Miracle-dz/UniFAR-FTUs huggingface dataset:
Channel Aware Routing Metric for IEEE 802.11 multi-channel Mesh Networks

Implementing multiple channels among the multi-radio nodes of Wireless Mesh Networks (WMNs) improve the capacity of the network. In this paper, we propose Channel Aware Routing Metric (CARM) as a new routing metric that facilitates the use of available channels in 802.11 WMNs. It chooses a route that has better link quality, reduced switching delay and better channel diversity. Unlike all the other metrics, CARM makes a combination between the number of interfaces and the number of channels available to improve the performance of the network. Simulation results show that by utilizing all the channels in the frequency spectrum, CARM performs better than other standard metrics.
Why Johnny Can't Blow the Whistle: Identifying and Reducing Usability Issues in Anonymity Systems

Tor is one of the most widely used anonymity networks in the world. The anonymity provided to any individual Tor user is a function of the total number of Tor users. Adoption of anonymity tools, including Tor, can be hindered by a lack of usability. Therefore, enhancing Tor's usability and making it easier for more people to use Tor successfully increases security for all Tor users. To enhance Tor usability we begin by identifying stop-points which may act as barriers to using the Tor Browser Bundle (TBB). We suggest changes based on our analysis of these stop-points. To follow through, in our second study we test whether the changes we recommended to the Tor Project are effective in increasing usability, and find a significant decrease in stop-points across the board. Based on these studies, we both suggest new design heuristics appropriate for improving the usability of anonymity systems and identify design heuristics which are particularly salient in the design of anonymity systems.
Allergic enteritis in children

The gastrointestinal form of food allergy is very common in children. The most frequently observed types are allergic proctitis and proctocolitis. In most cases the symptoms subside within the first 2 months of life. The babies seem healthy, and the only abnormality is a small amount of blood in stool. Symptoms can also include small intestine inflammation and colitis. Patients may present with irritability, abdominal pain, flatulence, colic, postprandial vomiting, chronic diarrhoea, and hindered physical development. The diagnosis of allergic enteritis is based on the clinical examination and the results of additional tests including an endoscopy of the lower digestive tract with histopathological assessment. Cow’s milk proteins are the most common nutrition proteins responsible for the development of the symptoms of allergic enteritis. The most essential method of treating allergic enteritis is the elimination diet. The symptoms should subside within 1–2 weeks from the beginning of the diet.
Plasmonic Terahertz Waveguide Based on Anisotropically Etched Silicon Substrate

We experimentally examine anisotropically etched silicon surfaces for terahertz (THz) plasmonic guided wave applications. Highly doped silicon surfaces are anisotropically etched to form a one-dimensional array of subwavelength concave pyramidal troughs. The plasmonic wave guides are found to support highly confined guided modes both in transverse and longitudinal directions. The resonant frequencies of the modes can be controlled by adjusting the geometrical parameters of the troughs. The existence of guided modes in plasmonic wave guides is also established through finite-element-based numerical simulations. These wave guides could provide a silicon-based alternative to metallic wave guides for use in future THz devices.
Polygonal approximation of digital curves using adaptive MCMC sampling

Polygonal approximation (PA) of the digital planar curves is an important topic in computer vision community. In this paper, we address this problem in the energy-minimization framework. We present a novel stochastic search scheme, which combines a split-and-merge process and a stochastic approximation Monte Carlo (SAMC) sampling procedure for global optimization. The SAMC sampling method can effectively handle the local-trap problem suffered by many local search methods, while the split-and-merge process is used to construct a more informative proposal distribution, and thus further improves the overall sampling efficiency. Experimental results on various benchmarks show that the proposed algorithm can achieve high-quality solutions and comparable results to those of state-of-the-art methods.
Improved Animal Tracking Algorithms Using Distributed Kalman-based Filters

Animal tracking has been addressed by different initiatives over the last two decades. Most of them rely on satellite connectivity on every single node and lack of energy-saving strategies. This paper presents several new contributions on the tracking of dynamic heterogeneous asynchronous networks (primary nodes with GPS and secondary nodes with a kinetic generator) motivated by the animal tracking paradigm with random transmissions. A simple approach based on connectivity and coverage intersection is compared with more sophisticated algorithms based on ad-hoc implementations of distributed Kalman-based filters that integrate measurement information using Consensus principles in order to provide enhanced accuracy. Several simulations varying the coverage range, the random behavior of the kinetic generator (modeled as a Poisson Process) and the periodic activation of GPS are included. In addition, this study is enhanced with HW developments and implementations on commercial off-the-shelf equipment which show the feasibility for performing these proposals on real hardware.
Pan-Genome Analysis of Brazilian Lineage A Amoebal Mimiviruses

Since the recent discovery of Samba virus, the first representative of the family Mimiviridae from Brazil, prospecting for mimiviruses has been conducted in different environmental conditions in Brazil. Recently, we isolated using Acanthamoeba sp. three new mimiviruses, all of lineage A of amoebal mimiviruses: Kroon virus from urban lake water; Amazonia virus from the Brazilian Amazon river; and Oyster virus from farmed oysters. The aims of this work were to sequence and analyze the genome of these new Brazilian mimiviruses (mimi-BR) and update the analysis of the Samba virus genome. The genomes of Samba virus, Amazonia virus and Oyster virus were 97%–99% similar, whereas Kroon virus had a low similarity (90%–91%) with other mimi-BR. A total of 3877 proteins encoded by mimi-BR were grouped into 974 orthologous clusters. In addition, we identified three new ORFans in the Kroon virus genome. Additional work is needed to expand our knowledge of the diversity of mimiviruses from Brazil, including if and why among amoebal mimiviruses those of lineage A predominate in the Brazilian environment.
Panoramic Scanned Page Using Mobile Phone Camera

Today, almost all mobile phones introduced in market are equipped with built in cameras and in this work, we have proposed a new application by using this camera. A scanned image of a large document is achieved by completely traversing this camera on it. All successive frames are joined seamlessly to generate a panoramic image of the page. It is a difficult task due to, lateral movements of camera along with hand shaking, change in illumination due to hand shadow etc. Matter is further complexed by the fact that text alphabets does not possess distinct features which is a key requirement for panoramic image generation. A framework is designed for coarse to refine alignment of images based on the background modeling approach. Foreground segmentation and correspondence estimation are expressed as a unified labeling problem, and are solved efficiently via tree dynamic programming (TDP). Experiments proved our algorithm to be robust in performance.
The Valuation and Hedging of Deferred Commission Asset Backed Securities

Due to a timing mismatch between fee receipts and commission payments, there is a newand growing market for securities backed by fees from back-end load and level load mutualfunds. This paper develops a contingent claims methodology for the valuation of thesesecurities. The resulting security value depends primarily on the current value of fund assets and the fee schedule. The valuation formula also provides an analytical expression for the appropriate strategy for hedging fluctuations in asset value. As a case study, we investigate the hedging performance of an institution that holds a portfolio of these securities.
Approximate Entropy-Based Epileptic EEG Detection Using Artificial Neural Networks

The electroencephalogram (EEG) signal plays an important role in the diagnosis of epilepsy. The EEG recordings of the ambulatory recording systems generate very lengthy data and the detection of the epileptic activity requires a time-consuming analysis of the entire length of the EEG data by an expert. The traditional methods of analysis being tedious, many automated diagnostic systems for epilepsy have emerged in recent years. This paper proposes a neural-network-based automated epileptic EEG detection system that uses approximate entropy (ApEn) as the input feature. ApEn is a statistical parameter that measures the predictability of the current amplitude values of a physiological signal based on its previous amplitude values. It is known that the value of the ApEn drops sharply during an epileptic seizure and this fact is used in the proposed system. Two different types of neural networks, namely, Elman and probabilistic neural networks, are considered in this paper. ApEn is used for the first time in the proposed system for the detection of epilepsy using neural networks. It is shown that the overall accuracy values as high as 100% can be achieved by using the proposed system
ZIVM: A Zero-Copy Inter-VM Communication Mechanism for Cloud Computing

With the advent of virtualization technology and its propagation to the infrastructure of Cloud distributed systems, there is an emergent request for more effective means of communication between virtual machines (VMs) lying on distributed memory than traditional message based communication means. This paper presents a distributed virtual shared memory mechanism called ZIVM (Zero-copy Inter-VM) to ease the programming of inter-VM communications in a transparent way and at the same time to achieve comparable and bearable execution performance. ZIVM has been implemented as a virtual cluster on a hosted virtual machine using the KVM hypervisor. Experimental results have shown near native performance in terms of latency and bandwidth.
RARβ regulates neuronal cell death and differentiation in the avian ciliary ganglion

Programmed cell death during chicken ciliary ganglion (CG) development is mostly discussed as an extrinsically regulated process, guided either by the establishment of a functional balance between preganglionic and postganglionic activity or the availability of target‐derived neurotrophic factors. We found that the expression of the gene coding for the nuclear retinoic acid receptor β (RARB) is transiently upregulated prior to and during the execution phase of cell death in the CG. Using retroviral vectors, the expression of RARB was knocked down during embryonic development in ovo. The knockdown led to a significant increase in CG neuron number after the cell death phase. BrdU injections and active caspase‐3 staining revealed that this increase in neuron number was due to an inhibition of apoptosis during the normal cell death phase. Furthermore, apoptotic neuron numbers were significantly increased at a stage when cell death is normally completed. While the cholinergic phenotype of the neurons remained unchanged after RARB knockdown, the expression of the proneural gene Cash1 was increased, but somatostatin‐like immunoreactivity, a hallmark of the mature choroid neuron population, was decreased. Taken together, these results point toward a delay in neuronal differentiation as well as cell death. The availability of nuclear retinoic acid receptor β (RARβ) and RARβ‐induced transcription of genes could therefore be a new intrinsic cue for the maturation of CG neurons and their predisposition to undergo cell death. © 2015 Wiley Periodicals, Inc. Develop Neurobiol 75: 1204–1218, 2015
Delay Spread Estimation For OFDM Based Mobile Communication Systems

In this paper we present a new channel delay spread estimator for OFDM based communication systems. The estimator operates in a wide range of channel delay spreads and mobile users velocities (0−360 km/h). The estimated value can be taken to select filters on the actual channel state, for instance two-dimensional (2D) Wiener filters. The estimator is based on a decision feedback signal, which is correlated with the incoming data stream to get an estimate of the channel impulse response (CIR). From this CIR, the estimate of the channel delay spread can easily be computed. In this paper we show, that the estimator is reliable for user velocities of up to 360 km/h, which is essential for future mobile communication systems.
Object detection using RGBD data for interactive robotic manipulation

We discuss about practical consideration of 3D object detection and pose estimation using an RGBD sensor for interactive robotic manipulation. Template matching based object detection with an RGBD data works good, but it requires further pose refinement for a robot to manipulate it. The pose data can be used to augment a virtual object in the scene so that a user can manipulate it intuitively. In addition, an automatic database collection system is introduced for easier use of this system.
Integration of bottom-up and top-down cues in Bayesian network for object detection

Automatic detection of objects in cluttered images involves a lot of uncertainty, and has been a great challenge in computer vision. However, humans can easily find their interested objects via the mechanisms of visual selective attention. Inspired by this, a visual attention model which integrates bottom-up and top-down cues in the Bayesian network is proposed. In this model, the bottom-up color and shape cues are combined with the top-down color and shape priors, and all these cues are related with their locations, simulating the convergence of bottom-up and top-down cues in visual area V4 of human visual system. Then, a Bayesian network is constructed according to these cues, and each cue is represented as a node in the network. Finally, a saliency map about localizing the target objects is created through the inference in the Bayesian network. The uncertainty in object detection is reduced by the inference greatly. The experiments show that this model can detect interested objects in images with complex backgrounds, even if the objects have different sizes, colors or shapes, and appear in different places of an image. In comparison with the results of famous Itti's visual attention model, the advantage of our model is that it can obtain the contours of objects, which is very helpful for further process of object recognition.
Network Connectivity with a Family of Group Mobility Models

We investigate the communication range of the nodes necessary for network connectivity, which we call bidirectional connectivity, in a simple setting. Unlike in most of existing studies, however, the locations or mobilities of the nodes may be correlated through group mobility: nodes are broken into groups, with each group comprising the same number of nodes, and lie on a unit circle. The locations of the nodes in the same group are not mutually independent, but are instead conditionally independent given the location of the group. We examine the distribution of the smallest communication range needed for bidirectional connectivity, called the critical transmission range (CTR), when both the number of groups and the number of nodes in a group are large. We first demonstrate that the CTR exhibits a parametric sensitivity with respect to the space each group occupies on the unit circle. Then, we offer an explanation for the observed sensitivity by identifying what is known as a very strong threshold and asymptotic bounds for CTR.
Interactive Rendering of Meso-structure Surface Details using Semi-transparent 3D Textures

Several techniques have been introduced to display meso-structure surface details to enhance the appearance of complex surfaces. One strategy is to avoid altogether costly semi-transparency in interactive contexts. However when dealing with hierarchical surface representations (important to filtering) and complex light transfers, semi-transparency must be treated. We propose a method that combines in a novel way multiple techniques from hardware rendering and volume visualization in order to render on current graphics hardware semitransparent meso-structure surface details stored in a 3D texture. The texture is mapped to an outer shell defined by tetrahedra extruded from the surface triangular mesh. The tetrahedra are first sorted on the CPU to be rendered in correct order. The attenuated color for each ray traversing each tetrahedron is efficiently computed with a hardware voxel traversal algorithm. The resulting structure is general enough to simulate at interactive rates from semitransparent surface details to opaque displacement maps, including several surface shading effects (visual masking, self-shadowing, absorption of light).
Heuristics of Applying Statistical Tests Using Appropriate Measurement Scales

This paper aims to present the abridged guidelines for the usage of various measurement scales in social research. Selection of measurement scales play a pivotal role in social science research and most of statistical techniques and tests require a specific measurement scales to be employed in the research. This paper starts with a summary of measurement scales and then provides useful guidelines for permissible arithmetic operations, permissible descriptive statistics, and permissible graphical presentations. It also provides summary of statistical tests for independent and dependent variables containing different measurement scales and permissible uni-variate, bivariate and multivariate statistical analysis for different measurement scales. At the end it provides limitations of this study.
SchemaAnalyst: Search-Based Test Data Generation for Relational Database Schemas

Data stored in relational databases plays a vital role in many aspects of society. When this data is incorrect, the services that depend on it may be compromised. The database schema is the artefact responsible for maintaining the integrity of stored data. Because of its critical function, the proper testing of the database schema is a task of great importance. Employing a search-based approach to generate high-quality test data for database schemas, SchemaAnalyst is a tool that supports testing this key software component. This presented tool is extensible and includes both an evaluation framework for assessing the quality of the generated tests and full-featured documentation. In addition to describing the design and implementation of SchemaAnalyst and overviewing its efficiency and effectiveness, this paper coincides with the tool's public release, thereby enhancing practitioners' ability to test relational database schemas.
An investigation of preservice early childhood teachers’ adoption of ICT in a teaching practicum context in Hong Kong

ABSTRACT The research reported here investigated the use of information and communication technologies (ICT) by 15 Hong Kong preservice early childhood teachers (PSTs) who had completed a course regarding the use of ICT in early childhood settings as they participated in their first-year teaching practicum. The study examined the preservice teachers use of ICT and their ability to integrate ICT into their teaching practices. The research took place in 7 preschool settings across the Hong Kong Special Administration Region (SAR). The results indicated that preservice teachers used ICT mostly in the context of a teacher-directed approach to learning. The contexts allowed for few child-directed activities and very few child-initiated activities. Similarly, when the preservice teachers incorporated learning activities that used ICT, they initiated and directed most of the activities. The findings from this study indicate that school factors, such as school-level curriculum, ICT infrastructure, and the mentor-teacher’s teaching philosophy exerted a powerful influence on the way that preservice teachers were able to use ICT in their teaching practicum.
Novel Layered Clustering-Based Approach for Generating Ensemble of Classifiers

This paper introduces a novel concept for creating an ensemble of classifiers. The concept is based on generating an ensemble of classifiers through clustering of data at multiple layers. The ensemble classifier model generates a set of alternative clustering of a dataset at different layers by randomly initializing the clustering parameters and trains a set of base classifiers on the patterns at different clusters in different layers. A test pattern is classified by first finding the appropriate cluster at each layer and then using the corresponding base classifier. The decisions obtained at different layers are fused into a final verdict using majority voting. As the base classifiers are trained on overlapping patterns at different layers, the proposed approach achieves diversity among the individual classifiers. Identification of difficult-to-classify patterns through clustering as well as achievement of diversity through layering leads to better classification results as evidenced from the experimental results.
TatB Functions as an Oligomeric Binding Site for Folded Tat Precursor Proteins

The TatABC subunits of the twin-arginine translocation machinery allow transport of folded proteins by an unknown mechanism. Here we show that the entire surfaces of folded Tat substrates contact TatB via both of its predicted helices. Our data suggest that TatB forms an oligomeric binding site that transiently accommodates folded Tat precursors.
INCIDENTAL VOCABULARY ACQUISITION THROUGH VIEWING L2 TELEVISION AND FACTORS THAT AFFECT LEARNING

Abstract Research has begun to demonstrate that L2 words can be learned incidentally through watching audio-visual materials. Although there are a large number of studies that have investigated incidental vocabulary learning through reading a single text, there are no studies that have explored incidental vocabulary learning through viewing a single full-length TV program. The present study fills this gap. Additionally, three word-related variables (frequency of occurrence, cognateness, word relevance) and one learner-related variable (prior vocabulary knowledge) that might contribute to incidental vocabulary learning were examined. Two experiments were conducted with Dutch-speaking EFL learners to measure the effects of viewing TV on form recognition and meaning recall (Experiment 1) and meaning recognition (Experiment 2). The findings showed that viewing TV resulted in incidental vocabulary learning at the level of meaning recall and meaning recognition. The research also revealed that learning was affected by frequency of occurrence, prior vocabulary knowledge, and cognateness.