Miracle-dz/UniFAR-FTUs huggingface dataset:
A Source Code Recommender System to Support Newcomers

Newcomers in a software development project often need assistance to complete their first tasks. Then a mentor, an experienced member of the team, usually teaches the newcomers what they need to complete their tasks. But, to allocate an experienced member of a team to teach a newcomer during a long time is neither always possible nor desirable, because the mentor could be more helpful doing more important tasks. During the development the team interacts with a version control system, bug tracking and mailing lists, and all these tools record data creating the project memory. Recommender systems can use the project memory to help newcomers in some tasks answering their questions, thus in some cases the developers do not need a mentor. In this paper we present Mentor, a recommender system to help newcomers to solve change requests. Mentor uses the Prediction by Partial Matching (PPM) algorithm and some heuristics to analyze the change requests, and the version control data, and recommend potentially relevant source code that will help the developer in the change request solution. We did three experiments to compare the PPM algorithm with the Latent Semantic Indexing (LSI). Using PPM we achieved results for recall rate between 37% and 66.8%, and using LSI the results were between 20.3% and 51.6%.
The teleost dermomyotome

Recent work in teleosts has renewed interest in the dermomyotome, which was initially characterized in the late 19th century. We review the evidence for the teleost dermomyotome, comparing it to the more well‐characterized amniote dermomyotome. We discuss primary myotome morphogenesis, the relationship between the primary myotome and the dermomyotome, the differentiation of axial muscle, appendicular muscle, and dermis from the dermomyotome, and the signaling molecules that regulate myotome growth from myogenic precursors within the dermomyotome. The recognition of a dermomyotome in teleosts provides a new perspective on teleost muscle growth, as well as a fruitful approach to understanding the vertebrate dermomyotome. Developmental Dynamics 236:2432–2443, 2007. © 2007 Wiley‐Liss, Inc.
The Association of the GABRP Polymorphisms with Systemic Lupus Erythematosus

Gamma-aminobutyric acid receptor subunit pi (GABRP) is involved in inhibitory synaptic transmission in the central nervous system. This gene encodes multisubunit chloride channels and is also expressed in numerous nonneuronal tissues such as the uterus and the ovaries. This study was aimed to validate whether the polymorphisms in the GABRP gene are associated with the susceptibility to systematic lupus erythematosus (SLE). The genotype frequencies of the rs929763, rs732157, and rs3805455 of the GABRP gene in SLE patients were significantly different from those of the control group (P < 0.0001, P = 0.05 and 0.002, resp.). Additional analysis showed that the genotype of the rs929763 and rs3805455 of the GABRP gene were also significantly associated with female SLE patients (P < 0.0001, P = 0.005, resp.). Two haplotype frequencies including a major haplotype of GABRP SNPs were more significantly different between the SLE patients and the healthy controls (P = 0.038 and 4.2E − 24, resp.). These results suggest that the polymorphisms in the GABRP gene might be associated with the susceptibility to SLE and the haplotype of GABRP SNPs is useful genetic marker for SLE.
Driving-Bots with a Neuroevolved Brain: Screaming Racers

The Videogame Industry of today is now just as strong as, and generates similar revenues to the Film Industry. Computer Games are distributed throughout the world and are sold to millions of people. Of the many different types of games, one of the most popular genres is car racing. Developers of this type of game are increasingly improving their Artificial Intelligence Systems so that their virtual drivers can exhibit Human-Level behaviours, and even higher. In this paper we show how these virtual drivers can be generically evolved using Neuroevolution, so obtaining several, distinct driving-bots with an increasing level of performance. These driving-bots can then be used as virtual opponents for different racing games, saving time and money in the development of a realistic AI System. To train our driving-bots and to test their performance we have developed Screaming Racers, a simple car-racing online videogame.
A new stemmer for Nepali language

Nepali is an inflectionally rich language. The unavailability of a stemmer, that effectively eliminates inflections, makes the task of searching, text mining, information retrieval and natural language processing in Nepali challenging. Stemming helps in mapping all variants of inflected words to their respective stems. Stemmers are widely used in Text Mining, Information Retrieval and Natural Language Processing systems to improve the performance of such systems. This paper presents a new rule-based stemmer for Nepali language. We have composed 128 suffix rules, which are executed in step-by-step and iterative manner to eliminate inflections. The proposed stemmer was tested on 5000 Nepali words and the overall accuracy was around 88.78%.
Robust SVD-Based Audio Watermarking Scheme With Differential Evolution Optimization

In this paper, a robust audio watermarking scheme based on singular value decomposition (SVD) and differential evolution (DE) using dither modulation (DM) quantization algorithm is proposed. Two novel SVD-based algorithms, lifting wavelet transform (LWT)-discrete cosine transform (DCT)-SVD and discrete wavelet transform (DWT)-DCT-SVD, are developed for audio copyright protection. In our method, LWT\DWT is first applied to decompose the host signal and obtain the corresponding approximate coefficients followed by DCT to take advantage of “energy compaction” property. SVD is further performed to acquire the singular values and enhance the robustness of the scheme. The adaptive DM quantization is adopted to quantize the singular values and embed the watermark. To withstand desynchronization attacks, synchronization code is inserted using audio statistical characteristics. Furthermore, the conflicting problem of robustness and imperceptibility is effectively resolved by the DE optimization. Simulation results demonstrate that both the LWT-DCT-SVD and DWT-DCT-SVD methods not only have good imperceptibility performance, but also resist general signal processing, hybrid and desynchronization attacks. Compared with the previous DWT-DCT, support vector regression (SVR)-DWT-DCT and DWT-SVD methods, our method obtains more robustness against the selected attacks.
Sharing model with multi-level feature representations

Hierarchical classification models have been proposed to achieve high accuracy by transferring effective information across the categories. One important challenge for this paradigm is to design what can be transferred across the categories. In this paper, we propose a novel method to learn a sharing model by taking advantage of multi-level feature representations. Unlike many of the existing methods which learn the sharing model based on identical feature space, multi-level feature detectors enable our model to capture rich visual information in hierarchical category structure. Moreover, hierarchical classifier parameters associated with multi-level feature representations are learned to model the visual correlation in the hierarchy. The experimental results on Caltech-256 dataset and ImageNet subset demonstrate that our method achieves excellent performance compared with some state-of-the-art methods, and shows the advantage of multi-level information transfer.
An Experience Report of Large Scale Federations

We present an experimental study of large-scale RDF federations on top of the Bio2RDF data sources, involving 29 data sets with more than four billion RDF triples deployed in a local federation. Our federation is driven by FedX, a highly optimized federation mediator for Linked Data. We discuss design decisions, technical aspects, and experiences made in setting up and optimizing the Bio2RDF federation, and present an exhaustive experimental evaluation of the federation scenario. In addition to a controlled setting with local federation members, we study implications arising in a hybrid setting, where local federation members interact with remote federation members exhibiting higher network latency. The outcome demonstrates the feasibility of federated semantic data management in general and indicates remaining bottlenecks and research opportunities that shall serve as a guideline for future work in the area of federated semantic data processing.
Development of grid-based tiled display wall for networked visualization

Tiled display wall has been emerged as a display platform for high-resolution and large-scale dataset visualization. Current development also incorporates it into general cluster computing, which usually involves large scale parallel computing. The emergence of the grid computing, which take advantage of the large scale distributed and parallel facilities and integrate them into a uniform accessible resource, also provide a great opportunity for tiled display wall used more extensively, in particular for nowadays highly demanded networked visualization. In this work we developed a grid-based tiled display wall. It allows virtual reality as well as data visualization across different geographically remote facilities. The system construction details will be introduced and various practical applications given to demonstrated its usefulness.
SENSITIVITY APPROACH TO OPTIMAL CONTROL FOR AFFINE NONLINEAR DISCRETE‐TIME SYSTEMS

This paper deals with the optimal control problem for a class of affine nonlinear discrete‐time systems. By introducing a sensitivity parameter and expanding the system variables into a Maclaurin series around it, we transform the original optimal control problem for affine nonlinear discrete‐time systems into the optimal control problem for a sequence of linear discrete‐time systems. The optimal control law consists of an accurate linear term and a nonlinear compensating term, which is an infinite sequence of adjoint vectors. In the present approach, iteration is required only for the nonlinear compensation series. By intercepting a finite sum of the series, we obtain a suboptimal control law that reduces the complexity of the calculations. A numerical simulation shows that the algorithm can be easily implemented and has a fast convergence rate.
Use of a Dense Single Nucleotide Polymorphism Map for In Silico Mapping in the Mouse

Rapid expansion of available data, both phenotypic and genotypic, for multiple strains of mice has enabled the development of new methods to interrogate the mouse genome for functional genetic perturbations. In silico mapping provides an expedient way to associate the natural diversity of phenotypic traits with ancestrally inherited polymorphisms for the purpose of dissecting genetic traits. In mouse, the current single nucleotide polymorphism (SNP) data have lacked the density across the genome and coverage of enough strains to properly achieve this goal. To remedy this, 470,407 allele calls were produced for 10,990 evenly spaced SNP loci across 48 inbred mouse strains. Use of the SNP set with statistical models that considered unique patterns within blocks of three SNPs as an inferred haplotype could successfully map known single gene traits and a cloned quantitative trait gene. Application of this method to high-density lipoprotein and gallstone phenotypes reproduced previously characterized quantitative trait loci (QTL). The inferred haplotype data also facilitates the refinement of QTL regions such that candidate genes can be more easily identified and characterized as shown for adenylate cyclase 7.
Using mass video notification methods to assist deaf people

Even though Deaf people in South Africa use texting via cell phones to communicate with hearing people they seldom use it amongst themselves. It is assumed that video messaging will be more accessible for the Deaf as their level of literacy may prevent them from making effective use of information that is disseminated via mass texting. The principal objective of the research was thus to explore a cost effective and efficient mass multimedia messaging system. The intention was to adapt a successful text-based mass notification system, developed by a local non-governmental organization, to accommodate efficient and affordable video mass messaging for Deaf people. The questions that underpin this research are: How should we compare and evaluate various video streaming messaging methods to find the most effective streaming method to deliver video messages? What transport vehicles should we consider: multimedia messaging service, the web, electronic mail or a cell phone resident push/pull application? What is the cost to the end-user and service provider and how can we make such a service more affordable? How does the video quality in terms of sign language vary between each transport vehicle? A mixed research methodology approach was followed to help answer the research questions. The preliminary results indicate that most Deaf people prefer to use the short message service prototype with a web-link to the video rather than the multimedia messaging service prototype with the video attached. Although Deaf people prefer to use the video short message service prototype they are still very concerned about the cost of using the system. They also are concerned about the quality of the sign language video.
The presence of cortical neurons in striatal-cortical co-cultures alters the effects of dopamine and BDNF on medium spiny neuron dendritic development

Medium spiny neurons (MSNs) are the major striatal neuron and receive synaptic input from both glutamatergic and dopaminergic afferents. These synapses are made on MSN dendritic spines, which undergo density and morphology changes in association with numerous disease and experience-dependent states. Despite wide interest in the structure and function of mature MSNs, relatively little is known about MSN development. Furthermore, most in vitro studies of MSN development have been done in simple striatal cultures that lack any type of non-autologous synaptic input, leaving open the question of how MSN development is affected by a complex environment that includes other types of neurons, glia, and accompanying secreted and cell-associated cues. Here we characterize the development of MSNs in striatal-cortical co-culture, including quantitative morphological analysis of dendritic arborization and spine development, describing progressive changes in density and morphology of developing spines. Overall, MSN growth is much more robust in the striatal-cortical co-culture compared to striatal mono-culture. Inclusion of dopamine (DA) in the co-culture further enhances MSN dendritic arborization and spine density, but the effects of DA on dendritic branching are only significant at later times in development. In contrast, exogenous Brain Derived Neurotrophic Factor (BDNF) has only a minimal effect on MSN development in the co-culture, but significantly enhances MSN dendritic arborization in striatal mono-culture. Importantly, inhibition of NMDA receptors in the co-culture significantly enhances the effect of exogenous BDNF, suggesting that the efficacy of BDNF depends on the cellular environment. Combined, these studies identify specific periods of MSN development that may be particularly sensitive to perturbation by external factors and demonstrate the importance of studying MSN development in a complex signaling environment.
A compact model for speaker-adaptive training

We formulate a novel approach to estimating the parameters of continuous density HMMs for speaker-independent (SI) continuous speech recognition. It is motivated by the fact that variability in SI acoustic models is attributed to both phonetic variation and variation among the speakers of the training population, that is independent of the information content of the speech signal. These two variation sources are decoupled and the proposed method jointly annihilates the inter-speaker variation and estimates the HMM parameters of the SI acoustic models. We compare the proposed training algorithm to the common SI training paradigm within the context of supervised adaptation. We show that the proposed acoustic models are more efficiently adapted to the test speakers, thus achieving significant overall word error rate reductions of 19% and 25% for 20K and 5K vocabulary tasks respectively.
RMS OPERATIONS SUPPORT: FROM THE SPACE SHUTTLE TO THE SPACE STATION

Like many other technologies, space robotics has evolved significantly over the past twenty years. Canada in general, and MD Robotics in particular, have contributed a great deal to these advances. This contribution is highlighted by the development and operations support of MD Robotics’ Canadarm and the second-generation space manipulator, Canadarm 2 . In this paper, we will highlight the experience and expertise gained while supporting the operation of Canadarm and illustrate how it has influenced both the design and planned operation of Canadarm 2 . It is shown that the lessons learned from this experience are sufficiently general that they can be applied to future space manipulators such as the Special Purpose Dexterous Manipulator, as well as the Japanese and the European Remote Manipulators.
KMS components for collaborative software maintenance – a pilot study

Software maintenance (SM) environment is highly complex, knowledge-driven and collaborative environment. Therefore, a Knowledge Management System (KMS) is critical to ensure various parties have the necessary information to perform SM activities. In an effort to model the requirements for sharing and sustaining knowledge in SM environment, we review literatures on Knowledge Management (KM), KMS and SM frameworks to identify the knowledge components, tools and technologies. An initial model of KMS components in collaborative SM is proposed, to be verified vis-à-vis a questionnaire survey. Before the questionnaires are sent out, a pilot study was conducted to identify misfit questionnaire items so that they could be revised before being sent out. Rasch Unified Measurement Method (RUMM) is used to analyze the pilot data. Item reliability is found to be poor and a few respondents and items are identified as misfits with distorted measurements. As a result, some problematic questions are revised and some predictably easy questions are excluded from the questionnaire.
Structure and Properties of Trade Networks (16)

We analyze the structure of trade networks, in which nodes represent agents and edges represent the resource exchanges between them. We study these networks by way of two realworld networks: the international trade network (ITN), which contains pairwise trade data between countries over a 50-year period, and the Commodity Flow Survey, which contains pairwise trade data between US states over a 5 year period. We describe our insights into the structure of these networks and the extent to which aspects of these structures can be modeled and predicted. We nd that a country’s GDP can be well modeled by its trade behavior in the ITN. We also beat a canonical model of trade ow prediction and observe interesting relationships between resource trade and population as well as land area in the US.
Simulation and Analysis of Passive and Active Suspension System Using Quarter Car Model for Different Road Profile

The objectives of this study are to obtain a mathematical model for the passive and active suspensions systems for quarter car model. Current automobile suspension systems using passive components only by utilizing spring and damping coefficient with fixed rates. Vehicle suspensions systems typically rated by its ability to provide good road handling and improve passenger comfort. Passive suspensions only offer compromise between these two conflicting criteria. Active suspension poses the ability to reduce the traditional design as a compromise between handling and comfort by directly controlling the suspensions force actuators. In this study, the Linear Quadratic Control (LQR) technique implemented to the active suspensions system for a quarter car model. Comparison between passive and active suspensions system are performed by using different types of road profiles. The performance of the controller is compared with the LQR controller and the passive suspension system.
A Deep Learning Approach to Persian Plagiarism Detection

Plagiarism detection is defined as automatic identification of reused text materials. General availability of the internet and easy access to textual information enhances the need for automated plagiarism detection. In this regard, different algorithms have been proposed to perform the task of plagiarism detection in text documents. Due to drawbacks and inefficiency of traditional methods and lack of proper algorithms for Persian plagiarism detection, in this paper, we propose a deep learning based method to detect plagiarism. In the proposed method, words are represented as multi-dimensional vectors, and simple aggregation methods are used to combine the word vectors for sentence representation. By comparing representations of source and suspicious sentences, pair sentences with the highest similarity are considered as the candidates for plagiarism. The decision on being plagiarism is performed using a two level evaluation method. Our method has been used in PAN2016 Persian plagiarism detection contest and results in %90.6 plagdet, %85.8 recall, and % 95.9 precision on the provided data sets.
A prospective randomized study comparing electrochemically deposited hydroxyapatite and plasma-sprayed hydroxyapatite on titanium stems

Background and purpose Plasma-sprayed hydroxyapatite (HA) is a successful coating for fixation of uncemented femoral stems. There may be alternative coatings with advantages in bone remodeling and transport of bone-active substances. We investigated whether an electrochemically deposited hydroxyapatite, Bonemaster (BM), might be a safe alternative in total hip arthroplasty. Our hypothesis was that the new coating would not be inferior to the conventional one. Patients and methods 50 patients (55 hips) were included. The stem was tapered and porous-coated proximally. On top of the porous coating was either HA or BM. Patients were evaluated postoperatively and after 3, 6, 12, and 24 months to measure fixation by radiostereometric analysis (RSA), bone mineral density by dual-energy X-ray absorptiometry (DXA), and conventional radiography. Clinical evaluation was performed with Harris hip score and Oxford hip score, both preoperatively and after 2 years. Results After 2 years, the stems had subsided 0.25 (HA) and 0.28 (BM) mm and there were no statistically significant differences between the groups in any direction, regarding both migration and rotation. The BM group retained significantly more bone than the HA group in Gruen zone 1 during the first 2 years. The Harris and Oxford hip scores were similar in both groups. Interpretation Electrochemically deposited hydroxyapatite on an uncemented stem does not appear to be inferior to plasma-sprayed HA regarding clinical and radiological results, bone remodeling, and micromotion after 2 years follow-up.