Reviewerly/exHarmony huggingface dataset:
NUI-SpatialMarkers: AR Spatial Markers For the Rest of Us

Multi-user Augmented Reality (AR) development tends to be very difficult and there are few tools that allow developers to easily deal with the unique problems that arise. One of the main problems that arises from multi-user AR is that of aligning objects. In this paper we present a light weight, open source system for solving the aligning problem. This system was specifically designed to make it as easy as possible for developers to modify components to fit their needs.
Shortest Unique Palindromic Substring Queries in Semi-dynamic Settings

A palindromic substring T[i..j] of a string T is said to be a shortest unique palindromic substring (SUPS) in T for an interval [p, q] if T[i..j] is a shortest one such that T[i..j] occurs only once in T, and [i, j] contains [p, q]. The SUPS problem is, given a string T of length n, to construct a data structure that can compute all the SUPSs for any given query interval. It is known that any SUPS query can be answered in $$O(\alpha )$$ time after O(n)-time preprocessing, where $$\alpha $$ is the number of SUPSs to output [Inoue et al., 2018]. In this paper, we first show that $$\alpha $$ is at most 4, and the upper bound is tight. Also, we present an algorithm to solve the SUPS problem for a sliding window that can answer any query in $$O(\log \log W)$$ time and update data structures in amortized $$O(\log \sigma )$$ time, where W is the size of the window, and $$\sigma $$ is the alphabet size. Furthermore, we consider the SUPS problem in the after-edit model and present an efficient algorithm. Namely, we present an algorithm that uses O(n) time for preprocessing and answers any k SUPS queries in $$O(\log n\log \log n + k\log \log n)$$ time after single character substitution. As a by-product, we propose a fully-dynamic data structure for range minimum queries (RmQs) with a constraint where the width of each query range is limited to polylogarithmic. The constrained RmQ data structure can answer such a query in constant time and support a single-element edit operation in amortized constant time.
Characterizing the reputation of evaluators using vectors in the object feature space

Evaluation is a frequent occurrence in our daily lives, especially in online systems. Establishing ways to characterize the reputation of an evaluator is therefore becoming an important problem in online systems, and this has attracted much attention. Most existing evaluation methods use the rating information in user–object bipartite networks to evaluate the reputations of evaluators. These methods use a scalar quantity to represent the reputation of each user, which is applied to try to identify malicious ratings and spamming attacks. In this paper, we suggest that the reputation should be characterized by a vector, and propose a reputation–evaluation algorithm based on the classification of objects. More specifically, the objects are classified into several categories according to the community structure information obtained from a one-mode projection onto the objects of a bipartite network. The reputation vector of an evaluator then represents his/her reputation for the objects in different categories. The evaluator is also assigned an appropriate attribute according to his/her reputation vector using K-means clustering. The results from both artificial and real rating data have shown that the presented method is better than a correlation-based ranking method in terms of both accuracy and robustness.
TLAs: Are Common These Days

Three-Letter Acronyms (TLAs) are very popular, and can be found in almost everything written or spoken these days. Why? Perhaps it is because we are busy, lazy, or maybe there is just a fascination with things that come in threes. Most likely, we write or speak in TLAs because it makes our language more efficient at conveying information with the least possible cost. TLAs transform largely redundant information into a more expeditious form.
Integration and Utilization Strategy of University English Teaching Information Resources Based on Fuzzy Clustering Algorithm

With the changes of the times and the development of science and technology, modern multimedia technique has entered the field of schooling without hesitation. Modern schooling faces new challenges as a result of the information society. A new way of teaching is to integrate curriculum and information technology. Message technology is used to support not only teaching and learning but also the use of message-based resources. Students’ innovative thinking and action ability in the process of integration can be effectively released by mobilising the initiative and enthusiasm of science and engineering students. The quality of university English education has significantly improved since the implementation of the web-based schooling model. However, a number of obstacles prevent educators from making better use of educational message resources. A fuzzy clustering algorithm is used in this paper. The time spent on clustering optimization is reduced by more than half using this algorithm. Its prototype-based clustering algorithm is simple, efficient, and adaptable to large numbers. In clustering analysis, it is the most commonly used algorithm and a research hotspot.
Employment Opportunities for Applicants with Cybercrime Records: A Field Experiment

Various studies have shown that convicted offenders often face difficulties in finding employment. These studies, however, only examined traditional types of crime and little is known about the job opportunities of convicted cybercrime offenders. Therefore, this study examines the influences of being convicted for a cybercrime on labour market chances in the IT sector in the Netherlands. An experiment was conducted in which fictitious job applications were sent to existing job openings between March and June 2021 ( N = 300), varying for type of crime (cybercrime, property crime, no offence) and ethnic background (Dutch or Turkish). In order to test the hypotheses, logistic regression analyses were carried out to test whether differences in responses were significant. No significant differences in positive responses were found between cybercrime offenders and non-offenders, implying that cybercrime offenders do not have less labour market opportunities. Moreover, significant differences were found between Dutch and Turkish applicants. The results of this study indicate that results from previous studies on job opportunities of traditional offenders are not generalisable to cybercrime offenders. Possibly, a cybercrime record gives a positive signal of IT-skills that are useful for employees, while a criminal record for a property crime is associated with negative characteristics.
A Statistical Perspective for Empirical Analysis of Bio-Inspired Algorithms for Medical Disease Detection

Medical disease detection is a vast field of image, signal and video processing that involves a large number of complex operations, which include but are not limited to data acquisition, pre-processing, segmentation, feature extraction, feature selection, classification and post-processing. The efficiency of signal classification is directly proportional to the efficiency with which these internal blocks are designed. In order to improve the efficiency of these blocks, several bio-inspired optimization algorithms are proposed by researchers. These include but are not limited to, Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Neural Networks (NN), etc. Each of these algorithms can be applied to optimize individual signal processing blocks, thereby improving overall system performance. Due to a large variety of available bio-inspired algorithms, it is ambiguous for system designers to select the best possible algorithmic combination for their medical disease classification design. In order to reduce this ambiguity, the underlying text evaluates performance of some of the most efficient bio-inspired algorithms, and statistically compares them on basis of their application. These applications vary w.r.t. identified disease, type of signal being processed, etc. This comparison will assist researchers and system designers to develop highly efficient medical disease classification systems for clinical use.
The Potential of VR-based Tactical Resource Planning on Spatial Data

Planning tactical operations on topographic maps, for rescue or military missions, is a complex process conducted by interdisciplinary experts and involves the time-consuming derivation of 3D information from 2D maps, mostly solely executed by experienced professionals. Previous research repeatedly showed that virtual reality (VR) can convey spatial relationships and complex 3D structures intuitively. In this work, we leverage the benefits of immersive head-mounted displays (HMDs) and present the design, implementation, and evaluation of a collaborative VR application for tactical resource planning on spatial data. We derived system and design requirements from consultations with domain experts and observations of a military on-site staff exercise, a simulation-based training aiming to strengthen rapid decision-making and teamwork during a time of crisis. To evaluate our prototype, we conducted semi-structured interviews with domain experts who organized and observed field tests at different military staff exercises. The interviews support the proposed design of the prototype and show general design implications for planning tools in VR. Our results show that the potential of VR-based tactical resource planning is dependent on the technical features as well as on non-technical environmental aspects, such as user attitude, prior experience, and interoperability.
A New Improved LSB Chaotic Image Steganography Scheme

The purpose of the Steganography is to hide and transfer secret or sensitive information/message in a multimedia medium, so that it can not be understood by unintended parties. In the literature there are variety of techniques utilizing spatial domain image steganography but enhanced steganography schemes are still needed for improving quality of stego-image. In the proposed work, a new spatial domain steganography scheme enhanced by chaotic maps is presented, namely Tent map, Logistic map, Bernoulli Map, Quadratic Map, Chebyshev map and Sine Map in different combinations to select the pixel location for hiding data. A compression is carried out on the secret message before hiding in the carrier image in order to improve secret message amount. Assessment of the proposed system is carried out not only with quality of the stego image statistical values like PSNR, MSE and histogram but also in terms of, entropy, correlation for each chaotic map. It is concluded from the statistical test results that the proposed scheme is imperceptible enough for hiding the information in a digital medium. Moreover the proposed system has passed rigorous Stego-Analysis tests with stego analysis tool Virtual Steganographic Laboratory (VSL)
WeatherNet: Transfer Learning-based Weather Recognition Model

A transfer learning (TL) based multi-classification model has been developed to classify and recognize collected weather dataset with 1000 different weather images belonging to four different classes of weather. MobileNet V2 has been applied as a pre-trained model with a combination of weather image classifiers which results in the best recognition accuracy of 98.25&#x0025; in the case of rainy (R) class images. Methodological techniques and challenges encountered while experimenting has also been presented in the detailed description. Along with this, the proposed model has also been compared with a simple convolutional neural network (CNN) model which results in outperformance of the TL model in terms of efficiency and efficacy.
A Heuristic for Constructing Minimum Average Stretch Spanning Tree Using Betweenness Centrality

A parameter crucial for preserving the underlying shortest path information in spanning tree construction is called stretch. It is the ratio of the distance of two nodes x and y in the spanning tree to the shortest distance between x and y in the graph. In this paper, we present a heuristic LSTree that constructs a Minimum Average Stretch Spanning Tree of an n&#x2212; node undirected and unweighted graph in $\mathcal{O}$(n) rounds of the CONGEST model. We like to stress that LSTree protocol is the first use of Betweenness centrality in the construction of low stretch trees. The heuristic outperforms the current benchmark algorithm of Alon et. al. as well as other spanning tree construction techniques presently known, when tested against synthetic as well as real-world graph inputs.
Particle Swarm Optimization Based on Racing Factor and Mutation Mechanism

Abstract A hybrid modified Mutation Mechanism (MM) and Racing factor (RF)-based particle swarm optimization (MM-RF-PSO) are presented in this letter. RF and MM are proposed to determine the approximate location of the global optimal solution. Once the approximate position of the optimal solution is determined, a method to dynamically adjust the parameters of algorithm is proposed, so that the algorithm can approach the optimal solution faster. At the same time, when the algorithm falls into the local optimum, a scheme of jumping out of the local optimum is proposed. Compared with other three improved PSO, the simulation results indicate the effectiveness of MM-RF-PSO.
The Devil is in the Framework. Comment on Mizrahi vs. all Debate on the Strength of Arguments from an Expert Opinion

In one of his papers, Moti Mizrahi argues that arguments from an expert opinion are weak arguments. His thesis may seem controversial due to the consensus on this topic in the field of informal logic. I argue that its controversy is framework-dependent, and if translated into a different framework, it appears to be a correct, however trivial, claim. I will use a framework based on Douglas Walton's argumentation scheme theory and his conception of examination dialogue to demonstrate that it is so. It appears that Mizrahi's idiosyncratic framework provides an excessively restrictive conception of an argument from expert opinion than Walton's scheme does. There is no quarrel between both frameworks, as they yield analogous, almost identical, outcomes of argument evaluation. The actual and crucial disagreement is on the topic of argument classification. Mizrahi's conception of arguments from an expert opinion imposes exact conditions that such argument must fulfil: an expert's opinion o truth-value must be unknown; o must be unsupported by any evidence; an expert's peers neither accept o nor reject it. These exclude, by definition, every possible strong, in Walton's terms, variant of such an argument. Therefore, if rephrased with the notions of the examination dialogue framework, Mizrahi's thesis sounds as follows: weak arguments from expert opinion are weak arguments.
Research on Artificial Bee Colony Method Based Complete Coverage Path Planning Algorithm for Search and Rescue Robot

In terms of the low efficiency of search and rescue robot&#x0027;s complete coverage path planning in the complex working environment, based on the traditional neural network optimization strategy, a complete coverage path planning strategy based on Artificial Bee Colony algorithm is proposed. Using the data collected by lidar or other sensors to build an environmental map model, with search and rescue robot as the main body, a neural network forward propagation model combined with an artificial bee colony algorithm was established, and the artificial bee colony method was used to optimize the parameters of the neural network by unsupervised training. It has improved the operability and portability of search and rescue robot working in different environments. And on this basis, an evaluation equation for evaluating the effect of complete coverage path planning is proposed, so as to automatically evaluate the quality of the generated complete coverage path during training. The simulation results show that for the unknown environment, based on the improved path planning algorithm, it has higher efficiency when performing the complete coverage path planning mission of the search and rescue robot.
Considerations for using historical geoscientific information in mineral resource estimation

In many cases, mineralization discovered by prior owners of a mineral property may have been considered to be too low grade to be of potential economic interest at that time. Changes in market conditions over time often warrant a review of the economic potential of historical exploration results. Therefore, any available historical geoscientific information can be of great value because it can save the cost and time required to completely replicate the historical data. As qualified persons (QPs) are ultimately responsible for all data used to prepare a mineral resource estimate, they bear the obligation of carrying out appropriate due diligence and validation of all information and historical work prior to their use for estimation. The task of assigning acceptance criteria rests upon the QP. Considering the wide range of possible scenarios, a detailed listing of acceptance criteria is far beyond the scope of this paper. Generally speaking, the acceptance criteria for using historical data will by necessity vary on a case-by-case basis. In all cases, the QPs are encouraged to fully document the criteria used to establish the acceptance criteria. This paper discusses some of the various actions that QPs may consider for validating historical data.
Development of Statistical Models of Systems and Automation Tools for Modeling and Forecasting Technological Processes

The paper deals with the implementation of the tasks of digitalization of industrial enterprises. The main issues concern the development of statistical models. The management tasks have been solved based on modern information technologies. The results of the selection of statistical models of systems and automation tools for modeling and forecasting technological processes are presented. The result is presented in the form of information blocks. They solve both the problem of generating random numbers with a selected statistical model and the problem of statistical analysis of current technological processes. Methods and tools for creating an information product with the help of modern software and the C++ programming language are used. Programs of statistical means of functioning of the automation system for symmetric and asymmetric statistical models of the spread of the controlled parameter and models of the metrological spread of the means of control (evaluation) of the technological process are proposed.
Vulnerability Exploiter for Web Applications

Vulnerability Exploiter is a tool designed to help users test the security of their web applications. By finding and exploiting common vulnerabilities, Vulnerability Exploiter assists in securing web applications. The vulnerability exploiter helps to find security flaws in your application. It checks and discovers the threats related to running applications on a dynamic web server. This tool reveals potential code execution, server side request forgery and possible denial of service threats to your application. This paper explains the intricacies of maintaining web integrity and various components of vulnerability exploited and means to avoid these in web applications.
Crawling Deep Web Data Based on Three-stage Template

In the open Internet environment, information can be obtained by crawling programs to download web pages containing technological innovations from related websites. Then programs parse the content of the web page according to the structure of the page and extract formatted data. And, it is difficult for general crawlers to crawl deep web content effectively. Although websites that retrieve information from databases have strong regularity in content display, ordinary deep web crawlers lack algorithms for these regularities and characteristics, so the crawling effect is limited. Through in-depth study on related deep web technology and data-rich website display process, the chapter proposes a Three-stage templated crawling technology for web data crawling. And experiments show that this technology can effectively crawl web pages retrieved from the database.
Exploring and Selecting Supershapes in Virtual Reality with Line, Quad, and Cube Shaped Widgets

Supershapes are used in Parametric Design to model, literally, thou-sands of natural and man-made shapes with a single 6 parameter formula. However, users are left to probe such a rich yet dense collection of supershapes using a set of independent 1-D sliders. Some of the formula&#x2019;s parameters are non-linear in nature, making them particularly difficult to grasp with conventional 1-D sliders alone. VR appears as a promising setting for Parametric Design with supershapes since it empowers users with more natural visual inspection and shape browsing techniques, with multiple solutions being displayed at once and the possibility to design more interesting forms of slider interaction. In this work, we propose VR shape widgets that allow users to probe and select supershapes from a multitude of solutions. Our designs take leverage on thumbnails, mini-maps, haptic feedback and spatial interaction, while supporting 1-D, 2-D and 3-D supershape parameter spaces. We conducted a user study (N = 18) and found that VR shape widgets are effective, more efficient, and natural than conventional VR 1-D sliders while also usable for users without prior knowledge on supershapes. We also found that the proposed VR widgets provide a quick overview of the main supershapes, and users can easily reach the desired solution without having to perform fine-grain handle manipulations.
A Binding Bigraphical Model of Context-Aware Adaptive Systems

Many context-aware adaptive applications (CAAAs) change their behaviors according to the user-configured adaptation rules at runtime, however, some of these rules result in inconsistence with the specifications of the CAAAs unfortunately. By employing binding characteristics in bigraphs to constrain both the context variables of the CAAAs and the conditions that the bigraphical reactions can occur, we propose a binding bigraphical model of CAAAs in this paper to try to solve this inconsistence. The adaptation rules, therefore, can be optimized to reduce some conflicts in the modeling phase of CAAAs and in consequence some inherent faults in rule-based CAAAs can be detected and removed earlier. Taking the PhoneAdapter as an example, we compare our model with the traditional formal model called A-FSM so as to show the effectiveness of the approach presented in this paper.