Miracle-dz/UniFAR-FTUs huggingface dataset:
Adapting Descriptions of People to the Point of View of a Moving Observer

This paper addresses the task of generating descriptions of people for an observer that is moving within a scene. As the observer moves, the descriptions of the people around him also change. A referring expression generation algorithm adapted to this task needs to continuously monitor the changes in the field of view of the observer, his relative position to the people being described, and the relative position of these people to any landmarks around them, and to take these changes into account in the referring expressions generated. This task presents two advantages: many of the mechanisms already available for static contexts may be applied with small adaptations, and it introduces the concept of changing conditions into the task of referring expression generation. In this paper we describe the design of an algorithm that takes these aspects into account in order to create descriptions of people within a 3D virtual environment. The evaluation of this algorithm has shown that, by changing the descriptions in real time according to the observers point of view, they are able to identify the described person quickly and effectively.
SCALING BAYESIAN OPTIMIZATION UP TO HIGHER DIMENSIONS: A REVIEW AND COMPARISON OF RECENT ALGORITHMS

Bayesian optimization is known to be a method of choice when it comes to solving optimization problems involving black-box, non-convex and low-dimensional functions in a few iterations. Yet, how to scale this method up to higher dimensions is a challenging and still unsolved research issue. In this paper, we first present and structure recent axes of research addressing this topic. We then experimentally compare three selected high-dimensional Bayesian optimization algorithms to random search on diverse high-dimensional functions. Our results suggest that no algorithm consistently outperforms the others across all types of difficulties encountered and that random search is in general very competitive, confirming recent research results.
Flow and changes in appearance

An important, largely unexplored area of computer image generation is the simulation of weathering and its effects on appearance. Weathering results from the interaction of the environment with the materials in the world. The ﬂow of water is one of the most pervasive and important natural forces involved in the weathering of materials, producing a distinctive set of patterns of washes and stains. This paper presents an intuitive phenomenological model for the ﬂow of water over surfaces that is capable of generating such changes in appearance. We model the ﬂow as a particle system, each particle representing a “drop” of water. The motion of the water particles is controlled by parameters such as gravity, friction, wind, roughness, and constraints that force the particles to maintain contact with the surface. The chemical interaction of the water with the surface materials is governed by a set of coupled differential equations describing both the rate of absorption of water by the surface and the rate of solubility and sedimentation of deposits on the surface. To illustrate the power of this simple model, we show examples of ﬂows over complex geometries made from different materials; the resulting patterns are striking and very difﬁcult to achieve using traditional tex-turing techniques.
Coordinated Regulation of Intracellular Fascin Distribution Governs Tumor Microvesicle Release and Invasive Cell Capacity

Tumor cell invasion is one result of the bidirectional interactions occurring between tumor cells and the surrounding milieu. The ability of tumor cells to invade through the extracellular matrix is in part regulated by the formation of a class of protease-loaded extracellular vesicles, called tumor microvesicles (TMVs), which are released directly from the cell surface. ABSTRACT Tumor cell invasion is one result of the bidirectional interactions occurring between tumor cells and the surrounding milieu. The ability of tumor cells to invade through the extracellular matrix is in part regulated by the formation of a class of protease-loaded extracellular vesicles, called tumor microvesicles (TMVs), which are released directly from the cell surface. Here we show that the actin bundling protein, fascin, redistributes to the cell periphery in a ternary complex with podocalyxin and ezrin, where it promotes TMV release. The peripheral localization of fascin is prompted by the loss of Rab35 signaling, which in turn unleashes ARF6 activation. The result is a mechanism through which Rab35 and ARF6 cooperatively and simultaneously regulate the distribution and localization of fascin and promote oncogenic signaling, which leads to TMV release while inhibiting invadopodium formation. These studies are clinically significant as fascin-loaded TMVs can be detected in bodily fluids and elevated fascin expression coupled with low Rab35 levels correlates with poor overall survival in some cancers.
Downlink Performance of MRT-BD in Multiuser Massive MIMO with Low Resolution ADCs

The multiuser massive MIMO (multi-input multi-output) system using the low-resolution analog-to-digital converters (ADCs) in the uplink is to realize low cost and power consumption demands, which, however, reduce the signal quality. Beamforming as a signal processing technique can supply high throughputs in the MIMO systems. In this paper, we investigate the robustness of low-resolution ADCs against the interference among the different streams in the uplink and the different users in downlink systems respectively, and propose the maximum ratio transmission - block diagonalization (MRT-BD) scheme as a kind of beamforming to evaluate the effects of low-resolution ADCs in the full digital massive MIMO system. The preliminary conclusion is that the MRT-BD scheme achieves our anticipation to make the rate achievable, even more than it in the infinite-resolution (no quantization) of BD case can be approached using ADCs with only a few bits of resolution.
Coloring in the Links

The richness that characterizes relationships is often absent when they are modeled using computational methods in network science. Typically, relationships are represented simply as links, perhaps with weights. The lack of finer granularity is due in part to the fact that, aside from linkage and strength, no fundamental or immediately obvious dimensions exist along which to categorize relationships. Here we propose a set of dimensions that capture major components of many relationships -- derived both from relevant academic literature and people's everyday descriptions of their relationships. We first review prominent findings in sociology and social psychology, highlighting dimensions that have been widely used to categorize social relationships. Next, we examine the validity of these dimensions empirically in two crowd-sourced experiments. Ultimately, we arrive at a set of ten major dimensions that can be used to categorize relationships: similarity, trust, romance, social support, identity, respect, knowledge exchange, power, fun, and conflict. These ten dimensions, while not dispositive, offer higher resolution than existing models. Indeed, we show that one can more accurately predict missing links in a social graph by using these dimensions than by using a state-of-the-art link embeddedness method. We also describe tinghy.org, an online platform we built to collect data about how social media users perceive their online relationships, allowing us to examine these dimensions at scale. Overall, by proposing a new way of modeling social graphs, our work aims to contribute both to theory in network science and practice in the design of social-networking applications.
DRIVE: Discovery seRvice for fully-Integrated 5G enVironmEnt in the IoT

A lot of research is being carried out about Internet of Things (IoT) and in the following years it will emerge more and more in our lives. Furthermore, with the advent of future fully-integrated 5G networks, new constraints need to be satisfied such as ultra-reliability and low-latency. With the help of Fog computing and the Multi-access Edge Computing (MEC) framework, services can be offered to the end users in a fast and practical way. Our work presents DRIVE a framework for service discovery in a 5G environment. However, in order to guarantee dynamic distribution and best management of services, we plan to deploy those services as container (e.g. Docker container). Moreover, we propose distribution of edge services at three different layer of communication: Application, Service, and Communication Layer. Given the above considerations, we propose an edge node, placed at the edge of network, that acts as the "brain" and take over the computation. The main innovative elements of the proposed framework, compared to the existing literature, include the possibility to select the working layer, the dynamic reconfiguration of the edge node and the field experimental results about the performance achieved by our solution over rapidly deployable environments with resourcelimited edge nodes such as Raspberry Pi devices.
Optimal Solving of Permutation-based Optimization Problems on Heterogeneous CPU/GPU Clusters

We revisit the parallelization of Branch-and-Bound (B&B) algorithms on massively parallel and heterogeneous architectures integrating multi-core processors and GPU accelerators. We provide a comprehensive description of the incremental development of a B&B-algorithm for the exact resolution of large permutation-based combinatorial optimization problems (COP). In order to highlight the challenges related to the different levels of the algorithm, we proceed incrementally by increasing the complexity of the targeted hardware step-by-step (as shown in Fig. 1) from sequential to multi-core, to GPUs and multi-GPU systems and finally to heterogeneous clusters combining multi-core CPUs and accelerator devices. On a cluster composed of 9 GPU- accelerated compute nodes (130,000 CUDA cores) the described methodology reduces the resolution time for a hard instance of the flow shop scheduling problem (FSP) from 600 hours (using 300 CPUs) to 9 hours1. Three permutation problems with different computational characteristics are used for experimental evaluation: FSP, quadratic assignment (QAP) and the N-Queens problem.
Optimizing Data Layout and System Configuration on FPGA-based Heterogeneous Platforms

The most attractive feature of field-programmable gate arrays (FPGAs) is their configuration flexibility. However, if the configuration is performed manually, this flexibility places a heavy burden on system designers to choose among a vast number of configuration parameters and program transformations. In this paper, we improve the state-of-the-art with two main innovations: First, we apply compiler-automated transformations to the data layout and program statements to create streaming accesses. Such accesses are turned into streaming interfaces when the kernels are implemented in hardware, allowing the kernels to run efficiently. Second, we use two-step mixed integer programming to first minimize the execution time and then to minimize energy dissipation. Configuration parameters are chosen automatically, including several important ones omitted by existing models. Experimental results demonstrate significant performance gains and energy savings using these techniques.
A flexible integration strategy for in-car telematics systems

This paper presents an approach for the planning of integration tests of automotive telematics systems. To our knowledge no method for the determination of an integration order exists that takes the project and the system environment into account, which in our opinion greatly influence the integration order. Furthermore, most known test generation methods and structural quality measures demand syntactically sound specifications to be applied efficiently. In our projects Message Sequence Charts are often created manually from the scratch with many different tools, and therefore they are of rather low syntactical quality. This paper addresses the determination of an integration strategy, which can easily be adapted to changes in the project or in the system environment, and which can be manually applied to any given specification.
Real-time relief mapping on arbitrary polygonal surfaces

We present a technique for mapping relief textures onto arbitrary polygonal models in real time, producing correct self-occlusions, interpenetrations, shadows and per-pixel lighting. The technique uses a pixel-driven formulation based on an efficient ray-height-field intersection implemented on the GPU. It has very low memory requirements, supports extreme close-up views of the surfaces and can be applicable to surfaces undergoing deformation.
In-the-wild facial expression recognition in extreme poses

In the computer research area, facial expression recognition is a hot research problem. Recent years, the research has moved from the lab environment to in-the-wild circumstances. It is challenging, especially under extreme poses. But current expression detection systems are trying to avoid the pose effects and gain the general applicable ability. In this work, we solve the problem in the opposite approach. We consider the head poses and detect the expressions within special head poses. Our work includes two parts: detect the head pose and group it into one pre-defined head pose class; do facial expression recognize within each pose class. Our experiments show that the recognition results with pose class grouping are much better than that of direct recognition without considering poses. We combine the hand-crafted features, SIFT, LBP and geometric feature, with deep learning feature as the representation of the expressions. The handcrafted features are added into the deep learning framework along with the high level deep learning features. As a comparison, we implement SVM and random forest to as the prediction models. To train and test our methodology, we labeled the face dataset with 6 basic expressions.
DFKI-MLT System Description for the WMT18 Automatic Post-editing Task

This paper presents the Automatic Post-editing (APE) systems submitted by the DFKI-MLT group to the WMT’18 APE shared task. Three monolingual neural sequence-to-sequence APE systems were trained using target-language data only: one using an attentional recurrent neural network architecture and two using the attention-only (transformer) architecture. The training data was composed of machine translated (MT) output used as source to the APE model aligned with their manually post-edited version or reference translation as target. We made use of the provided training sets only and trained APE models applicable to phrase-based and neural MT outputs. Results show better performances reached by the attention-only model over the recurrent one, significant improvement over the baseline when post-editing phrase-based MT output but degradation when applied to neural MT output.
Presence of an Agrobacterium-Type Tumor-Inducing Plasmid in Neorhizobium sp. NCHU2750 and the Link to Phytopathogenicity

Abstract The genus Agrobacterium contains a group of plant-pathogenic bacteria that have been developed into an important tool for genetic transformation of eukaryotes. To further improve this biotechnology application, a better understanding of the natural genetic variation is critical. During the process of isolation and characterization of wild-type strains, we found a novel strain (i.e., NCHU2750) that resembles Agrobacterium phenotypically but exhibits high sequence divergence in several marker genes. For more comprehensive characterization of this strain, we determined its complete genome sequence for comparative analysis and performed pathogenicity assays on plants. The results demonstrated that this strain is closely related to Neorhizobium in chromosomal organization, gene content, and molecular phylogeny. However, unlike the characterized species within Neorhizobium, which all form root nodules with legume hosts and are potentially nitrogen-fixing mutualists, NCHU2750 is a gall-forming pathogen capable of infecting plant hosts across multiple families. Intriguingly, this pathogenicity phenotype could be attributed to the presence of an Agrobacterium-type tumor-inducing plasmid in the genome of NCHU2750. These findings suggest that these different lineages within the family Rhizobiaceae are capable of transitioning between ecological niches by having novel combinations of replicons. In summary, this work expanded the genomic resources available within Rhizobiaceae and provided a strong foundation for future studies of this novel lineage. With an infectivity profile that is different from several representative Agrobacterium strains, this strain may be useful for comparative analysis to better investigate the genetic determinants of host range among these bacteria.
A case of locally-advanced Merkel cell carcinoma progressing with disseminated bone marrow metastases

EJD, vol. 28, n◦ 4, July-August 2018 could have been widespread atherosclerosis. However, such a diagnosis is not consistent with the inflammatory syndrome or the marked improvement in skin lesions upon immunosuppressive treatment. In a series of TA patients with cutaneous lesions, erythematous nodules were reported in 75% of cases, with necrotizing or granulomatous vasculitis in 73% of the pathological samples [5]. Panniculitis or granulomatous necrotizing panniculitis, fibrin thrombi in dermal vessels, and subcutaneous septal fibrosis were also found. In Japan, pyoderma gangrenosum or pyoderma gangrenosum-like ulcers are the most common cutaneous manifestations in TA, located on the trunk, buttock, and/or genitalia in 40% of cases [6]. Histological examination showed neutrophilic infiltrates and leukocytoclasis in the papillary dermis, and necrotizing vasculitis in a few cases [5, 6], suggesting that TA affects not only large arterial vessels, but also small vessels, as suspected in our patient. In the absence of specific pathological features, we cannot exclude that skin lesions resulted from reduced vascular flow, secondary to the inflammatory occlusion of large vessels, leading to tissue ischaemia. Interestingly, erythema was located precisely over occlusion of the underlying arteries. The neurological symptoms were compatible with ischaemia of the vasa nervorum that irrigates the lumbar plexus, as previously described in TA [7]. In summary, we present an original case of TA revealed by unusual cutaneous manifestations consisting of erythema in a “boxer-short” distribution, with necrotic ulceration close to the more prominent vascular occlusion, associated with multiple radiculopathies of ischaemic origin.
TableChat: Mobile Food Journaling to Facilitate Family Support for Healthy Eating

Support from family members is an important determinant of health. In this work, we probe opportunities for facilitating family support with TableChat, a chat-based mobile application for food journaling. Leveraging food as a test case of family support, TableChat virtually extends the experience of bonding over the dinner table. We surveyed 158 people about their existing family support practices and deployed TableChat with 10 families in the field. We found that tangible support was the most common form of support shared in TableChat and also the most appreciated by participants. However, we found that participants valued not only supportive actions taken by their family members, but also those deliberately not taken (e.g., not buying junk food). Finally, families reported that journaling meals eaten apart aided the exchange of support, satisfied curiosity, and provided a "check-in" that everything was alright, whereas journaling meals eaten together felt redundant. We conclude with a framework that illustrates how informatics tools can be designed to complement rather than compete with existing family interactions.
Multi-encoder Transformer Network for Automatic Post-Editing

This paper describes the POSTECH’s submission to the WMT 2018 shared task on Automatic Post-Editing (APE). We propose a new neural end-to-end post-editing model based on the transformer network. We modified the encoder-decoder attention to reflect the relation between the machine translation output, the source and the post-edited translation in APE problem. Experiments on WMT17 English-German APE data set show an improvement in both TER and BLEU score over the best result of WMT17 APE shared task. Our primary submission achieves -4.52 TER and +6.81 BLEU score on PBSMT task and -0.13 TER and +0.40 BLEU score for NMT task compare to the baseline.
Preparative enrichment of human tissue cells capable to change a site of growth in vitro or in vivo - Recent developments

Abstract Human cells are heterogeneous in regard to their biochemical features and functions. Detailed knowledge about each single cell type is important to understand the whole organism. In order to get a deeper insight in the concert of life, it has to be considered that cell populations such as thyroid cells, epithelial breast cells, endothelial cells, or chondrocytes are heterogeneous in regard to function, RNA expression patterns and protein content. This is true for normal cells and even more relevant for cancer cells. A number of sophisticated methods were developed to enrich cohorts of cells generally belonging to a defined type but outstanding by distinct characteristics, which can be detected by microscopic, proteomic or genomic methods. There is a great interest to investigate human cells, which are able to change their site of growth within the human body leaving an original site, migrating through vessels and reentering another site. In this review experiments are summarized showing that the application of microgravity-exposure of human cells and cell electrophoresis enable a characterization of cells, which leave a site of growth to enter another one. Biochemical features of separated subpopulations are described and their usefulness for deeper investigation is highlighted.
rucrdtw: Fast time series subsequence search in R

Calculating a DTW alignment is computationally relatively expensive, and as a consequence DTW is often a bottleneck in time series data mining applications. The UCR Suite (Rakthanmanon et al. 2012) provides a highly optimized algorithm for best-match subsequence searches that avoids unnecessary distance computations and thereby enables fast DTW and Euclidean Distance queries even in data sets containing trillions of observations.
Run-time correlation engine for system monitoring and testing

We present an approach and implementation for run-time correlation of large volumes of log data and symptom matching of know issues in the context of large enterprise applications. Our solution provides for (a) automatic data collection, (b) data normalisation into a common format, (c) run time correlation and analysis of the data to give a coherent view of system behaviour at run-time and (d) a symptom matching mechanism that can identify known errors in the correlated data on the fly. We have implemented our approach in the form of the Run-Time Correlation Engine (RTCE) and have applied it in a real industry test.
Improving quality through software process improvement in Thailand

For almost 10 years there have been attempts in Thailand to improve software quality by adopting western software process improvement models. Only 17 of the 380 companies in Thailand were able to implement software process models that we see here in the US. 14 out of the 17 companies were not able to improve their process to a higher level. Why were companies not successful in implementing these software process models? Did they find other ways to improve quality? The objective of this paper is to analyze the experiences of software developers, project managers and executive managers in implementing these software process models in Thailand. The results will show that cultural differences are a key factor to this problem. Thai people have different cultural values. which we will explore further in this paper.