Miracle-dz/UniFAR-FTUs huggingface dataset:
Constructive Role of SFC & RGB Fusion versus Destructive Intrusion

Digital Crime is the latest terrorist who can intrude into any domain by breaking any type of firewall or secret code without frittering even a single drop of blood. To fight this terror, a cryptic army was evolved but not good enough to succeed. As a consequence, an effective commando namely steganography has been evolved who can combat any type of destructive intrusion. In this paper, Space Filling Curve (SFC) and RBG colour compound stego action against the threat of digital crime has been proposed. The proposed stego system scans the colour image pixel by pixel along a complex path, not row by row, and hides the variable k bit of the secret data in each pixel visited in the order defined by a Space-Filling Curve (SFC) such as the Hilbert curve and the Moore curve traversing paths. Such curves visit each pixel in the color image which is split into Red, Green and Blue components. The effectiveness of the proposed stego system has been estimated by computing bit error rate (BER), Mean square error(MSE),Peak Signal to Noise Ratio (PSNR) and Mean Structural Similarity index(MSSIM). This paper also illustrates how security has been enhanced using this algorithm.
An evolutionary approach for test program compaction

The increasing complexity of electronic components based on microprocessors and their use in safety-critical application - like automotive devices - make reliability a critical aspect. During the life cycle of such products, it is needed to periodically check whether the processor cores are working correctly. In most cases, this task is performed by running short, fast and specialized test programs that satisfies in-field testing requirements. This paper proposes a method that exploits an evolutionary-computation technique for the automatic compaction of these in-field oriented test programs. The aim of the proposed approach is twofold: reduce execution time and memory occupation, while maintaining the fault coverage of the original test program. Experimental results gathered on miniMIPS, a freely available 5-stage pipelined processor core, demonstrate the effectiveness of the proposed technique.
Elbow detection for localization of a mobile robot inside pipeline using laser pointers

Robots for pipe inspection have been studied for a long time and many mobile mechanisms have been proposed to achieve the inspection task within pipelines. Localization is an important factor for inpipe robot to perform a successful autonomous operation. However, because of its unique characteristics of inpipe condition, sensors which have good performance in localization, like GPS and beacon, cannot be used. In this paper, a localization using elbow detection is presented. With the laser light image processing and the angular velocity of IMU, the odometry module of robot determines whether it is on straight pipe or elbow, and minimizes the integration error in orientation. The experiment environment has consisted of two straight pipes and an elbow, and the pipe map has been constructed as the result.
A chimeric MIP‐1α/RANTES protein demonstrates the use of different regions of the RANTES protein to bind and activate its receptors

Human RANTES (CCL5) and MIP‐1α (CCL3) bind and activate several CC chemokine receptors. RANTES is a high‐affinity ligand for CCR1 and CCR5, and it binds CCR3 with moderate affinity and CCR4 with low affinity. MIP‐1α has similar binding characteristics to RANTES except that it does not bind to CCR3. Here we have generated a chimera of human MIP‐1α and RANTES, called MIP/RANTES, consisting of the eight amino terminal residues of MIP‐1α preceding the CC motif, and the remainder of the sequence is RANTES. The chimera is able to induce chemotaxis of human monocytes. MIP/RANTES has >100‐fold reduction in binding to CCR1 and does not bind to CCR3 but retains full, functional binding to CCR5. It has equivalent affinity for CCR5 to MIP‐1α and RANTES, binding with an IC50 of 1.12 nM, and is able to mobilize calcium and induce endocytosis of CCR5 in PBMC in a manner equi‐potent to RANTES. It also retains the ability to inhibit R5 using HIV‐1 strains. Therefore, we conclude that the amino terminus of RANTES is not involved in CCR5 binding, but it is essential for CCR1 and CCR3.
Epidemiology of viral hepatitis in Sudan

Hepatitis virus infections are the most common cause of liver disease worldwide. Sudan is classified among the countries with high hepatitis B virus seroprevalence. Exposure to the virus varied from 47%–78%, with a hepatitis B surface antigen prevalence ranging from 6.8% in central Sudan to 26% in southern Sudan. Studies pointed to infection in early childhood in southern Sudan while there was a trend of increasing infection rate with increasing age in northern Sudan. Hepatitis B virus was the commonest cause of chronic liver disease and hepatocellular carcinoma and was the second commonest cause of acute liver failure in the Sudan. Studies of hepatitis C virus showed a low seroprevalence of 2.2%–4.8% and there was no association with schistosomiasis or with parenteral antischistosomal therapy. Hepatitis E virus was the commonest cause of acute hepatitis among pediatric, adult, and displaced populations. Recent introduction of screening of blood and blood products for hepatitis B virus and hepatitis C virus infections and the introduction of hepatitis B virus vaccine as part of the extended program of immunization is expected to reduce the infection rate of these viruses in the Sudan.
Scintigraphic measurement of regional gastrointestinal transit in the dog.

Scintigraphic techniques can measure sequentially gastric emptying, small bowel transit, and colonic transit in humans, and comparable methods for experimental studies in animals would be useful. We developed such a method in dogs and examined the effects of prokinetic drugs on regional transit. Two isotopes were given to fasting dogs. Polystyrene pellets labeled with99mTc were mixed in a can of dog food and 111In- labeled pellets were given in a gelatin capsule coated with a pH-sensitive polymer, designed to dissolve in the distal bowel. Gamma camera images were obtained for up to 24 h. Prokinetic drugs were given by intravenous injection. Duplicate baseline studies showed good agreement in seven dogs. In a second group ( n = 4), intra- and interanimal variabilities were established. Two novel prokinetic drugs (AU-116 and AU-130) accelerated small bowel and colonic transit. A simple noninvasive method for measuring whole gut transit in dogs was developed and validated. Two new prokinetics accelerated small bowel and colonic transit.
A test of water pouring height and run intermittence effects on single‐ring infiltration rates

Assessing how the infiltration process depends on the water impact energy improves interpretation of hydrological processes. Impact energies vary with the height of water pouring; that is, the distance between the water delivery point and the soil surface. The effects of the height of water pouring on infiltration in an initially near saturated soil can be tested in the field by two repeated Beerkan infiltration runs separated by a short pause (30 min) and using both low (non‐perturbing) and high (perturbing) heights of water application. The double two‐stage Beerkan run methodology was applied in two soils. The infiltration rate at the end of the perturbing stage of the experiment was 0.2–0.3 (sandy‐loam soil) and 0.15 (loam soil) times that obtained with the initial, nonperturbing stage whereas, without any perturbing effect, infiltration rates at the end of the second run were 0.5 times those at the end of the first run. Therefore, the methodology distinguished between a decrease in infiltration rate due to water redistribution during the pause and that attributable to soil surface perturbation. Maintaining a small depth of water (10 mm) on the infiltration surface was not an alternative to the classical Beerkan run for the non‐perturbing stage of the experiment since two times higher infiltration rates were measured with a greater hydrostatic pressure. In conclusion, the relationship between infiltration into an initially near saturated soil and the energy of the applied water can be determined directly in the field at any time with a simple and parsimonious experiment. This circumstance could improve soil hydraulic characterization for interpreting and simulating hydrological processes.
320-Channel Active Probe for High-Resolution Neuromonitoring and Responsive Neurostimulation

We present a 320-channel active probe for high-spatial-resolution neuromonitoring and responsive neurostimulation. The probe comprises an integrated circuit (IC) cell array bonded to the back side of a pitch-matched microelectrode array. The IC enables up to 256-site neural recording and 64-site neural stimulation at the spatial resolution of 400 μm and 200 μm, respectively. It is suitable for direct integration with electrode arrays with the shank pitch of integer multiples of 200 μm. In the presented configuration, the IC is bonded with a 8 × 8 400 μm-pitch Utah electrode array (UEA) and up to additional 192 recording channels are used for peripheral neuromonitoring. The 0.35 μm CMOS circuit array has a total die size of 3.5 mm × 3.65 mm. Each stimulator channel employs a current memory for simultaneous multi-site neurostimulation, outputs 20 μA-250 μA square or arbitrary waveform current, occupies 0.02 mm 2, and dissipates 2.76 μW quiescent power. Each fully differential recording channel has two stages of amplification and filtering and an 8-bit single-slope ADC, occupies 0.035 mm 2 , and consumes 51.9 μW. The neural probe has been experimentally validated in epileptic seizure propagation studies in a mouse hippocampal slice in vitro and in responsive neurostimulation for seizure suppression in an acute epilepsy rat model in vivo .
ScanComplete: Large-Scale Scene Completion and Semantic Segmentation for 3D Scans

We introduce ScanComplete, a novel data-driven approach for taking an incomplete 3D scan of a scene as input and predicting a complete 3D model along with per-voxel semantic labels. The key contribution of our method is its ability to handle large scenes with varying spatial extent, managing the cubic growth in data size as scene size increases. To this end, we devise a fully-convolutional generative 3D CNN model whose filter kernels are invariant to the overall scene size. The model can be trained on scene subvolumes but deployed on arbitrarily large scenes at test time. In addition, we propose a coarse-to-fine inference strategy in order to produce high-resolution output while also leveraging large input context sizes. In an extensive series of experiments, we carefully evaluate different model design choices, considering both deterministic and probabilistic models for completion and semantic inference. Our results show that we outperform other methods not only in the size of the environments handled and processing efficiency, but also with regard to completion quality and semantic segmentation performance by a significant margin.
An objective and subjective evaluation of content-based privacy protection of face images in video surveillance systems using JPEG XR

An objective and subjective evaluation of content-based privacy protection of face images in video surveillance systems using JPEG XR Hosik Sohn, Dohyoung Lee, Wesley De Neve, Konstantinos N. Plataniotis, and Yong Man Ro Image and Video Systems Lab, Department of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Yuseong-gu, Daejeon, 305-701, Korea Multimedia Lab, The Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, Toronto, Ontario, M5S 3GA, Canada Abstract The increasing ability of video surveillance systems to successfully recognize faces has recently raised privacy concerns. To mitigate these concerns, several tools have been developed to conceal the identity of face images. However, little attention has thus far been paid to a profound evaluation of the effectiveness of privacy protection tools, thus leaving room for achieving a better understanding of experimental conditions that may cause privacy leakage and the effectiveness of different approaches for evaluating the level of security offered by privacy protection tools. To that end, in this chapter, we make use of both objective and subjective assessments to analyze the privacy-preserving nature of a layered scrambling technique developed for video surveillance systems using JPEG Extended Range (JPEG XR). In our objective assessments, we apply automatic face recognition (FR) techniques and general-purpose visual security metrics to scrambled face images, testing their effectiveness under varying experimental conditions. In our subjective assessments, we study whether agreement exists between the judgments of human observers and the output of automatic FR. Our results show that the scrambled face images come, in general, with a feasible level of protection against automatic and human FR. However, for video surveillance requiring a high level of privacy protection, our results indicate that the strength of the scrambling technique studied needs to be enhanced at low bit rates, that chroma information needs to be scrambled, and that the presence of eye glasses and a low number of gallery face images may contribute to the success of a replacement attack. Our results also demonstrate that, compared to automatic FR, the general-purpose visual security metrics studied are less suited for detecting weaknesses in tools that aim at identity concealment. Additionally, our results show that our objective and subjective assessments are not always in agreement.
Cluster-based location report for person tracking in wireless sensor networks

In traditional tracking systems, the mobiles report their locations periodically. With the number of the mobiles increasing, these methods result in high loss rate of packets and rapid depletion of the network energy. In practice, we observe that some mobiles are so close to each other that we are informed the same location from the localization algorithm. Thus it is necessary and possible to reduce message complexity through merging the location messages. By exploiting the Received Signal Strength (RSS), this paper proposes a human-Behavior based Mobile Clustering Mechanism (BMC) for Rf-based Person Tracking Systems. It constructs clusters according to the distance between mobiles and maintains clusters efficiently. In BMC, only the cluster-heads report locations periodically instead of each node, thereby decreasing the message complexity greatly. Signal interference will wobble the clusters in practical environment, so it degrades the performance of BMC dramatically. To address the issue, Signal Smoothness is developed. The simulation shows that BMC based location report outperforms traditional methods by 64% of message reduction on average in impartial testing scenes.
Source Speech and Language Resources for Frisian

In this paper, we present several open source speech and language resources for the under-resourced Frisian language. Frisian is mostly spoken in the province of Fryslân which is located in the north of the Netherlands. The native speakers of Frisian are Frisian-Dutch bilingual and often code-switch in daily conversations. The resources presented in this paper include a code-switching speech database containing radio broadcasts, a phonetic lexicon with more than 70k words and a language model trained on a text corpus with more than 38M words. With this contribution, we aim to share the Frisian resources we have collected in the scope of the FAME! project, in which a spoken document retrieval system is built for the disclosure of the regional broadcaster’s radio archives. These resources enable research on code-switching and longitudinal speech and language change. Moreover, a sample automatic speech recognition (ASR) recipe for the Kaldi toolkit will also be provided online to facilitate the Frisian ASR research.
Dense multibody motion estimation and reconstruction from a handheld camera

Existing approaches to camera tracking and reconstruction from a single handheld camera for Augmented Reality (AR) focus on the reconstruction of static scenes. However, most real world scenarios are dynamic and contain multiple independently moving rigid objects. This paper addresses the problem of simultaneous segmentation, motion estimation and dense 3D reconstruction of dynamic scenes. We propose a dense solution to all three elements of this problem: depth estimation, motion label assignment and rigid transformation estimation directly from the raw video by optimizing a single cost function using a hill-climbing approach. We do not require prior knowledge of the number of objects present in the scene - the number of independent motion models and their parameters are automatically estimated. The resulting inference method combines the best techniques in discrete and continuous optimization: a state of the art variational approach is used to estimate the dense depth maps while the motion segmentation is achieved using discrete graph-cut based optimization. For the rigid motion estimation of the independently moving objects we propose a novel tracking approach designed to cope with the small fields of view they induce and agile motion. Our experimental results on real sequences show how accurate segmentations and dense depth maps can be obtained in a completely automated way and used in marker-free AR applications.
Postglacial Colonization of the Qinling Mountains: Phylogeography of the Swelled Vent Frog (Feirana quadranus)

Background The influence of Pleistocene climatic fluctuations on intraspecific diversification in the Qinling–Daba Mountains of East Asia remains poorly investigated. We tested hypotheses concerning refugia during the last glacial maximum (LGM) in this region by examining the phylogeography of the swelled vent frog (Feirana quadranus; Dicroglossidae, Anura, Amphibia). Methodology/Principal Findings We obtained complete mitochondrial ND2 gene sequences of 224 individuals from 34 populations of Feirana quadranus for phylogeographic analyses. Additionally, we obtained nuclear tyrosinase gene sequences of 68 F. quadranus, one F. kangxianensis and three F. taihangnica samples to test for mitochondrial introgression among them. Phylogenetic analyses based on all genes revealed no introgression among them. Phylogenetic analyses based on ND2 datasets revealed that F. quadranus was comprised of six lineages which were separated by deep valleys; the sole exception is that the Main Qinling and Micang–Western Qinling lineages overlap in distribution. Analyses of population structure indicated restricted gene flow among lineages. Coalescent simulations and divergence dating indicated that the basal diversification within F. quadranus may be associated with the dramatic uplifts of the Tibetan Plateau during the Pliocene. Coalescent simulations indicated that Wuling, Daba, and Western Qinling–Micang–Longmen Mountains were refugia for F. quadranus during the LGM. Demographic analyses indicated that the Daba lineage experienced population size increase prior to the LGM but the Main Qinling and the Micang–Western Qinling lineages expanded in population size and range after the LGM, and the other lineages almost have stable population size or slight slow population size decline. Conclusions/Significance The Qinling–Daba Mountains hosted three refugia for F. quadranus during the LGM. Populations that originated in the Daba Mountains colonized the Main Qinling Mountains after the LGM. Recent sharp expansion of the Micang–Western Qinling and Main Qinling lineages probably contribute to their present-day secondary contact.
Towards an Understanding of Hill-Climbing Procedures for SAT

Recently several local hill-climbing procedures for propositional satisfiability have been proposed which are able to solve large and difficult problems beyond the reach of conventional algorithms like Davis-Putnam. By the introduction of some new variants of these procedures, we provide strong experimental evidence to support our conjecture that neither greediness nor randomness is important in these procedures. One of the variants introduced seems to offer significant improvements over earlier procedures. In addition, we investigate experimentally how performance depends on their parameters. Our results suggest that runtime scales less than simply exponentially in the problem size.
Genericity conditions for finite cyclicity of elementary graphics

Abstract In this paper we explore the Khovanskii method for proving the finite cyclicity of elementary graphics and how it can be applied in practice. The genericity conditions needed in that case form a proper subset of the usual methods. Moreover some of the conditions are non-intrinsic and can be artificially created by action of the automorphism groups preserving the normal forms near the singularities and their action on regular transitions. Hence we introduce an extension of the method which treats the usual functional-Pfaffian systems together with the admissible changes of coordinates in the functional equations.
Internalist and externalist HCI

The history of technology, as a discipline, supports alternate points of view termed internalist and externalist, which terms highlight an approximately similar division in points of view within HCI. Conventional HCI is externalist, rightly concerned with human-centered issues; but externalism risks ignoring important internalist issues. A successful human-computer system is better if it is successful from both perspectives. This discussion paper argues that the externalist view, while necessary and immensely useful, is not sufficient---and in the worst case, risks eclipsing innovation from internalist quarters.
Coronary Plaque Classification With Intravascular Ultrasound Radiofrequency Data Analysis

Background—Atherosclerotic plaque stability is related to histological composition. However, current diagnostic tools do not allow adequate in vivo identification and characterization of plaques. Spectral analysis of backscattered intravascular ultrasound (IVUS) data has potential for real-time in vivo plaque classification. Methods and Results—Eighty-eight plaques from 51 left anterior descending coronary arteries were imaged ex vivo at physiological pressure with the use of 30-MHz IVUS transducers. After IVUS imaging, the arteries were pressure-fixed and corresponding histology was collected in matched images. Regions of interest, selected from histology, were 101 fibrous, 56 fibrolipidic, 50 calcified, and 70 calcified-necrotic regions. Classification schemes for model building were computed for autoregressive and classic Fourier spectra by using 75% of the data. The remaining data were used for validation. Autoregressive classification schemes performed better than those from classic Fourier spectra with accuracies of 90.4% for fibrous, 92.8% for fibrolipidic, 90.9% for calcified, and 89.5% for calcified-necrotic regions in the training data set and 79.7%, 81.2%, 92.8%, and 85.5% in the test data, respectively. Tissue maps were reconstructed with the use of accurate predictions of plaque composition from the autoregressive classification scheme. Conclusions—Coronary plaque composition can be predicted through the use of IVUS radiofrequency data analysis. Autoregressive classification schemes performed better than classic Fourier methods. These techniques allow real-time analysis of IVUS data, enabling in vivo plaque characterization.