Reviewerly/exHarmony huggingface dataset:
Assessment Model of Safety Situation in Low-Altitude Airspace Based on AGA-FCM

With the opening of low-altitude airspace in China and the increasing general aviation operation, the safety problem has become increasingly severe. It is necessary to assess the safety situation in low-altitude airspace for improving air traffic management efficiency and low-altitude airspace safety. In this paper, a method to assess safety situation in low-altitude airspace is proposed based on adaptive genetic algorithm (AGA) and fuzzy C-means clustering algorithm (FCM). It studies the safety state and trend of low-altitude airspace in the process of aircraft interaction. Firstly, by combining characteristics of low-altitude operating environment and data from flight simulation, an index system is constructed to assess safety situation in low-altitude airspace. Then, an AGA-FCM-based assessment model and a spatial visualization method of safety situation are proposed. Finally, according to the simulation data analysis of a low-altitude airspace operation scenario, temporal and spatial distributions of safety situation are calculated. Verified by the fuzzy matter-element model, the results confirm that the proposed assessment model of safety situation in low-altitude is effective and feasible. Therefore, it provides a useful reference for improving planning and management level of low-altitude airspace.
Implementation Evaluation Metrics for ERP Solution

Most institution of higher learning are implementing enterprise resource planning (ERP) in automating various activities. The architecture of most of the ERP is based on the service-oriented architecture (SOA) where each module can be called as service. In most of the contracts signed between the vendor and the university, payment is tied to the level of implementation. The question is how to then measure the level of implementation. This chapter proposes a metric that could be used. The metric was derived based on an acceptance test on each of functionality of module as per terms of reference. The result of a test was rated as a fail; the result was then coded such that a fail was assigned a zero (0), pass one (1), and query a half (½), from which a metric was derived which measures the level implementation.
Conclusions and Future Work on the Generalized Type-2 Fuzzy Sugeno Integral

In this work, the main goal was to develop a method to extend the fuzzy Sugeno integral using generalized type-2 fuzzy logic. The proposed method was developed and it was demonstrated that it works properly in two very different applications.
Key-Controlled PEG-LDPC Algorithm Design and Its Application in Secure Communication

Because of the security of the symmetric cryptosystem, a secure communication scheme based on PEG-LDPC codes has been put forward in this paper. The secure and reliable integrated communication is based on hiding and changing generator matrix randomly and simultaneously under the premise of ensuring error correction ability of LDPC codes. The performance of LDPC codes constructed by PEG algorithm is excellent, and this algorithm can construct an LDPC code with arbitrary code length and code rate.
On the investigation of population sizing of genetic algorithms using optimal mixing

Genetic algorithms using optimal mixing have shown promising results, while lack of theoretical supports. This paper investigates population sizing from the supply aspect under the optimal mixing scenario. Specifically, more precise analyses on supply, including the expectation and the lower bound, are made. In addition, considering recombining one randomly generated chromosome with the rest of the population to achieve the global optimum, the tight bounds of the size of the population providing proper fragments chosen by restricted oracles are derived. Tight bounds on problems with ring topologies where a subfunction overlaps two other subfunctions are also derived. Finally, experiments are conducted and well match the derivations.
Detection of trace elements in metallurgical products under complex background based on visual saliency

Aiming at the problem of detecting blurred targets by line scan CCD images in complex background, a target detection algorithm based on visual saliency is proposed. According to the characteristics of the line scan CCD target image, the feature of the weak target is analyzed, and the CCD image is preprocessed. By calculating the difference between two near frames in the image, all the complex backgrounds of static and slow motion are removed. A new feature vector is constructed, and a double search window similar to the target shape is designed. A significant image of the line scan CCD image is obtained by calculating the similarity of the feature vectors in the center of the window and the surrounding pixels. The salient map is then clustered and segmented to extract the target. The experimental results show that compared with weighted average filtering and median filtering, this method can effectively suppress noise and background, detect dark targets in images, increase the global signal-to-noise ratio by two times, and improve the detection reliability.
Finite Identification with Positive and with Complete Data

We study the differences between finite identifiability of recursive languages with positive and with complete data. In finite families the difference lies exactly in the fact that for positive identification the families need to be anti-chains, while in the infinite case it is less simple, being an anti-chain is no longer a sufficient condition. We also study maximal learnable families, identifiable families with no proper extension which can be identified. We show that these often though not always exist with positive identification, but that with complete data there are no maximal learnable families at all. We also investigate a conjecture of ours, namely that each positively identifiable family has either finitely many or uncountably many maximal noneffectively positively identifiable extensions. We verify this conjecture for the restricted case of families of equinumerous finite languages.
Practical Methods for Data Analysis

Data analysis is essential for understanding the phenomena observed in the actual environment. Data analysis forms a workflow consisting of data acquisition, collection, visualization and quantification, and interpretation. The purpose of data analysis is to find insights into phenomena that we have attended to and make decision-makers change their behavior. Data utilization should form an improvement cycle with Check, Action, Plan, and Do (CAPD). This chapter shows a fundamental definition of data (four types of data formats, such as time series, network, spatial, and linguistic data). Several methodological frameworks for analyzing data and how to use the results obtained from data analysis are discussed.
Face Recognition Algorithm Based on Nonlinear Principal Component Feature Extraction Neural Network

In order to solve the face recognition problem with different factors such as light, human expression and angle of shooting, a nonlinear principal component feature extraction neural network model is used in this paper. Researchers have proposed many algorithms for identifying applications, but the limitations of single algorithms cannot meet the requirements of practical application. By introducing the nonlinear principal component analysis (PCA), the proposed algorithm deletes a large amount of nonlinear data on the premise that a small amount of information can be guaranteed after linear dimensionality reduction. And the computational complexity of the neural network algorithm (BPNN) is large, so we use the nonlinear principal component analysis method to ensure the amount of information of the original data, and combined with the neural network algorithm to improve the efficiency of the algorithm. Empirical results show that PCA method can effectively reduce redundant data and ensure data integrity. Data after dimensionality reduction can improve the computational efficiency of neural network algorithm. The BPNN based PCA model can effectively solve the time consumption and recognition accuracy of the face recognition.
Prediction Model of Wavelet Neural Network for Hybrid Storage System

The Hybrid storage system needs to distinguish the data state to manage data migration. The frequently data may be placed solid-state hard disk to improve the accessing performance. Here a novel prediction model of the frequently accessing data that is called hot access data is proposed. This model extracts the workload features and is built based on the wavelet neural network to identify the data state. The prediction model is trained by the sampling data from historical workloads and can be applied in the hybrid storage system. The experimental results show that the proposed model has better accuracy and faster learning speed than BP neural network model. Additionally, it has better independent on training data and generalization ability to adapt to various storage workloads.
Path Planning for an Unmanned Aerial Vehicle Considering Dynamic Geo-Fence in Urban Environment

Recently, Unmanned Aerial Vehicles (UAVs) are widely used for various purposes such as aerial reconnaissance and delivery in urban areas. However, in some urban areas there are geo-fences where aerial vehicles cannot pass through. So, the importance of a path planning including obstacle avoidance has increased. In addition to the actual observable obstacles, it is also necessary to plan the route considering special areas or boundaries such as geo-fence. In this paper, we propose an algorithm to avoid dynamically changing geo-fence. To generate an efficient path which does not pass through the geo-fence, we add a time parameter. This proposed path planning algorithm considers not only obstacles on the map at present. The goal is to create an efficient path that also takes into account the geo-fence information dynamically generated over time, along with the speed of the UAV and the time it takes to pass through a specific location. Simulations are carried out to verify the performance of the proposed path planning algorithm.
Dynamic FP Tree Based Rare Pattern Mining Using Multiple Item Supports Constraints

Data mining is a fundamental ingredient for making association rules among the largest variety of itemsets. Rare pattern mining is extremely useful judgment to generate the unknown, hidden, unusual pattern, using predefined minimum support confidence constraint from transactional datasets. Rare association rule is related to rare items that represent useful knowledge. Mining rare patterns from those database is more interesting rather than frequent pattern mining. In this paper, we presents the taxonomy of different support constraint model for rare pattern mining. Also we have performed a comprehensive literature review on existing tree based rare pattern mining algorithms. Finally, we have proposed a multiple item support constraint based dynamic rare pattern tree approaches that only generates rare itemset without considering frequent itemsets generation.
From Digital to Analogue: An Interdisciplinary Case Study to Enhance the Communication of Design Products Through Physical Constraints

Emerging technologies have the potential to make everyday life easier with an increasing number of benefits. However, it is argued that digital products are developed from a techno-centric perspective rather than being human-centered. With the complicated structures they have, they may also cause dissatisfaction and difficulty in their use, due to the unfamiliarity to the mental models of the users. In the area of human-computer interaction, many learning and outcomes have been achieved. This research aims to explore how this knowledge can be benefited for the design of products that are controlled by analogue means. Within the scope of the research, 5-week workshop was planned and applied to Communication Design senior students, who had many design experience with digital media. The outcomes revealed that, when user-centered design method and metaphorical thinking are integrated in the design process, the products’ cognitive, physical, sensory and functional affordance improved.
INFORMATION BATTLE AS A FORM OF EDUCATIONAL WORK

The technology of the information battle is a two-stage activity in the formation of the students’ research and communication skills, as well as the ability to independently study the proposed topic and present it to the others. It optimizes the educational process, changes not only the student’s learning activity, but also the teacher’s position, makes it possible to individualize learning, improve the efficiency of the pedagogical process, ensuring the quality of specialist training at a competitive level. An option is given to use technology in a class on #СТОПВИЧСПИД.
Accounting for Dynamic Diversity Among Child Users of IoT

As IoT becomes increasingly pervasive, children are more regularly encountering IoT. The recent GDPR legislation in Europe goes some way toward protecting children as they make use of these IoT and other technologies, but there remain significant challenges in ensuring that the IoT that pervades children's world is socially responsible. This paper explores some of the reasons why the ethical implications of IoT for children is difficult to contain, and suggests several ways that design might make progress toward socially responsible IoT.
Indoor Positioning and Path Planning Platform for iRobot Create 2 Sweeping Robot

Many robots have been proposed for smart applications in recent years However, while these robots have good ability to move between fixed points separated by short distances, they perform less well when required to navigate complex interior spaces with an irregular layout and multiple obstacles due to their relatively crude positioning and path control capabilities.Accordingly, the present study proposes an integrated system consisting of a Raspberry Pi development platform, various sensor devices and iBeacon technology to facilitate the path control, indoor positioning, and obstacle avoidance of a programmable iRobot Create 2 sweeping robot.The capabilities of the proposed system and its various components are investigated by means of practical experiments and numerical simulations.In general, the results confirm that the proposed integrated system provides a viable platform for the future development of sophisticated indoor robots for smart indoor applications.
An application of combined effect time dependent data CETD matrix

This paper presents to study the maximum age group of major problems of Housemaids by different age interval. In section one, we recall the introduction to Fuzzy and Combined Effect Time Dependent Data (CETD) Matrix. Section two describes the Introductions to housemaids. In section three shows the previous research work which we have used in our research. In section four gives the maximum age group of psychological problems of housemaids in chennai-using by different age interval (CETD) matrix using 5x7 matrices by different age interval. In final section gives the conclusions and suggestions based on our study.
Introducing the Problem

In this chapter the so-called ‘indexing problem’ of multi-line triangulation will be introduced, motivated by the example of the sensor principle Flying Triangulation (see Sect. 3.3.3 and [1–5]). The indexing problem is the main reason for the low efficiency of current multi-line triangulation approaches.
Do Humans Reason with $$\mathcal{E}$$ -Matchers?

The Weak Completion Semantics is a novel, integrated and computational cognitive theory. Recently, it has been applied to ethical decision making. To this end, it was extended by equational theories as needed by the fluent calculus. To compute least models equational matching problems have to be solved. Do humans consider equational matching in reasoning episodes?
Pedagogical culture of the head of the body of internal affairs Mongolia and the ways of its formation

The object of the study, which formed the basis of the article, is the pedagogical culture of the head of the internal affairs agencies, while the subject is the ways of forming the pedagogical culture of the head of the internal affairs agencies. As the goal of the study, the authors see the definition of ways to effectively form a pedagogical culture of heads of internal affairs forces. The research method was the following: the method of expert assessments and the analysis of the results of the pedagogical activity of the heads of the internal affairs forces of Mongolia. The sphere of the general culture of a leader, as a citizen of his country and a person, contains his spiritual and material values. In addition, it is possible to include in this area also methods for the implementation of pedagogical activities that are necessary for society to socialize the individual and ensure the historical process of generational change. That is, the essence of the pedagogical culture of the head of the internal affairs forces is somewhat wider than the sphere of educational activities. Accordingly, during the process of forming the pedagogical culture of the head of the internal affairs forces, a new level of its general culture is being formed, such universal human qualities as spirituality, mercy, a sense of social justice, respect for human dignity, conscience, etc. are being formed. The research results are aimed at improving the efficiency of the existing pedagogical system and activates the process of improving the formation of pedagogical culture among the heads of the internal affairs forces of Mongolia.
Dynamics of Potential Functionality of Objects

Abstract This article guides the reader through the seemingly simple issues of the assessment, protec-tion and transfer of the potentials of an object’s functionality through its internal and external buffers, by employing Cartesian multiplication and signatures. The change in the potentials of buffers and the functionality of objects is the focus of this research, guaranteeing the correct use of potentials in relation to the whole “shell” of the object. In order to avoid any collision in the transport of functional potentials, each proper buffer is, by definition, connected to one and only one object. On the probability scale ∑ [0..1], the potential of the object’s functionality is expressed as the system sum [0..1] of all the potentials of its proper buffer components. A practical and important part of the article contains two methodologically important examples of tabular construction and analysis: an example of the dynamics of the potentials of an object with two buffers, together with a table of the potentials of a two-buffer object; and an example of the Cartesian product of graphs with lost determinism together with the table of potentials of a two-buffer object with an extensive option structure.
Visualization of Component-Based Software Architectures: A Comparative Evaluation of the Usability in Virtual Reality and 2D

Software visualization provides a good opportunity to explore complex software architectures. But to reach a high level of usability it is important to evaluate such visualizations properly. We present the results of an usability study that we conducted to compare the visualization of component-based software architectures in both 2D and Virtual Reality (VR), based on different representations. Study participants had to conduct five interactive tasks. The results of our study shows that users are more likely able to complete the tasks in 2D than in VR, that they are more likely able to faster complete the tasks in 2D than in VR, and that they experience more satisfaction while using 2D than VR. Because evaluations of software visualization approaches are still rare, our results might help to create further study designs and offers some advice for the development of future visualizations—especially in VR.
Representation of Recipe Flow Graphs in Succinct Data Structures

The recipe flow graph is a directed acyclic graph for representing the procedure of the cooking recipe, and it is expected to contribute to the research to understand the whole meaning of the recipe text precisely. The recent rapid increase in health awareness has generated a large amount of user-generated recipe texts and corresponding recipe flow graphs in social networking services. In this research, to alleviate the problem of huge memory consumption and long computation time for handling a large number of recipe flow graphs, we propose to utilize succinct data structures to store the databases of recipe flow graphs. The effectiveness of our implementations of flow graph databases in two types of succinct data structures for trees and graphs was confirmed by the preliminary experiments using real recipe flow graphs.
A Soft Computing-Based Daily Rainfall Forecasting Model Using ELM and GEP

Precise daily rainfall forecasting play a very significant role in modern society that it can not only help for planning of people’s day-to-day activities, agriculture and business, but also assist water resource management in the region to warn or alleviate the effect of drought or flood disaster. However, various inherently complex meteorological factors and dynamic behavior influence the rainfall, with result that it is very difficult to accurately forecast daily rainfall. This study presents a soft computing modeling method based on Extreme Learning Machine (ELM) and Gene Expression Programming (GEP) to enhance the forecast performance. The proposed mode is compared with other five rainfall forecasting models to assess its performance for rainfall forecasting by Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). Experimental results show that the proposed method outperforms other models in terms of accuracy.
Attribution by Indictment

The challenges of attributing malicious cyber activity — that is, identifying its authors and provenance with a sufficient degree of certainty — are well documented. This essay focuses on a phenomenon that I call “attribution by indictment.” Since 2014, the United States has issued more than a dozen indictments that implicate four foreign states in malicious cyber activity: China, Iran, Russia, and North Korea. Ten of these indictments were issued in 2018, suggesting that this practice is likely to continue and even intensify in the near term. Attribution by indictment uses domestic criminal law, enforced transnationally, to define and enforce certain norms of state behavior in cyberspace. This essay analyzes the U.S. practice of attribution by indictment as a response to malicious cyber activity.
A Dialogue System for Elderly People Considering Impression Formation and User’s Character

In recent years, lack of communication among solitary elderly has become a big problem. In order to deal with the above situation, development of a dialogue system for solving the lack of communication of the elderly has been drawing attention in recent years. The concept of the system proposed in this paper is to induce communication in consideration of the situation of elderly people during dialogue. An agent who is friendly to the elderly conducts a conversation taking into account the feelings of the elderly, thereby enabling dialogue close to the elderly.