Reviewerly/exHarmony huggingface dataset:
On Longest Common Property Preserved Substring Queries

We revisit the problem of longest common property preserving substring queries introduced by Ayad et al. (SPIRE 2018, arXiv 2018). We consider a generalized and unified on-line setting, where we are given a set X of k strings of total length n that can be pre-processed so that, given a query string y and a positive integer $$k'\le k$$ , we can determine the longest substring of y that satisfies some specific property and is common to at least $$k'$$ strings in X. Ayad et al. considered the longest square-free substring in an on-line setting and the longest periodic and palindromic substring in an off-line setting. In this paper, we give efficient solutions in the on-line setting for finding the longest common square, periodic, palindromic, and Lyndon substrings. More precisely, we show that X can be pre-processed in O(n) time resulting in a data structure of O(n) size that answers queries in $$O(|y|\log \sigma )$$ time and O(1) working space, where $$\sigma $$ is the size of the alphabet, and the common substring must be a square, a periodic substring, a palindrome, or a Lyndon word.
Linear-time online algorithm for inferring the shortest path graph from a walk label

We consider the problem of inferring an edge-labeled graph from the sequence of edge labels seen in a walk on that graph. It has been known that this problem is solvable in O(nlog⁡n) time when the targets are path or cycle graphs. This paper presents an online algorithm for the problem of this restricted case that runs in O(n) time, based on Manacher's algorithm for computing all the maximal palindromes in a string.
Immersive Serious Games for Post-Stroke Motor Rehabilitation

This article describes a demonstration of an ongoing research work that explores the extents of how immersive systems may support serious games development for post-stroke upper limb rehabilitation. Beyond the entertainment that is expected from games, the focus goes towards the exploitation of embodiment that should contribute to reinforce the patient engagement, what is known to contribute to the faster and deeper recovery, but also the sensory stimulation that is crucial to the development of new neural pathways.
The Effect of E-Learning on Students Learning of STMIK STIKOM Bali

E-Learning is described as distance learning that utilizes information technology so that it can facilitate interaction between lecturers and students effectively. This study examined the effect of e-Learning towards student learning, which uses quantitative methods by conducting sample surveys of the institution's student population. Sampling techniques are generally carried out randomly for all students as they took the same strata. This random sample used the Issac and Michael formulas with degrees of freedom (dk = 1) and a level of error of 10%. Data collection using research instruments, data analysis is quantitative in order to test the hypothesis set. The results of this study are the effect of eLearning on student activity, e-Learning has a positive impact on learning, e-Learning effectiveness in accessing student assignments and the relationship between the appearance and ease of using e-Learning.
Local Sensitive Hashing for Proximity Searching

Proximity or similarity searching is one of the most important tasks in artificial intelligence concerning multimedia databases. If there is a distance function to compare any two objects in a collection, then similarity can be modeled as a metric space. One of the most important techniques used for high dimensional data is the permutation-based algorithm, where the problem is mapped into another space (permutations space) where distances are much easier to compute, but solving similarity queries with the least number of distances computed is still a challenge. The approach in this work consists in using Locality-Sensitive Hashing (LSH). The experiments reported in this paper show that the proposed way to adapt LSH to the permutation based algorithm has a competitive tradeoff between recall and distances.