1,720,978 research outputs found
A Fairness-Based Heuristic Technique for Long-Term Nurse Scheduling
No full textWe present a new heuristic long-term solution to the Nurse Scheduling Problem (NSP). Nurse scheduling requires the satisfaction of a set of constraints: Hard constraints that must be satisfied, and soft constraints that are specified by the nurses according to their preferences. The quality of a technique is measured by the level of satisfaction of those constraints, which we measure using a penalty system. We propose a three-phase solution based on the way nurses trade shifts: In the first phase, we generate a schedule that satisfies all the hard constraints irrespective of the individual nurses. Then, each nurse is matched to her optimal schedule. Finally, we satisfy as many of the soft constraints as possible using shift swapping between the different nurses’ schedules. We analyze the performance of our technique and it obtained satisfactory results in reasonable time compared to a brute-force generated optimal schedule that takes an extremely long time to generate. We extended the scheduling technique to multiple scheduling periods by carrying the old penalties accumulated by a nurse to her new schedule. This guarantees fairness over the long term, and decreased the variance in overall penalties by over 50% compared to independently scheduling each schedule period
COVID-19 Vaccine Response on Social Media Using LDA Analysis
No full textThe COVID-19 pandemic causes an enormous interruption to human activity. Vaccines were developed at breathtaking speed and the global community was quick to react to their deployment. The primary focus of this paper is to analyze the global population’s response to the vaccine rollout during the December 2020 to November 2021 phase of the pandemic. To achieve this objective, we use a dataset of tweets written in response to the vaccines using the various vaccine names as the search hashtag. The data was cleaned and tokenized then the Latent Dirichlet Allocation (LDA) topic modeling algorithm was applied. Through analysis of Twitter data, it was possible to identify countries actively participating in vaccination efforts, the involved companies, and political leaders who were vocal on this topic. Two particular vaccines were discussed the most, Moderna and Covaxin. The LDA analysis shows a cluster of similar topics discussing the technical aspect of the vaccines and two distinct topics about the political and social aspect of the vaccine rollouts
Teaching Self-Balancing Trees Using a Beauty Contest
Full text linkTrees data structures and their performance is one of the main topics to teach in a data structures course. Appreciating the importance of tree structure and tree height in software performance is an important concept to teach. In this paper, a simple and amusing activity is presented. It demonstrates to students the importance of a well-balanced tree by comparing the height of a binary search tree to a balanced (AVL) tree build upon some personal data to find the “prettiest” tree (minimum height). The activity highlights the fact that, irrelevant of your data sequence, a balanced tree guarantees a height of O(log n) and everyone “wins” the beauty contest
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
A Family of Hierarchical Encoding Techniques for Image and Video Communications
Full text linkAs the demand for image and video transmission and interactive multimedia applications continues to grow, scalable image and video compression that has robust behavior over unreliable channels are of increasing interest. These desktop applications require scalability as a main feature due to its heterogeneous nature, since participants in an interactive multimedia application have different needs and processing power. Also, the encoding and decoding algorithm complexity must be low due to the practical considerations of low-cost low-power receiver terminals. This requires image and video encoding techniques that jointly considers compression, scalability, robustness, and simplicity.
In this dissertation, we present a family of image and video-encoding techniques, which are developed to support conferencing applications. We achieve scalability, robustness and low computational complexity by building our encoding techniques based on the quadtree and octree representation methods.
First we developed an image encoding technique using the quadtree representation of images and vector quantization. We use a mean-removal technique to separate the means image and the difference image. The difference image is then encoded as a breadth first traversal of the quadtree corresponding to the image. Vector quantization is then used to compress the quadtree nodes based on the spatial locality of the quadtree data. Our next step was to use the quadtree-based image encoding technique as a base for developing a differential video encoding technique. We extended it to encode video by applying the well-known IPB technique to the image encoding system.
Then, we explore another method of extending our image encoding technique to encode video streams. The basic idea was to use exactly the same three steps used in our image encoding technique, mean removal, conversion to tree structure, and vector quantization, and replace the quadtree structure with an octree structure. The octree is the three-dimensional equivalent of the quadtree. We divide the sequence of frames into groups and view each group as a three-dimensional object. By encoding frames together, we can obtain substantial savings in encoding time and better compression results.
Finally, we combined both the differential quadtree and octree approaches to generate a new hybrid encoding technique. We encode one frame using the quadtree-based image encoding technique, and then encode the following group of frames as a differential octree based upon the first frame.
Using a set of experiments, the quadtree-based image encoding and differential video encoding techniques were shown to provide reasonable compression in comparison with similar techniques, while the octree and hybrid video encoding techniques gave impressive compression results. Furthermore, we demonstrated that our encoding techniques are time efficient compared to the more common frequency based techniques. We also compare their scalability feature favorably with other well-known scalable techniques. Moreover, we demonstrated their ability to tolerate and conceal error. The new encoding techniques proved to be efficient methods of encoding for interactive multimedia applications
Fast and Memory-Efficient TFIDF Calculation for Text Analysis of Large Datasets
Full text linkTerm frequency – Inverse Document Frequency (TFIDF) is a vital first step in text analytics for information retrieval and machine learning applications. It is a memory-intensive and complex task due to the need to create and process a large sparse matrix of term frequencies, with the documents as rows and the term as columns and populate it with the term frequency of each word in each document. The standard method of storing the sparse array is the “Compressed Sparse Row” (CSR), which stores the sparse array as three one-dimensional arrays for the row id, column id, and term frequencies. We propose an alternate representation to the CSR: a list of lists (LIL) where each document is represented as its own list of tuples and each tuple storing the column id and the term frequency value. We implemented both techniques to compare their memory efficiency and speed. The new LIL representation increase the memory capacity by 52% and is only 12% slower in processing time. This enables researchers with limited processing power to be able to work on bigger text analysis datasets
Novel Recursive Technique for Finding the Optimal Solution of the Nurse Scheduling Problem
No full textSolving the Nurse Scheduling problem Is a major research area in Operations Research. Due to it being an NP-Hard problem, most researchers develop a heuristic solution for it The NSP has several constraints that need to be satisfied: several mandatory “hard” constraints that reflect hospital requirements, and several optional “soft constraints that reflect the nurses\u27 preferences. In this paper, we present a recursive solution to the problem that makes use of those constraints to shrink the search space and obtain results in a reasonable amount of lime. We present two variations of the solution. a nurse-by-nurse method of building the optimal schedule, and a shift-by-shift approach. Both variations were implemented and tested with various scenarios and the shift-by-shift solution provided much better results. The solution can also be modified easily to provide fair long-term scheduling
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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