Miracle-dz/UniFAR-FTUs huggingface dataset:
An Approach for Authenticating Smartphone Users Based on Histogram Features

In this study, we propose to adopt histogram features obtained from smartphone sensors for building authentication models, which could be used to nonintrusively authenticate smartphone users in varying operating scenarios (e.g. standing and sitting) when engaged in using stationary apps. We adopted two smartphone sensors, namely touchscreen and orientation sensor, to evaluate their feasibility. Consequently, sixteen touch-based features and thirty-three orientation-based features were separately used to construct two authentication models. To evaluate the performance of two constructed models, thirty-five subjects joined for collecting experimental data in two operating scenarios, standing and sitting. The experimental results showed that the equal error rate (EER) of touch-based model was approximately 6.56% with features extracted from ten flick touch gestures and reduced to approximately 3.05% with sixty flick touch gestures. For orientation-based model, the EERs were approximately 10.27% and 7.07%, separately. The results showed that the histogram features of the adopted two sensors are feasible for authentication purpose. Specially, this study further discusses the phenomenon of multiple behavioral pattern over the adopted two sensors caused among different operating scenarios, such as standing and sitting.
Threshold optimization of contextual fire detection algorithm using fuzzy clustering

A contextual algorithm that is widely used for identifying forest fire pixels uses a threshold derived from statistical examinations of temperature distributions of background pixels. In general, about 3σ (standard deviation) above the mean of these background temperatures is used for the threshold. In case where land cover types are multifaceted in the background pixels, whose distributions of surface temperatures are clearly diverse, the s value becomes overestimated resulting in increased threshold. This is a typical edge problem encountered in the current contextual algorithm which explains why relatively small fires are often omitted. Therefore, in this paper, a new algorithm to optimize the threshold is proposed to overcome the above problem. In this algorithm, statistical inferences of various land covers in the background pixels as well as its center pixel are used. For this, a fuzzy clustering is applied to the background pixels and corresponding statistical distribution of temperatures of each cluster is examined to derive a series of thresholds of the clusters. Then the characteristics of the center pixel are analyzed based on memberships of different clusters. Lastly, an optimum threshold is calculated throughout some arithmetic operations to the derived thresholds and memberships information. In this study, the proposed algorithm was applied to the MODIS imageries that were attained during several fire seasons. The results were compared with those from the current algorithm developed by NASA MODIS science team. The proposed algorithm showed relatively high accuracy by detecting several pixels that the current algorithm failed to sense. For a ground truth, forest fire data provided by the Korea Forest Service were used.
Progressive Bayes: a new framework for nonlinear state estimation

This paper is concerned with recursively estimating the internal state of a nonlinear dynamic system by processing noisy measurements and the known system input. In the case of continuous states, an exact analytic representation of the probability density characterizing the estimate is generally too complex for recursive estimation or even impossible to obtain. Hence, it is replaced by a convenient type of approximate density characterized by a finite set of parameters. Of course, parameters are desired that systematically minimize a given measure of deviation between the (often unknown) exact density and its approximation, which in general leads to a complicated optimization problem. Here, a new framework for state estimation based on progressive processing is proposed. Rather than trying to solve the original problem, it is exactly converted into a corresponding system of explicit ordinary first-order differential equations. Solving this system over a finite "time" interval yields the desired optimal density parameters.
Evolutionary co-optimization of control and system parameters for a resonating robot arm

In this paper we simultaneously optimize the parameters describing the morphology of a robot arm and the parameters of its nonlinear controller. A novel concept of a pick-and-place robot arm is considered, which is called the resonating arm (RA). It uses a nonlinear spring mechanism to generate pick-and-place motions without the need for powerful actuators. This improves energy efficiency, cost and weight of the robot arm. Because of the complex interactions of the spring mechanism and the controller, we use evolutionary co-optimization to optimize the RA system as a whole. The results reveal that evolutionary co-optimization yields near optimal solutions for a 1 degree of freedom (1-DOF) RA, which require 43% less torque than the solution found through a separate optimization of the system and the control parameters. In case of a 2-DOF RA, evolutionary co-optimization resulted in credible solutions as well, but with less consistency.
Further observations on the effects of trypsin on the volume and functions of mitochondria isolated from normal liver and AH-130 Yoshida ascites hepatoma.

Evidence is given indicating that the outer membrane of mitochondria from AH-130 Yoshida ascites hepatoma has low resistance to trypsin. The outer membrane of freshly-isolated hepatoma mitochondria is impermeable to cytochrome c and dextran, but it seems to be easily digested by trypsin. The proteolytic enzyme partially inactivates the adenylate kinase and cytochrome c oxidase of these mitochondria. Inhibition of both enzymes by trypsin is also observed in rat liver mitochondria, but only after the outer membrane has been made permeable to large molecules. The succinate-cytochrome c reductase of both hepatoma and liver mitochondria is not inactivated by trypsin even if the outer membrane is made permeable to large molecules by digitonin. Inactivation of succinate-cytochrome c reductase occurs when trypsin is added after a strong sonic treatment of mitochondria. The adenosine triphosphatase of both types of mitochondria is resistant to trypsin also after the sonic fragmentation of the particles. A marked inhibition of adenosine triphosphatase by proteolysis takes place in phospholipase C-defatted mitochondria from hepatoma and liver when incubation with trypsin precedes the reconstitution of the enzyme by phospholipids extracted from liver. Swelling-inducing amounts of trypsin affect some inner membrane-linked functional activities of hepatoma and liver mitochondria; however, in liver mitochondria, the time of onset of swelling is much later than in hepatoma mitochondria, since the swelling in the former is preceded by a lag phase during which no functional impairment occurs. These results are interpreted as indicative of structural alterations of the outer membrane of hepatoma mitochondria, whereas no differences with regard to sensitivity of trypsin seem to exist between the inner membrane of liver and hepatoma mitochondria.
Nonparametric feature normalization for SVM-based speaker verification

We investigate several feature normalization and scaling approaches for use in speaker verification based on support vector machines. We are particularly interested in methods that are "knowledge-free" and work for a variety of features, leading us to investigate MLLR transforms, phone N-grams, prosodic sequences, and word N-gram features. Normalization methods studied include mean/variance normalization, TFLLR and TFLOG scaling, and a simple nonparametric approach: rank-normalization. We find that rank-normalization is uniformly competitive with other methods, and improves upon them in many cases.
A novel model for Enhanced Principal Component Analysis

In this paper, a novel mathematical model for Enhanced Principal Component Analysis (EPCA) is proposed. With the new mathematical model, the performance of EPCA could be enhanced in pattern recognition area. Compared with PCA, EPCA could adaptively distinguish different variables of sample vector according to their scale in statistics. The optimization problem of EPCA could be solved in the framework used to solve the optimization problem of PCA, so EPCA dose not require more computational complexity than other improved PCA algorithms. When applied to face recognition, EPCA are robust to different facial expression, different illumination intensity and large variation in lighting direction. EPCA outperforms many famous algorithms (PCA, FLD and ICA) in the experiments on Harvard face database.
City distribution service quality: A factor impacting on supplier-customer relationship and customer satisfaction

This paper seeks to propose a conceptual structural equation model to investigate the relationships among city distribution service quality (SQ), supplier-customer relationship (SCR) and customer satisfaction (CS) and to demonstrate their direct and indirect effects on each other. An empirical study is conducted in Beijing and the collected survey data are used to verify the relationships among the three factors expressed in the proposed structural equation model. The results show that SQ has a direct and significant impact on SCR and CS. In addition, SQ influences CS indirectly through SCR which has direct and significant influences on CS. The most significant dimension of SQ is responsiveness and the least one is tangibles. The results are useful for other large international cities where the circumstances are similar to Beijing since data from Beijing were collected and used in this research.
Using WMS log files as an indicator of QoS and application performance in on-demand streaming videos

When utilizing video streaming for professional purposes, the quality of service needs to be evaluated by the service provider. This is the case especially when the service must be available for a large number of customers with a wide range of network interfaces and terminal equipment. Service providers have usually information about network-level metrics. However, the problem is that conditions that appear similar in a networklevel may cause very different responses in an application level, and the other way round. In this article, we study how Windows Media Server's log files can be used to evaluate the QoS of video transmission, and we also examine the application level performance based on the log files. The level of QoS affects user satisfaction and thus QoE, although the relationship between them may be complicated. Understanding how the application responds to deteriorated network conditions gives tools to evaluate also QoE. The examination is limited to on-demand streaming sessions in which UDP is used as a transport protocol.
An N = 2 worldsheet approach to D-branes in bihermitian geometries: I. Chiral and twisted chiral fields

We investigate N = (2, 2) supersymmetric nonlinear σ-models in the presence of a boundary. We restrict our attention to the case where the bulk geometry is described by chiral and twisted chiral superfields corresponding to a bihermitian bulk geometry with two commuting complex structures. The D-brane configurations preserving an N = 2 worldsheet supersymmetry are identified. Duality transformations interchanging chiral for twisted chiral fields and vice versa while preserving all supersymmetries are explicitly constructed. We illustrate our results with various explicit examples such as the WZW-model on the Hopf surface S3 × S1. The duality transformations provide e.g new examples of coisotropic A-branes on Kahler manifolds (which are not necessarily hyper-Kahler). Finally, by dualizing a chiral and a twisted chiral field to a semi-chiral multiplet, we initiate the study of D-branes in bihermitian geometries where the cokernel of the commutator of the complex structures is non-empty.
Responses of Zn assimilation by coastal plankton to macronutrients

We examined the Zn uptake in marine diatoms and its transfer to marine copepods under different nutrient‐replete and ‐deplete conditions. Zn uptake, quantified by measurements of both total cellular and intracellular Zn accumulation in two coastal diatoms (Thalassiosira pseudonana and Thalassiosira weissflogii), was greatly dependent on the ambient nitrogen conditions. Semicontinuous culture experiments demonstrated that diatom cells accumulated much less Zn with decreasing ambient nitrate concentration. The calculated Zn uptake rate decreased by 1.8 times in T. pseudonana and 1.5 times in T. weissflogii with a decrease in ambient N concentration from 176 µM to 17.6 µM. N‐starved cells also accumulated much less Zn compared with N‐enriched cells. The uptake rate decreased by 2.5–2.6 times when both diatoms were starved of N for 2 d. The intracellular partitioning of Zn in the diatom T. pseudonana was positively related to the ambient N level within the short‐term exposure period (5 h). P starvation, however, resulted in an increase in Zn accumulation in the diatoms, whereas Si starvation did not significantly affect the rate of Zn uptake in diatoms. The trophic transfer was quantified by measurement of Zn assimilation efficiency in two copepods (Calanus sinicus and Acartia spinicauda) feeding on diatoms with a different N quota. Assimilation generally increased with an increase in the N quota of the diatoms. In one experiment (C. sinicus feeding on diatom T. weissflogii), the influence of different N status in diatoms on Zn assimilation by copepods was statistically significant. In contrast, the elimination rate (physiological turnover rate) was independent of the N quota of the cells. Nitrogen enrichment may lead to an increase in Zn uptake and transfer in marine plankton. Our study therefore suggests that there is considerable interaction between macronutrients and Zn uptake by plankton in aquatic systems.
Librarians' Leadership Efficacy, Training, and School Involvement: Collaboration between Teachers and School Librarians in Israel

This paper analyzes the correlation between the type of training received by librarians, their leadership efficacy and their involvement in the life of the school, and patterns of teacher-librarian collaboration (TLC) in Israel. The study was based on 291 questionnaires answered by school librarians, teachers, and principals of public schools in Israel. The research findings indicate that leadership ability is predictive of an advanced pattern of teacher-librarian collaboration (TLC).
Product Centric Web Page Segmentation and Localization

The Internet is home to an ever increasing array of goods and services available to the general consumer. These products are often discovered through search engines whose focus is on document retrieval rather than product procurement. The demand for details of specific products as opposed to just documents containing such information has resulted in an influx of product collection databases, deal aggregation services, mobile apps, twitter feeds and other just-in-time methods for rapid finding, indexing, and notifying shoppers to sale events. This has led to our development of intelligent Web crawler technology aimed towards this specific category of information retrieval. In this paper, we demonstrate our solution for Web page categorization, segmentation and localization for identifying Web pages with shopping deals and automatically extracting specifics from the identified Web pages. Our work is supported with empirical data of its effectiveness. A screencast demonstration is also available online at http://youtu.be/HHPme6AJuCk.
An Improved Active Shape Model for Facial Feature Location

Active shape model (ASM) has been widely accepted as one of the best methods for image understanding. In this paper, we propose to improve ASM by introducing Procrustes analysis technique in the matching of feature landmark points of a set of training images and strengthening the edge in searching face profile. Firstly, each landmark point labeled manually is matched by its local profile in its current neighborhood. Then, by analyzing the variations of shape over the training set as in the ASM, we build a mean shape model (MSM) which can mimic this variation. The principle component analysis (PCA) is exploited in this part. Thirdly, we must adjust the parameters which can best fit a model instance to a new image and then the new image can be interpreted after much iteration at the end. Our experiments of the proposed method have shown some effectiveness comparing with the conventional ASM.
Start-up Inertia versus Flexibility: The Role of Founder Identity in a Nascent Industry

Through an inductive, comparative study of four early entrants in the nascent air taxi market, we examine why start-ups, generally characterized as flexible, malleable entities, might instead exhibit inertial behavior. While two of the firms engaged in ongoing experimentation and adaptation, two firms actively reinforced their original venture concepts, even in the face of environmental shifts and declining firm performance. Comparisons of the firms revealed the importance of founders’ identities. Two founders saw themselves as “revolutionaries” building novel ventures to drive radical change. In contrast, two sets of founders saw themselves as “discoverers” identifying new opportunities and exploiting them to build successful businesses. We propose that these identities contributed to the firms’ inertia and flexibility primarily through the mechanism of identity affirmation. Acting in a manner consistent with their self-views, revolutionary founders committed to and actively reinvested in radical venture concepts, rejecting potentially adaptive changes that they felt compromised novelty. In contrast, discoverer founders prioritized experimentation and change in reaction to shifting conditions. We propose an emergent framework exploring how, in a nascent industry, a founder’s identity can set off self-reinforcing cycles of firm inertia or flexibility.
Comparison of Endovascular and Intraventricular Gene Therapy With Adeno-Associated Virus-α-L-Iduronidase for Hurler Disease.

BACKGROUND Hurler disease (mucopolysaccharidosis type I [MPS-I]) is an inherited metabolic disorder characterized by deficiency of the lysosomal enzyme α-L-iduronidase (IDUA). Currently, the only therapies for MPS-I, enzyme replacement and hematopoietic stem cell transplantation, are generally ineffective for central nervous system manifestations. OBJECTIVE To test whether brain-targeted gene therapy with recombinant adeno-associated virus (rAAV5)-IDUA vectors in an MPS-I transgenic mouse model would reverse the pathological hallmarks. METHODS Gene therapy approaches were compared using intraventricular or endovascular delivery with a marker (rAAV5-green fluorescent protein) or therapeutic (rAAV5-IDUA) vector. To improve the efficiency of brain delivery, we tested different applications of hyperosmolar mannitol to disrupt the blood-brain barrier or ependymal-brain interface. RESULTS Intraventricular delivery of 1 × 10 viral particles of rAAV5-IDUA with systemic 5 g/kg mannitol co-administration resulted in IDUA expression throughout the brain, with global enzyme activity >200% of the baseline level in age-matched, wild-type mice. Endovascular delivery of 1 × 10 viral particles of rAAV5-IDUA to the carotid artery with 29.1% mannitol blood-brain barrier disruption resulted in mainly ipsilateral brain IDUA expression and ipsilateral brain enzyme activity 42% of that in wild-type mice. Quantitative assays for glycosaminoglycans showed a significant decrease in both hemispheres after intraventricular delivery and in the ipsilateral hemisphere after endovascular delivery compared with untreated MPS-I mice. Immunohistochemistry for ganglioside GM3, another disease marker, showed reversal of neuronal inclusions in areas with IDUA co-expression in both delivery methods. CONCLUSION Physiologically relevant biochemical correction is possible with neurosurgical or endovascular gene therapy approaches for MPS-I. Intraventricular or endovascular delivery of rAAV5-IDUA was effective in reversing brain pathology, but in the latter method, effects were limited to the ipsilateral hemisphere.
Topology Optimization in Hybrid Tree/Mesh-based Peer-to-Peer Streaming System

Peer-to-Peer (P2P) video streaming is the fastest growing application of the Internet. One of the main challenge is to provide a high quality of service through the dynamic behavior of the network because a peer may join or leave anytime. Currently, P2P streaming network exist two types of users: streaming users - who use mobile devices with 3G/4G connection expect to watch the live video immediately and storage users - who use PC with wired Internet will download and then watch the video later. We realized that the streaming users may stop watching live video after a while if they find the video is out of their interest. Users leaving causes dynamic and affect the data delivery. On the other hand, the storage users that are downloading the video do not have the concern of interest and playback quality, until they start to watch the video. Hence, the storage users are relatively more stable than streaming users. This paper, we investigate the strategies on the topology construction and maintenance of P2P streaming systems with storage users are closer to the broadcaster than streaming users. And also we apply our idea on hybrid push-pull protocol that combines the benefits of pull and push mechanisms for live video delivery to provide better video streaming quality
Navigation image matching based on two-level keypoints

A fundamental problem in scene matching is the precise determination of correspondences between pairs of images, especially used in the cruise missile. Many methods have been proposed and work very well for image data in personal computers. However, with the speed of cruise missile becoming faster and faster, the time consumption of matching methods are too large and cannot be equal to the matching need in the scene matching of cruise missile. This paper proposes a novel matching framework based on a new two-level keypoints structure to find points and local image regions correspondences between pairs of images. Harris corner detector is used to extract the two-level keypoints with different detecting radius (low-level keypoints' detecting radius is small and high-level keypoints' detecting radius is large). Then two new feature descriptors are proposed according to the two-level keypionts. Low-level feature descriptors are formed by sampling the pixel values around the low-level keypoints. High-level keypoint can represent a local image region, whose center point is the high-level keypoint. The local region can be divided into several ring parts by different radiuses. Every high-level feature descriptor is formed by counts the numbers of low-level keypoints in every ring parts, which belongs to the local image region. We additionally optimize the matching regions by a vote approach.