Miracle-dz/UniFAR-FTUs huggingface dataset:
One-Pot Synthesis of Multiply Substituted Quinoline and Quinazoline Derivatives via [2+2+2] Cascade Annulation with Diaryliodonium Salts

Abstract An efficient and regioselective method to multisubstituted quinoline and quinazoline derivatives with diaryliodonium salts catalyzed by Cu(OTf)2 has been presented. The reaction proceeded via cascade annulation in the mode of [2+2+2] form. This novel strategy enables use of readily available materials and bears great flexibility on the substitution groups.
Teaching Basic Skills through Microcomputer Assisted Instruction

Low achieving students in grades 4–6 were given supplementary microcomputer assisted instruction in reading and mathematics. Students' performance was assessed with a pretest/posttest nonequivalent control group design using standardized achievement and affective tests. Although all microcomputer experimental groups showed statistically significant pretest/posttest gains in reading and mathematics, the control groups using conventional instructional methods also showed similar gains. Analysis of covariance of achievement gains revealed only one experimental group, sixth grade reading, to be statistically superior to the control groups' performance. No significant changes in students' attitudes toward schooling or sense of control over their own performance were detected. Implications of this study's design and findings are discussed with respect to past CAI research and present CAI school practices.
Translating Kung Fu Panda's kung fu-related elements: cultural representation in dubbing and subtitling

Regarding dubbing and subtitling choices as comparable cultural solutions, this article examines different translation strategies, employed by both professional audiovisual translators and amateur subtitlers of five Chinese versions for Kung Fu Panda (i.e. three licensed versions dubbed respectively in Cantonese, Standard Mandarin, and Taiwan Mandarin; two fan/amateur subtitled versions), for rendering kung fu-related elements. The findings presented in this article show that both professional audiovisual translators and amateur subtitlers have a strong preference for interventional strategies (i.e. adaptation, rephrasing, replacement). Their cultural decisions are motivated by contextual considerations (e.g. film genre, audience expectations, matching words and images, coherence and understanding) rather than being restricted by constraints such as synchronization and space restriction, which highlights audiovisual translators' active role in cultural representation.
Qualitative repository analysis with RepoGrams

The availability of open source software projects has created an enormous opportunity for empirical evaluations in software engineering research. However, this availability requires that researchers judiciously select an appropriate set of evaluation targets and properly document this rationale. This selection process is often critical as it can be used to argue for the generalizability of the evaluated tool or method. To understand the selection criteria that researchers use in their work we systematically read 55 research papers appearing in six major software engineering conferences. Using a grounded theory approach we iteratively developed a codebook and coded these papers along five different dimensions, all of which relate to how the authors select evaluation targets in their work. Our results indicate that most authors relied on qualitative and subjective features to select their evaluation targets. Building on these results we developed a tool called RepoGrams, which supports researchers in comparing and contrasting source code repositories of multiple software projects and helps them in selecting appropriate evaluation targets for their studies. We describe RepoGrams’s design and implementation, and evaluate it in two user studies with 74 undergraduate students and 14 software engineering researchers who used RepoGrams to understand, compare, and contrast various metrics on source code repositories. For example, a researcher interested in evaluating a tool might want to show that it is useful for both software projects that are written using a single programming language, as well as ones that are written using dozens of programming languages. RepoGrams allows the researcher to find a set of software projects that are diverse with respect to this metric.
Position estimation method based on the optical displacement sensor for an autonomous hull cleaning robot

This paper presents the new position estimation method which contains the optical displacement sensor and the dead reckoning based position estimation algorithm for automation of hull cleaning robot. To evaluate feasibility of the proposed position estimation method on the hull cleaning robot, it was applied on the small scale robot model which has an identical drive method with the hull cleaning robot and then a set of the position estimation experiments were performed. The experimental results of the position estimation demonstrate that the estimated results with the optical displacement sensors is more accurate than used rotary encoder method. In addition, it continuously calculated the robot position quite close to the real robot driving path. In a follow-up study, the proposed position estimation method will be complemented and exploited on the actual hull cleaning robot by adding additional sensor modules that correct measurement errors.
Multi-dimensional Multi-granularities Data Mining for Discovering Innovative Healthcare Services

Data Mining is getting increasingly important for discovering association patterns for health service innovation and Customer Relationship Management (CRM) etc. Yet, there are deficits of existing data mining techniques. Since most of them perform a plain mining based on predefined schemata through the data warehouse as a whole, a re-scan must be done whenever new attributes are added. Secondly, an association rule may be true on a certain granularity but fail on a smaller one and vise verse. Last but not least, they are usually designed to find either frequent or infrequent rules. After a survey of a category of significant health services, we propose a data mining algorithm alone with a forest data structure to solve aforementioned weaknesses at the same time. At first, we construct a forest structure of concept taxonomies that can be used for representing the knowledge space. On top of it, the data mining is developed as a compound process to find the large-itemsets, to generate, to update and to output association rules that can represent services portfolio. After a set of benchmarks derived to measure the performance of data mining algorithms, we present the performance with respect to efficiency, scalability, information loss, etc. The results show that the proposed approach is better than existing methods with regard to the level of efficiency and effectiveness.
Real-time epileptic seizure detection using reservoir computing

1 Purpose : This study proposes the use of a new classification algorithm, Reservoir Computing, to develop a real-time and accurate epileptic seizure detection system. 2 Methods: Reservoir Computing (RC) is a training method for recurrent neural networks where only a simple linear readout function is trained and where the neural network, the reservoir, is randomly created. As input for this reservoir we use a selection of different EEG features currently existing in seizure detection literature. This selection was made during training using a basic feature selection method. The output of the reservoir was trained using a ridge regression algorithm. 3 Results : In this study intracranial rat data from two different types of generalized epilepsy are detected: absence and tonic-clonic epilepsy. For both seizure types our approach resulted in an area under the Receiver Operating Characteristics curve (AUC) of 0.99 on the test data. For absences an average detection delay of 0.3s was noted, for tonic-clonic seizures this was 1.5s. The SWD detection method was tested on 15 hours of EEG-data coming from 13 GAERS rats, from which 10% was used for training. Our method outperformed the other implemented methods from which the best method was developed by Fanselow et al. in 2000 and resulted in an AUC of 0.96 and an average detection delay of more than 3 seconds. To evaluate the tonic-clonic seizure detection method 4 hours and 23 minutes of data of 4 rats was used. 20% of the total dataset was used for training, the rest was used for testing. Again our method outperformed other methods where the best method by White et al. in 2006 which resulted in a AUC of 0.82. 4 Conclusion : This study shows that it is possible to perform seizure detection using the described Reservoir Computing method and that it outperforms existing methods.
ComSen: A Detection System for Identifying Compromised Nodes in Wireless Sensor Networks

Wireless sensor networks (WSNs) are vulnerable to adversaries as they are frequently deployed in open and unattended environments. Adversaries can extract vital information, such as security keys, from compromised nodes and use them to launch insider attacks, so detecting when a node is compromised is important to securing WSNs. In this paper, we present ComSen, an accurate and lightweight intrusion detection system for identifying compromised nodes in wireless sensor networks. Through quantitative results, we demonstrate the benefits of ComSen: (1) it is not vulnerable to slander attacks, (2) it provides detection rates of 99% and false positive ratios of less than 2% in environments with loss rates of 30%, which cannot be achieved by existing systems, (3) it runs on most WSNs because it uses common application features (sensor readings, receive power, send rate, and receive rate) and can adjust its detection behavior if the sensor application doesn’t have periodic transmissions or lacks inter-node communication, and (4) it has low memory, computation, and communication overheads that allows it to scale to networks of over thousands of nodes. Keywords-wireless sensor network; ComSen; intrusion detection system;
CiteRank: combination similarity and static ranking with research paper searching

Search engines and social bookmarking systems are important tools for web resource discovery. The performance and capabilities of web search engines are vital. This paper proposes CiteRank, a combination of a similarity ranking with a static ranking. Similarity ranking measures the match between a query and a research paper index; while a static ranking, or a query independent ranking, measures the quality of a research paper. For this particular study, a group of factors containing: number of groups contained the posted paper, year of publication, research paper posted time, and priority of a research paper was used to determine a static ranking score. The NDCG was used as an evaluation metric. CiteRank was compared with SimRank and StaticRank. The results of the experiment showed that CiteRank produces a better ranking than the other methods. This implies that CiteRank can improve the effectiveness of research paper searching on social bookmarking websites.
Dynamics of concurrent software development

In a concurrent development process different releases of a software product overlap. Organizations involved in concurrent software development not only experience the dynamics common to single projects, but also face interactions between different releases of their product: they share resources among different stages of different projects, including customer support, they have a common code base and architecture that carries problems across releases, they use the same capabilities, and their market success in early releases impacts their resources in later ones. Drawing on two case studies we discuss some of the feedback processes central to concurrent software development and build a simple simulation model to analyze the resulting dynamics. This model sheds light on tipping dynamics, the nature of inter-project feedback loops, and alternative resource allocation policies relevant to management of concurrent software development. Copyright © 2009 John Wiley & Sons, Ltd.
Topography based design of the T-DAB SFN for a mountainous area

A method for designing a terrestrial digital audio broadcasting single frequency network (T-DAB SFN) for a mountainous region is proposed. A computer database and the digital terrain elevation data are used in designing the network. Two fundamental approaches are compared; first, utilization of the existing transmitter sites is maximized by applying the initial cost constraint; then, the coverage percent of the service is forced to approach to 100% by applying the coverage efficiency constraint. Finally, a T-DAB SFN hybrid design procedure optimizing both constraints is proposed. The three design approaches are illustrated on the coverage of the mountainous Istanbul-Ankara highway. The results are compared using a reference cost look up table. The hybrid approach is shown to optimize the initial cost and the coverage efficiency, and can be applied to similar networking problems.
Generation of Program Analysis Tools

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Pronoomenid lapsekeeles: mõnda mina ja sina omandamisest

Artiklis vaadeldakse ainsuse 1. ja 2. isiku pronoomeni omandamist lastel vanuses 1;7–3;1 CHILDES-i eesti keele allkorpuse ning teistest allikatest leitud toetava keelematerjali pohjal. Pohianaluus on tehtud Andrease allkorpuse 76 tunnipikkuse lindistuse pohjal. Lisaks lapse konele on analuusitud ka sisendkeelt. Analuusitud materjali pohjal voib vaita, et demonstratiivpronoomenid ilmuvad enne personaalpronoomeneid. Personaalpronoomeneid hakkab laps kasutama umbes kaheaastaselt. Esialgu leidub uksikuid juhuslikke naiteid, pronoomenite taiskasvanuparane kasutus kujuneb valja alles mone aja parast. Sisendkeele analuus naitab, et ema hakkab lapse kasvades kasutama taiskasvanuparasemat keelt. Kui vestluses kaheaastasega kasutab ema valdavalt lapse nime ja endast raakides sona emme, siis kolmeaastasega vesteldes viitab ema endale ja lapsele pigem pronoomeniga. Ainsuse 1. isiku pikka ja luhikest pronoomenit mina/ma (subjektina) esineb Andreasel peaaegu kolm tuhat korda, ning ainsuse 2. isiku pronoomeneid kolm korda vahem. Sisendkeelega vorreldes on Andreasel 1. ja 2. isiku pronoomeni pikki vorme rohkem kui emal. Pronoomenite varases kasutuses teevad lapsed ka vigu, sagedamini ajavad nad segamini 1. ja 2. isiku pronoomeni. DOI: http://dx.doi. org/10.5128/ERYa3.24
Development of the Modified Cellular Automata Sphere Growth Model for Creation of the Digital Material Representations

Development of reliable algorithm for generation of statistical representations of microstructure morphologies is the subject of the present work. The implemented cellular automata sphere growth model is presented first. Obtained grain size distribution of digital microstructure is compared with experimental measurements to prove efficiency of the proposed algorithm. Then, the grain growth model was additionally combined with the genetic algorithm optimization to extend its microstructure generation capabilities. Finally, possibilities of practical applications of generated digital material representation for modelling texture evolution during channel die test is presented.
Optimizing Hidden Markov Model with Baum-Welch Algorithm for Vehicle Driver's Intention Recognition

In this paper, a method for vehicle driver’s intention recognition is investigated through an optimized hidden Markov model (HMM). As uncertainties exist between modeling and application of intention recognition with HMM, the Baum-Welch (B-W) algorithm is introduced to optimize and update the parameters of the established HMM. The major steps within the optimization process, such as acquisitions of forward probabilities, backward probabilities, maximum expected probabilities ratio, elements updates of matrixes π, A and B, and setups of recursion terminated condition, are fully described in the paper. An elaborate example presented at the end of the paper shows the credibility and effectiveness of the proposed algorithm.
Gate Count Comparison of Different 16-Bit Carry Select Adders

Addition is the most fundamental computational process encountered in digital system. An area efficient carry select adder is proposed in this paper by comparing the Gate count of Regular and Modified 16-bit carry select adders with a proposed Common Boolean Logic carry select adder. In this paper, Gate count evaluation of Regular, Modified and proposed designs are given in terms of INVERTER, NAND and NOR Gates. The comparison results shows that the common Boolean logic carry select adder structure require lesser number of gates than that of Regular and Modified 16-bit carry select adder.
Image Classification Based on Color Topic Model

This paper addresses semantic image classification with topic model, which focusing on discovering a hidden semantic to solve the semantic gap between low-level visual feature and high-level feature. In our approach, Latent Dirichlet Allocation (LDA) model successfully reflect the high level features and the RGB SIFT features which integrating the Scale-invariant feature transform (SIFT) features with color features on the assumption that pictures generated by mixture of latent semantic which we called topics. The proposed approach has a sufficient theoretical basis and the experimental evaluations the COREL database demonstrate its promise of the effectiveness.
Two Novel Term Weighting For TextCategorization

In text categorization (TC) based on the vector space model, documents are represented as a vector, where each component is associated with a particular term from the text collection vocabulary. Traditionally, each component value is assigned using the information retrieval (IR) TFIDF measure. While this weighting method seems very appropriate for IR, weighting methods that take into account the importance of the term to the discrimination of the categories may provide better results in TC. To apply this idea, we use in this work variants of TFIDF weighting, where the idf part is replaced by functions used to conduct term selection. In an approach on real-world data to automatically distribute the legislative bills to the committees at the Federal District Legislative Assembly in Brasilia, Brazil, the replacement of the idf part in TFIDF by a new term selection measure – absl-logit – and by bi-normal separation [1] produced the best general classification results with support vector machines (SVM), when compared with TFIDF and with the use of common term selection measures – chi-square, information gain, gain ratio and odds ratio – to replace the idf part in TFIDF.
Using Model Updating to Predict the Failure of Reinforced Concrete Elements

Finding an accurate analytical model that is a good match for experimental data is not a straightforward task. Generally analytical model parameters are tuned, using previously tested methods, to achieve an acceptable match for the experimental results. Model updating is a popular method that has been widely used since the early 1990s for this purpose. In this paper, research carried out for predicting the behaviour of masonry wall panels has been extended to find a suitable non-linear model for reinforced concrete (RC) beams that matches the experimental laboratory results. Data from laboratory experiments carried out by other researchers are used to confirm the validity of this analytical model. A Genetic Algorithm (GA) tool is used for the model updating process. The GA optimisation process finds a set of optimum parameters for use in the FE model. The outcome of this study was a close match with the experimental results, thus utilisation of this technique will dramatically reduce the number of expensive laboratory experimental tests which would otherwise be necessary. KYEWORD: Model updating, System Identification, Optimisation, Genetic Algorithms,
Acquiring Semantically Meaningful Models for Robotic Localization, Mapping and Target Recognition

Abstract : The goal of this proposal is to develop novel representations and techniques for localization, mapping and target recognition from videos of indoors and urban outdoors environments. The proposed techniques will facilitate enhanced navigation capabilities by means of visual sensing and enable scalable, long-term navigation and target detection in outdoors and indoors environments. The attained representations will also be applicable towards human-robot interaction, enhancement of human navigational and decision making capabilities and provide compact semantically meaningful summaries of the acquired sensory experience. The proposed representations will be governed by principles of compositionality, facilitate bottom-up learning, enable efficient inference and could be adapted to a task at hand. The main novelty of the approach will be the use both 3D and 2D geometric and photometric cues computed either from video sequence or from novel RBG-D cameras, which provide synchronized video and range data at frame rate. Video poses challenges related to more extreme variations in viewpoint and scale, dramatic changes in lighting and large amount of clutter and occlusions, but also enables computation of 3D structure and motion cues, which can aid segmentation and recognition of object and non-object categories. As a part of this proposal we have developed techniques for semantic labeling of outdoors and indoors environments using photometric and geometric cues from video. The proposed approach is informed by novel features and representations for learning models of objects and non-object categories from video, works effectively with multiple sensing modalities and can be deployed on static frames as well as video in a recursive setting. We have tested the approach extensively on benchmark sequences of indoors and outdoors environments.
Fully Printed Dual‐Band Power Divider Miniaturized by CRLH Phase‐Shift Lines

In this letter, a compact and fully printed composite right‐ and left‐handed (CRLH) dual‐band power divider is proposed. The branches of the conventional Wilkinson power divider are replaced by subwavelength CRLH phase‐shift lines having +90° for one frequency and −90° for another frequency for dual‐band and miniaturization performance. Equations are derived for the even‐ and odd‐mode analysis combined with the dual‐band CRLH circuit. A PCS and a WLAN band are chosen as the test case and the circuit approach agrees with the CAD simulation and the measurement. Additionally, the CRLH property is shown with the dispersion diagram and the eightfold size reduction is noted.