Downloads & Free Reading Options - Results

In this paper we describe a process of algorithmic discovery that was driven by our goal of achieving complete, mechanically verified algorithms that compute conflict prevention bands for use in en route air traffic management. The algorithms were originally defined in the PVS specification language and subsequently have been implemented in Java and C++. We do not present the proofs in this paper: instead, we describe the process of discovery and the key ideas that enabled the final formal proof of correctness

In this paper we describe a process of algorithmic discovery that was driven by our goal of achieving complete, mechanically verified algorithms that compute conflict prevention bands for use in en route air traffic management. The algorithms were originally defined in the PVS specification language and subsequently have been implemented in Java and C++. We do not present the proofs in this paper: instead, we describe the process of discovery and the key ideas that enabled the final formal proof of correctness

This article is from Particle and Fibre Toxicology , volume 10 . Abstract Background: Cobalt-ferrite nanoparticles (Co-Fe NPs) are attractive for nanotechnology-based therapies. Thus, exploring their effect on viability of seven different cell lines representing different organs of the human body is highly important. Methods: The toxicological effects of Co-Fe NPs were studied by in-vitro exposure of A549 and NCIH441 cell-lines (lung), precision-cut lung slices from rat, HepG2 cell-line (liver), MDCK cell-line (kidney), Caco-2 TC7 cell-line (intestine), TK6 (lymphoblasts) and primary mouse dendritic-cells. Toxicity was examined following exposure to Co-Fe NPs in the concentration range of 0.05 -1.2 mM for 24 and 72 h, using Alamar blue, MTT and neutral red assays. Changes in oxidative stress were determined by a dichlorodihydrofluorescein diacetate based assay. Data analysis and predictive modeling of the obtained data sets were executed by employing methods of Knowledge Discovery from Data with emphasis on a decision tree model (J48). Results: Different dose–response curves of cell viability were obtained for each of the seven cell lines upon exposure to Co-Fe NPs. Increase of oxidative stress was induced by Co-Fe NPs and found to be dependent on the cell type. A high linear correlation (R2=0.97) was found between the toxicity of Co-Fe NPs and the extent of ROS generation following their exposure to Co-Fe NPs. The algorithm we applied to model the observed toxicity belongs to a type of supervised classifier. The decision tree model yielded the following order with decrease of the ranking parameter: NP concentrations (as the most influencing parameter), cell type (possessing the following hierarchy of cell sensitivity towards viability decrease: TK6 > Lung slices > NCIH441 > Caco-2 = MDCK > A549 > HepG2 = Dendritic) and time of exposure, where the highest-ranking parameter (NP concentration) provides the highest information gain with respect to toxicity. The validity of the chosen decision tree model J48 was established by yielding a higher accuracy than that of the well-known “naive bayes” classifier. Conclusions: The observed correlation between the oxidative stress, caused by the presence of the Co-Fe NPs, with the hierarchy of sensitivity of the different cell types towards toxicity, suggests that oxidative stress is one possible mechanism for the toxicity of Co-Fe NPs.

This article is from BMC Bioinformatics , volume 13 . Abstract Background: A scientific name for an organism can be associated with almost all biological data. Name identification is an important step in many text mining tasks aiming to extract useful information from biological, biomedical and biodiversity text sources. A scientific name acts as an important metadata element to link biological information. Results: We present NetiNeti (Name Extraction from Textual Information-Name Extraction for Taxonomic Indexing), a machine learning based approach for recognition of scientific names including the discovery of new species names from text that will also handle misspellings, OCR errors and other variations in names. The system generates candidate names using rules for scientific names and applies probabilistic machine learning methods to classify names based on structural features of candidate names and features derived from their contexts. NetiNeti can also disambiguate scientific names from other names using the contextual information. We evaluated NetiNeti on legacy biodiversity texts and biomedical literature (MEDLINE). NetiNeti performs better (precision = 98.9% and recall = 70.5%) compared to a popular dictionary based approach (precision = 97.5% and recall = 54.3%) on a 600-page biodiversity book that was manually marked by an annotator. On a small set of PubMed Central’s full text articles annotated with scientific names, the precision and recall values are 98.5% and 96.2% respectively. NetiNeti found more than 190,000 unique binomial and trinomial names in more than 1,880,000 PubMed records when used on the full MEDLINE database. NetiNeti also successfully identifies almost all of the new species names mentioned within web pages. Conclusions: We present NetiNeti, a machine learning based approach for identification and discovery of scientific names. The system implementing the approach can be accessed at http://namefinding.ubio.org.

This document considers a direct iterative method for solving the linear system AU = Y which arises from the discretization of a boundary value problem involving an elliptic partial differential operator L of order 2m.

This document considers a direct iterative method for solving the linear system AU = Y which arises from the discretization of a boundary value problem involving an elliptic partial differential operator L of order 2m.

This document considers a direct iterative method for solving the linear system AU = Y which arises from the discretization of a boundary value problem involving an elliptic partial differential operator L of order 2m.

This document considers a direct iterative method for solving the linear system AU = Y which arises from the discretization of a boundary value problem involving an elliptic partial differential operator L of order 2m.

This document considers a direct iterative method for solving the linear system AU = Y which arises from the discretization of a boundary value problem involving an elliptic partial differential operator L of order 2m.

There are many tools available to government fund managers for making investment decisions, especially regarding the retirement options available to U.S. service members, including Social Security, Military Retirement, Traditional Individual Retirement Accounts (IRAs), Roth IRAs, and the Uniformed Services Thrift Savings Plan (TSP). This project concentrates on both long-term and short-term investments by exploiting the combination of two types of investment methods. The first is to predict the future directions of prices by discovering the patterns of prices. The other is to combine fundamental and technical analysis successfully, which requires the study of their relationship. The project consists of two independent parts. The first part introduces a knowledge representation model that codifies stock price movements in binary format and then applies proper data mining techniques to discover profitable patterns of four candlesticks. The second part seeks to answer the following question: If there are relationships between technical and fundamental analysis, can strategies to increase investment returns be developed?

There are many tools available to government fund managers for making investment decisions, especially regarding the retirement options available to U.S. service members, including Social Security, Military Retirement, Traditional Individual Retirement Accounts (IRAs), Roth IRAs, and the Uniformed Services Thrift Savings Plan (TSP). This project concentrates on both long-term and short-term investments by exploiting the combination of two types of investment methods. The first is to predict the future directions of prices by discovering the patterns of prices. The other is to combine fundamental and technical analysis successfully, which requires the study of their relationship. The project consists of two independent parts. The first part introduces a knowledge representation model that codifies stock price movements in binary format and then applies proper data mining techniques to discover profitable patterns of four candlesticks. The second part seeks to answer the following question: If there are relationships between technical and fundamental analysis, can strategies to increase investment returns be developed?

A new discovery of the private methods of France, ... 1691.. Digitized from IA40313018-37 . Previous issue: bim_early-english-books-1641-1700_a-new-declaration-of-the_1660 . Next issue: bim_early-english-books-1641-1700_a-new-king-anointed-_1659 .

Book digitized by Google from the library of Harvard University and uploaded to the Internet Archive by user tpb.

This monographic series volume contains two separate monographs. "The Training of Student Teachers in Discovery Methods of Instruction and Learning," (John Heywood, Sarah Heywood) discusses the polarization of discovery learning and expository teaching. It describes a unit in the applied psychology of instruction, commonly known as "the student teacher as researcher programme," which is included in a secondary teacher education course at an Irish university. Students compared two methods of teaching, expository and guided discovery or discovery, utilizing experimental methods. The evidence indicates that, while guided discovery and discovery techniques produce no better pupil test results than expository methods, they do create a better learning environment, one that is more conducive to pupil motivation. Difficulties encountered by student teachers implementing discovery techniques included devising assessment procedures and confusion and reluctance on the part of pupils. The report includes statistical breakdowns on the results of student teachers' experiments and examples of their lesson plans. "Comparing Guided Discovery and Expository Methods: Teaching the Water Cycle in Geography," (Iain Donovan) involved teaching the same geography topic, the water cycle, to two secondary classes of approximately equal ability, using guided discovery learning for one class and expository teaching for the other. Each class was given the same test after the relevant lesson to ascertain which learning strategy was more effective in achieving the common objectives. Findings indicated that low ability students benefited more from the expository lesson whereas, to a less significant degree, high ability pupils benefited more from the guided discovery lesson. The results both confirm and contradict the findings of previous research on guided discovery and expository teaching strategies, both of which are discussed. (IAH)

Unsupervised learning aims at the discovery of hidden structure that drives the observations in the real world. It is essential for success in modern machine learning. Latent variable models are versatile in unsupervised learning and have applications in almost every domain. Training latent variable models is challenging due to the non-convexity of the likelihood objective. An alternative method is based on the spectral decomposition of low order moment tensors. This versatile framework is guaranteed to estimate the correct model consistently. My thesis spans both theoretical analysis of tensor decomposition framework and practical implementation of various applications. This thesis presents theoretical results on convergence to globally optimal solution of tensor decomposition using the stochastic gradient descent, despite non-convexity of the objective. This is the first work that gives global convergence guarantees for the stochastic gradient descent on non-convex functions with exponentially many local minima and saddle points. This thesis also presents large-scale deployment of spectral methods carried out on various platforms. Dimensionality reduction techniques such as random projection are incorporated for a highly parallel and scalable tensor decomposition algorithm. We obtain a gain in both accuracies and in running times by several orders of magnitude compared to the state-of-art variational methods. To solve real world problems, more advanced models and learning algorithms are proposed. This thesis discusses generalization of LDA model to mixed membership stochastic block model for learning user communities in social network, convolutional dictionary model for learning word-sequence embeddings, hierarchical tensor decomposition and latent tree structure model for learning disease hierarchy, and spatial point process mixture model for detecting cell types in neuroscience.

viii, 163 pages ; (8vo)

We analyze the convergence rate of a simplified version of a popular Gibbs sampling method used for statistical discovery of gene regulatory binding motifs in DNA sequences. This sampler satisfies a very strong form of ergodicity (uniform). However, we show that, due to multimodality of the posterior distribution, the rate of convergence often decreases exponentially as a function of the length of the DNA sequence. Specifically, we show that this occurs whenever there is more than one true repeating pattern in the data. In practice there are typically multiple such patterns in biological data, the goal being to detect the most well-conserved and frequently-occurring of these. Our findings match empirical results, in which the motif-discovery Gibbs sampler has exhibited such poor convergence that it is used only for finding modes of the posterior distribution (candidate motifs) rather than for obtaining samples from that distribution. Ours are some of the first meaningful bounds on the convergence rate of a Markov chain method for sampling from a multimodal posterior distribution, as a function of statistical quantities like the number of observations.

We analyze the convergence rate of a simplified version of a popular Gibbs sampling method used for statistical discovery of gene regulatory binding motifs in DNA sequences. This sampler satisfies a very strong form of ergodicity (uniform). However, we show that, due to multimodality of the posterior distribution, the rate of convergence often decreases exponentially as a function of the length of the DNA sequence. Specifically, we show that this occurs whenever there is more than one true repeating pattern in the data. In practice there are typically multiple such patterns in biological data, the goal being to detect the most well-conserved and frequently-occurring of these. Our findings match empirical results, in which the motif-discovery Gibbs sampler has exhibited such poor convergence that it is used only for finding modes of the posterior distribution (candidate motifs) rather than for obtaining samples from that distribution. Ours are some of the first meaningful bounds on the convergence rate of a Markov chain method for sampling from a multimodal posterior distribution, as a function of statistical quantities like the number of observations.

Runge-Kutta (RK) methods are an important family of iterative methods for approximating the solutions of ordinary differential equations (ODEs) and differential algebraic equations (DAEs). It is common to use an RK method to discretize in time when solving time dependent partial differential equations (PDEs) with a method-of-lines approach as in Maxwell’s Equations. Different types of PDEs are discretized in such a way that could result in a high dimensional ODE or DAE.We use a low-storage RK (LSRK) method that stores two registers per ODE dimension, which limits the impact of increased storage requirements. Classical RK methods, however, have one storage variable per stage. In this thesis we compare the efficiency and accuracy of LSRK methods to RK methods. We then focus on optimizing the truncation error coefficients for LSRK to discover new methods. Reusing the tools from the optimization method, we discover new methods for low-storage half-explicit RK (LSHERK) methods for solving DAEs.

Many automatic attribute discovery methods have been developed to extract a set of visual attributes from images for various tasks. However, despite good performance in some image classification tasks, it is difficult to evaluate whether these methods discover meaningful attributes and which one is the best to find the attributes for image descriptions. An intuitive way to evaluate this is to manually verify whether consistent identifiable visual concepts exist to distinguish between positive and negative images of an attribute. This manual checking is tedious, labor intensive and expensive and it is very hard to get quantitative comparisons between different methods. In this work, we tackle this problem by proposing an attribute meaningfulness metric, that can perform automatic evaluation on the meaningfulness of attribute sets as well as achieving quantitative comparisons. We apply our proposed metric to recent automatic attribute discovery methods and popular hashing methods on three attribute datasets. A user study is also conducted to validate the effectiveness of the metric. In our evaluation, we gleaned some insights that could be beneficial in developing automatic attribute discovery methods to generate meaningful attributes. To the best of our knowledge, this is the first work to quantitatively measure the semantic content of automatically discovered attributes.

Many automatic attribute discovery methods have been developed to extract a set of visual attributes from images for various tasks. However, despite good performance in some image classification tasks, it is difficult to evaluate whether these methods discover meaningful attributes and which one is the best to find the attributes for image descriptions. An intuitive way to evaluate this is to manually verify whether consistent identifiable visual concepts exist to distinguish between positive and negative images of an attribute. This manual checking is tedious, labor intensive and expensive and it is very hard to get quantitative comparisons between different methods. In this work, we tackle this problem by proposing an attribute meaningfulness metric, that can perform automatic evaluation on the meaningfulness of attribute sets as well as achieving quantitative comparisons. We apply our proposed metric to recent automatic attribute discovery methods and popular hashing methods on three attribute datasets. A user study is also conducted to validate the effectiveness of the metric. In our evaluation, we gleaned some insights that could be beneficial in developing automatic attribute discovery methods to generate meaningful attributes. To the best of our knowledge, this is the first work to quantitatively measure the semantic content of automatically discovered attributes.

Many automatic attribute discovery methods have been developed to extract a set of visual attributes from images for various tasks. However, despite good performance in some image classification tasks, it is difficult to evaluate whether these methods discover meaningful attributes and which one is the best to find the attributes for image descriptions. An intuitive way to evaluate this is to manually verify whether consistent identifiable visual concepts exist to distinguish between positive and negative images of an attribute. This manual checking is tedious, labor intensive and expensive and it is very hard to get quantitative comparisons between different methods. In this work, we tackle this problem by proposing an attribute meaningfulness metric, that can perform automatic evaluation on the meaningfulness of attribute sets as well as achieving quantitative comparisons. We apply our proposed metric to recent automatic attribute discovery methods and popular hashing methods on three attribute datasets. A user study is also conducted to validate the effectiveness of the metric. In our evaluation, we gleaned some insights that could be beneficial in developing automatic attribute discovery methods to generate meaningful attributes. To the best of our knowledge, this is the first work to quantitatively measure the semantic content of automatically discovered attributes.

An essay for the discovery of the longitude at sea, by several new methods fully and particularly laid before the publick. By Isaac Hawkins. 1714.. Digitized from IA40313611-27 . Previous issue: bim_eighteenth-century_an-essay-to-shew-the-cau_freke-john-surgeon_1746 . Next issue: bim_eighteenth-century_general-view-of-the-agri_stone-thomas-surveyor_1794 .

Runge-Kutta (RK) methods are an important family of iterative methods for approximating the solutions of ordinary differential equations (ODEs) and differential algebraic equations (DAEs). It is common to use an RK method to discretize in time when solving time dependent partial differential equations (PDEs) with a method-of-lines approach as in Maxwell s Equations. Different types of PDEs are discretized in such a way that could result in a high dimensional ODE or DAE. We use a low-storage RK (LSRK) method that stores two registers per ODE dimension, which limits the impact of increased storage requirements. Classical RK methods, however, have one storage variable per stage. In this thesis we compare the efficiency and accuracy of LSRK methods to RK methods. We then focus on optimizing the truncation error coefficients for LSRK to discover new methods. Reusing the tools from the optimization method, we discover new methods for low-storage half-explicit RK (LSHERK) methods for solving DAEs.

Plant Breeding/Biotechnology; Biological Techniques; Nucleic Acid Chemistry

In genome-wide association studies (GWASs) of common diseases/traits, we often analyze multiple GWASs with the same phenotype together to discover associated genetic variants with higher power. Since it is difficult to access data with detailed individual measurements, summary-statistics-based meta-analysis methods have become popular to jointly analyze data sets from multiple GWASs. In this paper, we propose a novel summary-statistics-based joint analysis method based on controlling the joint local false discovery rate (Jlfdr). We prove that our method is the most powerful summary-statistics-based joint analysis method when controlling the false discovery rate at a certain level. In particular, the Jlfdr-based method achieves higher power than commonly used meta-analysis methods when analyzing heterogeneous data sets from multiple GWASs. Simulation experiments demonstrate the superior power of our method over meta-analysis methods. Also, our method discovers more associations than meta-analysis methods from empirical data sets of four phenotypes. The R-package is available at: http://bioinformatics.ust.hk/Jlfdr.html.

I. General view and basis of scientific research.--II. General conditions of scientific research.--III. Personal preparation for research.--IV. Actual working in original scientific research.--V. Special methods of discovery

I. General view and basis of scientific research.--II. General conditions of scientific research.--III. Personal preparation for research.--IV. Actual working in original scientific research.--V. Special methods of discovery

Technological developments have been enabling additional sharing and reuse of scientific information. Current indexing methods support query-based search and filtering, however they do not support overviews and exploration. Due to these limitations of existing indexing methods, it is challenging to discover records and connections that relate information in new and potentially insightful ways. We developed prototype systems and computational methods for integrating collections from multiple sources within a domain into a single, unified graph data structure. Graph-theoretic measures and visualizations were then applied to identify relations and records that support discovery tasks. Three collections of molecular information were studied: (1) influenza protein sequences from the National Center for Biotechnology Information, (2) Open Notebook Science notebooks and databases from Drexel University and other academic chemical research laboratories, and (3) project data from drug discovery projects at Pfizer R&D. We designed methods for data integration within these collections. We then analyzed the integrated collections to design interactive visual tools and computational methods that could systematically identify relations and records that have a high potential to lead to novel discoveries in these areas. We conducted interviews with domain experts to evaluate the effectiveness of these designs. These studies demonstrate the feasibility of the new indexing methods to improve the discoverability of novel connections across multiple collections within a domain.

Technological developments have been enabling additional sharing and reuse of scientific information. Current indexing methods support query-based search and filtering, however they do not support overviews and exploration. Due to these limitations of existing indexing methods, it is challenging to discover records and connections that relate information in new and potentially insightful ways. We developed prototype systems and computational methods for integrating collections from multiple sources within a domain into a single, unified graph data structure. Graph-theoretic measures and visualizations were then applied to identify relations and records that support discovery tasks. Three collections of molecular information were studied: (1) influenza protein sequences from the National Center for Biotechnology Information, (2) Open Notebook Science notebooks and databases from Drexel University and other academic chemical research laboratories, and (3) project data from drug discovery projects at Pfizer R&D. We designed methods for data integration within these collections. We then analyzed the integrated collections to design interactive visual tools and computational methods that could systematically identify relations and records that have a high potential to lead to novel discoveries in these areas. We conducted interviews with domain experts to evaluate the effectiveness of these designs. These studies demonstrate the feasibility of the new indexing methods to improve the discoverability of novel connections across multiple collections within a domain.

There are many tools available to government fund managers for making investment decisions, especially regarding the retirement options available to US service members, including Social Security, Military Retirement, Traditional Individual Retirement Accounts, Roth Individual Retirement Accounts and Uniformed Services Thrift Savings Plan. This project concentrates on both long and short term investments by exploiting the combination of two types of investment methods. The first is to predict the future directions of prices by discovering the patterns of prices. The other is to combine fundamental and technical analysis successfully, which requires the study of their relationship. The project consists of two independent parts. The first part introduces a knowledge representation model that codifies stock price movements in binary format and then applies proper data mining techniques in order to discover profitable patterns of four candlesticks. The second part seeks to answer the question: \"If there are relationships between technical and fundamental analysis, can strategies to increase investment returns be developed?

According to the popular opinion, the effect of the prerequisites of hikmat (wisdom) in tamasok (seeking) is one of the wide-ranging fundamental issues after the era of Sultan Ulama. According to Akhund Khorasani's point of view, one of the prerequisites of the hikmat is to adhere to the etlagh (application), qadr moteyaghan and methods of discovering and understanding it. qadr moteyaghan is a person or a part of the motlagh (applied) that is definitely within the scope of the ruling . By dividing qadr moteyaghan into two types: qadr moteyaghan in the position of takhatob (communication) that is internal and external qadr moteyaghan , Akhund has considered qadr moteyaghan in the position of takhatob as an obstacle to application, but some usulists have not made a difference between the types of qadr moteyaghan in regard to application. After a detailed analysis of the types of qadr moteyaghan , this essay aims to answer this important question: What is the necessity of researching and applying the basic rules regarding the validity and authenticity of qadr moteyaghan , as well as its priority to adhere to its application, and how is this qadr moteyaghan discovered ? In this research, by analytical and descriptive method, by examining different points of view and with special reliance on the opinions of Imam Khomeini and Martyr Sadr, the conclusion has been reached that, first of all, the implementation of the principles of hekmat is a consensus matter for the wise. Secondly, qadr moteyaghan does not prevent application to both of its types, and in fact, the primacy of qadr moteyaghan goes back to the fact that the speaker is in the position of communicating and qadr moteyaghan does not prevent application until it reaches the point of apparent enseraf (reffering to something), and as if in the statement of Akund Khorasani the meaning of the word on the bounded essence is confused with the description of a share that contains a certain attribute and the word that indicates the limitation of this attribute and its involvement in the subject of the ruling. Thirdly, knowing qadr moteyaghan is obtained in the customary way, with the help of the appropriateness of the ruling and the subject, and sometimes by using verbal clues .

I. General view and basis of scientific research.--II. General conditions of scientific research.--III. Personal preparation for research.--IV. Actual working in original scientific research.--V. Special methods of discovery

I. General view and basis of scientific research.--II. General conditions of scientific research.--III. Personal preparation for research.--IV. Actual working in original scientific research.--V. Special methods of discovery

This paper is in the public domain in USA. Metadata comes from the CrossRef API, see full record in the source URL below.

This paper is in the public domain in USA. Metadata comes from the CrossRef API, see full record in the source URL below.

This paper is in the public domain in USA. Metadata comes from the CrossRef API, see full record in the source URL below.

This paper is in the public domain in USA. Metadata comes from the CrossRef API, see full record in the source URL below.

This paper is in the public domain in USA. Metadata comes from the CrossRef API, see full record in the source URL below.

This paper is in the public domain in USA. Metadata comes from the CrossRef API, see full record in the source URL below.

I. General view and basis of scientific research.--II. General conditions of scientific research.--III. Personal preparation for research.--IV. Actual working in original scientific research.--V. Special methods of discovery

We report on the results of a recent blind search survey for gamma-ray pulsars in Fermi Large Area Telescope (LAT) data being carried out on the distributed volunteer computing system, Einstein@Home. The survey has searched for pulsations in 118 unidentified pulsar-like sources, requiring about 10,000 years of CPU core time. In total, this survey has resulted in the discovery of 17 new gamma-ray pulsars, of which 13 are newly reported in this work, and an accompanying paper. These pulsars are all young, isolated pulsars with characteristic ages between 12 kyr and 2 Myr, and spin-down powers between $10^{34}$ and $4\times10^{36}$ erg/s. Two of these are the slowest spinning gamma-ray pulsars yet known. One pulsar experienced a very large glitch $\Delta f/f \approx 3.5\times10^{-6}$ during the Fermi mission. In this, the first of two associated papers, we describe the search scheme used in this survey, and estimate the sensitivity of our search to pulsations in unidentified Fermi-LAT sources. One such estimate results in an upper limit of 57% for the fraction of pulsed emission from the gamma-ray source associated with the Cas A supernova remnant, constraining the pulsed gamma-ray photon flux that can be produced by the neutron star at its center. We also present the results of precise timing analyses for each of the newly detected pulsars.

This study was designed to investigate the effects of discovery and expository methods of presentation on the immediate acquisition and retention of geometry concepts by seventh graders. Four geometry concepts, "quadrilateral,""rhombus,""trapezoid," and "parallelogram," were presented in written lessons which used either an expository or a discovery approach. Ss studied the lessons on four consecutive days. They were given a test on the concepts either immediately after completion of the lessons or one day or 21 days after completion of the lessons. Ss who received the test one day after completion were retested 21 days after completion. The findings of the study were as follows: (1) Ss who studied the expository lessons had significantly higher scores than Ss who studied the discovery lessons; (2) An independent groups analysis revealed no significant difference between treatment groups. However, a repeated measures analysis revealed that Ss in the discovery group tended to forget less than Ss in the expository group over the 21-day retention interval; and (3) The expository group spent only one-third as much time on the lessons, yet had immediate acquisition superior to the discovery group and 21-day retention equal to the discovery group. (Author/JM)

I will present novel machine learning methods for the discovery of important DNA sequence elements encoded in bacterial genomes. Knowledge of these elements provides insight into important problems in computational biology such as uncovering gene functions, gene-regulatory networks, and evolutionary relationships among genes and organisms. This talk will focus on my contributions related to the design and learning of graphical probability models of these elements. In particular, I will present methods for (i) refining the structure of stochastic context-free grammars, (ii) training sequence models with 'weakly' labeled data, (iii) designing models that incorporate multiple and diverse evidence sources and (iv) modeling and predicting arbitrarily overlapping elements in sequence data. The results of cross-validation experiments on the heavily studied bacterium E. coli show that the accuracy of our predictions exceeds the previous state-of-the-art. ©2005 Microsoft Corporation. All rights reserved.

I will present novel machine learning methods for the discovery of important DNA sequence elements encoded in bacterial genomes. Knowledge of these elements provides insight into important problems in computational biology such as uncovering gene functions, gene-regulatory networks, and evolutionary relationships among genes and organisms. This talk will focus on my contributions related to the design and learning of graphical probability models of these elements. In particular, I will present methods for (i) refining the structure of stochastic context-free grammars, (ii) training sequence models with 'weakly' labeled data, (iii) designing models that incorporate multiple and diverse evidence sources and (iv) modeling and predicting arbitrarily overlapping elements in sequence data. The results of cross-validation experiments on the heavily studied bacterium E. coli show that the accuracy of our predictions exceeds the previous state-of-the-art. ©2005 Microsoft Corporation. All rights reserved.

I will present novel machine learning methods for the discovery of important DNA sequence elements encoded in bacterial genomes. Knowledge of these elements provides insight into important problems in computational biology such as uncovering gene functions, gene-regulatory networks, and evolutionary relationships among genes and organisms. This talk will focus on my contributions related to the design and learning of graphical probability models of these elements. In particular, I will present methods for (i) refining the structure of stochastic context-free grammars, (ii) training sequence models with 'weakly' labeled data, (iii) designing models that incorporate multiple and diverse evidence sources and (iv) modeling and predicting arbitrarily overlapping elements in sequence data. The results of cross-validation experiments on the heavily studied bacterium E. coli show that the accuracy of our predictions exceeds the previous state-of-the-art. ©2005 Microsoft Corporation. All rights reserved.

This paper is in the public domain in USA. Metadata comes from the CrossRef API, see full record in the source URL below.

236 p. 25 cm

236 p. 25 cm

Alexander the Great was one of the most successful military commanders in history, and was undefeated in battle. By the time of his death, he had conquered most of the world known to the ancient Greeks.<br></br>Alexander the Great is one of many biographies aimed at young people written by Jacob Abbott and his brother. The biographies are written in such a way that makes them appealing and easily accessible to everyone. - Written by Wikipedia and Lizzie Driver

2Peter the Great

By Jacob Abbott

There are very few persons who have not heard of the fame of Peter the Great, the founder, as he is generally regarded by mankind, of Russian civilization. The celebrity, however, of the great Muscovite sovereign among young persons is due in a great measure to the circumstance of his having repaired personally to Holland, in the course of his efforts to introduce the industrial arts among his people, in order to study himself the art and mystery of shipbuilding, and of his having worked with his own hands in a ship-yard there. The little shop where Peter pursued these practical studies still stands in Saardam, a ship-building town not far from Amsterdam. The building is of wood, and is now much decayed; but, to preserve it from farther injury, it has been encased in a somewhat larger building of brick, and it is visited annually by great numbers of curious travelers.<br></br>The whole history of Peter, as might be expected from the indications of character developed by this incident, forms a narrative that is full of interest and instruction for all. (from the Preface of <i>Peter the Great</i>)

3Little Eve Edgarton

By Eleanor Hallowell Abbott

Eve Edgarton is not who she seems she is. A short encounter with Mr. Barton show that first impressions are not always right or indicative of one's seemingly obvious preference or one's proclivity. (Summary by Kehinde)

4Peace On Earth, Good-Will to Dogs

By Eleanor Hallowell Abbott

If you don't like Christmas stories, don't read this one!<br></br> And if you don't like dogs, I don't know just what to advise you to do!<br></br> For I warn you perfectly frankly that I am distinctly pro-dog and distinctly pro-Christmas, and would like to bring to this little story whatever whiff of fir-balsam I can cajole from the make-believe forest in my typewriter, and every glitter of tinsel, smudge of toy candle, crackle of wrapping paper, that my particular brand of brain and ink can conjure up on a single keyboard! And very large-sized dogs shall romp through every page! And the mercury shiver perpetually in the vicinity of zero! And every foot of earth be crusty-brown and bare with no white snow at all till the very last moment when you'd just about given up hope! And all the heart of the story is very,—oh very young!<br></br> For purposes of propriety and general historical authenticity there are of course parents in the story. And one or two other oldish persons. But they all go away just as early in the narrative as I can manage it.—Are obliged to go away!<br></br> Yet lest you find in this general combination of circumstances some sinister threat of audacity, let me conventionalize the story at once by opening it at that most conventional of all conventional Christmas-story hours,—the Twilight of Christmas Eve." (excerpt from the text)

5Molly Make-Believe

By Eleanor Hallowell Abbott

Carl Stanton is an invalid suffering from an unusual bout of rheumatism. His fiancee is gone for the winter and though he begs her to write to help ease his boredom and pain she is stingy with her letters. She sends him what she calls a 'ridiculous circular' which she states is very apropos of his sentimental passion for letters. In a sudden fit of mischief, malice and rheumatism, Carl decides to respond to the circular which results in bringing about the necessary distraction in a flurry of letters that do ease Carl's boredom and pain but also bring him something else that he never quite expected. (summary by Kehinde)

6Indiscreet Letter

By Eleanor Hallowell Abbott

Three fellow travelers on a train enter into a discussion concerning what they would call an 'indiscreet letter.' The discussion, albeit short, produces some rather interesting revelations during the journey and at journey's end. (Summary by Kehinde)

7Seven Wives and Seven Prisons; Or, Experiences in the Life of a Matrimonial Monomaniac

By L. A. Abbott

This work the author claims is indeed a true story of how he happened to be married seven times to seven different women and the rollicking, hilarious events that led (or stumbled) to the marriages and the ah--disassembling/failing/failures of each said marriage which happened oftentimes to land him in prison. The summarist finds the work a very tongue-in-cheek diatribe/lament/account of his obsessive zeal in 'marrying the right one', but is also the mirthful chronicle of said author's very unconventional adventures. (Summary by Kehinde)

8White Linen Nurse

By Eleanor Hallowell Abbott

The White Linen Nurse is a hysterical story of an exhausted nurse who comes to regret her profession and then somehow finds herself caring for the invalid daughter of the Senior Surgeon. The unexpected events which lead her there and also those which take her forward from that point are sure to evoke laughter and tears - a never to be forgotten story that will send a warm glow to your heart. (Summary by Kehinde)

9Cleopatra

By Jacob Abbott

A biography of the famous Cleopatra of Egypt, written in a manner, equally interesting to children and to adults.

<i>Flatland: A Romance of Many Dimensions</i> is an 1884 science fiction novella by the English schoolmaster Edwin Abbott Abbott. As a satire, <i>Flatland</i> offered pointed observations on the social hierarchy of Victorian culture. However, the novella's more enduring contribution is its examination of dimensions; in a foreword to one of the many publications of the novella, noted science writer Isaac Asimov described <i>Flatland</i> as "The best introduction one can find into the manner of perceiving dimensions." As such, the novella is still popular amongst mathematics, physics and computer science students. (Summary by Wikipedia)

There are certain names which are familiar, as names, to all mankind; and every person who seeks for any degree of mental cultivation, feels desirous of informing himself of the leading outlines of their history, that he may know, in brief, what it was in their characters or their doings which has given them so widely-extended a fame. Consequently, great historical names alone are selected; and it has been the writer's aim to present the prominent and leading traits in their characters, and all the important events in their lives, in a bold and free manner, and yet in the plain and simple language which is so obviously required in works which aim at permanent and practical usefulness. This volume is dedicated to William the Conqueror. (Summary from the preface of the book)

There are certain names which are familiar, as names, to all mankind; and every person who seeks for any degree of mental cultivation, feels desirous of informing himself of the leading outlines of their history, that he may know, in brief, what it was in their characters or their doings which has given them so widely-extended a fame. Consequently, great historical names alone are selected; and it has been the writer's aim to present the prominent and leading traits in their characters, and all the important events in their lives, in a bold and free manner, and yet in the plain and simple language which is so obviously required in works which aim at permanent and practical usefulness. This volume is dedicated to Queen Elizabeth. (Summary from the preface of the book)

There are certain names which are familiar, as names, to all mankind; and every person who seeks for any degree of mental cultivation, feels desirous of informing himself of the leading outlines of their history, that he may know, in brief, what it was in their characters or their doings which has given them so widely-extended a fame. Consequently, great historical names alone are selected; and it has been the writer's aim to present the prominent and leading traits in their characters, and all the important events in their lives, in a bold and free manner, and yet in the plain and simple language which is so obviously required in works which aim at permanent and practical usefulness. This volume is dedicated to Richard I. (Summary from the preface of the book)

There are certain names which are familiar, as names, to all mankind; and every person who seeks for any degree of mental cultivation, feels desirous of informing himself of the leading outlines of their history, that he may know, in brief, what it was in their characters or their doings which has given them so widely-extended a fame. Consequently, great historical names alone are selected; and it has been the writer's aim to present the prominent and leading traits in their characters, and all the important events in their lives, in a bold and free manner, and yet in the plain and simple language which is so obviously required in works which aim at permanent and practical usefulness. This volume is dedicated to Mary Queen of Scots. (Summary from the preface of the book)

There are certain names which are familiar, as names, to all mankind; and every person who seeks for any degree of mental cultivation, feels desirous of informing himself of the leading outlines of their history, that he may know, in brief, what it was in their characters or their doings which has given them so widely-extended a fame. Consequently, great historical names alone are selected; and it has been the writer's aim to present the prominent and leading traits in their characters, and all the important events in their lives, in a bold and free manner, and yet in the plain and simple language which is so obviously required in works which aim at permanent and practical usefulness. This volume is dedicated to Charles I. (Summary from the preface of the book)

There are certain names which are familiar, as names, to all mankind; and every person who seeks for any degree of mental cultivation, feels desirous of informing himself of the leading outlines of their history, that he may know, in brief, what it was in their characters or their doings which has given them so widely-extended a fame. Consequently, great historical names alone are selected; and it has been the writer's aim to present the prominent and leading traits in their characters, and all the important events in their lives, in a bold and free manner, and yet in the plain and simple language which is so obviously required in works which aim at permanent and practical usefulness. This volume is dedicated to Hannibal. (Summary from the preface of the book)

17Daniel Boone

By John Stevens Cabot Abbott

This is a detailed biography of the life and adventures of Daniel Boone. His accomplishments are brushed over in history classes these days and not given the recognition they deserve. This biography clearly paints a picture of the benevolent person of Daniel Boone as well as the achievements he made in furthering European settlement in America. (Summary by Allyson Hester)

Throughout three years of school, Rae Malgregor had been perfectly pliant, perfectly compliant to all the demands placed on her. But now, on the eve of graduation, she couldn’t go on with the mask of artificiality and the air of perfection. She had been chasing this nursing job three whole years, but there was just no wag to it! The Superintendent was stunned. Her best student! The Senior Surgeon was all grey granite business and livid that his time was being taken up with a hysterical nurse! And yet, though he wouldn’t have admitted it to anyone, especially himself, his interest was piqued. (Introduction by MaryAnn)

19Romulus

By Jacob Abbott

Jacob Abbott wrote many historical books for children. He was careful to ensure historical accuracy, and as he said himself in the preface to this book "Whatever of interest ... these stories may possess is due solely to the facts themselves which are recorded in them, and to their being brought together in a plain, simple, and connected narrative."<br /><br />This is the story of Romulus, the founding of Rome and the early years of its history, written in a way both readable and enjoyable for adults and children alike. (Summary by Ruth Golding)

20History of Julius Caesar

By Jacob Abbott

The book chronicles the extraordinary life and leadership of Rome’s Emperor Julius Caesar, from his early years to his assassination. (Summary by Cathy Barratt)

21Richard III (Makers of History series)

By Jacob Abbott

Jacob Abbott chronicles the unspeakably treacherous rise of Richard III to the throne of England in the midst of the war between the Yorks and the Lancasters and his ultimate fall on the Field of Bosworth. (Introduction by Cathy Barratt)

22Margaret of Anjou

By Jacob Abbott

Margaret of Anjou, wife of England’s Henry VI, played a key role in launching the storied War of the Roses – the 30-year civil conflict fuelled by the Lancasters and the Yorks, each vying for the British throne in the 15th century.

23David Crockett: His Life and Adventures

By John Stevens Cabot Abbott

David "Davy" Crockett (August 17, 1786 – March 6, 1836) was a celebrated 19th century American folk hero, frontiersman, soldier and politician. He is commonly referred to in popular culture by the epithet “King of the Wild Frontier.” He represented Tennessee in the U.S. House of Representatives, served in the Texas Revolution, and died at the Battle of the Alamo. This narrative attempts faithfully to record the influences under which David Crockett was reared and the incidents of his wild and wondrous life. It begins with his ancestors' immigration to the American wilderness, his adventures among the Indians, his political career in Tennessee and beyond, and ending with his heroic stand at the Alamo. (Summary by Brett W. Downey)

24Gentle Measures in the Management and Training of the Young

By Jacob Abbott

Subtitled, "The principles on which a firm parental authority may be established and maintained, without violence or anger, and the right development of the moral and mental capacities be promoted by methods in harmony with the structure and the characteristics of the juvenile mind." This book gives practical advice on how to raise children using "gentle measures" that do not damage the children's emotions or self esteem. Most of the information is as relevant and practical today as it was when published in 1871. (Summary by TriciaG)

25Molly Make-Believe (version 2)

By Eleanor Hallowell Abbott

Carl Stanton is an invalid suffering from an unusual bout of rheumatism. His fiancée is gone for the winter and though he begs her to write to help ease his boredom and pain she is stingy with her letters. She sends him what she calls a "ridiculous circular" which she states is very apropos of his sentimental passion for letters. In a sudden fit of mischief, malice and rheumatism, Carl decides to respond to the circular which results in bringing about the necessary distraction in a flurry of letters that do ease Carl’s boredom and pain but also bring him something else that he never quite expected. (Summary by Wikisource)

26Richard II, Makers of History

By Jacob Abbott

Chronicles the life of Richard II, born in 1367 in Bordeaux, France, who later wore the crown of King of England. (Summary by Cathy Barratt)

27Empire of Russia from the Remotest Periods to the Present Time

By John Stevens Cabot Abbott

A history of Russia from 500 B.C. to 1855 A.D., written by John Stevens Cabot Abbott, the brother of Jacob Abbott. (Summary by Jean Bascom)