Reviewerly/exHarmony huggingface dataset:
A Dual-Thread Method for Time-Optimal Trajectory Planning in Joint Space Based on Improved NGA

To solve the problem that the time-consuming optimization process of Genetic Algorithm (GA) can erode the expected time-saving brought by the algorithm, time-optimal trajectory planning based on cubic spline was used, after the modification to classical fitness sharing function of NGA, a dual-threaded method utilizing elite strategy characteristic was designed which was based on Niche Genetic Algorithm (NGA) with the fitness sharing technique. The simulation results show that the proposed method can mitigate the contradiction of the long term the optimization algorithm takes but a short running time the trajectory gets, demonstrating the effectiveness of the proposed method. Besides, the improved fitness sharing technique has reduced the subjective process of determining relevant parameters and the optimized trajectory results met performance constraints of the robot joints.
Using Interlinear Glosses as Pivot in Low-Resource Multilingual Machine Translation

We demonstrate a new approach to Neural Machine Translation (NMT) for low-resource languages using a ubiquitous linguistic resource, Interlinear Glossed Text (IGT). IGT represents a non-English sentence as a sequence of English lemmas and morpheme labels. As such, it can serve as a pivot or interlingua for NMT. Our contribution is four-fold. Firstly, we pool IGT for 1,497 languages in ODIN (54,545 glosses) and 70,918 glosses in Arapaho and train a gloss-to-target NMT system from IGT to English, with a BLEU score of 25.94. We introduce a multilingual NMT model that tags all glossed text with gloss-source language tags and train a universal system with shared attention across 1,497 languages. Secondly, we use the IGT gloss-to-target translation as a key step in an English-Turkish MT system trained on only 865 lines from ODIN. Thirdly, we we present five metrics for evaluating extremely low-resource translation when BLEU is no longer sufficient and evaluate the Turkish low-resource system using BLEU and also using accuracy of matching nouns, verbs, agreement, tense, and spurious repetition, showing large improvements.
Deep-Learned Artificial Intelligence for Semantic Communication and Data Co-processing

Trans-disciplinary activity in system-informational culture (SIC) caused great knowledge sophistication and necessity for any person to have synthesis of true scientific presentations. Complication of informational flows satiated with scientific meanings needs their co-processing with the help of deep-learned artificial intelligence (DL IA). Artificial intelligence (IA) will assist man to identify universalities for third world understanding. Otherwise, it will be impossible to live comfortably in computer instrumental systems and its applications. Arising intellectual difficulties will alter significantly SIC subject armed with DL IA − powerful means of learning, cognition, and world study. Trained rational consciousness allows achieving semantic level of communication in SIC. In its work, DL IA leans on system axiomatic method and personal cogno-ontological knowledge base descript in language of categories. Examples explain contributed technology.
A Synthetic Integrative Algorithm of Fast Concurrent Detection-Recognition with Effective Tracking of Aerial Objects based on Deep Learning of CNN

In this paper, a synthetic integrative algorithm of fast concurrent detection-recognition with effective tracking of aerial objects is presented, in which the deep learning of CNN is employed to carry out high-performance detection, recognition and tracking of aerial objects. In the synthetic integrative algorithm, a concurrent detection-recognition mechanism is designed and implemented based on DarkNet-53 with FPN structure and RFB module. Furthermore, the object movement is predicted by well-trained Siamese RPN with image transformation so as to achieve a high-performance tracking for aerial objects. In view of the shortcoming of missing target in the tracking stage and some false positive results in the stage of concurrent detection-recognition a discriminative classifier is designed to deal with and eliminate the false positive ones. Finally, a synthetic optimization strategy is proposed towards the integration of concurrent detection-recognition with tracking by filtering out disturbances with the discriminative classifier and confirming effective results by the IOU matching so as to make the whole algorithm works well and achieve a superior performance. Based on the simulation demonstration with a software of X-Plane 10, two datasets, Aerial Object Detection (AOD) and Aerial Object Tracking (AOT), are generated, and a series of experiments are conducted on the AOD and AOT to verify and validate the performance advantages of our proposed algorithms.
Survey on Spam Filtering Using Netspam Framework

Majority of people uses internet and trust's the contents over it. The scenario where anyone can bring out a survey gives an open edge to the spammer to generate fake surveys about products and services. Identification of these intruder and fake contain is a widely debated issue of research as of now tremendous amount of studies has been done till now, then also the existing work lacks behind in differentiating spam reviews and none of them gives the significant result to the collected feature type. This application uses a new structure, called NetSpam, which offers spam features to demonstrate product review data sets as heterogeneous information networks in order to design a spam review detection method in such networks. Using the importance of spam features helps us to achieve better results on review data sets with respect to different metrics. The outcomes represent that NetSpam results with the previous methods and encompassed by four categories of features: The first type of features performs better than the other categories, involving review - behavioral, user - behavioral, linguistic review and user - linguistic.
Consensus-Based Kalman filter for multi-target tracking with integrated measurements*

A distributed Kalman filter for integrated measurement of interactive multi-target tracking is proposed. The consistency Kalman filter is a distributed information fusion algorithm. Each target is estimated by the absolute measurement information and the relative measurement information of neighbor target. The absolute measurement information is the measurement information of multiple sensors. The estimated value is obtained by the consistency fusion. That is, in wireless sensor network, the sensor node and neighbor node carry out the data exchange. All nodes get consistent and high-precision estimates. The design of the gain matrix is obtained by minimizing the upper bound of the estimation error covariance matrix. The effectiveness of the algorithm is verified by numerical simulation.
Pengembangan Sistem Pemetaan Status Mutu Air Sungai Berbasis Web Menggunakan Extreme Programming

The high water pollution index causes a decrease in water quality so that it can interfere with the health of living things. In order to overcome this, the government has tried to monitor water quality whose results can be known by the community. However, information disclosure and ease of accessing information are felt to be lacking. This study aims to present information about the quality status of river water and its relatively up-to-date and easily accessed by the public online. The storet method is used to determine the status of river water quality with seven parameters: temperature, EC, TDS, pH, DO, BOD and E.coli. The features provided will be explained in the results and discussion presented in several UML diagrams. In order to get results that match user expectations, this system was developed with extreme programming system development methods.
Innovative Reform in Teaching of Foundation of Machine Manufacturing Technology Course

Foundation of machine manufacturing technology is a very important course for students majoring in machinery.To overcome the problems existing in the teaching process of this course, an in-depth investigation is conducted and corresponding improvement adjustments are given.Furthermore, the teaching reform is explored and a more reasonable course teaching system is constructed.From teaching means, teaching arrangement, assessment method and teaching content, this paper discusses how to improve the teaching quality of the foundation of machine manufacturing technology course.The multi-directional and open practice teaching platform proposed in this paper can be a useful tool to satisfy the needs of application-oriented personnel training.
Developing Artificial Intelligence in Fighting, Preventing and Combating the Digital Business Crimes

The Industrial Revolution 4.0 and (AI) are the key factors creating the emergence of high-tech crimes, including digital business crimes.In the article, the authors discussed the most general knowledge and the application of AI in the fight and prevention against crimes in digital business.The article also pointed out the role of AI application in combating and preventing various types of crime and initially pointed out the advantages and disadvantages of the application of AI in the fight, prevention, and combat against various types of crime.From there, the author gave some remarkable points in the development of AI in fighting and combating digital business crimes in Vietnam in the future.
Adoption of the Guidelines for Higher Education Libraries in Portugal: contributions to assessment

Three years after the publication and large-scale dissemination of the guideline document "Recommendations for Higher Education Libraries", we seek to understand the extent to which this document has been adopted by librarians and how revealing practices and experiences have been introduced in Portuguese higher education libraries. This paper aims to assess the application of the Recommendations in the area of user training, particularly in information literacy; in digital content management, including data and scientific production; and in the direct support to students, teachers and researchers, not forgetting the aspects of space management and information resources as a whole. For this purpose, a questionnaire survey was used for higher education libraries in Portugal. The most implemented areas are information literacy and the management of institutional repositories, and the one with the lowest level of the application relates to support for editorial projects.
Students’ Perceptions of the Utilization of ICT in English Learning: Way or Barrier?

This study aimed to describe the students' perceptions of the utilization of ICT in English learning.One hundred and thirty-four students of a private university in South Sumatera were involved as participants of this study.The questionnaires were administered to gain a portrait of students' perceptions.Based on the findings, it was figured out that ICT promoted learning activity, maintained learning motivation, and increased learning achievements.However, ICT potentially hindered students' focus and exposed students to data misuse.These contrary results lead to the discussion on how to maximize the positive impacts of ICT utilization and minimize its potential negative impacts.Several recommendations were formulated such as conducting correlational research to find out the relationship between ICT use and students' English achievement or investigating the effects of ICT implementation on students' English learning achievement through experimental design.
T-Mix: A Threshold Cryptography Mixing Service for Bitcoin

Bitcoin is the first successful implementation of the blockchain, which eliminates the role of trusted centralized settlement entities. Although Bitcoin was designed with anonymity in mind, it has recently faced privacy challenges as some users’ identities have been revealed (Biryukov and Khovratovich 2014; Fleder et al. 2015; Maesa et al. 2016, 2017) To address this issue, mixing services are used in Bitcoin to increase user anonymity. Mixcoin provides a centralized mixing service that reduces the impact of blockchain transaction analysis by hiding the links among transaction addresses to preserve users’ anonymity. However, Mixcoin has shortcomings against active attacks in which the attacker can compromise mixing service and inject fraudulent transaction addresses to steal funds. Mixcoin has an integrity issue in that the mixing service enabled dishonest behavior. This paper proposes T-Mix, a protocol that addresses Mixcoin’s shortcomings by enhancing its availability and integrity using threshold cryptography. We present Mixcoin’s threat model followed by a description of T-Mix.
Posterior Ratio Estimation of Latent Variables

Density Ratio Estimation has attracted attention from the machine learning community due to its ability to compare the underlying distributions of two datasets. However, in some applications, we want to compare distributions of random variables that are \emph{inferred} from observations. In this paper, we study the problem of estimating the ratio between two posterior probability density functions of a latent variable. Particularly, we assume the posterior ratio function can be well-approximated by a parametric model, which is then estimated using observed information and prior samples. We prove the consistency of our estimator and the asymptotic normality of the estimated parameters as the number of prior samples tending to infinity. Finally, we validate our theories using numerical experiments and demonstrate the usefulness of the proposed method through some real-world applications.
UAV Path Planning Simulating Driver’s Visual Behavior with RRT algorithm

To solve the problem of long time-consuming and low success rate of UAV path planning in the complex blockage environment, we combine the RRT algorithm with the driver's visual behavior and propose a RRT UAV path planning method simulating driver's visual behavior in this paper. We use the RRT algorithm with fast search capability to expand the nodes and incorporate the UAV's partial constraints into the path planning algorithm. The driver's visual behavior is used to provide visual guidance points for the UAV. Finally, the greedy method is used to process the obtained paths to get a shorter and smoother path. The simulation results show that the proposed algorithm can quickly find a feasible path in complex environment space, which can be used for UAV path planning.
Learning Japanese Language Based on 2013 Curriculum at Elementary Schools in Bali

This study aimed at describing the implementation of the 2013 curriculum in learning Japanese at elementary schools in Bali, considering that learning Japanese has not been taught only in high /vocational school level.The results of questionnaires and interviews revealed that only 20% of them have implemented the 2013 curriculum for Japanese language.The context of Japanese language learning at this level is the addition of character education and literacy.From the respondents (students), it was found that there was a tendency for students to like Japanese (67.4%), because they were interested in Hiragana and Katakana letters, besides of Japanese culture and food.On the contrary, respondents who were not interested stated the difficulty of memorizing Japanese letters as reasons for their dislike.This study also showed that the nonoptimal implementation of the 2013 curriculum for Japanese was due to the absence of 2013 curriculum-based learning tools.
Preserving unitarity for overlapping multichannel states: Breit-Wigner versus K matrix -- comparison, advantages and disadvantages

The K-matrix method is often used to describe overlapping resonances. It guarantees the unitarity of the scattering matrix but its parameters are not resonances masses and widths. It is also unclear how to separate resonant and background contributions and to describe background in terms of phase shifts. The Breit-Wigner (BW) approach operates with parameters having direct experimental meaning but a simple sum of the BW functions is not unitary. We show how to construct the unitary S-matrix by taking into account the interference of the BW functions. The method is simple and straightforward, background can be added to resonance amplitudes in the standard quantum mechanics form. In examples we give a comparison between the K-matrix and unitary BW-approaches.
Development of an online assessment based on the Shareable Content Object Reference Model (SCORM) to optimize the use of BeSmart UNY

Abstract This study aimed at developing an Online Assessment based on the Shareable Content Object Reference Model (SCORM) package. This study focused on: (1) obtaining an online assessment design based on SCORM package for the subject of Medical Instrumentation and Electronics based on needs analysis; (2) examining the functionality of the developed online assessment and (3) analyzing the usability of the developed online assessment. This software development process used the ADDIE development model. The testing stage of this study was conducted to verify and to validate the software. The software verification process was performed with functionality testing by media and material experts, and usability testing by users. The results indicated that: (1) it was obtained the design of an online assessment based on SCORM package for the subject of Medical Instrumentation and Electronics, including an online assessment in Besmart packed with SCORM Packages in the form of quiz integration (multiple-choice, short answer, true or false, drag and drop questions); (2) the functionality testing by material experts with a score of 3.88 and a media expert with a score of 4.16 suggested that the developed online assessment was feasible in the aspect of functionality; (3) usability testing by users achieved the score of 3.88 indicating that the developed online assessment was feasible in the aspect of usability.
Automatic Counting for Canine Red Blood Cell based on Two-stage Circular Hough Transform

Red blood cell counting is one of the most requested blood tests and can be effectively done by the dedicated equipment. In this paper, we proposed the two-stage circular Hough transform as the alternative automatic method for canine red blood cell counting. The possible blood cell area in the input slide image is first extracted. In the first stage, the Circular Hough transform with low sensitivity is applied to detect the non-overlapped cells. The detected cells are removed. The Circular Hough transform with high sensitivity is re-applied to the remaining region in order to detect the overlapped cells. The proposed method can be easily implemented into personal computers. The proposed algorithm was tested with many slides of canine red blood cell. It provided the counting with the average error of less than 5% with the best result of 1.439% error.
Rolling sphere along an inclined multi-slotted track

In this work we study the motion of a small metal ball along an inclined multi-slotted track. Specifically, the effect of the slot width on the ball speed at the lower part of the track is analyzed in detailed both analytically and experimentally. Experimental results are in satisfactory agreement with the theoretical model.
Integrated Architecture of Web Services using Multiagent System for Minimizing Interoperability

A web service Interoperability issues arise mainly due to semantic and syntactic levels. Syntactic level comprises standards for data type definition, parameter passing during operations and incompatible data formats while passing messages between services. Semantic level comprises data and data formats should be meaningful and precise when passing to other application. Guidelines have been defined by Web Service Interoperability Organization (WS-I) basic profile version 1.1/2.0 to reduce interoperability issues at a complex level and remove at an elementary level. But after so many years it has achieved success to a limited extent. Therefore, in this paper, a framework of web services with a multiagent system is proposed that would be helpful in minimizing the interoperability issues between two platforms JAVA and.NET. The framework includes a JADE gateway agent to reduce interoperability issues.
TempLe: Learning Template of Transitions for Sample Efficient Multi-task RL

Transferring knowledge among various environments is important to efficiently learn multiple tasks online. Most existing methods directly use the previously learned models or previously learned optimal policies to learn new tasks. However, these methods may be inefficient when the underlying models or optimal policies are substantially different across tasks. In this paper, we propose Template Learning (TempLe), the first PAC-MDP method for multi-task reinforcement learning that could be applied to tasks with varying state/action space. TempLe generates transition dynamics templates, abstractions of the transition dynamics across tasks, to gain sample efficiency by extracting similarities between tasks even when their underlying models or optimal policies have limited commonalities. We present two algorithms for an "online" and a "finite-model" setting respectively. We prove that our proposed TempLe algorithms achieve much lower sample complexity than single-task learners or state-of-the-art multi-task methods. We show via systematically designed experiments that our TempLe method universally outperforms the state-of-the-art multi-task methods (PAC-MDP or not) in various settings and regimes.
GRAPHICAL PASSWORD AUTHENTICATION - SURVEY

The most common computer authentication approach is to use alphanumerical usernames and passwords. This method has been proven to have vast drawbacks. For example, users tend to choose passwords that can be easily guessed. On the other hand, if a password is difcult to guess, then it is frequently difcult to remember. To address this problem, some researchers have developed authentication strategies that use images as passwords. In this paper, we conduct a complete survey of the current graphical password techniques. We classify these strategies into two categories: recognition-based and recall-based approaches. We discuss the strengths and barriers of each technique and point out the future research instructions in this area. We also try to answer two necessary questions: “Are graphical passwords as secure as text-based passwords?”; “What are the important design and implementation issues for graphical passwords?” This survey will be useful for data protection researchers and practitioners who are involved in nding an choice to text-based authentication methods.
Best Practices and Recommendations for Cybersecurity Service Providers

Abstract This chapter outlines some concrete best practices and recommendations for cybersecurity service providers, with a focus on data sharing, data protection and penetration testing. Based on a brief outline of dilemmas that cybersecurity service providers may experience in their daily operations, it discusses data handling policies and practices of cybersecurity vendors along the following five topics: customer data handling; information about breaches; threat intelligence; vulnerability-related information; and data involved when collaborating with peers, CERTs, cybersecurity research groups, etc. There is, furthermore, a discussion of specific issues of penetration testing such as customer recruitment and execution as well as the supervision and governance of penetration testing. The chapter closes with some general recommendations regarding improving the ethical decision-making procedures of private cybersecurity service providers.