Miracle-dz/UniFAR-FTUs huggingface dataset:
Optical exploration of micro/nanoscale irregularities created on metallic surfaces by femtosecond laser irradiation

In this paper, we suggest a direct method based on light scattering and Beckmann formulation for the coarse surface RMS roughness and correlation length measurements. Metallic steel samples irradiated under controlled interaction conditions with ultrafast femtosecond laser system are selected as the random rough surfaces for investigation. Stabilized low-intensity He-Ne laser and an appropriate power meter are selected as the main elements of the experimental measurement probe. The light source and detector are located symmetrically around the surface normal and the reflected light is collected to be used in Beckmann formulation. In this regard, the dependency of the surface scattering to the illumination angle is also investigated. Atomic Force Microscopy and Scanning Electron Microscopy are utilized as standard common methods to extract the surface features and check the reliability of the theoretical approach.
Balancing safety and speed in the military path finding problem: analysis of different ACO algorithms

hCHAC, a MOACO implemented to solve the problem of finding the path that minimizes resources, while maximizing safety for a military unit in realistic battlefields, is compared with some other approaches: two extreme methods, which only considers one objective in the search, and a mono-objective algorithm, which combines the two objectives terms of the formulae in a single. In addition, two state transition rules (combined and dominance-based) have been used in some of the approaches.All of them have been tested in different difficulty maps and hCHAC using the combined state transition rule has been considered the best approach.
Production Mode Choice and Price Competition in the Presence of Network Effects: Shrink-Wrap via Cloud Service

We investigate how firms facing different production modes of software service determine their production mode and pricing decisions in the presence of network effects. We develop a two-stage game model to examine the network effect on the choices of production mode and the strategic behavior of the firms. We find that if all firms adopt cloud service production mode, the resulting software price is higher than if they adopt shrink-wrapped production mode. We also find that network effects lower the level of market price.
Exploring how children use their hands to think: an embodied interactional analysis

In order to better understand how to design hands-on child-computer interaction, we explore how different styles of interaction facilitate children's thinking while they use their hands to manipulate objects. We present an exploratory study of children solving a spatial puzzle task. We investigate how the affordances of physical, graphical and tangible interfaces may facilitate the development of thinking skills including mental visualisation, problem space exploration and collaboration. We utilise the theory of complementary actions taken from embodied cognition to develop a video coding methodology that allows us to classify behavioural activity and make inferences about thinking skills development. Our findings indicated that the combination of direct hands-on input style with audio-visual feedback facilitated by the tangible user interface enabled a dynamic task completion strategy, which supports the development of mental skills with a slight time cost. The mouse and graphical user interface supported a trial and error approach, which may limit skills development. The physical cardboard puzzle enabled effective task completion but provided less support for social interaction and problem space exploration. We conclude with design recommendations.
Inferring Networked Device Categories from Low-Level Activity Indicators

We study the problem of inferring the type of a networked device in a home network by leveraging low level traffic activity indicators seen at commodity home gateways. We analyze a dataset of detailed device network activity obtained from 240 subscriber homes of a large European ISP and extract a number of traffic and spatial fingerprints for individual devices. We develop a two level taxonomy to describe devices onto which we map individual devices using a number of heuristics. We leverage the heuristically derived labels to train classifiers that distinguish device classes based on the traffic and spatial fingerprints of a device. Our results show an accuracy level up to 91% for the coarse level category and up to 84% for the fine grained category. By incorporating information from other sources (e.g., MAC OUI), we are able to further improve accuracy to above 97% and 92%, respectively. Finally, we also extract a set of simple and human-readable rules that concisely capture the behaviour of these distinct device categories.
WOHA: Deadline-Aware Map-Reduce Workflow Scheduling Framework over Hadoop Clusters

In this paper, we present WOHA, an efficient scheduling framework for deadline-aware Map-Reduce workflows. In data centers, complex backend data analysis often utilizes a workflow that contains tens or even hundreds of interdependent Map-Reduce jobs. Meeting deadlines of these workflows is usually of crucial importance to businesses (for example, workflows tightly linked to time-sensitive advertisement placement optimizations can directly affect revenue). Popular Map-Reduce implementations, such as Hadoop, deal with independent Map-Reduce jobs rather than workflows of jobs. In order to simplify the process of submitting workflows, solutions like Oozie emerge, which take a workflow configuration file as input and automatically submit its Hadoop jobs at the right time. The information separation that Hadoop only handles resource allocation and Oozie workflow topology, although preventing the Hadoop master node from getting involved with complex workflow analysis, may unnecessarily lengthen the workflow spans and thus cause more deadline misses. To address this problem and at the same time honor the efficiency of Hadoop master node, WOHA allows client nodes to locally generate scheduling plans which are later used as resource allocation hints by the master node. Under this framework design, we propose a novel scheduling algorithm that improves deadline satisfaction ratio by dynamically assigning priorities among workflows based on their progresses. We implement WOHA by extending Hadoop-1.2. 1. Our experiments over an 80-server cluster show that WOHA manages to increase the deadline satisfaction ratio by 10% compared to state-of-the-art solutions, and scales up to tens of thousands of concurrently running workflows.
Basis Pursuit for robust passive acoustic beamforming

Beamforming is a process that supplies directional gain to sensor array processing. One modality where beamforming adds great value is passive sonar, where real-aperture arrays receive signals emitted by acoustic sources. In passive sonar systems, the beamformer is the backbone of a processing structure that detects, localizes, and classifies external targets. Conventional beamformers use deterministic time-delays (often implemented as phase shifts) to arrange coherent addition of plane-wave signals at each sensor. Recently, adaptive beamformers take advantage of signal time history by imposing a model on the environment. Basis Pursuit is another reconstruction approach used in Compressed Sensing that also enforces a physics-based model - in this case a model of scene sparsity. This paper describes an application of this technique to the beamforming problem. The main benefit of the Basis Pursuit beamforming approach is that it is robust to missing array elements, providing nearly full-aperture performance in a reduced sensor environment. This result is advantageous in the case of processing with inoperative hydrophones. It may also provide cost savings by allowing array design with fewer hydrophones.
A Site of Auditory Experience-Dependent Plasticity in the Neural Representation of Auditory Space in the Barn Owl's Inferior Colliculus

The barn owl's optic tectum contains a map of auditory space that is based, in part, on a map of interaural time difference (ITD). Previous studies have shown that this ITD map is shaped by auditory experience. In this study, we investigated whether the plasticity responsible for experience-induced changes in ITD tuning in the tectum occurs within the tectum itself or at an earlier stage in the auditory pathway. We altered auditory experience in young owls by implanting an acoustic filtering device in one ear that caused frequency-dependent changes in sound timing and level. We analyzed the representation of ITD in normal and device-reared owls in two nuclei in the ascending pathway: the external nucleus of the inferior colliculus (ICX), the primary source of ascending auditory input to the tectum, and the lateral shell of the central nucleus of the inferior colliculus (ICCls), the primary source of input to the ICX. In the ICX, device rearing caused adaptive, frequency-dependent changes in ITD tuning, as well as changes in frequency tuning. These changes in tuning were similar to changes that occurred in the optic tectum in the same owls. In contrast, in the ICCls, tuning for ITD and frequency was unaffected by device rearing. The data indicate that plasticity at the level of the ICX is largely responsible for the adaptive adjustments in ITD tuning and frequency tuning that are observed in the optic tecta of owls raised with abnormal auditory experience.
Joint Stochastic Geometry and Mean Field Game Optimization for Energy-Efficient Proactive Scheduling in Ultra Dense Networks

In this paper, we investigate the energy efficiency performance of optimal proactive scheduling strategies in the context of ultra-dense networks. The network consists of a superposition of homogeneous Poisson point process, whereas the users requests follow a space-time homogeneous point process. The objective is to define the optimal transmission powers at any time, that allows to completely serve every user request, while minimizing the total consumed energy. We also assume the system has predictive knowledge about the future transmission contexts. The problem is cast as a dynamic stochastic game which is hard to solve in ultra-dense networks, due to a complex coupling in the interference term, the large number of elements interacting, as well as uncertainties on the channel dynamics, interference, and future requests. Our contribution first lies in addressing the inherent complexity issue of the optimization, by transitioning into an equivalent and more tractable mean field game. Second, we propose to combine this mathematical framework with elements of stochastic geometry. The numerical simulations provide good insights on notable performance gains in terms of energy efficiency, compared to reference scheduling strategies. Additional simulations harnessing the impact of future knowledge uncertainty on the performance of the proposed strategies are also provided.
Simulation of Collision Resistant Secure Sum Protocol

secure multi-party computation is widely studied area in computer science. It is touching all most every aspect of human life. This paper demonstrates theoretical and experimental results of one of the secure multi-party computation protocols proposed by Shukla et al. implemented using visual C++. Data outflow probability is computed by changing parameters. At the end, time and space complexity is calculated using theoretical and experimental results.
An Evaluation of the Efficacy of a Perceptually Controlled Immersive Environment for Learning Acupuncture

This paper presents a basic but functional Perceptual User Interface (PUI) controlled immersive environment (IE) on an electronic learning platform (e-Learning) in order to deliver educational material relating to the NADA (National Acupuncture Detoxification Association) protocol for acupuncture. The purpose of this study is set out a proposed process for evaluating the learning efficacy of the PUI IE e-Learning application when compared with a typical Graphical User Interface (GUI) e-Learning IE application. Both are to be compared to a more traditional learning method. This paper evaluates user interface (UI) sentiment of the systems in advance of this proposed evaluation.
Seeking Genomic Duplication in Prokaryotic Genomes by Equivalent Tandem Repeats Distributions

Gene duplication and large-scale segmental duplication of genome including whole-genome duplication (WGD) are thought to be driving forces of evolution. So far, it has been revealed by recent analysis that WGD had occurred on many eukaryotic genomes, for instance, maize, Arabidopsis, yeast, and vertebrate, even more than once[4]. Although it is not clear whether or not WGD had occurred on prokaryotic genomes[1, 5], there seems not to exist an apparent reason that WGD never occurs on prokaryotic genomes; it is rather natural to think that some prokaryotes had experienced WGD. The standard manner to investigate genome evolution that is used in recent researches is analyzing homologous genes on the genome. In this study, however, we focused attention on tandem repeats (TRs) instead of genes and analyses equivalent TR-pairs (or, say, repeats of TRs), because TRs are rather free from selection pressure if they are located on inter-genic regions, and thus they might preserve signs of WGD more measurably than genes.
Development and Implementation of a Nanotomography Setup at the PETRA III Beamline P05

X-ray nanotomography is used to analyze materials on the sub-micrometer scale. Many soft biological materials, i.e. most organic tissues, can be imaged with soft X-rays. For materials with a higher electron density, such as bone or teeth, metals, and ceramics, X-ray energies of more than 10 keV need to be used. All these setups require X-ray optics for either direct imaging of the object in question or for preparing a magnified projection. The P05 Imaging Beamline for X-ray micro- and nanotomography is situated at the newly refurbished PETRA III 3rd generation storage ring at DESY. A dedicated experiment for X-ray nanotomography at higher energies was built in one of the two experimental hutches. An X-ray optics concept tailored for this experiment was specified and an accompanying mechanics concept was devised. Based on these concepts, the experiment was designed and installed. In addition to testing the nanotomography experimental components, the beamline front end was commissioned and the influence of these components on the nanotomography experiment was investigated. Higher harmonics from the undulator and monochromator as well as beam position drifts caused by mechanical drifting the monochromator were investigated to analyze their influence on the nanotomography. The X-ray optics were tested in detail and an operational setup was achieved for both the X-ray microscopy and the cone-beam setup. The achieved resolution of the hard X-ray microscope is better than 100 nm line and space. Nanotomographies were performed on a nanoporous gold sample and a photonic glass sample. Image correlation and correction allowed to perform a reconstruction of the photonic glass sample using a filtered backprojection algorithm. The packing fraction of the photonic glass could be successfully extracted from the 3D-dataset.
Design of matrix converter topology and modulation algorithms with shorted and opened failure tolerance

This paper proposes a matrix converter structure and modulation techniques for fault-tolerant operations in case of single-switch short-circuit failures as well as single-switch open-circuit faults and single-phase open-circuit failures. The fault tolerant topology is achieved by redefining the matrix converter configuration with the help of auxiliary devices including connecting devices and fast-acting fuses. Based on the reconfigured converter structure, fault-tolerant control schemes are individually developed to produce output currents for obtaining continuous operation, depending on the types of occurred failures. The proposed fault-tolerant topology and associated pulsewidth modulation algorithms require only minimum hardware modifications to the conventional off-the-shelf three-phase matrix converter, by including electronic components such as triacs/SCRs and fast-acting fuses. In addition, the developed approach offers the potential of mitigating not only semiconductor device faults also drive related faults such as motor insulation failures. The added fault-tolerant capability can greatly improve reliability of the overall matrix converter system even after shorted switch or opened switch/phase losses, with minimal system cost increase. Simulation and experimental results are shown to demonstrate the feasibility of the proposed fault-tolerant scheme to the matrix converter drives.
Educational monitoring tool based on faceted browsing and data portraits

Due to the idiosyncrasy of online education, students may become disoriented, frustrated or confused if they do not receive the support, feedback or guidance needed to be successful. To avoid this, the role of teachers is essential. In this regard, instructors should be facilitators who guide students throughout the teaching-learning process and arrange meaningful learner-centered experiences. However, unlike face-to-face classes, teachers have difficulty in monitoring their learners in an online environment, since a lot of learning management systems provide faculty with student tracking data in a poor tabular format that is difficult to understand. In order to overcome this drawback, this paper presents a novel graphical educational monitoring tool based on faceted browsing that helps instructors to gain an insight into their classrooms' performance. Moreover, this tool depicts information of each individual student by using a data portrait. Thanks to this monitoring tool, teachers can, on the one hand, track their students during the teaching-learning process and, on the other, detect potential problems in time.
Accurate computation of the right tail of the sum of dependent log-normal variates

We study the problem of the Monte Carlo estimation of the right tail of the distribution of the sum of correlated log-normal random variables. While a number of theoretically efficient estimators have been proposed for this setting, using a few numerical examples we illustrate that these published proposals may not always be useful in practical simulations. In other words, we show that the established theoretical efficiency of these estimators does not necessarily convert into Monte Carlo estimators with low variance. As a remedy to this defect, we propose a new estimator for this setting. We demonstrate that, not only is our novel estimator theoretically efficient, but, more importantly, its practical performance is significantly better than that of its competitors.
E-Beam Patterned Gold Nanodot Arrays on Optical Fiber Tips for Localized Surface Plasmon Resonance Biochemical Sensing

Electron beam lithography (EBL) was used to directly pattern periodic gold nanodot arrays on optical fiber tips. Localized surface plasmon resonance of the E-beam patterned gold nanodot arrays on optical fiber tips was utilized for biochemical sensing. The advantage of the optical fiber based localized surface plasmon resonance (LSPR) sensors is the convenience to work with and work in harsh environments. An optical fiber tip LSPR refractive index sensor of 196 nm per refractive index unit (RIU) sensitivity has been demonstrated. The affinity sensing property of the fiber tip sensor was demonstrated using biotin/streptavidin as the receptor/analyte. The detection limit for streptavidin was determined to be 6 pM.
Incremental learning of full body motion primitives for humanoid robots

This paper describes an approach for on-line, incremental learning of full body motion primitives from observation of human motion. The continuous observation sequence is first partitioned into motion segments, using stochastic segmentation. Motion segments are next incrementally clustered and organized into a hierarchical tree structure representing the known motion primitives. Motion primitives are encoded using hidden Markov models, so that the same model can be used for both motion recognition and motion generation. At the same time, the relationship between motion primitives is learned via the construction of a motion primitive graph. The motion primitive graph can then be used to construct motions, consisting of sequences of motion primitives. The approach is implemented and tested on the IRT humanoid robot.
Effects of Lead Pollution on Ammonia Parkinsoniana (Foraminifera): Ultrastructural and Microanalytical Approaches

The responses of Ammonia parkinsoniana (Foraminifera) exposed to different concentrations of lead (Pb) were evaluated at the cytological level. Foraminifera-bearing sediments were placed in mesocosms that were housed in aquaria each with seawater of a different lead concentration. On the basis of transmission electron microscopy and environmental scanning electron microscopy coupled with energy dispersive spectrometer analyses, it was possible to recognize numerous morphological differences between untreated (i.e., control) and treated (i.e., lead enrichment) specimens. In particular, higher concentrations of this pollutant led to numerical increase of lipid droplets characterized by a more electron-dense core, proliferation of residual bodies, a thickening of the organic lining, mitochondrial degeneration, autophagosome proliferation and the development of inorganic aggregates. All these cytological modifications might be related to the pollutant-induced stress and some of them such as the thickening of organic lining might suggest a potential mechanism of protection adopted by foraminifera.
A heuristic to determine low leakage sleep state vectors for CMOS combinational circuits

Input vector control has been used to minimize the leakage power consumption of a circuit in sleep state. In this paper, we present a novel heuristic for determining a low leakage vector to be applied to a circuit in sleep state. The heuristic is a greedy search based on the controllability of nodes in the circuit and uses the functional dependencies among cells in the circuit to guide the search. Results on a set of ISCAS and MCNC benchmark circuits show that in all cases our heuristic returns a vector having a leakage within 5% of that of the vector obtained using an extensive random search, with orders of magnitude improvement in computational speed.