PeerJ preprintsPub Date : 2018-12-30DOI: 10.7287/peerj.preprints.27456v1
E. Roussos
{"title":"Data decomposition: from independent component analysis to sparse representations","authors":"E. Roussos","doi":"10.7287/peerj.preprints.27456v1","DOIUrl":"https://doi.org/10.7287/peerj.preprints.27456v1","url":null,"abstract":"This paper provides a unifying review of some recent approaches of decomposing data, images, and signals into sets of components. We start from the classical algebraic method of singular value decomposition and then introduce principal and independent component analysis. The text continues with the main subject of this paper, sparse representation and decomposition, emphasizing their biological plausibility. In this paper emphasis will be given to the geometric perspective, with the mathematics kept to a minimum.","PeriodicalId":93040,"journal":{"name":"PeerJ preprints","volume":"94 1","pages":"e27456"},"PeriodicalIF":0.0,"publicationDate":"2018-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83872509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
PeerJ preprintsPub Date : 2018-12-27DOI: 10.7287/peerj.preprints.27451/supp-1
I. Smolyar, T. Bromage, M. Wikelski
{"title":"Layered patterns in nature, medicine and materials: quantification of anisotropic structures and cyclisity","authors":"I. Smolyar, T. Bromage, M. Wikelski","doi":"10.7287/peerj.preprints.27451/supp-1","DOIUrl":"https://doi.org/10.7287/peerj.preprints.27451/supp-1","url":null,"abstract":"Various natural patterns—such as terrestrial sand dune ripples, lamellae in vertebrate bones, growth increments in fish scales and corals, aorta and lamellar corpuscle of humans and animals—comprise layers of different thicknesses and lengths. Microstructures in manmade materials—such as alloys, perlite steels, polymers, ceramics, and ripples induced by laser on the surface of graphen—also exhibit layered structures. These layered patterns form a record of internal and external factors regulating pattern formation in their various systems, making it potentially possible to recognize and identify in their incremental sequences trends, periodicities, and events in the formation history of these systems. The morphology of layered systems plays a vital role in developing new materials and in biomimetic research. The structures and sizes of these two-dimensional (2-D) patterns are characteristically anisotropic: That is, the number of layers and their absolute thicknesses vary significantly in different directions. The present work develops a method to quantify the morphological characteristics of layered patterns that accounts for anisotropy in the object of study. To reach this goal, we use Boolean functions and an N-partite graph to formalize layer structure and thickness across a 2-D plane and to construct charts of 1) “layer thickness vs. layer number” and 2) “layer area vs. layer number.” We present a parameter for structural disorder in a layered pattern (DStr) to describe the deviation of a study object’s anisotropic structure from an isotropic analog and illustrate that charts and DStr could be used as local and global morphological characteristics describing various layered systems such as images of, for example, geological, atmospheric, medical, materials, forensic, plants, and animals. Suggested future experiments could lead to new insights into layered pattern formation.","PeriodicalId":93040,"journal":{"name":"PeerJ preprints","volume":"87 1","pages":"e27451"},"PeriodicalIF":0.0,"publicationDate":"2018-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85021306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
PeerJ preprintsPub Date : 2018-12-18DOI: 10.7287/peerj.preprints.27434v1
Nasim Samei, Roberto Solis-Oba
{"title":"A local search algorithm for the constrained max cut problem on hypergraphs","authors":"Nasim Samei, Roberto Solis-Oba","doi":"10.7287/peerj.preprints.27434v1","DOIUrl":"https://doi.org/10.7287/peerj.preprints.27434v1","url":null,"abstract":"In the constrained max k-cut problem on hypergraphs, we are given a weighted hypergraph H=(V, E), an integer k and a set c of constraints. The goal is to divide the set V of vertices into k disjoint partitions in such a way that the sum of the weights of the hyperedges having at least two endpoints in different partitions is maximized and the partitions satisfy all the constraints in c. In this paper we present a local search algorithm for the constrained max k-cut problem on hypergraphs and show that it has approximation ratio 1-1/k for a variety of constraints c, such as for the constraints defining the max Steiner k-cut problem, the max multiway cut problem and the max k-cut problem. We also show that our local search algorithm can be used on the max k-cut problem with given sizes of parts and on the capacitated max k-cut problem, and has approximation ratio 1-|Vmax|/|V|, where |Vmax| is the cardinality of the biggest partition. In addition, we present a local search algorithm for the directed max k-cut problem that has approximation ratio (k-1)/(3k-2).","PeriodicalId":93040,"journal":{"name":"PeerJ preprints","volume":"46 1","pages":"e27434"},"PeriodicalIF":0.0,"publicationDate":"2018-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80866167","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
PeerJ preprintsPub Date : 2018-12-13DOI: 10.7287/peerj.preprints.27428v1
Jacob Porter
{"title":"Using machine learning to predict DNA read alignment quality","authors":"Jacob Porter","doi":"10.7287/peerj.preprints.27428v1","DOIUrl":"https://doi.org/10.7287/peerj.preprints.27428v1","url":null,"abstract":"An empirical understanding of how DNA read features affect read mapping and alignment quality could be useful in designing better read mapping and alignment software, read trimmers, and sequence masks. Many programs appear to use arbitrarily chosen features that are putatively relevant to DNA alignment quality. Machine learning gives a ready way to empirically assess a variety of features and rank them according to their importance. Sequence complexity features such as run length distribution, DUST, and entropy and quality measures from the DNA read data were used to predict read mapping quality on Ion Torrent and Illumina data sets using both bisulfite-treated and untreated short DNA reads. Surprisingly, run length distribution mean and variance did as well or better than DUST and entropy even though several programs use DUST and entropy. Predictive accuracy of the models had F1-scores between 0.5-0.95; thus, the feature set is useful for understanding alignment quality.","PeriodicalId":93040,"journal":{"name":"PeerJ preprints","volume":"38 1","pages":"e27428"},"PeriodicalIF":0.0,"publicationDate":"2018-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82252458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
PeerJ preprintsPub Date : 2018-12-08DOI: 10.7287/peerj.preprints.27420v1
K. Lindorff-Larsen
{"title":"An automatic seating plan algorithm","authors":"K. Lindorff-Larsen","doi":"10.7287/peerj.preprints.27420v1","DOIUrl":"https://doi.org/10.7287/peerj.preprints.27420v1","url":null,"abstract":"An appropriate seating plan is an important prerequisite for any good party be it a formal wedding or an informal dinner. Yet anyone who has designed a seating plan knows that it can prove frustratingly difficult to find a solution that solves the large number of formal, physical and personal constraints associated. Here I present a flexible algorithm for automating the task. The algorithm matches guests to seats taking into account constraints provided through a dissimilarity matrix calculated, for example, using answers to questions designed to classify personality, as well as other formal or informal constraints.","PeriodicalId":93040,"journal":{"name":"PeerJ preprints","volume":"198 1","pages":"e27420"},"PeriodicalIF":0.0,"publicationDate":"2018-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80227742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
PeerJ preprintsPub Date : 2018-12-05DOI: 10.7287/peerj.preprints.27408v1
C. Lortie
{"title":"A comment on computational biology and connecting the dots","authors":"C. Lortie","doi":"10.7287/peerj.preprints.27408v1","DOIUrl":"https://doi.org/10.7287/peerj.preprints.27408v1","url":null,"abstract":"Increasingly, big data, coding, and quantitative methods contribute to contemporary ecological and evolutionary endeavours. This is not in opposition to effective ideation nor does it play to the false dichotomy of theory versus data. Computational expeditions with data, models, simulations or any other number of approaches both expand the toolkit of science and promote more structured reasoning. The implications of computational biology integrated with scientific pursuits such as experiments and theory development include the following positive outcomes: enhanced open science, better reproducibility, data literacy, author inclusivity, social good, and novel ideation opportunities. We face a climate apocalypse and unprecedented ecological challenges of collapsing ecosystem functions. Computation coupled with ideation is one mechanism to align the hearts and heads of scientists and decision makers alike.","PeriodicalId":93040,"journal":{"name":"PeerJ preprints","volume":"10 1","pages":"e27408"},"PeriodicalIF":0.0,"publicationDate":"2018-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87602207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
PeerJ preprintsPub Date : 2018-12-05DOI: 10.7287/peerj.preprints.27410v1
Junling Cai, Ning Zhang
{"title":"Mixed integer nonlinear programming for three-dimensional aircraft conflict avoidance","authors":"Junling Cai, Ning Zhang","doi":"10.7287/peerj.preprints.27410v1","DOIUrl":"https://doi.org/10.7287/peerj.preprints.27410v1","url":null,"abstract":"The problem of aircraft conflict avoidance for Air Traffic Management systems is studied. In the scenario, aircraft are considered to fly within a shared three-dimensional airspace and not allowed to approach close less than a minimum safe separation during their flights in order to avoid various conflicts. This paper proposes a formulation of the three-dimensional conflict avoidance problem as a Mixed Integer Non-Linear Programming (MINLP) model where aircraft are allowed to change both their heading angle and velocity simultaneously to keep the separation. The validity of the proposed model is demonstrated by a comparison of the results from the MINLP model and the previous conflict avoidance models with one maneuver of the heading angle or the velocity. The numerical studies show that the MINLP model improves the efficiency of computation and maintain the safety of flights even by using a standard global optimization solver","PeriodicalId":93040,"journal":{"name":"PeerJ preprints","volume":"25 1","pages":"e27410"},"PeriodicalIF":0.0,"publicationDate":"2018-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83838096","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
PeerJ preprintsPub Date : 2018-11-29DOI: 10.7287/peerj.preprints.27396v1
T. Rao
{"title":"An open source software package for primality testing of numbers of the form p2^n+1, with no constraints on the relative sizes of p and 2n","authors":"T. Rao","doi":"10.7287/peerj.preprints.27396v1","DOIUrl":"https://doi.org/10.7287/peerj.preprints.27396v1","url":null,"abstract":"We develop an efficient software package to test for the primality of p2^n+1, p prime and p>2^n. This aids in the determination of large, non-Sierpinski numbers p, for prime p, and in cryptography. It furthermore uniquely allows for the computation of the smallest n such that p2^n+1 is prime when p is large. We compute primes of this form for the first one million primes p and find four primes of the form above 1000 digits. The software may also be used to test whether p2^n+1 divides a generalized fermat number base 3.","PeriodicalId":93040,"journal":{"name":"PeerJ preprints","volume":"34 1","pages":"e27396"},"PeriodicalIF":0.0,"publicationDate":"2018-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76089658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
PeerJ preprintsPub Date : 2018-11-23DOI: 10.7287/peerj.preprints.27377v1
Shaun C. D'Souza
{"title":"LSTM neural network for textual ngrams","authors":"Shaun C. D'Souza","doi":"10.7287/peerj.preprints.27377v1","DOIUrl":"https://doi.org/10.7287/peerj.preprints.27377v1","url":null,"abstract":"Cognitive neuroscience is the study of how the human brain functions on tasks like decision making, language, perception and reasoning. Deep learning is a class of machine learning algorithms that use neural networks. They are designed to model the responses of neurons in the human brain. Learning can be supervised or unsupervised. Ngram token models are used extensively in language prediction. Ngrams are probabilistic models that are used in predicting the next word or token. They are a statistical model of word sequences or tokens and are called Language Models or Lms. Ngrams are essential in creating language prediction models. We are exploring a broader sandbox ecosystems enabling for AI. Specifically, around Deep learning applications on unstructured content form on the web.","PeriodicalId":93040,"journal":{"name":"PeerJ preprints","volume":"1 1","pages":"e27377"},"PeriodicalIF":0.0,"publicationDate":"2018-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74443169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
PeerJ preprintsPub Date : 2018-11-19DOI: 10.7287/peerj.preprints.27358v2
Nick Papoulias
{"title":"For and against PEGs: Why we need multi-ordered grammars","authors":"Nick Papoulias","doi":"10.7287/peerj.preprints.27358v2","DOIUrl":"https://doi.org/10.7287/peerj.preprints.27358v2","url":null,"abstract":"Since their introduction in 2004, Parsing Expression Grammars (PEGs for short) have been gaining widespread adoption both in industry and academia. More than 400 subsequent works cite B. Ford's original paper, while a total of 29 implementations in 14 different programming languages are reported in active use. Nevertheless reviewing PEG-related bibliography reveals that the original argumentation in favor of PEGs has actually been weakened by subsequent work, regarding basic parsing features such as (a) recursion handling and (b) associativity support. To this day all proposed enhancements either address these issues in isolation or in implementation specific ways. It is still unclear if there is a single way to parse PEGs without facing these issues or introducing implementation directives external to the formalism. Our subsequent analysis takes us a step further, questioning the very core of the initial PEG proposal: (c) by design unambiguous grammars. We then discuss why a form of ordered choice and conditional operators that PEGs advocate are worth saving, but only within a wider synthesis that could address the aforementioned issues. To this end we present our on-going effort with the Gray algorithm and MOGs (Multi-Ordered Grammars), a possible alternative to the PEG and CFG formalisms.","PeriodicalId":93040,"journal":{"name":"PeerJ preprints","volume":"8 1","pages":"e27358"},"PeriodicalIF":0.0,"publicationDate":"2018-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89985237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}