Miracle-dz/UniFAR-FTUs huggingface dataset:
DOMAIN-SPECIFIC MODELING ENVIRONMENT BASED ON UML PROFILES

Domain-Specific Modeling Languages (DSML) play a key role in model-driven development. There are many approaches how to create a DSML. Recent trends in domain-specific modeling languages and issues of creating and using UML profiles are discussed in this paper. Then we present a novel approach for defining a full-featured DSML based on a UML profile and its customization instead of heavyweight metamodeling. This approach was implemented in MagicDraw UML tool and already successfully accepted by its users. Also, MagicDraw UML developers themselves applied it for creating SysML, DoDAF and UPDM modeling environments. The main benefit of this approach is that it allows a DSML modeler to reuse powerful features of already existing tools. We propose a seven-step DSML development process and illustrate it by an example demonstrating creation of a DSML for modeling organization structures. We also discuss benefits of taking the presented approach and some ideas for future enhancements based on the feedback of users.
Cognitive function and living situation in COPD: is there a relationship with self-management and quality of life?

Background Cognitive impairment is increasingly being found to be a common comorbidity in chronic obstructive pulmonary disease (COPD). This study sought to understand the relationship of comprehensively measured cognitive function with COPD severity, quality of life, living situation, health care utilization, and self-management abilities. Methods Subjects with COPD were recruited from the outpatient pulmonary clinic. Cognitive function was assessed using the Montreal Cognitive Assessment (MOCA). Self-management abilities were measured using the Self Management Ability Score 30. Quality of life was measured using the Chronic Respiratory Disease Questionnaire. Pearson correlation was used to assess the bivariate association of the MOCA with other study measures. Multivariate analysis was completed to understand the interaction of the MOCA and living situation on COPD outcomes of hospitalization, quality of life, and self-management ability. Results This study included 100 participants of mean age 70±9.4 years (63% male, 37% female) with COPD (mean FEV1 [forced expiratory volume in 1 second] percentage predicted 40.4±16.7). Mean MOCA score was 23.8±3.9 with 63% of patients having mild cognitive impairment. The MOCA was negatively correlated with age (r=−0.28, P=0.005) and positively correlated with education (r=+0.24, P=0.012). There was no significant correlation between cognitive function and exacerbations, emergency room (ER) visits, or hospitalizations. There was no association between the MOCA score and self-management abilities or quality of life. We tested the interaction of living situation and the MOCA with self-management abilities and found statistical significance (P=0.017), indicating that individuals living alone with higher cognitive function report lower self-management abilities. Conclusion Cognitive impairment in COPD does not appear to be meaningfully associated with COPD severity, health outcomes, or self-management abilities. The routine screening for cognitive impairment due to a diagnosis of COPD may not be indicated. Living alone significantly affects the interaction between self-management abilities and cognitive function.
Enhancing Mutual Awareness in Group Recommender Systems

An increasingly important type of recommender system comprises those that generate recommendations for groups rather than for individuals. The decision of a group member whether or not to accept a given recommendation can depend not only on her own evaluation of the content of the recommendation but also on her beliefs about the evaluations of the other group members and about their motivation (e.g., egocentric vs. cooperative). Yet this type of mutual awareness may be hard to achieve when group recommendations are delivered by a web-based system to group members who cannot communicate face-to-face. After introducing these issues on a general level, we discuss them more concretely by discussing a prototype group recommender system that uses several novel methods to enhance mutual awareness among group members, ranging from a group-oriented interface technique for specifying preferences to animated characters that serve as representatives of group members who are not currently available for communication.
The Ant Colony Optimization for Ship Pipe Route Design in 3D Space

Ship pipe route design (SPRD) is an area, which requires experienced experts because of its complexity and the large search space involved. It is one of the stages of ship design that remains not automated completely. Ant colony optimization (ACO) is a novel population-based evolutionary search technique to solve optimization problems by using principle of pheromone information. This paper describes a study of automatic SPRD using ACO. It includes the constructions of appropriate mathematical model for SPRD and ant colony optimization with dynamic local search (ACODLS) solving SPRD in three-dimensional space. Simulation results indicate that the performance and CPU time of the proposed algorithm are competitive with other existing algorithms used to generate solutions to the SPRD
An Investigation of Metaphors on the Concept of Teacher among Preservice Turkish Teachers

The purpose of this study is to investigate the perception of preservice Turkish teachers with respect to the concept of teacher through metaphors. The research has the research pattern adopted the phenomenology pattern, a qualitative research approach which prioritizes examining and understanding social phenomena within the context they belong to. The participants consist of freshman students studying at the departments of Turkish Language Teaching at Yildiz Technical University (46), Sabahattin Zaim University (36) and Aydin University (32) during 2013- 2014 academic year. The present study is of a particular importance since the sample includes preservice students from private universities. The questions pursued in the study are which metaphors preservice Turkish teachers produce for the concept of teacher and which conceptual categories those metaphors are sorted out based on their common features. To that end, the participants are asked to complete the sentence “A teacher is like . , because . ”. Content analysis, a qualitative data analysis method, is employed during the data analysis process. According to the findings, the preservice Turkish teachers have produced 42 valid metaphors. The results obtained in the research yield that preservice Turkish teachers consider the concept of teacher as source of information, mentor and guide, example of love and sacrifice, molder
Design and control in the maximization of human vertical jumping 1 , 2

We sought to explore an intriguing question: how can muscle mass be redistributed in leg muscles to allow for maximal jump performance? We performed forward simulations of human jumping movements using a foursegment inverted pendulum model of the skeleton and hilltype models of six leg muscles (soleus, gastrocnemius, vasti, hamstrings, rectus femoris and glutei). Preliminary results suggest that selectively changing relative muscle crosssectional area and muscle lengths can result in jump height improvement by approximately 20%. The resulting muscle distributions are profoundly different than average human muscle distributions. In contrast, modest changes to the timing of muscle onsets are required for the new muscle distributions.
Pricing with Bandwidth Guarantees for Clients with multi-ISP Connections

The increase in internet coverage and decrease in internet access price has resulted in demand for good internet service. Clients want some guarantee in internet access quality. In this paper, we present a model in which clients are guaranteed connection and bandwidth and if clients do not get the service they request, the service provider pays a penalty to the clients. We consider a system of internet clients with multiple internet service provider (ISP) connections to a set of ISPs. When a client arrives, an ISP has to decide whether to accept the client, and then the price to charge from the client for the duration of its connection. Rejection of a client results in a penalty and delay in getting the requested bandwidth also incurs a penalty. We assume a Poisson arrival process with the rate of arrival sensitive to the price being charged. A client requests bandwidth for a time that is exponentially distributed, then the client is idle for a time that is also exponentially distributed; and then either the client departs or requests bandwidth again after the idle period is over. A service provider tries to maximize its income by charging appropriate prices based on its current state and deciding whether to accept more clients or not. Since penalties are imposed, such solutions also automatically balance load among service providers, and so the quality of service to clients improves. We present solutions that maximize the income of service providers. The solutions are then compared using simulation. Simulation results show that our analysed solution significantly improve quality of service of clients and increase the income of service providers as compared to a simple heuristic based solution that is otherwise could to be used.
Efficient algorithm for decoding layered space-time codes

Layered space-time codes have been designed to exploit the capacity advantage of multiple antenna systems in Rayleigh fading environments. A new efficient decoding algorithm based on QR decomposition is presented, which requires only a fraction of the computational effort compared with the standard decoding algorithm requiring the multiple calculation of the pseudo inverse of the channel matrix.
Low-cost large area processing using small area substrates-a novel multitiled palletization concept for MCM-D thin film process

Multichip module-deposited (MCM-D) has been the solution for integrated high density packaging due to its superior line resolution and higher inputs/outputs (I/O) density compared to MCM-C and multichip module-laminate (MCM-L) technologies. However the consumer demand for high performance products at reduced costs is ever increasing, and this trend is expected to continue in the 21st Century. In order to find a low-cost solution for future MCM-D packaging, a novel palletization process which incorporates several tiles (alumina or silicon) on a large carrier glass (pallet) has been established in this study. The multitiling format provides simultaneous processing of several small tiles onto a re-usable CTE matched carrier glass. The tiles are attached to the glass with a low modulus adhesive that can be released at an elevated temperature (/spl sim/450/spl deg/C). The objective of this study is to develop a multitiling process for a 300 mm/spl times/300 mm area that is scalable up to 600 mm/spl times/600 mm format. There are several challenges in realization of the large area palletization approach, such as formulation and qualification of a high temperature reworkable adhesive and minimization of out-of-plane warpage of the tiled assembly. Finite element models for warpage and its validation by shadow moire measurement, formulation of a compliant adhesive for thermal stability up to 400/spl deg/C are reported in previous publications. This paper deals with (1) the validation of the palletization concept on a 300 mm x 300 mm glass with weight restriction below 3 lbs and thickness limitation to <6.25 mm, and (2) qualification of the formulated adhesive through a correlative study on high temperature detachability of the attached tiles, chemical compatibility of the adhesive with acids, bases, and less polar solvents, and interfacial shear strength at the lass/adhesive/tile joints. MCM-D thin film process on the tiled substrates is to be conducted by the member companies of the MCM-D Consortium.
Full-Duplex Amplify-and-Forward Relaying: Power and Location Optimization

In this paper, we consider a full-duplex (FD) amplify-and-forward relay system and optimize its power allocation and relay location to minimize the system symbol error rate (SER). We first derive the asymptotic expressions of the outage probability and SER performance by taking into account the residual self interference (RSI) in FD systems. We then formulate the optimization problem based on the minimal SER criterion. Analytical and numerical results show that optimized relay location and power allocation can greatly improve system SER performance, and the performance floor caused by the RSI can be significantly reduced via optimizing relay location or power allocation.
Learning super-resolution from misaligned examples

Implementations of Example-Based Super-Resolution (EBSR) have been developed extensively. Any such EB-SR method is typically evaluated against a constructed test set as to define its performance and applicability. Nevertheless, it is rare for a formed test set to precisely resemble data met in a real-world problem. Usually, low-quality training and test subsets are obtained directly from their corresponding high-quality ground truth data. This allows for a complete and reliable quantitative examination of performance at a later stage. In a real-world problem however, test data are obtained from another source, as for example, printed images. Naturally, low-quality scanned halftones and high-quality continuous tone images would possibly be spatially incoherent training pairs. Such circumstances give rise to one major consideration, misalignment in training subsets. The present work demonstrates the significance of effect of misalignment among training subsets in applying EB-SR and supports the necessity of image registration in preprocessing to overcome this problem.
An ERP study of the processing of Mandarin classifiers

Comprehension of Mandarin classifier-noun sequences was examined by comparing event-related brain potential (ERP) responses to classifier-noun matches (一 张 纸; a sheet of paper ) and mismatches (一 张 咖啡; a sheet of coffee ). One goal was to determine which ERP components are sensitive to such matches, as a clue about the nature of the underlying combinatorial processes. Another goal was to examine effects of classifier constraint strength ( a piece of … vs a sheet of … ) on anticipation of the subsequent noun. Results showed that nouns evoked larger N400 in mismatching classifier-noun sequences, suggesting that combinatorial processing was primarily semantic. General classifiers evoked a larger sustained frontal negativity than specific classifiers, reflecting effects of constraint strength on anticipation of the upcoming noun. In addition, classifier presence was manipulated. The classifier-absent condition evoked a P600 in the first half of the experiment and an Anterior Negativity in the second half, suggesting that readers changed processing strategy over time.
Reinforcement Learning Algorithms for Average-Payoff Markovian Decision Processes

Reinforcement learning (RL) has become a central paradigm for solving learning-control problems in robotics and artificial intelligence. RL researchers have focussed almost exclusively on problems where the controller has to maximize the discounted sum of payoffs. However, as emphasized by Schwartz (1993), in many problems, e.g., those for which the optimal behavior is a limit cycle, it is more natural and computationally advantageous to formulate tasks so that the controller's objective is to maximize the average payoff received per time step. In this paper I derive new average-payoff RL algorithms as stochastic approximation methods for solving the system of equations associated with the policy evaluation and optimal control questions in average-payoff RL tasks. These algorithms are analogous to the popular TD and Q-learning algorithms already developed for the discounted-payoff case. One of the algorithms derived here is a significant variation of Schwartz's R-learning algorithm. Preliminary empirical results are presented to validate these new algorithms.
A Consensus-Driven Approach for Structure and Texture Aware Depth Map Upsampling

This paper presents a method for increasing spatial resolution of a depth map using its corresponding high-resolution (HR) color image as a guide. Most of the previous methods rely on the assumption that depth discontinuities are highly correlated with color boundaries, leading to artifacts in the regions where the assumption is broken. To prevent scene texture from being erroneously transferred to reconstructed scene surfaces, we propose a framework for dividing the color image into different regions and applying different methods tailored to each region type. For the region classification, we first segment the low-resolution (LR) depth map into regions of smooth surfaces, and then use them to guide the segmentation of the color image. Using the consensus of multiple image segmentations obtained by different super-pixel generation methods, the color image is divided into continuous and discontinuous regions: in the continuous regions, their HR depth values are interpolated from LR depth samples without exploiting the color information. In the discontinuous regions, their HR depth values are estimated by sequentially applying more complicated depth-histogram-based methods. Through experiments, we show that each step of our method improves depth map upsampling both quantitatively and qualitatively. We also show that our method can be extended to handle real data with occluded regions caused by the displacement between color and depth sensors.
Dalit Children Dropout in Schools: Need for Inclusive Curriculum

Dalit children are generally marginal with respect to students of other categories, and their dropout rate is an alarming situation in India. Scholars, social scientists and educationists have tried to understand the reasons of student disengagement from the school system and have revealed various causes and given many varied suggestions that are related to a child’s family background and socio-cultural background. Although several attempts have been made to understand the reasons for dropout, still it is not explored well. Also, cultural politics for dropout of particular group is not yet explored at the micro and macro levels. In this article, we try to understand how school, through its structures and ideology including textbook culture, influences student’s decisions to stay out. This study also considers traditional explanations for understanding the socio-background behaviours of the children for dropout. At the same time, we try to understand the role of school in Dalit children dropout.
Bias and Prejudice towards History in Indian Struggle for Independence

The Indian national movement was undoubtedly one of the biggestmass movements modern society has ever seen. It was a movement whichgalvanized millions of people of all classes and ideologies into politicalaction and brought to its knees a mighty colonial empire. The history ofIndian freedom movement has been classified on the nature of the freedomfighters: Mohandas Karamchand Gandhi (1869-1948) and Jagadish ChandraBose (1858-1937), i.e. the pacifist, non-violent approach and the extremist,radical approach. This article questions relate to the present perception ofboth personalities and the bias related to their means considered by themin their struggle for freedom.
PSIC: profile extraction from sequence alignments with position-specific counts of independent observations.

Sequence weighting techniques are aimed at balancing redundant observed information from subsets of similar sequences in multiple alignments. Traditional approaches apply the same weight to all positions of a given sequence, hence equal efficiency of phylogenetic changes is assumed along the whole sequence. This restrictive assumption is not required for the new method PSIC (position-specific independent counts) described in this paper. The number of independent observations (counts) of an amino acid type at a given alignment position is calculated from the overall similarity of the sequences that share the amino acid type at this position with the help of statistical concepts. This approach allows the fast computation of position-specific sequence weights even for alignments containing hundreds of sequences. The PSIC approach has been applied to profile extraction and to the fold family assignment of protein sequences with known structures. Our method was shown to be very productive in finding distantly related sequences and more powerful than Hidden Markov Models or the profile methods in WiseTools and PSI-BLAST in many cases. The profile extraction routine is available on the WWW (http://www.bork.embl-heidelberg. de/PSIC or http://www.imb.ac.ru/PSIC).
The Chemical Composition and Age of the Metal-poor Halo Star BD +17°3248

We have combined new high-resolution spectra obtained with the Hubble Space Telescope (HST) and ground-based facilities to make a comprehensive new abundance analysis of the metal-poor, halo star BD +17°3248. We have detected the third r-process peak elements osmium, platinum, and (for the first time in a metal-poor star) gold, elements whose abundances can only be reliably determined using HST. Our observations illustrate a pattern seen in other similar halo stars with the abundances of the heavier neutron capture elements, including the third r-process peak elements, consistent with a scaled solar system r-process distribution. The abundances of the lighter neutron capture elements, including germanium and silver, fall below that same scaled solar r-process curve, a result similar to that seen in the ultra-metal-poor star CS 22892-052. A single site with two regimes or sets of conditions, or perhaps two different sites for the lighter and heavier neutron capture elements, might explain the abundance pattern seen in this star. In addition, we have derived a reliable abundance for the radioactive element thorium. We tentatively identify U II at 3859 Å in the spectrum of BD +17°3248, which makes this the second detection of uranium in a very metal-poor halo star. Our combined observations cover the widest range in proton number (from germanium to uranium) thus far of neutron capture elements in metal-poor Galactic halo stars. Employing the thorium and uranium abundances in comparison with each other and with several stable elements, we determine an average cosmochronological age for BD +17°3248 of 13.8 ± 4 Gyr, consistent with that found for other similar metal-poor halo stars.
Hyperspectral image classification based on spectra derivative features and locality preserving analysis

High spectral resolution and correlation hinders the application of traditional hyperspectral classification methods in the spectral domain. To address this problem, derivative information is studied in an effort to capture salient features of different land-cover classes. Two locality-preserving dimensionality-reduction methods-specifically, locality-preserving nonnegative matrix factorization and local Fisher discriminant analysis-are incorporated to preserve the local structure of neighboring samples. Since the statistical distribution of classes in hyperspectral imagery is often a complicated multimodal structure, classifiers based on a Gaussian mixture model are employed after feature extraction and dimension reduction. Finally, the classification results in the spectral as well as derivative domains are fused by a logarithmic-opinion-pool rule. Experimental results demonstrate that the proposed algorithms improve classification accuracy even in a small training-sample-size situation.