single accelerometer inside a smartphone as a sensor to detect those postures that may be risks for patients with hip surgery to dislocate their joints. Various postures were analyzed using Euclidean distances to determine the feasibility to detect eight postures that were harmful. With the mobile phone attached to the affected upper leg, it was found that there was one harmful posture that could not be detected due to its close similarity with a normal posture. Meanwhile, the other two harmful postures, although indistinguishable based on their measured data, were still detectable with the suitably selected threshold. The distance measure analysis is useful as an indicator as to which posture will be near to missing out in the detection process. This will form a guideline for further design of a practical and more robust detecting system.
Analysis of Strategy for Targeted New Student Using K-Means Algorithm

The admission of new students at Universitas Klabat is held every semester. Especially in Faculty of Computer Science which has two departments, namely Information Systems and Informatics that are growing. So that new student data continues to grow every year. The data obtained can be managed to produce important information as an institutional reference in making decisions, such as determining a promotion strategy. Through the right promotion strategy, Faculty can reduce costs for promotion. Therefore, this research was conducted to determine an effective and efficient promotion strategy to targeted new student and information can be spread on the right target. This study uses data from newly enrolled students consisting of 243 data using several attributes such as program study, gender, origin, religion, school, major, and promotion. We used K-Means algorithm, which is one of the non-hierarchical clustering data methods in classifying student data into several clusters based on data similarity, so that students who have the same characteristics are grouped into one cluster. We also used a statistical gap method to determine an optimum cluster. The cluster of students was classified into three clusters in the followings: cluster 0 produces 59 data, cluster 1 produces 94 data, and cluster 2 produces 90 data.