Miracle-dz/UniFAR-FTUs huggingface dataset:
Parallel spatial-domain liver segmentation of CT abdominal images

Liver segmentation in abdominal CT images is vital prior to liver disease diagnosis and computer-aided diagnosis. Since an abdominal CT image is some complex in which the pixels of the liver region and some other adjacent parts often distribute in the same value range, commonly used value-based segmentation methods have difficulty in dealing with this situation. In order to overcome this shortcoming, in this paper we present a spatial-domain segmentation method in which both the value information of the pixels and the spatial relationship between them are utilized in the segmentation process and meanwhile the spatial information, such as the area, boundary or location, of the target is extracted, thus the target region to be segmented can be distinguished from the other parts in same value range by use of the spatial information. Furthermore, a parallel algorithm is designed and implemented on GPU for improving the computation efficiency of the spatial-domain segmentation method. Experiment results obtained in the work confirm the effectiveness of the new segmentation algorithm.
Drosophila Adiponectin Receptor in Insulin Producing Cells Regulates Glucose and Lipid Metabolism by Controlling Insulin Secretion

Adipokines secreted from adipose tissue are key regulators of metabolism in animals. Adiponectin, one of the adipokines, modulates pancreatic beta cell function to maintain energy homeostasis. Recently, significant conservation between Drosophila melanogaster and mammalian metabolism has been discovered. Drosophila insulin like peptides (Dilps) regulate energy metabolism similarly to mammalian insulin. However, in Drosophila, the regulatory mechanism of insulin producing cells (IPCs) by adipokine signaling is largely unknown. Here, we describe the discovery of the Drosophila adiponectin receptor and its function in IPCs. Drosophila adiponectin receptor (dAdipoR) has high homology with the human adiponectin receptor 1. The dAdipoR antibody staining revealed that dAdipoR was expressed in IPCs of larval and adult brains. IPC- specific dAdipoR inhibition (Dilp2>dAdipoR-Ri) showed the increased sugar level in the hemolymph and the elevated triglyceride level in whole body. Dilps mRNA levels in the Dilp2>dAdipoR-Ri flies were similar with those of controls. However, in the Dilp2>dAdipoR-Ri flies, Dilp2 protein was accumulated in IPCs, the level of circulating Dilp2 was decreased, and insulin signaling was reduced in the fat body. In ex vivo fly brain culture with the human adiponectin, Dilp2 was secreted from IPCs. These results indicate that adiponectin receptor in insulin producing cells regulates insulin secretion and controls glucose and lipid metabolism in Drosophila melanogaster. This study demonstrates a new adipokine signaling in Drosophila and provides insights for the mammalian adiponectin receptor function in pancreatic beta cells, which could be useful for therapeutic application.
OTP-Based Two-Factor Authentication Using Mobile Phones

Two-factor authentication (2FA) provides improved protection, since users are prompted to provide something they know and something they have. This method delivers a higher-level of authentication assurance, which is essential for online banking security. Many banking systems have satisfied the2FA requirements by sending a One Time Password (OTP), something possessed, through an SMS to the user's phone device. Unfortunately, international roaming and SMS costs and delays put restrictions on this system reliability. This paper presents a novel two-factor authentication scheme whereby a user's device produces multiples OTPs from an initial seed using the proposed production scheme. The initial seed is produced by the communications partners' unique parameters. Applying the many from one function to a certain seed removes the requirement of sending SMS-based OTPs to users, and reduces the restrictions caused by the SMS system.
High-Resolution Spectroscopy of X-Ray Quasars: Searching for the X-Ray Absorption from the Warm-Hot Intergalactic Medium

We present a survey of six low- to moderate-redshift quasars with Chandra and XMM-Newton. The primary goal is to search for the narrow X-ray absorption lines produced by highly ionized metals in the warm-hot intergalactic medium. All the X-ray spectra can be fitted by a power law with the neutral hydrogen absorption method. The residuals that may be caused by additional emission mechanisms or calibration uncertainties are taken account by a polynomial in order to search for narrow absorption features. No real absorption line is detected at above the 3 σ level in all of the spectra. We discuss the implications of the lack of absorption lines for our understanding of the baryon content of the universe and the metallicity of the intergalactic medium (IGM). We find that the nondetection of X-ray absorption lines indicates that the metal abundance of the IGM should be smaller than ~0.3 solar abundance. We also discuss implications of the nondetection of any local (z ~ 0) X-ray absorption associated with the interstellar medium, Galactic halo, or Local Group, such as has been seen along several other lines of sight (LOSs). By comparing a pair of LOSs we estimate a lower limit on the hydrogen number density for the (z ~ 0) 3C 273 absorber of nH ≳ 4 × 10-3 cm-3.
A New Objective Weight on Interval Type-2 Fuzzy Sets

— The design of weight is one of the important parts in fuzzy decision making, as it would have a deep effect on the evaluation results. Entropy is one of the weight measure based on objective evaluation. Non--probabilistic-type entropy measures for fuzzy set and interval type-2 fuzzy sets (IT2FS) have been developed and applied to weight measure. Since the entropy for (IT2FS) for decision making yet to be explored, this paper proposes a new objective weight method by using entropy weight method for multiple attribute decision making (MADM). This paper utilizes the nature of IT2FS concept in the evaluation process to assess the attribute weight based on the credibility of data. An example was presented to demonstrate the feasibility of the new method in decision making. The entropy measure of interval type-2 fuzzy sets yield flexible judgment and could be applied in decision making environment.
CLOTHO: saving programs from malformed strings and incorrect string-handling

Software is susceptible to malformed data originating from untrusted sources. Occasionally the programming logic or constructs used are inappropriate to handle the varied constraints imposed by legal and well-formed data. Consequently, softwares may produce unexpected results or even crash. In this paper, we present CLOTHO, a novel hybrid approach that saves such softwares from crashing when failures originate from malformed strings or inappropriate handling of strings. CLOTHO statically analyses a program to identify statements that are vulnerable to failures related to associated string data. CLOTHO then generates patches that are likely to satisfy constraints on the data, and in case of failures produces program behavior which would be close to the expected. The precision of the patches is improved with the help of a dynamic analysis. We have implemented CLOTHO for the JAVA String API, and our evaluation based on several popular open-source libraries shows that CLOTHO generates patches that are semantically similar to the patches generated by the programmers in the later versions. Additionally, these patches are activated only when a failure is detected, and thus CLOTHO incurs no runtime overhead during normal execution, and negligible overhead in case of failures.
In Silico Modeling of Ligand Molecule for Target Protein in Diabetes Mellitus Type II Insight Mechanism~!2009-09-05~!2009-12-21~!2010-02-18~!

Type II Diabetes Mellitus or Non-Insulin dependent Diabetes mellitus (NIDDM) is one of the common diseases worldwide and often recognized as life style disease. The major symptom of this disease is an increase in blood glucose level resulting in polydypsia, polyuria and polyphagia. The cause of this abnormality is either lack of insulin production or insensitivity to the insulin produced inside the body. Glucagon like peptide (GLP) produced by the glucagons gene is responsible for insulin secretion. Thus proper functioning of GLP can be a remedy for Type II Diabetes mellitus. DiPeptidyl Peptidase IV (DPPIV) checks the GLP, thus in order to restore the normal functioning of these, the activity of DPP IV has to be checked using DPP IV inhibitors. In this paper the target sequence was retrieved, modeled using modeller 8vl followed by validation by PROCHECK. Ligand molecule was constructed by LIGBUILDER. Docking was carried out with methylamine as a lead molecule and DPPIV as receptor to design a drug molecule. Designing of a drug molecule was followed by screening for its activity and drug likeness. The present studies provide new insights for efficient inhibition of DPP IV to restore the normal activity of the body overcoming the negative effects left by other
WDM Mesh Networks with Dynamic Traffic

This article presents a mathematical model that results in a low-cost network design to satisfy a set of point-to-point demands that arrive and leave the network along of time. It considers the problem of routing working traffic and assigning wavelengths in an all-optical network avoiding if possible that wavelengths assignment changes and flow rerouting. The model allows to know when a reconfiguration/expansion is needed. The model provides a physical network configuration selecting a lowest cost set of components of the network (subnetworks and OXCs) with sufficient capacities to attend the demands and the required wavelengths in all time.
Examining a Large Keystroke Biometrics Dataset for Statistical-Attack Openings

Research on keystroke-based authentication has traditionally assumed human impostors who generate forgeries by physically typing on the keyboard. With bots now well understood to have the capacity to originate precisely timed keystroke sequences, this model of attack is likely to underestimate the threat facing a keystroke-based system in practice. In this work, we investigate how a keystroke-based authentication system would perform if it were subjected to synthetic attacks designed to mimic the typical user. To implement the attacks, we perform a rigorous statistical analysis on keystroke biometrics data collected over a 2-year period from more than 3000 users, and then use the observed statistical traits to design and launch algorithmic attacks against three state-of-the-art password-based keystroke verification systems. Relative to the zero-effort attacks typically used to test the performance of keystroke biometric systems, we show that our algorithmic attack increases the mean Equal Error Rates (EERs) of three high performance keystroke verifiers by between 28.6% and 84.4%. We also find that the impact of the attack is more pronounced when the keystroke profiles subjected to the attack are based on shorter strings, and that some users see considerably greater performance degradation under the attack than others. This article calls for a shift from the traditional zero-effort approach of testing the performance of password-based keystroke verifiers, to a more rigorous algorithmic approach that captures the threat posed by today’s bots.
Estimating texture independently of tone in simulated images of forest canopies

Tone and texture are two fundamental characteristics of remotely sensed images. Current research on the remote sensing of tropical forest biomass uses the tone (i.e., backscatter) of Synthetic Aperture Radar (SAR) images as this is related directly to biomass (albeit up to the backscatter/biomass asymptote). As a tropical forest canopy ages so its unevenness increases, progressing from smooth to rough. Therefore a measure of SAR texture that is independent of SAR tone has the potential of increasing the biomass maxima that can be estimated with SAR data. This experiment used simulated SAR images designed to reproduce forest canopies and different patterns of tone (or contrast) and texture (or clumpiness). Twenty six texture measures (derived from local statistics, the grey-level co-occurrence matrix (GLCM) and variograms) were calculated for these simulated images. Measures sensitive to texture (clumpiness) and/or tone (contrast) were identified using Analysis of Variance (ANOVA). Seven texture measures were recommended for the estimation of tropical forest biomass with SAR images.
New views of transfer function based performance analysis of coded modulations

Transfer function methods are attractive in the performance analysis of coded modulations since they allow averaging of all possible error event probabilities. However, they can be computationally intensive when the code has a large number of states. A method to reduce the complexity of the transfer function method is proposed. In addition, transfer function methods for computing the upper bound of the bit error probability in a flat fading channel are presented. These bounds are simple and tight at high SNR.
Do you know how to configure your enterprise relational database to reduce incidents?

With the advancement of relational databases, the number of configuration parameters that control memory allocation, concurrency, cost of query plans, I/O optimization, logging, recovery or transaction consistency, increases. Users and even expert database administrators struggle to tune these parameters in order to ensure high availability and performance, and in many cases rely on their experience and some rules of thumb. Research on improving database manageability has shown that this is a critical, but hard problem. In this paper, we propose a highly accurate multivariate statistical model that identifies databases which are bound to raise high volumes of incidents over time. Moreover, we show that by adding detailed configuration parameters to the model, we can better link the problems reported in incident tickets to specific poor database configurations. Finally, we analyze trends of top-ranked parameters and compare their values between problematic and non-problematic databases, in order to suggest better configurations.
Impact of traffic pattern on benefits of practical Multi-hop Network Coding in wireless networks

In the pioneering works, network coding has shown great potential to improve the performance of wireless networks. However, most of them are implemented under specific traffic pattern. Since various traffic patterns will affect the promising gains of network coding, in this paper, we study how traffic pattern affects the benefits of general practical network coding scheme — Multi-hop Network Coding (MNC) in wireless networks. First, we analyze the idiosyncratic properties of MNC and raise two practical issues of MNC neglected before: iteration coding and path division. Subsequently, we put forward traffic factors to describe some characteristics of realistic traffic flows, and then qualitatively analyze the relations between the traffic factors and the gains of MNC. In addition, throughput boundary with MNC is formulated in the perspective of flows. Our evaluation also shows that particular MNC should be applied according to different traffic patterns to maximize network throughput and reduce the systematic overhead.
The LMC eclipsing binary HV 2274 revisited

We reanalyse the UV/optical spectrum and optical broad-band data of the eclipsing binary HV 2274 in the LMC, and derive its distance following the method given by Guinan et al. ([CITE],[CITE]) of fitting theoretical spectra to the stars' UV/optical spectrum plus optical photometry. We describe the method in detail, pointing out the various assumptions that have to be made; moreover, we discuss the systematic effects of using different sets of model atmospheres and different sets of optical photometric data. It turns out that different selections of the photometric data, the set of model atmospheres and the constraints on the value of the ratio of selective to total extinction in the V -band, result in a 25% range in distances (although some of these models have a large ${\chi}^2$). For our best choice of these quantities the derived value for the reddening to HV 2274 is $E(B-V)$ = 0.103 ± 0.007, and the de-reddened distance modulus is $DM = 18.46$ ± 0.06; the DM to the center of the LMC is found to be 18.42 ± 0.07. This is significantly larger than the DM of 18.30 ± 0.07 derived by Guinan et al. ([CITE]).
The effect of power consumption on the real time performance of routing protocols for ad hoc wireless networks

This paper aims to study and analyze the real time performance of dominant routing protocols for ad hoc wireless networks under power consumption constraints. It is evaluated the influence of the power consumption to the whole system performance (throughput, delay, network lifetime, channel fairness etc.) under various data flow patterns. The results of this study can be very useful for cross-layer design targeted to the improvement of the whole system performance of the ad hoc wireless networks
Reliable Point-to-Point Underwater Acoustic Data Transfer: To Juggle or Not to Juggle?

Reliable data transfer speeds using underwater acoustic communication systems are limited by long propagation delays, small link data rates, and high bit error rates. We consider the practical problem of transferring a data file or data stream reliably from one half-duplex underwater node to another. In a typical automatic repeat request (ARQ) approach, a node transmits one or more packets and waits for the corresponding acknowledgments (ACKs). With long propagation delay, the long waiting time for ACKs results in low average throughput. The long propagation delay, however, presents an opportunity for two nodes to simultaneously transmit data and ACKs toward each other in a juggling-like approach, potentially reducing the average waiting time for ACKs. The approach needs to satisfy certain timing constraints, and its performance is largely dependent on the network settings and chosen parameters. Through analytical and numerical studies, we provide key insights into appropriate choice of ARQ strategies and protocol parameters under different internodal propagation delays. We show that the juggling-like ARQ (J-ARQ) provides good data streaming throughput but performs poorly for small file transfers. We propose a novel rate-less code-based J-ARQ protocol that overcomes this limitation and offers high data transfer speeds for small files in long propagation delay environments.
A Pupillometric Examination of Cognitive Control in Taxonomic and Thematic Semantic Memory

Semantic cognition includes taxonomic and thematic relationships, as well as control systems to retrieve and manipulate semantic knowledge to suit specific tasks or contexts. A recent report (Thompson et al., 2017) suggested that retrieving thematic relationships (i.e., relations based on participation in the same event or scenarios) requires more effort or cognitive control, especially when the relevant relations are weak, than retrieving identity relations that are based on sensory-motor features. It is not clear whether the same contrast applies to the broader set of taxonomic relations, which are also based on shared sensory-motor features. In this study we tested cognitive control requirements of retrieving taxonomic and thematic knowledge using a physiological measure of cognitive effort: pupil dilation. Participants completed a semantic relatedness judgement task that manipulated semantic type (thematic vs. taxonomic) and relatedness strength (high vs. low) of word pairs. Cognitive control in the similarity task was examined using task-evoked pupillary responses (TEPRs), as well as standard behavioral measures (reaction times and accuracy). Compared with high-strength relations, low-strength semantic relations elicited larger TERPs, slower reaction times, and lower accuracy, consistent with higher control demands. Compared to thematic relations, taxonomic relations also elicited larger TERPs and slower reaction times, suggesting that retrieving taxonomic relations required more cognitive effort. Critically, our pupillometric data indicated that controlled processing was particularly important for low-strength taxonomic pairs rather than low-strength thematic pairs. These findings indicate that semantic control demands are primarily determined by relatedness strength, not whether the relationship is taxonomic or thematic.
Automatic Vehicle Number Plate Recognition Using Morphological Edge Detection and Segmentation

The vehicle number plate recognition automatically controls access to a secured area for authorized members. We tested our method for number plate recognition which includes five main testimonials first is pre-processing of the input image, then cropping the pre- processed image that follows by the image edge extraction operated on the cropped image after this the character segmentation process algorithm and then finally to the character recognition which gives the improved results that shows our method has the average precision that can be put into practice.
Spectral efficiency of beamforming-based parameter estimation in the single source case

It is well known that beamforming and Capon spectral or direction estimators are biased and inefficient with respect to the Cramer-Rao bound (CRB). On the other hand, the MUSIC algorithm is known to be asymptotically unbiased and efficient, in the single zero-mean circular Gaussian source case only. In this latter case, we prove in this paper that for constant steering vector modulus, the beamforming and Capon spectral or direction estimators of possible several parameters per source are asymptotically (with respect to the number of snapshots) unbiased and efficient as well, a property previously overlooked. Finally, the theoretical numerical and empirical values of the mean square errors (MSE) of the spectral MUSIC, beamforming and Capon estimators of the direction of arrival (DOA) for a single source impinging on a planar array are compared.
Semantic-Driven Matchmaking and Composition of Web Services Using Case-Based Reasoning

With the rapid proliferation of Web services as the medium of choice to securely publish application services beyond the firewall, the importance of accurate, yet flexible matchmaking of similar services gains importance both for the human user and for dynamic composition engines. In this paper, we present a novel approach that utilizes the case based reasoning methodology for modelling dynamic Web service discovery and matchmaking, and investigate the use of case adaptation for service composition. Our framework considers Web services execution experiences in the decision making process and is highly adaptable to the service requester constraints. The framework also utilizes OWL semantic descriptions extensively for implementing both the components of the CBR engine and the matchmaking profile of the Web services.
Joint Power Splitting and Antenna Selection in Energy Harvesting Relay Channels

The simultaneous wireless transfer of information and power with the help of a relay equipped with multiple antennas is considered in this letter, where a “harvest-and-forward” strategy is proposed. In particular, the relay harvests energy and obtains information from the source with the radio-frequent signals by jointly using the antenna selection (AS) and power splitting (PS) techniques, and then the processed information is amplified and forwarded to the destination relying on the harvested energy. This letter jointly optimizes AS and PS to maximize the achievable rate for the proposed strategy. Considering that the joint optimization is according to the non-convex problem, a two-stage procedure is proposed to determine the optimal ratio of received signal power split for energy harvesting, and the optimized antenna set engaged in information forwarding. Simulation results confirm the accuracy of the two-stage procedure, and demonstrate that the proposed “harvest-and-forward” strategy outperforms the conventional amplify-and-forward (AF) relaying and the direct transmission.