Miracle-dz/UniFAR-FTUs huggingface dataset:
Closing the Gap Between Learning and Instruction

In this paper, I explore the mismatch between the pedagogical intentions and plans of the educational institution, curriculum, teacher, and textbook, and the outcomes as realized through the skills and knowledge that learners take away from instructional encounters. Although there will never be a one-to-one relationship between teaching and learning, there are ways in which teachers and learners and teaching and learning can be brought closer together. In this article, I look at ways of closing the gap in relation to experiential content, learning process, and language content. The theme holding these three disparate domains together is that of learner centredness, and it is this concept which I take as my point of departure.
Advanced integration of multimedia assistive technologies: A prospective outlook

In the recent years several studies on population ageing in the most advanced countries argued that the share of people older than 65 years is steadily increasing. In order to tackle this phenomena, a significant effort has been devoted to the development of advanced technologies for supervising the domestic environments and their inhabitants to provide them assistance in their own home. In this context, the present paper aims to delineate a novel, highly-integrated system for advanced analysis of human behaviours. It is based on the fusion of the audio and vision frameworks, developed at the Multimedia Assistive Technology Laboratory (MATeLab) of the Università Politecnica delle Marche, in order to operate in the ambient assisted living context exploiting audio-visual domain features. The existing video framework exploits vertical RGB-D sensors for people tracking, interaction analysis and users activities detection in domestic scenarios. The depth information has been used to remove the affect of the appearance variation and to evaluate users activities inside the home and in front of the fixtures. In addition, group interactions are monitored and analysed. On the other side, the audio framework recognises voice commands by continuously monitoring the acoustic home environment. In addition, a hands-free communication to a relative or to a healthcare centre is automatically triggered when a distress call is detected. Echo and interference cancellation algorithms guarantee the high-quality communication and reliable speech recognition, respectively. The system we intend to delineate, thus, exploits multi-domain information, gathered from audio and video frameworks each, and stores them in a remote cloud for instant processing and analysis of the scene. Related actions are consequently performed.
Role of Aerosol Absorption in Satellite Sensor Calibration

The importance of aerosol absorption in satellite sensor vicarious calibration and/or satellite measurement of physical parameters is reiterated in a sensitivity study performed using a radiative transfer model, with field-measured data as input. Broadband shortwave surface fluxes need to be measured according to new protocols, described herein, to infer atmospheric absorption to improve calibration accuracy to within the plusmn2% stated goal of next-generation sensors such as Visible/Infrared Imager/Radiometer Suite.
The hacker's challenge: active access to information, visceral democracy and discursive practice

This paper examines the relationship between hacking and democracy. It suggests that hacking, as a culturally formed and informed practice, is involved in struggles over the signification and significance of democracy. In particular, hacking is associated with an ethics and practice of active access to information. However, after tracing historical and cultural shifts in practices, discourses and representations of hacking, the paper also suggests that hacking is becoming increasingly dissociated from its founding cultures and their ethics, as computer technology and technological skill sets become more widely available, networked and encoded. As such, hackers' overall relationship to the active access of information, and therefore to democracy, remains ambivalent and uncertain.
Using Language Corpora in Initial Teacher Education: Pedagogic Issues and Practical Applications

The vast increase in the number of corpus-based materials, such as dictionaries and grammars, attests to the importance of corpus linguistics to English language description. Developments are also evident in the use of corpora in the classroom in data-driven learning (Johns, 1991). These rapid developments in the use of language-related technology have not been matched by updated practices in teacher education. This article makes a case for the inclusion of corpus linguistics in initial language teacher education to enhance teachers' research skills and language awareness. The authors offer examples of corpus-based tasks for increasing students' understanding of word classes, register-related grammatical choices, and socioculturally conditioned grammatical choices. Practical considerations for the integration of language corpora in a teacher education program are outlined.
Whole-Group Instruction Practices and Children's Attention: A Preliminary Report

This study developed a typology of recommended teacher practices related to whole-group instruction in preschool classrooms and examined the relationship between teachers' use of the practices and children's attentiveness. Thirty-nine classrooms in 31 schools (15 public and 16 private) were observed during regularly scheduled whole-group instruction sessions. Bivariate correlations indicated a positive relationship between children's attentiveness and number of practices that teachers used, but not between attentiveness and length of activity. Regression analyses suggested a set of eight specific practices that are related, with length of activity, to children's attentiveness.
Action Monitoring Cortical Activity Coupled to Submovements

Visual Abstract Numerous studies have examined neural correlates of the human brain’s action-monitoring system during experimentally segmented tasks. However, it remains unknown how such a system operates during continuous motor output when no experimental time marker is available (such as button presses or stimulus onset). We set out to investigate the electrophysiological correlates of action monitoring when hand position has to be repeatedly monitored and corrected. For this, we recorded high-density electroencephalography (EEG) during a visuomotor tracking task during which participants had to follow a target with the mouse cursor along a visible trajectory. By decomposing hand kinematics into naturally occurring periodic submovements, we found an event-related potential (ERP) time-locked to these submovements and localized in a sensorimotor cortical network comprising the supplementary motor area (SMA) and the precentral gyrus. Critically, the amplitude of the ERP correlated with the deviation of the cursor, 110 ms before the submovement. Control analyses showed that this correlation was truly due to the cursor deviation and not to differences in submovement kinematics or to the visual content of the task. The ERP closely resembled those found in response to mismatch events in typical cognitive neuroscience experiments. Our results demonstrate the existence of a cortical process in the SMA, evaluating hand position in synchrony with submovements. These findings suggest a functional role of submovements in a sensorimotor loop of periodic monitoring and correction and generalize previous results from the field of action monitoring to cases where action has to be repeatedly monitored.
Reverse engineering of double compressed images in the presence of contrast enhancement

A comparison between two forensic techniques for the reverse engineering of a chain composed by a double JPEG compression interleaved by a linear contrast enhancement is presented here. The first approach is based on the well known peak-to-valley behavior of the histogram of double-quantized DCT coefficients, while the second approach is based on the distribution of the first digit of DCT coefficients. These methods have been extended to the study of the considered processing chain, for both the chain detection and the estimation of its parameters. More specifically, the proposed approaches provide an estimation of the quality factor of the previous JPEG compression and the amount of linear contrast enhancement.
A Comprehensive Look at LH 72 in the Context of the Supergiant Shell LMC 4

Stellar spectroscopy, UBV photometry, Hα imaging, and analysis of data from the Australia Telescope Compact Array H I survey of the LMC are combined in a study of the LMC OB association LH 72 and its surroundings. LH 72 lies on the rim of a previously identified H I shell, SGS 14, and in the interior of LMC 4, one of the LMC's largest known supergiant shells. Our analysis of the H I data finds that SGS 14 is expanding with a velocity of vexp ∼ 15 km s-1, giving it an expansion age of ∼15 Myr. Through the stellar spectroscopy and photometry, we find similar ages for the oldest stars of LH 72, ∼15–30 Myr. We confirm that LH 72 contains an age spread of ∼15–30 Myr, similar to the range in ages of stars derived for the entire surrounding supergiant shell. Combining analysis of the O and B stars with Hα imaging of the H II region DEM 228, we find that DEM 228 accounts for only 60% of the available ionizing Lyman continuum photons. Comparing the distribution of ionized gas with that of the H I, we find that DEM 228 and LH 72 are offset by ∼1′–2′ from the peak 21 cm emission toward the interior of SGS 14. Taken together, these results imply that SGS 14 has cleared its interior of gas and triggered the formation of LH 72. On the basis of our results, we suggest that LMC 4 was not formed as a unit but by overlapping shells, such as SGS 14, and that LH 72 will evolve to produce a stellar arc similar to others seen within LMC 4.
Using an induced relational decision tree for rule injection in a learning classifier system

Transfer learning, using systems with rich and general representations, to improve adaptive rule based systems designed to efficiently react in changing environments is the idea behind the problem studied in this paper. In this framework, the aim of this research is studying the benefits of using relational learning in combination with an evolutionary propositional learning system as XCS. The proposed method starts by learning a first order relational decission tree using a set of simplified instances of a problem. The learned relational model is then used to help a learning classifier system to deal with a more complex instance of the task. The researched strategy is based on injecting rules derived from the relational model in the discovering subsystem of the XCS. Results show that this method can be used to automatically adapt the behaviour of a learning rule based system when the environment increases its complexity.
Semi-automatic wavelet soft-thresholding applied to digital image error level analysis

8 In this paper a method for detection of image forgery in lossy compressed digital images known as error level analysis (ELA) is presented and it’s noisy components are filtered with automatic wavelet soft-thresholding. With ELA, a lossy compressed image is recompressed at a known error rate and the absolute differences between these images, known as error levels, are computed. This method might be weakened if the image noise generated by the compression scheme is too intense, creating the necessity of noise filtering. Wavelet thresholding is a proven denoising technique which is capable of removing an image’s noise avoiding altering other components, like high frequencies regions, by thresholding the wavelet transform coefficients, thus not causing blurring. Despite its effectiveness, the choice of the threshold is a known issue. However there are some approaches to select it automatically. In this paper, a lowpass filter is implemented through wavelet thresholding, attenuating error level noises. An efficient method to automatically determine the threshold level is used, showing good results in threshold selection for the presented problem. Standard test images have been doctored to simulate image tampering, error levels for these images are computed and wavelet thresholding is performed to attenuate noise. Results are presented, confirming the method’s efficiency at noise filtering while preserving necessary error levels. 9
Security Sector Reform in Liberia: An Uneven Partnership without Local Ownership

Abstract The security situation in Liberia is currently quite good, and at a glance the peacebuilding process seems to be moving ahead. However, the root causes of the conflict have not been adequately addressed, but have in fact become more interlinked in the aftermath of the civil war. Instead of addressing local perceptions of insecurity the international community made plans for Liberia without considering the context in which reforms were to be implemented. The peace in post-conflict Liberia is therefore still fragile and the international presence is regarded as what secures the peace. Still, the UN is supposed to start its full withdrawal in 2010—indicating that the international community will leave the country without addressing the root causes of conflict.
Migration histories and occupational achievement

We have investigated the impact of men's and women's migration histories on their occupational achievement. Compared with previous work, our operationalisation of migration histories is much more detailed; we include not only the distinction between onward and return migration, but also the crucial aspects of the destination and short-term versus long-term effects of migration. Using retrospective survey data for the Netherlands and a least-squares regression model of socio-economic status, we explain the socio-economic status of men and women in a given year from the migration history up to that year, controlling for other factors known to influence socio-economic status. Support was found for the hypothesis that migration has a positive long-term impact on men's occupational achievement. Only multiple migrations affect women's occupational achievement significantly, in a positive way. Copyright © 2005 John Wiley & Sons, Ltd.
Learning with Deictic Representations

The Problem: Humans speak, and probably think, of the world as being made up of objects. Individual objects have features, and sets of objects stand in various relations to one another. If artificial agents are to successfully interact with our world, they will need to represent and reason about objects, their features, and relations that hold among them. We are interested in how agents embedded in inherently relational environments, such as physically embodied robots, can learn to act.
GraphX: a resilient distributed graph system on Spark

From social networks to targeted advertising, big graphs capture the structure in data and are central to recent advances in machine learning and data mining. Unfortunately, directly applying existing data-parallel tools to graph computation tasks can be cumbersome and inefficient. The need for intuitive, scalable tools for graph computation has lead to the development of new graph-parallel systems (e.g., Pregel, PowerGraph) which are designed to efficiently execute graph algorithms. Unfortunately, these new graph-parallel systems do not address the challenges of graph construction and transformation which are often just as problematic as the subsequent computation. Furthermore, existing graph-parallel systems provide limited fault-tolerance and support for interactive data mining. We introduce GraphX, which combines the advantages of both data-parallel and graph-parallel systems by efficiently expressing graph computation within the Spark data-parallel framework. We leverage new ideas in distributed graph representation to efficiently distribute graphs as tabular data-structures. Similarly, we leverage advances in data-flow systems to exploit in-memory computation and fault-tolerance. We provide powerful new operations to simplify graph construction and transformation. Using these primitives we implement the PowerGraph and Pregel abstractions in less than 20 lines of code. Finally, by exploiting the Scala foundation of Spark, we enable users to interactively load, transform, and compute on massive graphs.
Speech recognition interface design for in-vehicle system

This paper aims to provide a framework of guidelines for the design of an in-vehicle speech recognition interface. In the first section, a background of speech recognition technology is introduced to explain why it is necessary to provide specific guidelines for in-vehicle speech recognition interfaces. The second session reviews two parts of previous research work; existing guidelines on general speech recognition interface design and physical and cognitive performances during driving and using speech recognition. However, the current research results do not conclude on how to design a speech recognition interface for in-vehicle systems, thus for the third section, an actual case-study from our organization was evaluated to identify usability issues. It describes how to apply general speech recognition guidelines into an in-vehicle speech recognition interface and introduces new solutions to solve the found usability issues.
Pilot Contamination Elimination for Large-Scale Multiple-Antenna Aided OFDM Systems

Pilot contamination constitutes a particularly significant impairment in large-scale multi-cell systems. We propose an effective pilot contamination elimination scheme for multi-cell time division duplexing based orthogonal frequency division multiplexing systems, by carefully designing a sophisticated amalgam of downlink (DL) training and `scheduled' uplink (UL) training. During the DL training stage, each base station (BS) transmits the DL pilot symbols (PSs) to its mobile stations (MSs) for them to estimate their frequency-domain channel transfer functions (FDCHTFs), which are then embedded in the UL PSs by `predistorting' the PSs with the estimated FDCHTFs. During the scheduled UL training, each BS's UL receiver in turn extracts the FDCHTFs of its MSs from their received PSs by eliminating the pilot contamination imposed by the simultaneously transmitted UL PSs of all other cells. Our simulation results demonstrate that the pilot contamination is completely eliminated by the proposed scheme, even for the network consisting of a large number of unity frequency reuse cells. Most significantly, unlike many existing pilot contamination reduction schemes, our scheme does not rely on the assumption that each BS knows the second-order statistics of all the interfering UL channels.
Noc-HMP

Scalability and performance in multicore processors for embedded and real-time systems usually don't go well each with the other. Networks on Chip (NoCs) provide scalable execution platforms suitable for such kind of embedded systems. This article presents a NoC-based Heterogeneous Multi-Processor system, called NoC-HMP, which is a scalable platform for embedded systems developed in the GALS language SystemJ. NoC-HMP uses a time-predictable TDMA-MIN NoC to guarantee latencies and communication time between the two types of time-predictable cores and can be customized for a specific performance goal through the execution strategy and scheduling of SystemJ program deployed across multiple cores. Examples of different execution strategies are introduced, explored and analyzed via measurements. The number of used cores can be minimized to achieve the target performance of the application. TDMA-MIN allows easy extensions of NoC-HMP with other cores or IP blocks. Experiments show a significant improvement of performance over a single core system and demonstrate how the addition of cores affects the performance of the designed system.
The attenuation of very low frequency brain oscillations in transitions from a rest state to active attention

Background: The default mode interference hypothesis (Sonuga-Barke & Castellanos, 2007) predicts (1) the attenuation of very low frequency oscillations (VLFO; e.g., .05 Hz) in brain activity within the default mode network during the transition from rest to task, and (2) that failures to attenuate in this way will lead to an increased likelihood of periodic attention lapses that are synchronized to the VLFO pattern. Here, we tested these predictions using DC-EEG recordings within and outside of a previously identified network of electrode locations hypothesized to reflect DMN activity (i.e., S3 network; Helps et al., 2008). Method: 24 young adults (mean age 22.3 years; 8 male), sampled to include a wide range of ADHD symptoms, took part in a study of rest to task transitions. Two conditions were compared: 5 min of rest (eyes open) and a 10-min simple 2-choice RT task with a relatively high sampling rate (ISI 1 s). DC-EEG was recorded during both conditions, and the low-frequency spectrum was decomposed and measures of the power within specific bands extracted. Results: Shift from rest to task led to an attenuation of VLFO activity within the S3 network which was inversely associated with ADHD symptoms. RT during task also showed a VLFO signature. During task there was a small but significant degree of synchronization between EEG and RT in the VLFO band. Attenuators showed a lower degree of synchrony than nonattenuators. Discussion: The results provide some initial EEG-based support for the default mode interference hypothesis and suggest that failure to attenuate VLFO in the S3 network is associated with higher synchrony between low-frequency brain activity and RT fluctuations during a simple RT task. Although significant, the effects were small and future research should employ tasks with a higher sampling rate to increase the possibility of extracting robust and stable signals.
A Robust Multi-Party Key Agreement Protocol Resistant to Malicious Participants

By its very nature, a non-authenticated multi-party key agreement protocol cannot provide participant and message authentication, so it must rely on an authenticated network channel. This paper presents the inability of two famous multi-party key agreement protocols to withstand malicious participant attacks, even though their protocols are based on the authenticated network channel. This attack involves a malicious participant disrupting the multi-party key agreement among honest participants. In this case, other honest participants do not correctly agree on a common key. Obviously, the malicious participant cannot obtain the common key either, and the communication confidentiality among participants is not breached. However, in some emergency situations or applications, a multi-party key agreement protocol design that is resistant to malicious participants is useful. Therefore, in this paper, a non-authenticated multi-party key agreement protocol resistant to malicious participants is proposed. The proposed robust protocol requires constant rounds to establish a common key. Each participant broadcasts a constant number of messages. Under the assumption of the Decision Diffie--Hellman problem and the random oracle model, we will show that the proposed protocol is provably secure against passive adversaries and malicious participants.