Miracle-dz/UniFAR-FTUs huggingface dataset:
Recognition of ongoing complex activities by sequence prediction over a hierarchical label space

Human activity recognition from full video sequence has been extensively studied. Recently, there has been increasing interest in early recognition or recognition from partial observation. However, from a small fraction of the video, it might be demanding if not even impossible to make a fine grained prediction of the activity that is taking place. Therefore, we propose the first method to predict ongoing activities over a hierarchical label space. We approach this task as a sequence prediction problem in a recurrent neural network where we predict over a hierarchical label space of activities. Our model learns to realize accuracy-specificity trade-offs over time by starting with coarse labels and proceeding to more fine grained recognition as more evidence becomes available in order to meet a prescribed target accuracy. In order to study this task we have collected a large video dataset of complex activities with long duration. The activities are annotated in a hierarchical label space from coarse to fine. By directly training a sequence predictor over the hierarchical label space, our method outperforms several baselines including prior work on accuracy specificity tradeoffs originally developed for object recognition.
Managing Dynamic Reconfiguration for Fault-tolerance on a Manycore Architecture

With the advent of many core architectures comprising hundreds of processing elements, fault management has become a major challenge. We present an approach that uses the occam-pi language to manage the fault recovery mechanism on a new many core architecture, the Platform 2012 (P2012). The approach is made possible by extending our previously developed compiler framework to compile occam-pi implementations to the P2012 architecture. We describe the techniques used to translate the salient features of the occam-pi language to the native programming model of the P2012 architecture. We demonstrate the applicability of the approach by an experimental case study, in which the DCT algorithm is implemented on a set of four processing elements. During run-time, some of the tasks are then relocated from assumed faulty processing elements to the faultless ones by means of dynamic reconfiguration of the hardware. The working of the demonstrator and the simulation results illustrate not only the feasibility of the approach but also how the use of higher-level abstractions simplifies the fault handling.
Immune monitoring of pancreatic islet graft: towards a better understanding, detection and treatment of harmful events

Importance of the field: Long-term clinical outcomes of islet transplantation are hampered by rejection and recurrence of autoimmunity, which lead to a gradual decrease in islet function usually taking place over the first five years after transplantation. An accurate monitoring strategy could allow for the detection and treatment of harmful immune events, potentially resulting in higher rates of insulin-independence. Areas covered in this review: This article provides a critical review of the various assays currently available for the assessment of allo- and autoimmunity both prior to and after islet transplantation. The accuracy in predicting clinical outcome is specifically addressed. What the reader will gain: Most current tests based on the assessment of allo- and auto-immune antibody are of minimal help in clinical practice. Cell-based tests (including the assessment of cytotoxic T lymphocyte precursors, proliferation tests, enzyme-linked immunospot) have the potential to allow earlier and more accurate detection of harmful events. Take home message: A specific and accurate immune monitoring has the potential to significantly improve islet transplant outcomes. The development and use of such tests (favouring cell-based tests) should be promoted.
Image-guided weathering: A new approach applied to flow phenomena

The simulation of weathered appearance is essential in the realistic modeling of urban environments. A representative and particularly difficult effect to produce on a large scale is the effect of fluid flow. Changes in appearance due to flow are the result of both the global effect of large-scale shape, and local effects, such as the detailed roughness of a surface. With digital photography and Internet image collections, visual examples of flow effects are readily available. These images, however, mix the appearance of flows with the specific local context. We present a methodology to extract parameters and detail maps from existing imagery in a form that allows new target-specific flow effects to be produced, with natural variations in the effects as they are applied in different locations in a new scene. In this article, we focus on producing a library of parameters and detail maps for generating flow patterns; and this methodology can be used to extend the library with additional image exemplars. To illustrate our methodology, we show a rich collection of patterns applied to urban models.
Electro-manipulation of biological cells in microdevices

Electric fields are used to manipulate biological cells for diverse applications that include cell counting and sorting, gene delivery, and the creation of novel hybrid cell-types. Although several of these techniques have established applications, others are less studied and are underutilized. Here, we briefly review several electro-manipulations that we achieved using electric fields generated by a common set of inert planar microelectrodes. We supplement our results with selected examples from the literature, and discuss their potential use within miniaturized platforms for single cell science.
Strontium-Containing Apatite/Poly Lactide Composites Favoring Osteogenic Differentiation and in Vivo Bone Formation

Strontium was shown to enhance bone growth; however, its oral administration may lead to severe side effects. The application of strontium in orthopedic biomaterials may therefore be an alternative to achieve targeted and sustained strontium treatment to the surgery site in aid of bone growth locally. In this study, strontium-containing composites were prepared by introducing various levels of strontium into amorphous apatite and extruding the obtained apatite powders into polylactide in a weight ratio of 1:1. Strontium substitution increased apatite dissolution and enhanced the degradation behavior of the resulting composites. Sustained and dose-dependent strontium release from the composites was observed for up to 24 weeks in simulated physiological solution, indicating that strontium release can be tuned by its substitution level in the embedded apatite. Strontium-containing composites enhanced the osteogenic differentiation of murine mesenchymal stromal cells in vitro in a dose-dependent fashion. After heterotopic implantation with the combination of rhBMP-2, bone formation on strontium-containing composites was enhanced. These results suggest that strontium-releasing composites provide a local ion-rich (i.e., Sr2+ as well as Ca2+ and PO43–) environment that favors osteogenic differentiation and in vivo bone formation
The Web of People: A dual view on the WWW

In this paper, we describe an alternative web paradigm, called the Web of People. Rather than a web of pages, it is a web of persons. The paradigm is motivated by a number of obvious shortcomings of the current Web, in particular its tendency to provide centralized support tools for indexation and search. Instead our model exploits the distributed intelligence of the users. We describe the basic principles of the Web of People, its architecture, and its technical realization in a prototype system called SoMeOne. In particular, we elaborate on a search engine for the Web of People, aimed at finding people that act as relevant information sources.
Redistributive Non-Dissipative Battery Balancing Systems with Isolated DC/DC Converters: Theory, Design, Control and Implementation

Energy storage systems with many Lithium Ion battery cells per string require sophisticated balancing hardware due to individual cells having manufacturing inconsistencies, different self discharge rates, internal resistances and temperature variations. For capacity maximization, safe operation, and extended lifetime, battery balancing is required. Redistributive non-dissipative balancing further improves the pack capacity and efficiency over a Dissipative approach where energy is wasted as heat across shunt resistors. Redistribution techniques dynamically shuttles charge to and from weak cells during operation such that all of the stored energy in the stack is utilized. This thesis identifies and develops different balancing control methods. These methods include a unconstrained optimization problem using a Linear Quadratic Regulator (LQR) and a constrained optimization problem using Model Predictive Control (MPC). These methods are benchmarked against traditional rule based (RB) balancing. The control systems are developed using MATLAB/Simulink and validated experimentally on a multiple transformer individual cell to stack topology. The implementation uses the DC2100A Demo-board from Linear Technology with bi-directional flyback converters to transfer the energy between the cells.
Variable agreement between visual rating scales for white matter hyperintensities on MRI. Comparison of 13 rating scales in a poststroke cohort.

BACKGROUND AND PURPOSE Previous reports on the frequency, extent, and clinical correlates of white matter hyperintensities (WMHIs) have been contradictory. The purpose of this study was to test whether part of this variation could be explained by the different properties of the visual WMHI rating scales used. METHODS The periventricular (PVHIs) and deep white matter (DWMHIs) hyperintensities of 395 poststroke patients were systematically analyzed and transformed to correspond to 13 different rating scales. The scales were compared with the use of Goodman-Kruskal measures of association. The relative frequencies, means, and medians of PVHI and DWMHI grades as well as Spearman rank correlations between WMHI grade and hypertension were calculated. RESULTS At best more than 80% of the patients received an equivalent WMHI grade by different scales, but at worst the corresponding values were only 0.4% for PVHI and 18% for DWMHI. At best different scales categorized patients similarly in regard to WMHI grade, but at worst the corresponding values were 8% for PVHI and 57% for DWMHI ratings. The distribution of WMHI grades also varied, and when the effect of age on WMHI was assessed, some of the scales had a ceiling effect and some had a floor effect. Only 1 of the 7 PVHI, 5 of the 9 DWMHI, and 1 of the 3 combined rating scales showed a significant correlation with arterial hypertension, a putative risk factor for WMHIs. CONCLUSIONS Some of the inconsistencies in previous studies of WMHIs are due to differences in visual rating scales. Our findings may warrant international debate regarding harmonization of WMHI ratings.
Performance of daily activities by older adults with dementia: The role of an assistive robot

Older adults with cognitive impairment often have difficulties in remembering the proper sequence of activities of daily living (ADLs) or how to use the tools necessary to perform ADLs. They, therefore, require reminders in a timely fashion while performing ADLs. This is a very stressful situation for the caregivers of people with dementia. In this paper we describe a pilot study where a tele-operated assistive robot helps a group of older adults with dementia (OAwD) to perform an ADL, namely making a cup of tea in the kitchen. Five OAwD along with their caregivers participated in this study which took place in a simulated-home setting. The purpose of this study was to investigate the feasibility and usability of a robotic system in assisting the OAwD to perform ADL in a home setting. The findings from this study will contribute to achieve our ultimate goal of designing a full-fledged assistive robot that assists OAwD aging in their own homes. The assistive robots designed for people with dementia mostly focus on companionship. This is, to the best of our knowledge, the first attempt to design an assistive robot which will provide step-by-step guidance to people with dementia in their activities of daily living.
Knee Muscular Control During Jump Landing in Multidirections

Background Jump landing is a complex movement in sports. While competing and practicing, athletes frequently perform multi-planar jump landing. Anticipatory muscle activity could influence the amount of knee flexion and prepare the knee for dynamic weight bearing such as landing tasks. Objectives The aim of the present study was to examine knee muscle function and knee flexion excursion as athletes naturally performed multi-direction jump landing. Materials and Methods Eighteen male athletes performed the jump-landing test in four directions: forward (0°), 30° diagonal, 60° diagonal, and lateral (90°). Muscles tested were vastus medialis (VM), vastus lateralis (VL), rectus femoris (RF), semitendinosus (ST), and biceps femoris (BF). A ViconTM 612 workstation collected the kinematic data. An electromyography was synchronized with the ViconTM Motion system to quantify dynamic muscle function. Repeated measure ANOVA was used to analyze the data. Results Jump-landing direction significantly influenced (P < 0.05) muscle activities of VL, RF, and ST and knee flexion excursion. Jumpers landed with a trend of decreasing knee flexion excursion and ST muscle activity 100 ms before foot contact progressively from forward to lateral directions of jump landing. Conclusions A higher risk of knee injury might occur during lateral jump landing than forward and diagonal directions. Athletes should have more practice in jump landing in lateral direction to avoid injury. Landing technique with high knee flexion in multi-directions should be taught to jumpers for knee injury prevention.
Optimization Algorithms for Distributed Queries

The efficiency of processing strategies for queries in a distributed database is critical for system performance. Methods are studied to minimize the response time and the total time for distributed queries. A new algorithm (Algorithm GENERAL) is presented to derive processing strategies for arbitrarily complex queries. Three versions of the algorithm are given: one for minimizing response time and two for minimizing total time. The algorithm is shown to provide optimal solutions under certain conditions.
LOAD BALANCING OVER GEOGRAPHIC ADAPTIVE FIDELITY ROUTING PROTOCOL FOR WIRELESS SENSOR NETWORKS

The energy consumption is a great challenge in Wireless sensor networks that may affect the performance of the entire network. Even though many techniques are being still addressed to this issue, it is ongoing problem. One of the most energy efficient routing protocols is Geographic Adaptive Fidelity (GAF), which is the location based protocol. This reduces the use of energy by switching off some nodes that do not take part in routing. Load balancing reduces hot spots in sensor networks by spreading the workload across a sensor network there by increasing the life time of the sensor network. Here we use chebyshev sum metric for evaluation via simulation and this method is better compared to the routing based on Breadth first search(BFS) and shortest path obtained by Dijkstra’s algorithm. By combining Geographic Adaptive Fidelity with load balancing, a considerable amount of energy can be saved that tends to extend the lifespan of the whole network.
Model-Driven Requirements Specification for Software Product Lines

Model-driven methods for requirements specification in Software Product Lines (SPLs) support the construction of different models to provide a better understanding of each SPL feature and intended use scenarios. However, the different models must be composed to show the requirements of the target applications and, therefore, help to understand how features will be integrated in a new product of a software product line. Although well-established standards for creating metamodels and model transformations exist, there is currently no established foundation that allows practitioners to distinguish between the different modeling and composition approaches for requirements models. This chapter provides an overview of different approaches for specifying requirements models and composing models for specific products of an SPL. In particular, it emphasizes one of the most recurring specification techniques: model-driven and use case scenario-based specification. This technique, in combination with feature models and the Variability Modeling Language for Requirements (VML4RE), integrates our approach for model-driven requirements specification for SPLs.
Assessing the Impact of Sparsification on LSI Performance

We describe an approach to information retrieval using Latent Semantic Indexing (LSI) that directly manipulates the values in the Singular Value Decomposition (SVD) matrices. We convert the dense term by dimension matrix into a sparse matrix by removing a fixed percentage of the values. We present retrieval and runtime performance results, using seven collections, which show that using this technique to remove up 70% of the values in the term by dimension matrix results in similar or improved retrieval performance (as compared to LSI), while reducing memory requirements and query response time. Removal of 90% of the values results in significantly reduced memory requirements and dramatic improvements in query response time. Removal of 90% of the values degrades retrieval performance slightly for smaller collections, but improves retrieval performance by 60% on the large collection we tested.
Cell cycle regulators control centrosome elimination during oogenesis in Caenorhabditis elegans

In many animals, the bipolar spindle of the first zygotic division is established after the contribution of centrioles by the sperm at fertilization. To avoid the formation of a multipolar spindle in the zygote, centrosomes are eliminated during oogenesis in most organisms, although the mechanism of this selective elimination is poorly understood. We show that cki-2, a Caenorhabditis elegans cyclin-dependent kinase (Cdk) inhibitor, is required for their appropriate elimination during oogenesis. In the absence of cki-2, embryos have supernumerary centrosomes and form multipolar spindles that result in severe aneuploidy after anaphase of the first division. Moreover, we demonstrate that this defect can be suppressed by reducing cyclin E or Cdk2 levels. This implies that the proper regulation of a cyclin E–Cdk complex by cki-2 is required for the elimination of the centrosome that occurs before or during oogenesis to ensure the assembly of a bipolar spindle in the C. elegans zygote.
Constructing near spanning trees with few local inspections

Constructing a spanning tree of a graph is one of the most basic tasks in graph theory. Motivated by several recent studies of local graph algorithms, we consider the following variant of this problem. Let G be a connected bounded‐degree graph. Given an edge e in G we would like to decide whether e belongs to a connected subgraph G′ consisting of (1+ϵ)n edges (for a prespecified constant ϵ>0 ), where the decision for different edges should be consistent with the same subgraph G′ . Can this task be performed by inspecting only a constant number of edges in G? Our main results are: We show that if every t‐vertex subgraph of G has expansion 1/(logt)1+o(1) then one can (deterministically) construct a sparse spanning subgraph G′ of G using few inspections. To this end we analyze a “local” version of a famous minimum‐weight spanning tree algorithm. We show that the above expansion requirement is sharp even when allowing randomization. To this end we construct a family of 3‐regular graphs of high girth, in which every t‐vertex subgraph has expansion 1/(logt)1−o(1) . We prove that for this family of graphs, any local algorithm for the sparse spanning graph problem requires inspecting a number of edges which is proportional to the girth. © 2016 Wiley Periodicals, Inc. Random Struct. Alg. , 50, 183–200, 2017
Negative dependence and the geometry of polynomials

We introduce the class of strongly Rayleigh probability measures by means of geometric properties of their generating polynomials that amount to the stability of the latter. This class covers important models such as determinantal measures (e.g. product measures and uniform random spanning tree measures) and distributions for symmetric exclusion processes. We show that strongly Rayleigh measures enjoy all virtues of negative dependence, and we also prove a series of conjectures due to Liggett, Pemantle, and Wagner, respectively. Moreover, we extend Lyons' recent results on determinantal measures, and we construct counterexamples to several conjectures of Pemantle and Wagner on negative dependence and ultra log-concave rank sequences.
Language Identification of Encrypted VoIP Traffic :

Voice over IP (VoIP) has become a popular protocol for making phone calls over the Internet. Due to the potential transit of sensitive conversations over untrusted network infrastructure, it is well understood that the contents of a VoIP session should be encrypted. However, we demonstrate that current cryptographic techniques do not provide adequate protection when the underlying audio is encoded using bandwidth-saving Variable Bit Rate (VBR) coders. Explicitly, we use the length of encrypted VoIP packets to tackle the challenging task of identifying the language of the conversation. Our empirical analysis of 2,066 native speakers of 21 different languages shows that a substantial amount of information can be discerned from encrypted VoIP traffic. For instance, our 21-way classifier achieves 66% accuracy, almost a 14-fold improvement over random guessing. For 14 of the 21 languages, the accuracy is greater than 90%. We achieve an overall binary classification (e.g., “Is this a Spanish or English conversation? ”) rate of 86.6%. Our analysis highlights what we believe to be interesting new privacy issues in VoIP.
Applying Programming by Demonstration in an Intelligent Authoring Tool for Cognitive Tutors

We are building an intelligent authoring tool for Cognitive Tutors, a highly successful form of computer-based tutoring. The primary target users (the authors) are educators who are not familiar with cognitive task analysis and AI programming, which are essential tasks in building Cognitive Tutors. Instead of asking authors to write a cognitive model by hand, a Simulated Student embedded in the authoring tool lets an author demonstrate how to perform the tasks in the subject domain, for instance, solving an algebra equation. The Simulated Student observes an author’s demonstration and induces a set of production rules that replicate the demonstrated performances. Correct production rules, as well as production rules that are incorrect but similar to those a human student might produce, can be directly embedded in the Cognitive Tutor. We give a preliminary evaluation of an implemented Simulated Students based on inductive logic programming and path-finding.