Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving Part-of-Speech Tagging Accuracy for Croatian by Morphological Analysis

This paper investigates several methods of combining a second order hidden Markov model part-of-speech (morphosyntactic) tagger and a high-coverage inflectional lexicon for Croatian. Our primary motivation was to improve tagging accuracy of Croatian texts by using our newly-developed tagger CroTag, currently in beta-version. We also wanted to compare its tagging results – both standalone and utilizing the morphological lexicon – to the ones previously described in (Agic and Tadic 2006), provided by the TnT statistical tagger which we used as a reference point having in mind that both implement the same tagging procedure. At the beginning we explain the basic idea behind the experiment, its motivation and importance from the perspective of processing the Croatian language. We also describe tools – namely tagger and lexicon – and language resources used in the experiment, including their implementation method and input/output format details that were of importance. With the basics presented, we describe in theory four possible methods of combining these resources and tools with respect to their operating paradigm, input and production capabilities and then put these ideas to test using the F-measure evaluation framework. Results are then discussed in detail and conclusions and future work plans are presented.
Using an Educational Computer Game as a Motivational Tool for Supplemental Instruction Delivery for Novice Programmers in Learning Computer Programming

This study uses an educational computer game as a supplemental instruction delivery method and investigates its effect on students’ motivation toward computer programming, which is measured by Intrinsic Motivation Inventory. Twenty undergraduate students who enrolled in a basic computer programming course for non computer science major students volunteered to participate in this research study and were assigned to use one of two different supplemental instruction delivery methods for a three-week period. One group used an electronic quiz program and the other group used an educational computer game. Both methods used the same quiz bank and all quizzes were selected randomly. More quizzes were added every week after students learned more computer programming knowledge. After the treatment, students’ intrinsic motivation was compared for the effect of using different delivery methods. Although the results did not show a significant difference statistically, the participants in the computer game group demonstrated higher intrinsic motivation, and the mean difference scores were approaching statistical significance as compared to subjects in the control group. We suggest that the study should be administrated using more participants and the game should be polished to make it more appealing to undergraduate students.
An Approach for Enhance the Software Quality Based on Quality Model

The software development process enforces major effects on the quality of software at every development stage; therefore, a mutual goal of each software development phase concerns how to increase software quality. Software quality estimate thus aims to evaluate software quality level periodically and to specify software quality problems early. In order to obtain high-quality software products, the characteristics and costing of quality during the software development process is of crucial importance. The objective of this paper is to propose a quality model for integrating some quality attributes in software development, Model based which is based on ISO/IEC 9126 Quality Model, is used to generate a new approach for software Quality. Analytic Hierarchy Process (AHP) is used to evaluate an improved hierarchical quality model for software development.
Radio spectral study of the cluster of galaxies Abell 2255

Context. The study of the nonthermal components associated with the intra cluster medium (ICM) in galaxy clusters is important in understanding the history and evolution of clusters. Aims. Spectral index studies of halos, relics, and radio galaxies provide useful information on their origin and connection with merger processes. Moreover, they reveal the energy spectrum of the relativistic particles and the magnetic field distribution in galaxy clusters. Methods. We present WSRT multi-wavelength observations of the galaxy cluster Abell 2255 at 25 cm, 85 cm, and 2 m. The spectral index images allowed us to study the integrated spectrum of halo and relic and to investigate the physical properties of the Beaver head-tail radio galaxy belonging to the cluster. Results. In the radio halo, the spectral index is steeper at the center and flatter at the locations of the radio filaments, clearly detected at 25 cm. In the relics, the spectral index flattens, moving away from the cluster center. For the Beaver radio galaxy, the spectrum severely steepens from the head towards the end of the tail, because of the energy losses suffered by the relativistic particles. In the 2 m map, which is the first high-sensitivity image presented in the literature at such a long wavelength, a new Mpc-size emission region is detected between the known radio halo and the NW relic. Not detecting this feature in the more sensitive 85 cm observations implies that it must have a very steep spectrum (α ≤− 2.6). Conclusions. The observational properties of the radio halo suggest that either we are looking at a superposition of different structures (filaments in the foreground plus real halo in the background) seen in projection across the cluster center or that the halo is intrinsically peculiar. The newly detected extended region to the NW of the halo could be considered as an asymmetric extension of the halo itself. However, since radio halos are known in the literature as structures showing a regular morphology, the new feature could represent the first example of steep Mpc-size diffuse structures (MDS), detected around clusters at very low frequencies. The spectrum of the initial part of the tail of the Beaver, detected at the three wavelengths, is well-fitted by a single injection model.
Comparing the effectiveness of fine-grain memory caching against page migration/replication in reducing traffic in DSM clusters

In this paper, we compare and contrast two techniques to improve capacity/conflict miss traffic in CC-NUMA DSM clusters. Page migration/replication optimizes read-write accesses to a page used by a single processor by migrating the page to that processor and replicates all read-shared pages in the sharers' local memories. R-NUMA optimizes read-write accesses to any page by allowing a processor to cache that page in its main memory. Page migration/replication requires less hardware complexity as compared to R-NUMA, but has limited applicability and incurs much higher overheads even with tuned hardware/software support. In this paper, we compare and contrast page migration/replication and R-NUMA on simulated clusters of symmetric multiprocessors executing shared-memory applications. Our results show that: (1) both page migration/replication and R-NUMA significantly improve the system performance over “first-touch” migration in many applications, (2) page migration/replication has limited opportunity and can not eliminate all the capacity/conflict misses even with fast hardware support and unlimited amount of memory, (3) R-NUMA always performs best given a page cache large enough to fit an application's primary working set and subsumes page migration/replication, (4) R-NUMA benefits more from hardware support to accelerate page operations than page migration/replication, and (5) integrating page migration/replication into R-NUMA to help reduce the hardware cost requires sophisticated mechanisms and policies to select candidates for page migration/replication.
A Scouting Strategy for Real-Time Strategy Games

Real-time strategy (RTS) is a sub-genre of strategy video games. RTS games are more realistic with dynamic and time-constraint game playing, by abandoning the turn-based rule of its ancestors. Playing with and against computer-controlled players is a pervasive phenomenon in RTS games, due to the convenience and the preference of groups of players. Hence, better game-playing agents are able to enhance game-playing experience by acting as smart opponents or collaborators. One-way of improving game-playing agents' performance, in terms of their economic-expansion and tactical battlefield-arrangement aspects, is to understand the game environment. Traditional commercial RTS game-playing agents address this issue by directly accessing game maps and extracting strategic features. Since human players are unable to access the same information, this is a form of "cheating AI", which has been known to negatively affect player experiences. Thus, we develop a scouting mechanism for RTS game-playing agents, in order to enable game units to explore game environments automatically in a realistic fashion. Our research is grounded in prior robotic exploration work by which we present a hierarchical multi-criterion decision-making (MCDM) strategy to address the incomplete information problem in RTS settings.
Online quantum mixture regression for trajectory learning by demonstration

In this work, we present the online Quantum Mixture Model (oQMM), which combines the merits of quantum mechanics and stochastic optimization. More specifically it allows for quantum effects on the mixture states, which in turn become a superposition of conventional mixture states. We propose an efficient stochastic online learning algorithm based on the online Expectation Maximization (EM), as well as a generation and decay scheme for model components. Our method is suitable for complex robotic applications, where data is abundant or where we wish to iteratively refine our model and conduct predictions during the course of learning. With a synthetic example, we show that the algorithm can achieve higher numerical stability. We also empirically demonstrate the efficacy of our method in well-known regression benchmark datasets. Under a trajectory Learning by Demonstration setting we employ a multi-shot learning application in joint angle space, where we observe higher quality of learning and reproduction. We compare against popular and well-established methods, widely adopted across the robotics community.
A wake-up receiver with ad-hoc antenna co-design for wearable applications

Body Area Networks (BAN) have received significant attention in recent years and have found a wide range of applications, including wearable devices for fitness and health tracking, and mobile communications. Battery lifetime continues to be the main bottleneck in these small form factor devices, thus low power design and advanced power management techniques are required to sustain the increasing demands on power. As radio transceivers are typically the most power hungry subsystem in a wearable sensors device, optimizations to reduce the communication power consumption, such as using adaptive power management coupled with ultra-low power receivers have been widely investigated. In this work, we focus on the design of a novel wearable wake-up radio consuming only few nW during listening mode, significantly reducing the overall power consumption of communication, which enables aggressive power management techniques. We propose the co-design of an ad-hoc wearable antenna which directly matches the impedance of the analog frontend in order to improve the performance in terms of sensitivity and directivity in BAN context. Our novel wake up radio consumes only 400nW while providing short-range communication, and features on board addressing capability to further reduce the power due to false wake ups. Using in-field measurements, we evaluate the benefits of the ad-hoc antenna compared to state-of-the-art off-the-shelf solutions in terms of range, sensitivity and addressing capability. We quantify energy savings and estimate the lifetime prolongation of the sensor node by integrating our wake-up radio in a wearable system.
A semantic model for cross-modal and multi-modal retrieval

In this paper, a semantic model for cross-modal and multi-modal retrieval is studied. We assume that the semantic correlation of multimedia data from different modalities can be depicted in a probabilistic generation framework. Media data from different modalities can be generated by the same semantic concepts, and the generation process of each media data is conditional independent under the semantic concepts. The semantic generation model (SGM) for cross-modal and multi-modal analysis is proposed based on this assumption. We study two types of methods: direct method Gaussian distribution and indirect method random forest, to estimate the semantic conditional distribution of SGM. Then methods for cross-modal and multi-modal retrieval are derived from SGM. Experimental results show that SGM based methods for cross-modal retrieval improve the accuracy over the state-of-the-art cross-modal method, but don't increase the time consuming, and the SGM multimodal retrieval methods also outperform traditional methods in image retrieval. Moreover, indirect SGM based method outperforms direct SGM method in the two types of retrieval, which proves that indirect SGM can better describe the semantic distribution.
Segmenting Target Audiences: Automatic Author Profiling using Tweets: Notebook for PAN at CLEF 2015

This paper describes a methodology proposed for author profiling us- ing natural language processing and machine learning techniques. We used lexi- cal information in the learning process. For those languages without lexicons, we automatically translated them, in order to be able to use this information. Finally, we will discuss how we applied this methodology to the 3rd Author Profiling Task at PAN 2015 and we will present the results we obtained.
Association Rules for Auditing Systems

In this paper, we apply the association rules in data mining to an auditing system in order to mine the characteristics of audit data. The approach as a new mining technology can be used by an auditor to better interpret vast amounts of audit data. Association rules based algorithm is an outstanding methodology with which people can discover the hidden correlation relationships among dataset. It is applicable to mining of huge data which were difficult to start with. Because audit data usually contain a large number of rare data with different distribution characteristics, we hereby propose a multiple supports-based framework for digging data pattern from the rare data. We use all-confidence method to deal with crossing platform supports. In this paper we propose the MSAC_Apriori algorithm with generalized association rules, which helps establish the relationships during quantitative association analysis. Experimental results on practical datasets show that the proposed approach improves the performance by decreasing the number of frequent items without missing rare items.
Trends in the Development of Machinery and Associated Technology ” TMT 2009 , Hammamet , Tunisia , 16-21 October 2009 PROJECT APPROACH IN DESIGN OF COMPLEX ORGANIZATIONAL STRUCTURES

In conditions of globalization, expressed, the survival of companies is continuously adaptation to market conditions. Also, any organization cannot allow itself to exist like isolated island. The growing importance of project management can be traced through topics such as roles and responsibility, organizational structures, delegation of authority and decision making, and especially corporate profitability. Twenty years ago, companies had the choice whether or not to accept the project management. But today, the survival of the company may very well rest upon how well and how quickly project management is implemented. Manufacturing systems are becoming increasingly complex because growing requirements both for productivity and flexibility. This complexity is more evident when dealing with complex systems (for example clusters) where the usual control requirements are met by centralized systems that are too rigid and hard to manage, maintain and update. The project organization should result from the project strategy, it should be constructed in such a way that the strategy can be implemented within the environment of the project.
Dysembryoplastic neuroepithelial tumor: A rare case report

Dysembryoplastic neuroepithelial tumor and adolescents with intractable epilepsy. This tumor demonstrates typical histological features such as glial nodules and the so called imaging features but needs a multidisciplinary contribution from the clinical and diagnostic department involving the clinician, radiologist as well as the pathologist to reach a definite an conclusive diagnosis. However histopathology is the gold standard for the final diagnosis.
Discretization of Continuous Features by Resampling

A coding method for a two-level facsimile signal by the use of the two-dimensional coding principle, in which when successively coding addresses of a facsimile signal representative of the positions of information change picture elements, each having a binary level different from that of an immediately preceding picutre element, the above-mentioned addresses on each coding scanning line are classified into three modes that are determined by the states of information change picture elements on the coding scanning line and on a reference scanning line immediately preceding the coding scanning line. The above two-dimensinal coding principle and a one-dimensional coding principle may be adaptively adopted to shorten the transmission time and to lessen the influence of a transmission error.
Removing Timed Delays in Stochastic Automata

We present a method to remove timed delays (transitions corresponding to timed internal actions) from a subset of stochastic automata. After removing the internal actions, the steady state probability of a subset of the states of the automata is preserved. The stochastic automata considered in this paper have the property of being Markov regenerative processes
Singing and spirituality in a South African male voice group

Since the mid 1970s, a group of twelve business and professional members of a male singing group have continued singing together in Pretoria, South Africa. These singers were interviewed as part of a project on Spirituality and Well-being: Music in the community. From the interview data, two overarching themes emerged, membership benefits and spiritual connections; these are discussed in this research project. Members‟ views of benefits related mainly to fulfilment of personal, including musical, needs, although all were gratified that their singing provided enjoyment to community audiences and benefits to disadvantaged communities, mainly from ticket sale proceeds. Most saw an association between singing and the spiritual, but only a minority identified a religious connotation, the remainder relating to non-religious factors such as the „human spirit‟. A deep sense of commitment and a love of music impacts positively on social engagement, benefiting and enhancing quality of life for the group members.
Generating Rhythms with Genetic Algorithms

My system uses an interactive genetic algorithm to learn a user's criteria for the task of generating musical rhythms. Interactive genetic algorithms (Smith 91) are well suited to solving this problem because they allow for a user to simply execute fitness functions (that is, to choose which rhythms or features of rhythms he likes), without necessarily understanding the details or parameters of these functions. As the system learns (develops an increasingly accurate model of the function which represents the user's criteria), the quality of the rhythms it produces improves to suit the user's taste. This approach is largely motivated by Richard Dawkins, who succinctly summarizes the attraction of IGAs for artistic endeavors in stating: "Effective searching procedures become, when the search space is sufficiently large, indistinguishable from true creativity" (Dawkins 86).
Growing emotions: Using affect to help children understand a plant's needs

This study proposes a homeostasis-based affective system with emotion and mood as a way to communicate a plant's health state and environmental needs to preschool and primary school children. A system is proposed that expresses mood and emotion to express the plant's health state and its affective reaction to user-induced environmental changes respectively. A long-term goal is to enhance empathic reasoning in children and respect for plants and life in general, using affect as a communicative interface (even though the underlying system is not emotive per se). A fundamental issue addressed in this work is to what extend it is useful to add affective communication to a system that is otherwise non-affective (plants in our case) in order to better understand that system's state. A computer simulation of the affective plant was tested (n=7). Our results suggest that children can identify the simulated plant's needs and state based on graphically expressed affect, and can act to enhance the homeostasis of the plant.
An open source eye-gaze interface: expanding the adoption of eye-gaze in everyday applications

There is no standard software interface in the eye-tracking industry, making it difficult for developers to integrate eye-gaze into their applications. The combination of high cost eye-trackers and lack of applications has resulted in a slow adoption of the technology. To expand the adoption of eye-gaze in everyday applications, we present an eye-gaze specific application programming interface that is platform and language neutral, based on open standards, easily used and extended and free of cost.
Altered fracture repair in the absence of MMP9

The regeneration of adult skeletal tissues requires the timely recruitment of skeletal progenitor cells to an injury site, the differentiation of these cells into bone or cartilage, and the re-establishment of a vascular network to maintain cell viability. Disturbances in any of these cellular events can have a detrimental effect on the process of skeletal repair. Although fracture repair has been compared with fetal skeletal development, the extent to which the reparative process actually recapitulates the fetal program remains uncertain. Here, we provide the first genetic evidence that matrix metalloproteinase 9 (MMP9) regulates crucial events during adult fracture repair. We demonstrate that MMP9 mediates vascular invasion of the hypertrophic cartilage callus, and that Mmp9-/- mice have non-unions and delayed unions of their fractures caused by persistent cartilage at the injury site. This MMP9- dependent delay in skeletal healing is not due to a lack of vascular endothelial growth factor (VEGF) or VEGF receptor expression, but may instead be due to the lack of VEGF bioavailability in the mutant because recombinant VEGF can rescue Mmp9-/- non-unions. We also found that Mmp9-/- mice generate a large cartilage callus even when fractured bones are stabilized, which implicates MMP9 in the regulation of chondrogenic and osteogenic cell differentiation during early stages of repair. In conclusion, the resemblance between Mmp9-/- fetal skeletal defects and those that emerge during Mmp9-/- adult repair offer the strongest evidence to date that similar mechanisms are employed to achieve bone formation, regardless of age.