Miracle-dz/UniFAR-FTUs huggingface dataset:
VULNERABILITY ASSESSMENT OF MULTI BIOMETRIC SYSTEMS

The objective of this study was to provide vulnerability analysis for multi biometric systems and their performance against the known attacks. The report helps in identifying and analyzing risks that may have detrimental outcomes on the security provided by multi biometric systems. The risk assessment process was based on the standards of Risk Management (ISO 31000). Investigation of various research papers, experiments and whitepapers on risk analysis of biometric systems provided major insights in determining the overall risk associated with biometric systems in general, and the performance and security gains obtained from implementing multi biometric systems, in particular. Multi biometric systems provide performance gains in terms of increased reliability, accuracy and security. These gains come at the cost of increased constraints on operating environments, cost of operation, comparatively high computational costs (as compared to unimodal systems) and user convenience and these need to be taken into consideration while developing the systems. The report provides an introduction to the various biometric modalities and fusion rules available for the system designers, which can be implemented in order to obtain best performance in terms of reliability and accuracy for that particular implementation scenario. The functional, operational and technical requirements of the proposed biometric systems can be used for assessment of whether the intended security level can be obtained by implementing multiple sensors or comparing the signals from various samples; if additional computational power can be used by implementing multiple algorithms to obtain a reliable decision or to implement multiple modalities in order to make the system more robust. After further analysis of the risks and detailed study of previously carried research, it was concluded that more rigid, robust controls and better fusion rules were required to increase the security of the system. Various interoperability standards and testing frameworks for multi biometric systems need to be developed to make the process of integration of various systems more streamlined and to help remove the vulnerabilities present in loosely coupled biometric systems. As the technology changes rapidly and new techniques keep emerging to subvert the biometric systems, effort should be made, on the part of system designers and system developers, to keep an eye for emerging vulnerabilities along with keeping a check on existing ones in order to develop more secure and robust biometric authentication systems in the future. Table of
Active Sonar Beacons to aid Synthetic Aperture Sonar Autofocussing : Beacon-Controller Design and Performance

This paper presents the design and performance of a microprocessor based beaconcontroller. It has been developed as part of a new method to determine the path of a free-towed Synthetic Aperture Sonar (SAS) by autofocussing images of active beacons. The beacons are deployed on the seabed in the target area to listen for and transmit acoustic signals. The beacon-controller remotely controls their operation, through an RF modem, and logs the timing data to a PC using USB. At the same time it monitors the sonar transmit signal, via the tow cable, and time-stamps a data log when each chirp is transmitted. High accuracy timing information is obtained from a GPS timing receiver. Robust software techniques and extensive error checking are used to ensure the reliable operation of the PIC microcontroller which controls the complete operation of the beacon-controller. The target-performance of 15 chirps per second has been verified with the sonar and two simulated active beacons simultaneously transmitting in real-time.
Natural polymers for the microencapsulation of cells

The encapsulation of living mammalian cells within a semi-permeable hydrogel matrix is an attractive procedure for many biomedical and biotechnological applications, such as xenotransplantation, maintenance of stem cell phenotype and bioprinting of three-dimensional scaffolds for tissue engineering and regenerative medicine. In this review, we focus on naturally derived polymers that can form hydrogels under mild conditions and that are thus capable of entrapping cells within controlled volumes. Our emphasis will be on polysaccharides and proteins, including agarose, alginate, carrageenan, chitosan, gellan gum, hyaluronic acid, collagen, elastin, gelatin, fibrin and silk fibroin. We also discuss the technologies commonly employed to encapsulate cells in these hydrogels, with particular attention on microencapsulation.
Impact of the Smart City Industry on the Korean National Economy: Input-Output Analysis

The characteristics of the smart city industry and its effects on the national economy of Korea are investigated using input-output analysis. The definition and industrial classification of a smart city are established using the Delphi technique for experts in various fields, from information and communication technologies (ICT) to governmental policies for urban matters. The results of the analysis, including the production, value added and employment induction effects, show that the smart city industry has intermediate characteristics between ICT and urban construction industries, indicating that acquisition of the competitive edge of both the ICT and construction industries is the key to the success of the smart city industry. The crucial industries related to the smart city industry are identified based on an analysis of the forward and backward linkage effects, the results of which suggest the importance of the relevant service industries. The economic effects on the national economy induced by the governmental program for smart city demonstration are estimated using input-output analysis results. Overall, the results of this study indicate that facilitation of the smart city industry plays a key role not only in the sustainable city, but also in the growth of the national economy.
Geometric shape drawing using a 3 link planar manipulator

Using manipulators to draw artistic figures is a benchmark problem in robotics. In this paper we describe a 3-link planar manipulator which draws artistic shapes or geometric shapes on a canvas. We first take a snapshot of the shape to draw from the camera and process it for finding the outer boundary or edges. The edges are mapped onto the drawing canvas. The edges are converted from Cartesian coordinate space to the configuration space of the manipulator. The joint trajectories so generated are passed to the controller as a trajectory input, which draws the shape using the end-effector or a marker in our case. Our manipulator is able to draw many shapes with high precision and speed.
Single frame super-resolution using multiple graph structured program

Single frame Super-Resolution (SR) is a technique to generate a high-resolution (HR) image from one low-resolution (LR) image. Generally, single frame SR has trade-off between image quality and computational cost. In this paper, we propose a single frame SR method using multiple graph structured programs based on Cartesian Genetic Programming (CGP). In order to improve the trade-off, we use low computational cost graphs which are constructed from HR and LR images. We constructed each graph structured program simultaneously. Experimental result shows the effectiveness of combining multiple graph structured programs. We present a fast and good quality SR method using multiple programs.
Multi-View Point Registration via Alternating Optimization

Multi-view point registration is a relatively less studied problem compared with two-view point registration. Directly applying pairwise registration often leads to matching discrepancy as the mapping between two point sets can be determined either by direct correspondences or by any intermediate point set. Also, the local two-view registration tends to be sensitive to noises. We propose a novel multi-view registration method, where the optimal registration is achieved via an efficient and effective alternating concave minimization process. We further extend our solution to a general case in practice of registration among point sets with different cardinalities. Extensive empirical evaluations of peer methods on both synthetic data and real images suggest our method is robust to large disturbance. In particular, it is shown that our method outperforms peer point matching methods and performs competitively against graph matching approaches. The latter approaches utilize the additional second-order information at the cost of exponentially increased run-time, thus usually being less efficient.
Network Coding as a Performance Booster for Concurrent Multi-Path Transfer of Data in Multi-Hop Wireless Networks

The emerging use of multi-homed wireless devices along with simultaneous multi-path data transfer offers tremendous potentials to improve the capacity of multi-hop wireless networks. The use of simultaneous data transfer over separate disjoint paths in multi-hop wireless networks to increase network capacity is a less explored subject, mainly because of the challenges it triggers for the reliable transport layer protocols. Reliable transport layer protocols generally use packet sequence number as a mean to ensure delivery. As such, the out-of-order packet arrival in reliable transport layer protocols triggers receiver buffer blocking that causes throughput degradation and prevents the reliable multi-path transport layer protocol to realize its vast potential. This paper focuses on integrating network coding with a reliable multi-path transport layer protocol to resolve the receiver buffer blocking problem. We propose an adaptive network coding mechanism to desensitize the receiver against packet reordering and consequently eliminate the receiver buffer blocking problem. Our state-of-the-art network coding scheme uses a combination of Q-learning and logistic regression for rare data events to control the number of redundant packets based on the network dynamics. We confirmed the veracity of our proposed scheme by a queuing theory based mathematical model. Moreover, the effectiveness of the proposed scheme is demonstrated through simulations and testbed experiments.
Receptor-mediated transcytosis of IgA in MDCK cells is via apical recycling endosomes

Classically, the polymeric immunoglobulin receptor and its ligand, IgA, are thought to be sorted from basolateral early endosomes into transcytotic vesicles that directly fuse with the apical plasma membrane. In contrast, we have found that in MDCK cells IgA is delivered from basolateral endosomes to apical endosomes and only then to the apical cell surface. When internalized from the basolateral surface of MDCK cells IgA is found to accumulate under the apical plasma membrane in a compartment that is accessible to two apically added membrane markers: anti-secretory component Fab fragments, and avidin internalized from the biotinylated apical pole of the cell. This accumulation occurs in the presence of apical trypsin, which prevents internalization of the ligand from the apical cell surface. Using a modification of the diaminobenzidine density-shift assay, we estimate that approximately 80% of basolaterally internalized IgA resides in the apical endosomal compartment. In addition, approximately 50% of basolaterally internalized transferrin, a basolateral recycling protein, has access to this apical endosomal compartment and is efficiently recycled back to the basolateral surface. Microtubules are required for the organization of the apical endosomal compartment and it is dispersed in nocodazole-treated cells. Moreover, this compartment is largely inaccessible to fluid-phase markers added to either pole of the cell, and therefore seems analogous to the recycling endosome described in nonpolarized cells. We propose a model in which transcytosis is not a specialized pathway that uses unique transcytotic vesicles, but rather combines portions of pathways used by non- transcytosing molecules.
Model-Based Approaches for Independence-Enhanced Recommendation

This paper studies a new approach to enhance recommendation independence. Such approaches are useful in ensuring adherence to laws and regulations, fair treatment of content providers, and exclusion of unwanted information. For example, recommendations that match an employer with a job applicant should not be based on socially sensitive information, such as gender or race, from the perspective of social fairness. An algorithm that could exclude the influence of such sensitive information would be useful in this case. We previously gave a formal definition of recommendation independence and proposed a method adopting a regularizer that imposes such an independence constraint. As no other options than this regularization approach have been put forward, we here propose a new model-based approach, which is based on a generative model that satisfies the constraint of recommendation independence. We apply this approach to a latent class model and empirically show that the model-based approach can enhance recommendation independence. Recommendation algorithms based on generative models, such as topic models, are important, because they have a flexible functionality that enables them to incorporate a wide variety of information types. Our new model-based approach will broaden the applications of independence-enhanced recommendation by integrating the functionality of generative models.
Ancient indian document analysis using cognitive memory network

In this work, we propose a character segmentation system from ancient palm leaf manuscripts written in ancient Arya Ezhuthu(which was popularized as script to write Malayalam from 17th century). The automatic recognition of handwritten text from digital images of palm leaves dating back to 10th century BC. This can enable context based searching in large volumes of digital document. The subject about document image understanding is to extract and classify individual data meaningfully from palm leaf manuscript. We propose an automatic approach to detecting and identifying the characters. The proposed approach can improve the readability of the document. Text line segmentation is then applied and the characters are extracted.
Hepatic Muscarinic Acetylcholine Receptors Are Not Critically Involved in Maintaining Glucose Homeostasis in Mice

OBJECTIVE An increase in the rate of hepatic glucose production is the major determinant of fasting hyperglycemia in type 2 diabetes. A better understanding of the signaling pathways and molecules that regulate hepatic glucose metabolism is therefore of great clinical importance. Recent studies suggest that an increase in vagal outflow to the liver leads to decreased hepatic glucose production and reduced blood glucose levels. Since acetylcholine (ACh) is the major neurotransmitter of the vagus nerve and exerts its parasympathetic actions via activation of muscarinic ACh receptors (mAChRs), we examined the potential metabolic relevance of hepatocyte mAChRs. RESEARCH DESIGN AND METHODS We initially demonstrated that the M3 mAChR is the only mAChR subtype expressed by mouse liver/hepatocytes. To assess the physiological role of this receptor subtype in regulating hepatic glucose fluxes and glucose homeostasis in vivo, we used gene targeting and transgenic techniques to generate mutant mice lacking or overexpressing M3 receptors in hepatocytes only. RESULTS Strikingly, detailed in vivo phenotyping studies failed to reveal any significant metabolic differences between the M3 receptor mutant mice and their control littermates, independent of whether the mice were fed regular or a high-fat diet. Moreover, the expression levels of genes for various key transcription factors, signaling molecules, and enzymes regulating hepatic glucose fluxes were not significantly altered in the M3 receptor mutant mice. CONCLUSIONS This rather surprising finding suggests that the pronounced metabolic effects mediated by activation of hepatic vagal nerves are mediated by noncholinergic signaling pathways.
Performance analysis of IEEE 802.11 DCF based WNCS networks

Wireless network technologies, such as IEEE 802.11 based wireless local area networks (WLANs), have been adopted in wireless networked control systems (WNCS) for real-time applications. Distributed real-time control requires satisfaction of (soft) real-time performance from the underlying networks for delivery of real-time traffic. However, IEEE 802.11 networks are not designed for WNCS applications. They neither inherently provide quality-of-service (QoS) support, nor explicitly consider the characteristics of the real-time traffic on networked control systems (NCS), i.e., periodic round-trip traffic. Therefore, the adoption of 802.11 networks in real-time WNCSs causes challenging problems for network design and performance analysis. Theoretical methodologies are yet to be developed for computing the best achievable WNCS network performance under the constraints of real-time control requirements. Focusing on IEEE 802.11 distributed coordination function (DCF) based WNCSs, this paper analyses several important NCS network performance indices, such as throughput capacity, round trip time and packet loss ratio under the periodic round trip traffic pattern, a unique feature of typical NCSs. Considering periodic round trip traffic, an analytical model based on Markov chain theory is developed for deriving these performance indices under a critical real-time traffic condition, at which the real-time performance constraints are marginally satisfied. Case studies are also carried out to validate the theoretical development.
Measurement and modeling of adaptation to noise in images

Abstract— Webster has proposed “that adaptation increases the salience of novel stimuli by partially discounting the ambient background. ” This is an excellent, concise, description of the purpose and function of chromatic adaptation in image‐reproduction applications. However, Webster was not limiting this proposal to just chromatic adaptation, but rather using it as a general description for all forms of perceptual adaptation. Demonstrations of adaptation to other properties of image displays such as motion, blur, and spatial frequency led the authors to ponder the question of whether observers might adapt to the noise structure in images to enhance the novel stimuli — the systematic image content. This phenomenon, noise adaptation in images, was easily demonstrated, but apparently has not been carefully studied in the past. Psychophysical measurements of noise adaptation in color image perception is described and mathematical prediction of the effect is explored. The results illustrate the hypothesized pattern‐dependent adaptation and its prediction through adaptation of a 2‐D contrast‐sensitivity function in an image‐appearance‐model‐based difference metric.
High Level RTOS Scheduler Modeling for a Fast Design Validation

The use of higher level specification models will open new sceneries for optimization and architecture exploration like CPU/RTOS tradeoffs. Scheduling decision for realtime embedded applications has a great impact on system performance and, therefore, it is an important issue in RTOS design. Moreover, it is highly desirable to have the system designer able to evaluate and select the right scheduling policy at high abstraction levels, in order to allow faster exploration of the design space. In this paper, we address this problem by introducing an abstract RTOS scheduling model as well as a new approach to refine an unscheduled high level model to a high level model with RTOS scheduling. This approach is built on the top of the standard SystemC kernel and enables the system designer to quickly evaluate different scheduling policies and make the best choice in early design stages. Furthermore, we present a case study where our model is used to simulate and analyze a telecom system
Non-commutative D- and M-brane Bound States

We analyze certain brane bound states in M-theory and their descendants in type IIA string theory, all involving 3-form or 2-form background fluxes. Among them are configurations which represent NCYM, NCOS and ODp-theories in the scaling limit of OM-theory. In particular, we show how the conditions for the embedding to preserve supersymmetry are modified by the presence of the flux and discuss their relations for the various different bound states. Via the formalism of geometric quantization such a deformation of a supersymmetric cycle is related to a non-commutativity of its coordinates. We also study possible non-commutative deformations of the Seiberg-Witten curve of =2 supersymmetric gauge theories due to non-trivial H-flux.
- Ray Plasma Diagnostics of Stellar Winds in Very Young Massive Stars

High resolution X-ray spectra of very young massive stars opened a new chapter in the diagnostics and understanding of the properties of stellar wind plasmas. Observations of several very young early type stars in the Orion Trapezium demonstrated that the conventional model of shock heated plasmas in stellar winds is not sufficient to explain the observed X-ray spectra. Detailed X-ray line diagnostics revealed extreme temperatures in some of the candidates as well as evidence for high plasma densities. It is also evident from high resolution spectra of more conventional early type stars, that not all show such extreme characteristics. However, the fact that some of the stars show hot and dense components and some do not requires more understanding of the physical processes involved in stellar wind emissions. The Orion Trapezium stars distinguish themselves from all the others by their extreme youth. By comparing the diverse spectral properties of θ Ori A and θ Ori E with those of θ Ori C, we further demonstrate that X-ray spectral properties of very young massive stars are far from understood.
Comparative Study on Biochemical Properties and Antioxidative Activity of Cuttlefish (Sepia officinalis) Protein Hydrolysates Produced by Alcalase and Bacillus licheniformis NH1 Proteases

Antioxidative activities and biochemical properties of protein hydrolysates prepared from cuttlefish (Sepia officinalis) using Alcalase 2.4 L and Bacillus licheniformis NH1 proteases with different degrees of hydrolysis (DH) were determined. For the biochemical properties, hydrolysis by both enzymes increased protein solubility to above 75% over a wide pH range. The antioxidant activities of cuttlefish protein hydrolysates (CPHs) increase with increasing DH. In addition, all CPHs exhibited antioxidative activity in a concentration-dependent manner. NH1-CPHs generally showed greater antioxidative activity than Alcalase protein hydrolysates (P < 0.05) as indicated by the higher 1,1-diphenyl-1-picryhydrazyl (DPPH) radical scavenging activity and ferrous chelating activity. Both Alcalase and NH1 protein hydrolysates were able to retard lipid peroxidation and β-carotene-linoleic acid oxidation. Alcalase-CPH (DH = 12.5%) and NH1-CPH (DH = 15%) contained 75.36% and 80.11% protein, respectively, with histidine and arginine as the major amino acids, followed by glutamic acid/glutamine, serine, lysine, and leucine. In addition, CPHs have a high percentage of essential amino acids made up 48.85% and 50.04%. Cuttlefish muscle protein hydrolysates had a high nutritional value and could be used as supplement to poorly balanced dietary proteins.
Appearance-based Robot Visual Servo via a Wavelet Neural Network

This paper proposes a robot visual servo approach based on image appearance and a wavelet function neural network. The inputs of the wavelet neural network are changes of image features or the elements of image appearance vector, and the outputs are changes of robot joint angles. Image appearance vector is calculated by using eigen subspace transform algorithm. The proposed approach does not need a priori knowledge of the robot kinematics, hand-eye geometry and camera models. The experiment results on a real robot system show that the proposed method is practical and simple.