Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring Snapchat as a dynamic capture tool for social networking in persons with aphasia

ABSTRACT Background: Physical, communication, geographic, and attitudinal factors place individuals with aphasia at risk for social isolation. Social networking applications may reduce the impact of such factors, providing an accessible context that reduces isolation. While individuals with aphasia desire to use social networking technologies, high linguistic demands and complex interface design constrain participation. Modified social networking applications may scaffold successful participation, capitalizing on multimodality communication tools, including photograph-based exchange to support participation. Aims: This study examined the ability of individuals with aphasia to share daily experiences using Snapchat. The utility of the Snapchat platform in facilitating social exchange opportunities among individuals with aphasia was also explored. Methods & Procedures: Six participants with aphasia participated in a 1-month trial of peer-to-peer social networking via Snapchat, using iPods equipped with Snapchat. Following hands-on training and an aphasia-friendly reference manual, participants posted images using Snapchat. Technology support was provided throughout the trial. Screenshots of posted images with or without text or other modalities were collected during the 1-month trial. Qualitative coding characterized the nature of posted images. Post-trial interviews were recorded from five out of the six participants. Outcomes & Results: A total of 126 posts were collected (0–20 per day, 4–47 per person). Images, unaccompanied by text or drawing features, accounted for 79% of posts. Three participants accounted for almost 50% of the posts. Qualitative analyses generated three schemes for characterizing images: objective, engagement, and identity. Post-trial interviews revealed unanimous dissatisfaction with Snapchat as a social networking tool. While participants reported minor difficulties with technology and access to application, the primary barriers were a lack of reciprocity with other participants. Conclusions: Although the participants reported difficulty with Snapchat, they each used posts to share about themselves. Participants shared meaningful images, sometimes augmented with text or drawing. Our research team concluded that there is a need for individualized, ongoing access to technology support for troubleshooting. Further, participants need to feel comfortable in utilizing that support. Constraints on use, necessary for data collection, complicated implementation and reduced participation. Our team believes that offering individuals with aphasia more freedom to use the application features, such as friend-to-friend communication, would reduce challenges with viewing and responding to peer posts. Individuals with aphasia express a desire for a reviewable timeline of posts that they can revisit as many times as they like, at their own pace. Despite dissatisfaction expressed by participants, Snapchat and related applications hold promise as universally available social networking tools given some adjustments.
Supervised localization of cell nuclei on TMA images

We consider the problem of localizing renal cancer cell nuclei in Tissue Micro Array (TMA) images. We address this problem in three steps. An initial image processing-based procedure finds potential candidate nuclei, while the subsequent phase employs a trained classifier to prune the candidate cell nuclei found in the first. A third phase is then used to perform a clustering of the positive classified blobs. In this work, we study cases when the second step is attained by extracting fixed size patches centred on the candidates, and representing these images with pixel-intensity histograms or related pair-wise distances (dissimilarities). Our results, based on a Parzen classifier in the histogram feature space, show that the proposed procedure attains an optimal Fl-measure 0/0.9152 in localizing cell nuclei, providing state-of-the-art performance.
Allocation of Computational Resources for Soft MIMO Detection

We consider soft multiple-input multiple-output (MIMO) detection for the case of block fading. That is, the transmitted codeword spans over several independent channel realizations and several instances of the detection problem must be solved for each such realization. We develop methods that adaptively allocate computational resources to the detection problems of each channel realization, under a total per-codeword complexity constraint. Our main results are a formulation of the problem as a mathematical optimization problem with a well-defined objective function and constraints, and algorithms that solve this optimization problem efficiently computationally.
A Novel Hybridization of Artificial Neural Networks and ARIMA Models for Forecasting Resource Consumption in an IIS Web Server

Software aging has been observed in a long running software application. A technique named rejuvenation is proposed to counteract this problem. The key to the aging and rejuvenation problem is how to analyze/forecast the resource consumption of software system. In this paper, we propose a methodology of hybrid ARIMA and artificial neural networks to forecast resource consumption in an IIS web server which is a running commercial server and subjected to software aging. The proposed hybrid method consists of two steps. In the first step, an ARIMA model is used to analyze the linear component of the data. In the second step, an artificial neural network model is developed to model the residuals from ARIMA model. The results show that the proposed hybrid model can be a good trade-off to forecast resource consumption.
Structural Logistic Regression for Link Analysis

We present Structural Logistic Regression, an extension of logistic regression to modeling relational data. It is an integrated approach to building regression models from data stored in relational databases in which potential pre- dictors, both boolean and real-valued, are generated by structured search in the space of queries to the database, and then tested with statistical information crite- ria for inclusion in a logistic regression. Using statistics and relational represen- tation allows modeling in noisy domains with complex structure. Link prediction is a task of high interest with exactly such characteristics. Be it in the domain of scientific citations, social networks or hypertext, the underlying data are ex- tremely noisy and the features useful for prediction are not readily available in a "flat" file format. We propose the application of Structural Logistic Regression to building link prediction models, and present experimental results for the task of predicting citations made in scientific literature using relational data taken from the CiteSeer search engine. This data includes the citation graph, authorship and publication venues of papers, as well as their word content.
Research on a Dynamic Dispatching System of Service Grid

In order to implement the balanced distribution of the Service Grid system and to improve the utilization ratio of the resource as well as handling up rate of the system, the system of dynamic dispatching system basing on the Grid service has been designed and implemented after the study on the Grid service. Firstly, a layered loading balancing scheduling mode has been proposed, providing the structure of the dispatching service system. Secondly, a comprehensive service distribution algorithm has been designed and implemented in consideration of respective local service counts, each join points’ performance and current load distribution. Finally, the result of the experiment indicates that the scheduling system can improve the efficiency of dispatching service and the utilization ratio of distributed Grid resource.
A fixed budget analysis of randomized search heuristics for the traveling salesperson problem

Randomized Search heuristics are frequently applied to NP-hard combinatorial optimization problems. The runtime analysis of randomized search heuristics has contributed tremendously to their theoretical understanding. Recently, randomized search heuristics have been examined regarding their achievable progress within a fixed time budget. We follow this approach and present a first fixed budget runtime analysis for a NP-hard combinatorial optimization problem. We consider the well-known Traveling Salesperson problem (TSP) and analyze the fitness increase that randomized search heuristics are able to achieve within a given fixed budget.
Regular Open APIs

Open APIs are software intermediaries that make it possible for application programs to interact with data and processes, which can both be viewed as forms of services. In many scenarios, when one wants to obtain or publish a new service, one would like to check whether the new functionality can simply be obtained by suitably composing existing services. In this paper we study this problem by distinguishing between the two forms of services, that we call data-centric and process-centric, respectively. In the former, each API is an abstraction of a query specified on a data source, and composition amounts to building a new query by using the available APIs as views over the data. In the latter, each API abstracts a process made up by sequences of atomic actions, and composition means realizing a new process by suitably using the APIs exposed by the available services. We make the assumption that the semantics of services is specified by means of one of the most basic formalisms used in Computer Science, namely, regular languages. As a result, we get a rich analysis framework, where composition shows similarities to conformant and conditional planning. We describe composition principles and automated synthesis techniques for each of the two settings.
Physiological Responses of Kosteletzkya virginica to Coastal Wetland Soil

Effects of salinity on growth and physiological indices of Kosteletzkya virginica seedlings were studied. Plant height, fresh weight (FW), dry weight (DW), and net photosynthetic rate (P n) increased at 100 mM NaCl and slightly declined at 200 mM, but higher salinity induced a significant reduction. Chlorophyll content, stomatal conductance (G s), intercellular CO2 concentration (C i), and transpiration rate (E) were not affected under moderate salinities, while markedly decreased at severe salinities except for the increased C i at 400 mM NaCl. Furthermore, no significant differences of F v/F m and ΦPSII were found at lower than 200 mM NaCl, whereas higher salinity caused the declines of F v/F m, ΦPSII, and qP similar to P n, accompanied with higher NPQ. Besides, salt stress reduced the leaf RWC, but caused the accumulation of proline to alleviate osmotic pressure. The increased activities of antioxidant enzymes maintained the normal levels of MDA and relative membrane permeability. To sum up, Kosteletzkya virginica seedlings have good salt tolerance and this may be partly attributed to its osmotic regulation and antioxidant capacity which help to maintain water balance and normal ROS level to ensure the efficient photosynthesis. These results provided important implications for Kosteletzkya virginica acting as a promising multiuse species for reclaiming coastal soil.
Locality, Causality and Noncommutative Geometry

We analyse the causality condition in noncommutative field theory and show that the nonlocality of noncommutative interaction leads to a modification of the light cone to the light wedge. This effect is generic for noncommutative geometry. We also check that the usual form of energy condition is violated and propose that a new form is needed in noncommutative spacetime. On reduction from light cone to light wedge, it looks like the noncommutative dimensions are effectively washed out and suggests a reformulation of noncommutative field theory in terms of lower dimensional degree of freedom. This reduction of dimensions due to noncommutative geometry could play a key role in explaining the holographic property of quantum gravity.
PathGen Usage Examples

The following example shows how Pathgen has been used to perform analyses. They are intended to provide use cases for users who need the information that Pathgen can provide. Three copies of chromosome 21 (Trisomy 21) leads to phenotypes collectively referred to as Down syndrome (DS). Although it is known that approximately 300 genes are found on human chromosome 21 (Hsa21), and DS comprises a number of clinically defined phenotypes, relationships between genotype and phenotype are largely unknown (Epstein, 2001; Van Cleve and Cohen, 2006). Furthermore, the interaction between trisomic and non-trisomic genes in determining a DS phenotype is also not well defined (Roper and Reeves, 2006). A phenotype based approach to defining the genetic mechanisms of DS has been successful at unraveling some of these complexities (Roper, et al., 2006; Roper, et al., 2008). Craniofacial anomalies are distinctive phenotype common to all individuals with DS and persist from early prenatal to postnatal and adult stages Both newborn and adult Ts65Dn mice, a segmental trisomy DS model with about half of the Hsa21 gene orthologs, display similar craniofacial abnormalities as individuals with DS (Hill, et al., 2007; Reeves, et al., 1995; Richtsmeier, et al., 2000). Recently we demonstrated that the small mandible in Ts65Dn mice, a segmental trisomy model of DS, results from a reduced number of neural crest cells (NC) in a small PA1, a developmental precursor of the mandible, at embryonic day 9.5 (Roper, et al., 2008). Additional experiments using in vitro neural tube explants and NC cell culture have shown that NC generation and migration from the neural tube as well as the proliferation of NC in the PA1 is altered in Ts65Dn embryos. The addition of Sonic hedgehog (Shh) growth factor to trisomic cells from PA1 increased cell number to the same level as untreated control cells. Given previous demonstrations of a deficit in mitogenic response to Shh by trisomic cerebellar granule cell precursors, these results implicate common cellular and molecular bases of multiple DS phenotypes (Roper, et al., 2006). Shh and additional non-Hsa21 genes, including Fgf8, Bmp4, and Bmp2, are essential to NC formation and function in the E9.5 mandibular precursor (Basch and Bronner-Fraser, 2006). Additionally, a number of Hsa21 orthologs found in three copies in Ts65Dn mice are expressed in the PA1 normal mice at E9.5 (Gitton, et al., 2002; Reymond, et al., 2002). We hypothesize that the genes that influence NC and mandibular …
Parallel implementation of an adaptive, multigrid solver for the implicit solution of nonlinear parabolic systems, with application to a multi-phase-field model for tumour growth

The first half of the paper provides an overview of a new engineering software tool that is designed for the efficient solution of problems that may be modeled as systems of linear and nonlinear partial differential equations (PDEs) of parabolic type. Our tool is built upon the PARAMESH library, [15], which provides hierarchical mesh adaptivity in parallel in two and three dimensions. Our discretizations are based upon cell-centred finite difference schemes in space and implicit multi-step methods in time (primarily the second order backward differential formula (BDF2)). This results in the need to solve a nonlinear algebraic system at each time step, and we have implemented an optimal nonlinear multigrid method based upon full approximation scheme (FAS). The second half of the presentation illustrates the application of this new software framework to a challenging application, namely a multi-phase-field model of tumour growth [18]. We show some typical simulations for growth of the model tumours, and these results demonstrate second-order convergence in both space and time. We conclude with a discussion of the challenges of obtaining highly scalable parallel performance for a software tool that combines both local mesh adaptivity (requiring efficient dynamic load-balancing) and a multigrid solver (requiring careful implementation of coarse grid operations and inter-grid transfer operations in parallel).
A biologically inspired visual attention framework for artificial systems

In this report we are going to illustrate and detail our research efforts on the investigation of mechanisms implied in visual attention and on the definition of a methodology to transfer them to an artificial agent in order to attain rapid selection of meaningful points in a wide field of view. This research is integrated in a broader one aimed to the study of perception as the privileged tool to learn and reason about the world and subsequently interact with it. In so doing, attention is a way to bridge the gap between low level data acquisition and high level reasoning functions. Within this scope vision is of course the preferred sensory modality to exploit, given the rich amount of dense and high resolution information it can provide. In human brain most of the sensor processing is indeed related to vision. Active vision is the skill that allows to control vision sensors and to filter visual signals in order to respond to particular tasks and external stimuli in a fast and effective way. In biological systems it enables faster processing and reacting, providing meaningful information for subsequent activities such as navigation, manipulation, movements planning, interaction with the environment and with other partners, to mention only a few. The cognitive process at the very core of active vision is attention. This is a crucial capability since it optimizes the deployment of limited cognitive and memory resources. As such processing constraints arise in robotic platforms as well, particularly in real time tasks, visual attention and oculomotor planning are nowadays among the most challenging issues in computer vision. Endowing an artificial system with attentive abilities means to simplify several cognitive and vision tasks, to speed up object detection and recognition so as routines in task learning frameworks. Moreover is a crucial feature in the field of cognitive robotics as it fosters movement, action and intention recognition, grounding reasoning, inference and internal representation of the world on perception of significant social cues and interaction with humans.
Comparison methods of edge detection for USG images

This study discussed on a comparison of three techniques for edge detection of ultrasonography (USG) image. Ultrasound images are used to provide information about fetal development in the womb. The image generated by the two-dimensional ultrasound has not been able to provide complete information. Therefore, in order get the form of fetus on ultrasound image can be clearly identified with the necessary process of image analysis that can detect the boundaries of objects edges, so that it can differentiate between one object with another object on the ultrasound image. Comparison results between the edge detection methods namely Sobel, Prewitt and Canny are expected obtaining the best technique. It can be used in the ultrasound image segmentation process to obtain the best shape of the object of USG image. Based on the available data it can be concluded that the best edge detection methods is produced by Sobel method. The results show that Sobel Edge Detection has the best accuracy compared to other methods with a threshold value of 0.03. (Based on the research, Canny and Prewitt have the same value. Therefore, MSE of Sobel is lower than Canny and Prewitt. Information fetal development in the womb can be seen through a scanning process with ultrasonography technology. The resulting image of the process of two-dimensional ultrasonography has not been able to provide complete information.
IMDGuard: Securing implantable medical devices with the external wearable guardian

Recent studies have revealed security vulnerabilities in implantable medical devices (IMDs). Security design for IMDs is complicated by the requirement that IMDs remain operable in an emergency when appropriate security credentials may be unavailable. In this paper, we introduce IMDGuard, a comprehensive security scheme for heart-related IMDs to fulfill this requirement. IMDGuard incorporates two techniques tailored to provide desirable protections for IMDs. One is an ECG based key establishment without prior shared secrets, and the other is an access control mechanism resilient to adversary spoofing attacks. The security and performance of IMDGuard are evaluated on our prototype implementation.
Using Multicore Reuse Distance to Study Coherence Directories

Researchers have proposed numerous techniques to improve the scalability of coherence directories. The effectiveness of these techniques not only depends on application behavior, but also on the CPU's configuration, for example, its core count and cache size. As CPUs continue to scale, it is essential to explore the directory's application and architecture dependencies. However, this is challenging given the slow speed of simulators. While it is common practice to simulate different applications, previous research on directory designs have explored only a few—and in most cases, only one—CPU configuration, which can lead to an incomplete and inaccurate view of the directory's behavior. This article proposes to use multicore reuse distance analysis to study coherence directories. We develop a framework to extract the directory access stream from parallel least recently used (LRU) stacks, enabling rapid analysis of the directory's accesses and contents across both core count and cache size scaling. A key part of our framework is the notion of relative reuse distance between sharers, which defines sharing in a capacity-dependent fashion and facilitates our analyses along the data cache size dimension. We implement our framework in a profiler and then apply it to gain insights into the impact of multicore CPU scaling on directory behavior. Our profiling results show that directory accesses reduce by 3.3× when scaling the data cache size from 16KB to 1MB, despite an increase in sharing-based directory accesses. We also show that increased sharing caused by data cache scaling allows the portion of on-chip memory occupied by the directory to be reduced by 43.3%, compared to a reduction of only 2.6% when scaling the number of cores. And, we show certain directory entries exhibit high temporal reuse. In addition to gaining insights, we also validate our profile-based results, and find they are within 2--10% of cache simulations on average, across different validation experiments. Finally, we conduct four case studies that illustrate our insights on existing directory techniques. In particular, we demonstrate our directory occupancy insights on a Cuckoo directory; we apply our sharing insights to provide bounds on the size of Scalable Coherence Directories (SCD) and Dual-Grain Directories (DGD); and, we demonstrate our directory entry reuse insights on a multilevel directory design.