Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Method for Static and Dynamic Location Sensing in Wlan Network Infrastructure for Indoors

This paper describes a Positioning algorithm that uses the signal strength, RSS, received by a Wireless Local Area Network, to determine user's static and dynamic position. The system improves the positioning accuracy by mitigating multi-path and noise, through an empirical analysis of environment and a prepost cursor mitigator. Most of the systems present in the state of art provide a solution which can not be improved beyond certain point as they are case dependent. The system proposed here, however, is more efficient and adaptive due to its flexible nature as it encounters the error in RSS at two different levels. The mitigation of multi-path at first level decreases the error assuming the channel to be Rice distributed and using delay spread typical to indoors. On second level, it reduces the rest of the error based on empirical analysis of the environment. The algorithm used for static differs from the dynamic location sensing on the second level of error reduction. This gives a lot of scope for improvement in the positioning in later case. Due to the fact that this system is self learning and continuously updating itself as well it is comparatively less burdensome, the problem of dynamic location sensing no more exist. In fact, using proposed methodology, it is more likely to receive accurate positioning information in case of dynamic sensing without using any kind of filters as proposed in the state of art. However, further improvement is possible by incorporating dynamic filters. The implementation complexity is comparatively simple. The results for both static and dynamic sensing, in terms of relative error, is presented for indoor environments. Keywords— RSS (received signal strength), Wireless Local Area Network (WLAN), Wireless Positioning System (WPS), Feature Function, Pre-Post Curser Multi-path Mitigator, Static and Dynamic location sensing.
An Optimized Extreme Learning Machine for Epileptic Seizure Detection

(OELM) is proposed for the classification of EEG signals with the emphasis on epileptic seizure detection. OELM is an effective learning algorithm of single-hidden layer feed-forward neural networks. It requires setting the number of hidden neurons and the activation function. Adjustment in the input weights and hidden layer's biases are not needed during the implementation of the algorithm, and only one optimal solution is produced. This makes the OELM a valuable tool for the applications that need small response time and provide a good accuracy. The features such as energy, entropy, maximum value, minimum value, mean value and standard deviation of wavelet coefficients are used to represent the time frequency distribution of the EEG signals in each sub-band of the Wavelet Transformation. We have compared the proposed classifier with other traditional classifiers by evaluating it with the benchmark EEG dataset. It is found that the performance of the proposed OELM with Wavelet based statistical features is better in terms of training time and classification accuracy. An accuracy of 94% for classifying the epileptic EEG signals is achieved and needs less training time compared with SVM.
Perturbations and moduli space dynamics of tachyon kinks

The dynamic process of unstable D-branes decaying into stable ones with one dimension lower can be described by a tachyon field with a Dirac-Born-Infeld effective action. In this paper we investigate the fluctuation modes of the tachyon field around a two-parameter family of static solutions representing an array of brane-antibrane pairs. Besides a pair of zero modes associated with the parameters of the solution, and instabilities associated with annihilation of the brane-antibrane pairs, we find states corresponding to excitations of the tachyon field around the brane and in the bulk. In the limit that the brane thickness tends to zero, the support of the eigenmodes is limited to the brane, consistent with the idea that propagating tachyon modes drop out of the spectrum as the tachyon field approaches its ground state. The zero modes, and other low-lying excited states, show a fourfold degeneracy in this limit, which can be identified with some of the massless superstring modes in the brane-antibrane system. Finally, we also discuss the slow motion of the solution corresponding to the decay process in the moduli space, finding a trajectory which oscillates periodically between the unstable D-brane and the brane-antibrane pairs of one dimension lower.
On the tradeoffs between path computation efficiency and information abstraction in optical mesh networks

Distributed, IP-based control architecture has been proposed for switched optical mesh networks, as a means to automate operations, enhance interoperability and facilitate the deployment of new applications. While distributed control in general enhances scalability and flexibility, it also offers challenges to path computation, especially for shared mesh restored paths, because of the summarization of link state information disseminated by the routing protocol. This paper discusses the tradeoffs between the path computation efficiency and the abstraction level of link state information. Several heuristic algorithms for computing shared mesh restored paths are described, which require different levels of abstraction and summarization of link resource sharing information. The performance of these algorithms is compared in term of the efficiency of network capacity utilization, the computation complexity, and the amount of required network information. We show that with appropriately aggregated link state information the proposed path computation algorithms are able to utilize the network resource very efficiently.
Developmental kinetics of GAD family mRNAs parallel neurogenesis in the rat spinal cord

GABA (gamma-amino butyric acid), a fast-acting synaptic transmitter in the mature CNS, is synthesized from glutamate by GAD (glutamic acid decarboxylase). We have developed an ultrasensitive PCR technique to quantify the expression of GAD-related mRNAs during the development of the rat cervical spinal cord and have localized them using in situ hybridization. GAD65, GAD67, and an alternatively spliced variant of GAD67, EP10, were quantified each day from embryonic (E) day 11 through E21, and at postnatal days 0, 7, 14, and adult. GAD65 and GAD67 mRNAs were detected at E11 and increased exponentially over three orders of magnitude during embryonic development, then declined approximately threefold in the first-2 postnatal weeks. While the exponential growth phase coincided with the progressive appearance of GAD67 in situ signals in both the ventral and dorsal cord, the postnatal decline coincided with the virtual disappearance of expression in the ventral region. EP10 expression was prominent in the embryo, then declined markedly together with the mRNA encoding the neuroepithelial stem cell marker, nestin. The concerted appearance of GAD-related mRNAs paralleled transcripts encoding neuronal markers (light and heavy neurofilaments) and also closely correlated with the expression of GABA, mRNAs encoding GABAA receptor subunits, and depolarizing responses to GABA. We have used the results on GAD-related mRNA expressions to formulate a simple, minimal mathematical model that accounts for their kinetics in terms of positive and negative feedback loops.
Turning Maneuvers of a Multi-legged Modular Robot Using Its Inherent Dynamic Characteristics

This paper deals with the motion of a multi-legged modular robot. The robot consists of six homogenous modules, each of which has a body and two legs and is connected to the others through a three-degree-of-freedom joint. The leg joints are manipulated to follow periodic desired trajectories, and the joints between the modules act like a passive spring with a damper. This robot has characteristic dynamic properties. Specifically, a straight walk naturally turns into a meandering walk by changing the compliance of the joints between the modules without incorporation of any oscillatory inputs. We first show that this transition is excited due to a Hopf bifurcation, based on a numerical simulation and Floquet analysis. Following that, we examine whether the maneuverability and agility increase by utilizing the dynamic characteristics inherent in the robot. In particular, we conduct an experiment in which the robot pursues a target moving across the floor. We propose a simple controller to accomplish the task and achieve high maneuverability and agility by making the most of the robot's dynamic features
Gait Analysis Using Floor Markers and Inertial Sensors

In this paper, a gait analysis system which estimates step length and foot angles is proposed. A measurement unit, which consists of a camera and inertial sensors, is installed on a shoe. When the foot touches the floor, markers are recognized by the camera to obtain the current position and attitude. A simple planar marker with 4,096 different codes is used. These markers printed on paper are placed on the floor. When the foot is moving off the floor, the position and attitude are estimated using an inertial navigation algorithm. For accurate estimation, a smoother is proposed, where vision information and inertial sensor data are combined. Through experiments, it is shown that the proposed system can both track foot motion and estimate step length.
Triggering triggers and burying barriers to customizing software

General-purpose software applications are usually not tailored for a specific user with specific tasks, strategies or preferences. In order to achieve optimal performance with such applications, users typically need to transition to an alternative efficient behavior. Often, features of such alternative behaviors are not initially accessible and first need to be customized. However, few research works formally study and empirically measure what drives a user to customize. In this paper, we describe the challenges involved in empirically studying customization behaviors, and propose a methodology for formally measuring the impact of potential customization factors. We then demonstrate this methodology by studying the impact of different customization factors on customization behaviors. Our results show that increasing exposure and awareness of customization features, and adding social influence can significantly affect the user's customization behavior.
Effectiveness of social welfare programmes on poverty reduction and income inequality in China

Using the 1989 and 2009 China Health and Nutrition Surveys, this paper examines the effects of social welfare programmes on poverty and income inequality in China in 1989 and 2009. The findings indicate that social welfare programmes have played an important role in poverty reduction, reducing poverty rates by approximately 32%. The effects on income inequality, however, were reversed. For example, the ratio of top to bottom income quintiles grew after government transfers, suggesting that the programmes benefitted higher income families more than their counterparts. The inequalities among regions and income quintiles also increased over time.
The Stochastic Logarithmic Norm for Stability Analysis of Stochastic Differential Equations

To analyze the stability of It\^o stochastic differential equations with multiplicative noise, we introduce the stochastic logarithmic norm. The logarithmic norm was originally introduced by G. Dahlquist in 1958 as a tool to study the growth of solutions to ordinary differential equations and for estimating the error growth in discretization methods for their approximate solutions. We extend the concept to the stability analysis of It\^o stochastic differential equations with multiplicative noise. Stability estimates for linear It\^o SDEs using the one, two and $\infty$-norms in the $l$-th mean, where $1 \leq l < \infty $, are derived and the application of the stochastic logarithmic norm is illustrated with examples.
A Novel Approach to Improve the Iterative Detection Convergence of LDPC Coded CPM Modulated Signals

Continuous Phase Modulation (CPM) provides an attractive option for spectral efficient communication systems. Low-Density Parity-Check Code (LDPCC) combined with CPM has a potential to result in a spectrally efficient scheme that is also energy efficient in that it yields low error rates at low signal-to-noise ratios. In this paper we consider the concatenation of a LDPC encoder and a CPM modulator which can be decoded and demodulated iteratively. In order to decrease the positive feedback during iterative detection with short frame, an improved method based on weighed extrinsic information exchange is proposed. Theoretic analysis and simulation results show that the proposed method can not only prevent the phenomena of positive feedback from taking place, reduce the error floor and improve the performance of BER under the condition of low SNR effectively, but also reduce the average number of iteration as well as the iterative decoding delay.
Elevational Gradients in Bird Diversity in the Eastern Himalaya: An Evaluation of Distribution Patterns and Their Underlying Mechanisms

Background Understanding diversity patterns and the mechanisms underlying those patterns along elevational gradients is critically important for conservation efforts in montane ecosystems, especially those that are biodiversity hotspots. Despite recent advances, consensus on the underlying causes, or even the relative influence of a suite of factors on elevational diversity patterns has remained elusive. Methods and Principal Findings We examined patterns of species richness, density and range size distribution of birds, and the suite of biotic and abiotic factors (primary productivity, habitat variables, climatic factors and geometric constraints) that governs diversity along a 4500-m elevational gradient in the Eastern Himalayan region, a biodiversity hotspot within the world's tallest mountains. We used point count methods for sampling birds and quadrats for estimating vegetation at 22 sites along the elevational gradient. We found that species richness increased to approximately 2000 m, then declined. We found no evidence that geometric constraints influenced this pattern, whereas actual evapotranspiration (a surrogate for primary productivity) and various habitat variables (plant species richness, shrub density and basal area of trees) accounted for most of the variation in bird species richness. We also observed that ranges of most bird species were narrow along the elevation gradient. We find little evidence to support Rapoport's rule for the birds of Sikkim region of the Himalaya. Conclusions and Significance This study in the Eastern Himalaya indicates that species richness of birds is highest at intermediate elevations along one of the most extensive elevational gradients ever examined. Additionally, primary productivity and factors associated with habitat accounted for most of the variation in avian species richness. The diversity peak at intermediate elevations and the narrow elevational ranges of most species suggest important conservation implications: not only should mid-elevation areas be conserved, but the entire gradient requires equal conservation attention.
Double milling in self-propelled swarms from kinetic theory

We present a kinetic theory for swarming systems of interacting, self-propelled discrete particles. Starting from the Liouville equation for the many-body problem we derive a kinetic equation for the single particle probability distribution function and the related macroscopic hydrodynamic equations. General solutions include flocks of constant density and fixed velocity and other non-trivial morphologies such as compactly supported rotating mills. The kinetic theory approach leads us to the identification of macroscopic structures otherwise not recognized as solutions of the hydrodynamic equations, such as double mills of two superimposed flows. We find the conditions allowing for the existence of such solutions and compare to the case of single mills.
Two parameter extension of the k-Poincare quantum deformation

We consider the extensions of classical r-matrix for κ-deformed Poincaré algebra which satisfy modified Yang-Baxter equation. Two examples introducing additional deformation parameter (dimension-full 1 κ or dimensionless ξ) are presented. We describe the corresponding quantization (two-parameter κ-Poincaré quantum Hopf algebras) in explicite form as obtained by twisting of standard κ-deformed framework. In the second example quantum twist function depends on nonclassical generators, with κ-deformed coproduct. Finally we mention also the " soft " twists with carrier in fourmomenta sector.
The Theory of Intersectionality: A New Lens for Understanding the Barriers Faced by Autistic Women

While disabilities studies scholars have already taken a great step forward in integrating the theory of intersectionality , progress is still required. Many theoretical and empirical disability studies papers operationalize disability in a vague and all-inclusive manner. Although it is important to research disability in a global way, it is just as important to regard the more specific experiences of disability. The study of specific disabilities and the barriers that are faced by those who have them is critical since living with one type of disability can lead to very different experiences as compared with having a different disability (Hirschmann, 2012). In addition to adding Autism to the discussion of intersectionality within disability studies, it is critical to include a disability studies perspective to other fields of research in order to successfully incorporate an intersectional framework.
Intranasal Immunization with Influenza Virus-Like Particles Containing Membrane-Anchored Cholera Toxin B or Ricin Toxin B Enhances Adaptive Immune Responses and Protection against an Antigenically Distinct Virus

Vaccination is the most effective means to prevent influenza virus infection, although current approaches are associated with suboptimal efficacy. Here, we generated virus-like particles (VLPs) composed of the hemagglutinin (HA), neuraminidase (NA) and matrix protein (M1) of A/Changchun/01/2009 (H1N1) with or without either membrane-anchored cholera toxin B (CTB) or ricin toxin B (RTB) as molecular adjuvants. The intranasal immunization of mice with VLPs containing membrane-anchored CTB or RTB elicited stronger humoral and cellular immune responses when compared to mice immunized with VLPs alone. Administration of VLPs containing CTB or RTB significantly enhanced virus-specific systemic and mucosal antibody responses, hemagglutination inhibiting antibody titers, virus neutralizing antibody titers, and the frequency of virus-specific IFN-γ and IL-4 secreting splenocytes. VLPs with and without CTB or RTB conferred complete protection against lethal challenge with a mouse-adapted homologous virus. When challenged with an antigenically distinct H1N1 virus, all mice immunized with VLPs containing CTB or RTB survived whereas mice immunized with VLPs alone showed only partial protection (80% survival). Our results suggest that membrane-anchored CTB and RTB possess strong adjuvant properties when incorporated into an intranasally-delivered influenza VLP vaccine. Chimeric influenza VLPs containing CTB or RTB may represent promising vaccine candidates for improved immunological protection against homologous and antigenically distinct influenza viruses.
A pedestrian detection system based on binocular stereo

Pedestrian detection in dynamic and outdoor environment is considered to be a challenging task due to complicated scenes and human's various appearances. To achieve more efficient and precise detection, stereo vision is an attractive approach. This paper introduces a pedestrian detection system which makes use of binocular stereo. A new method of ROIs (Regions of Interest) extraction is proposed and the Latent SVM human classifier is employed to make the final decision. The ROIs extraction method uses two-stage segmentation, together with a minimal object scale acquirement approach based on region growing. And new strategies are adopted in the decision-making process to reduce detection errors. Experimental works show that with our approach, the detection speed increases effectively at the same detection rate, and the false alarm rate is substantially reduced.
An overview of methods for dependence analysis of concurrent programs

Program dependence analysis is an analysis technique to identify and determine various program dependencies in source codes, which has been widely used in program understanding, debugging, testing, reverse engineering, and maintenance. However, there are still many difficulties to be solved when carrying out dependence analysis for concurrent programs because the execution of statements is unpredictable. This survey describes methods and research directions for dependence analysis of concurrent programs, especially about how to obtain the dependencies between concurrently executed statements, the factors leading to intransitivity among dependencies, and how to deal with the intransitivity problem. By careful comparisons, users can select a proper algorithm for their requirements.
Effects of a Technology-Assisted Meditation Program on Healthcare Providers’ Interoceptive Awareness, Compassion Fatigue, and Burnout

Research suggests that meditation can relieve stress, cultivate self-regulation skills, improve ability to focus, and modify risk for compassion fatigue (CF) and burnout in healthcare providers. However, studied interventions are time-consuming and combining disparate approaches, resulting in unclear mechanisms of effect. This pilot study examined a novel 6-week technology-assisted meditation program, coherently grounded in the system of yoga therapy that required minimal time. Five 10- to 12-minute meditations were offered via smartphone apps supported by biweekly e-mails. Hospice and palliative professionals at a Midwestern US healthcare network participated in the program (n = 36). Each meditation integrated attention, synchronized breath, gentle movements and a meditation focus. Weekly e-mails introduced a new meditation and reminded participants how and why to practice. The participants used the meditations a mean of 17.18(SD, 8.69) times. Paired t tests found significant presurvey to postsurvey improvements for CF/burnout (P < .05) and interoceptive awareness (P < .001). Participation significantly heightened perceived ability and propensity to direct attention to bodily sensations, increased awareness of physical sensations’ connections to emotions, and increased active body listening. The technology-assisted yoga therapy meditation program successfully motivated providers to meditate. The program required minimal time yet seemed to reduce CF/burnout and improve emotional awareness and self-regulation by heightening attention to present-moment bodily sensations.
Utilizing solar power in wireless sensor networks

Sensor networks are designed especially for deployment in adverse and non-accessible areas without a fixed infrastructure. Therefore, energy conservation plays a crucial role for these networks. We propose to utilize solar power in wireless sensor networks, establishing a topology where, changing over time, some nodes can receive and transmit packets without consuming the limited battery resources. We propose and evaluate two protocols that perform solar-aware routing. The presented simulation results show that both protocols provide significant energy savings when utilizing solar power. The paper shows that incorporating the solar status of nodes in the routing decision is feasible and results in reduced overall battery consumption.