Miracle-dz/UniFAR-FTUs huggingface dataset:
Generalized Orderless Pooling Performs Implicit Salient Matching

Most recent CNN architectures use average pooling as a final feature encoding step. In the field of fine-grained recognition, however, recent global representations like bilinear pooling offer improved performance. In this paper, we generalize average and bilinear pooling to “α-pooling”, allowing for learning the pooling strategy during training. In addition, we present a novel way to visualize decisions made by these approaches. We identify parts of training images having the highest influence on the prediction of a given test image. This allows for justifying decisions to users and also for analyzing the influence of semantic parts. For example, we can show that the higher capacity VGG16 model focuses much more on the bird's head than, e.g., the lower-capacity VGG-M model when recognizing fine-grained bird categories. Both contributions allow us to analyze the difference when moving between average and bilinear pooling. In addition, experiments show that our generalized approach can outperform both across a variety of standard datasets.
Learning task outcome prediction for robot control from interactive environments

In order to manage complex tasks such as cooking, future robots need to be action-aware and posses common sense knowledge. For example flipping a pancake requires a robot to know that a spatula has to be under a pancake in order to succeed. We present a novel approach for the extraction and learning of action and common sense knowledge, and developed a game using a robot-simulator with realistic physics for data acquisition. The game environment is a virtual kitchen, in which a user has to create a pancake by pouring pancake-mix on an oven and flipping it using a spatula. The interaction is done by controlling a virtual robot hand with a 3D input sensor. We incorporate a realistic fluid simulation in order to gather appropriate data of the pouring action. Furthermore, we present a task outcome prediction algorithm for this specific system and show how to learn a failure model for the pouring and flipping action.
Repetition Priming and Anomia: An Investigation of Stimulus Dosage

A single-subject design was used to assess the influence of repeated attempts at picture-naming, coupled with repeated exposure to hearing and reading target words, on the acquisition and maintenance of trained stimuli, and generalization to untrained stimuli. Individuals with chronic aphasia participated in a multi-week repetition priming protocol designed to investigate the affects of stimulus dosage and lexical variables on naming accuracy and latency. Results revealed positive repetition priming effects for trained items across both acquisition and maintenance phases; such positive effects were not observed for untrained stimuli (i.e., response generalization) or alternate exemplars (i.e., stimulus generalization).
Pull-down versus traditional menu types: An empirical comparison

An experiment was conducted to test the performance of pull-down versus traditional or explicit menus. Sixty subjects, including novice and experienced computer users, manipulated both types of menus to complete banking tasks similar to those found on Automatic Teller M achines. The order of the menus was randomly varied to control for learning effects. Across both types of users, traditional-style menus elicited fewer errors than did pull-down menus; however, no significant difference was found in the time to complete the banking task. Experienced users outperformed novice users in the amount of time taken to complete the task regardless of menu type, though no difference was found in the number of errors committed by both user types.
Redefining Security Engineering

For a long time, security was not in the focus of software engineering and system engineering processes. Only quite recently the situation has changed and security issues are now more and more integrated into concrete steps of the development process. Various approaches exist for the elicitation of security requirements, for threat modeling, for risk analysis, or for security testing. These different approaches are more-and-more adapted for practical use and become integrated parts of software development life-cycles. Nevertheless, they only support isolated steps in the process (e.g. security of code) or concentrate on particular types of requirements (e.g. for access control). The long-term goal for security engineering shall be the establishment of processes supporting all steps of the engineering process in an integrated way and to co-ordinate the contributions by different roles in this process. This paper identifies the different tasks of security engineering and discusses what parts of these tasks can be realised by using existing approaches. Further, three embedded scenarios are used to identify some concrete requirements for a security engineering process. This discussion shall show the scope of future research and developments in the area of security engineering and motivate inter-disciplinary approaches to establish security engineering as a research discipline.
Self-Disclosing Trauma and Post-Traumatic Stress Symptoms in Couples: A Longitudinal Study

Objective: Most research concerning the implications of self-disclosure on trauma’s aftermath has focused on the salubrious effects disclosure may foster for the primary victim. However, the manner in which recipients of disclosure are symptomatically affected by it remains unexamined. Of particular interest are spouses who are often the primary support providers and are therefore susceptible to secondary traumatization. Assessing posttraumatic stress symptoms (PTSS) and self-disclosure among traumatized veterans and their wives, the current longitudinal study begins to fill this gap in the literature. Method: A total of 220 couples consisting of Israeli veterans, of whom 128 were former prisoners of war (ex-POWs) and 92 were combatants, and their wives were examined. PTSS and self-disclosure of both partners were assessed 30 and 35 years after the war using the Posttraumatic Stress Disorder Inventory (PTSD-I; Solomon et al., 1993) and the Self-Disclosure Index (SDI; Miller, Berg, & Archer, 1983), respectively. Analyses included Pearson intercorrelations analyses and four stepwise hierarchical multiple regression analyses. Results: Findings indicated that increments in veterans’ disclosure are not only consistently associated with the reduction of their wives’ PTSS but may also explain and predict some of the change in the wives’ PTSS over time. However, such a longitudinal effect was not evident concerning the veterans’ PTSS. Conclusion: Traumatized ex-POWs’ and combatants’ self-disclosure within the marital relationship may contribute to the amelioration of their wives’ secondary traumatization, and thus may be a goal worth pursuing in therapy. However, more research is needed to further understand this relation.
A New Technique for Verifying the Consistency of Distributed R-Trees

The ever-increasing of the large spatial datasets and the widely application of the complex computation have motivated the emergence of distributed algorithms to process spatial operations efficiently. The R-tree index is broadly used by researches as a distributed spatial structure for indexing and retrieval of spatial objects. However, a big challenge has arisen, that is, how to check the consistency of distributed R-Trees. In the past few years researches have been published on both distributed R-Tree and verification of distributed systems. Though none of them has proposed a technique to check the consistency of distributed R-Trees. This article presents a new approach for verifying the consistency of distributed R-Trees, which is called RConsistency. It allows collect information about the distributed R-Tree once it has been created. RConsistency also collects information about the distribute R-Tree and can helps to reduce the overlapping and dead area. It can be used with any index similar to R-Tree, since the RConsistency algorithm uses the nodes organization of the R-Tree to collect consistency information. The algorithm was used on DistGeo, a platform to process distributed spatial operations. A graphic tool, named RConsistency Visualizer, was developed to show the output of the RConsistency algorithm.
Predicting Relative Prominence in Noun-Noun Compounds

There are several theories regarding what influences prominence assignment in English noun-noun compounds. We have developed corpus-driven models for automatically predicting prominence assignment in noun-noun compounds using feature sets based on two such theories: the informativeness theory and the semantic composition theory. The evaluation of the prediction models indicate that though both of these theories are relevant, they account for different types of variability in prominence assignment.
Vaccine Adjuvant MF59 Promotes Retention of Unprocessed Antigen in Lymph Node Macrophage Compartments and Follicular Dendritic Cells

Ag retention within lymph nodes (LNs) upon vaccination is critical for the development of adaptive immune responses, because it facilitates the encounter of the Ag with cognate lymphocytes. During a secondary exposure of the immune system to an Ag, immune complexes (ICs) that contain the unprocessed Ag are captured by subcapsular sinus macrophages and are transferred onto follicular dendritic cells, where they persist for weeks, facilitating Ag presentation to cognate memory B cells. The impact of adjuvants on Ag retention within the draining LNs is unknown. In this article, we provide the first evidence, to our knowledge, that the oil-in-water emulsion adjuvant MF59 localizes in subcapsular sinus and medullary macrophage compartments of mouse draining LNs, where it persists for at least 2 wk. In addition, we demonstrate that MF59 promotes accumulation of the unprocessed Ag within these LN compartments and facilitates the consequent deposition of the IC-trapped Ag onto activated follicular dendritic cells. These findings correlate with the ability of MF59 to boost germinal center generation and Ag-specific Ab titers. Our data suggest that the adjuvant effect of MF59 is, at least in part, due to an enhancement of IC-bound Ag retention within the LN and offer insights to improve the efficacy of new vaccine adjuvants.
Density of Thrombus on Admission CT Predicts Revascularization Efficacy in Large Vessel Occlusion Acute Ischemic Stroke

Background and Purpose— Can lysability of large vessel thrombi in acute ischemic stroke be predicted by measuring clot density on admission nonenhanced CT (NECT), postcontrast enhanced CT, or CT angiogram (CTA)? Methods— We retrospectively studied 90 patients with acute large vessel ischemic strokes treated with intravenous (IV) tPA, intra-arterial (IA) tPA, and/or mechanical thrombectomy devices. Clot density [in Hounsfield unit (HU)] was measured on NECT, postcontrast enhanced CT, and CTA. Recanalization was assessed by the Thrombolysis in Cerebral Infarction grading system (TICI) on digital subtraction angiography. Results— Thrombus density on preintervention NECT correlated with postintervention TICI grade regardless of pharmacological (IV tPA r=0.69, IA tPA r=0.72, P<0.0001) or mechanical treatment (r=0.73, P<0.0001). Patients with TICI≥2 demonstrated higher HU on NECT (mean corrected HU IV tPA=1.58, IA tPA=1.66, mechanical treatment=1.7) compared with patients with TICI<2 (IV tPA=1.39, IA tPA=1.4, mechanical treatment=1.3) (P=0.01, 0.006, <0.0001 respectively). There was no association between recanalization and age, sex, baseline National Institute of Health Stroke Scale, treatment method, time to treatment, or clot volume. Conclusions— Thrombi with lower HU on NECT appear to be more resistant to pharmacological lysis and mechanical thrombectomy. Measuring thrombus density on admission NECT provides a rapid method to analyze clot composition, a potentially useful discriminator in selecting the most appropriate reperfusion strategy for an individual patient.
Perception of distance-to-obstacle through time-delayed tactile feedback

In previous vision-to-touch sensory substitution approaches, including most `electronic white canes', typical approaches include mapping space-to-space, space-to-intensity, or space-to-frequency. To our knowledge, however, mapping space to time-delay has not been considered. Yet, because organisms must anticipate impending collisions with obstacles or anticipate being contacted by approaching objects, many organisms have developed computational short-cuts where distance-to-target is assumed to be proportional to a time-span. This short-cut often manifests itself in low-level sensorimotor behaviours and perceptual mechanisms. We studied whether untrained humans would spontaneously employ such a short-cut to estimate distance-to-obstacle in the absence of vision. The observers pressed a push button and a tactile pulse was delivered to the hand with a delay proportional to the distance to an obstacle detected by an optical range finder that they wore. The observers were not informed of the nature of the coding but could freely probe the obstacle while walking toward the target. Upon randomized presentation of obstacle distances, the observers quickly calibrated their judgement of distance-to-obstacle and were able to estimate this distance within a range of four meters for a proportionality factor corresponding to a velocity of one m/s.
Hypothesis Transformation and Semantic Variability Rules Used in Recognizing Textual Entailment

Based on the core approach of the tree edit distance algorithm, the system central module is designed to target the scope of TE -- semantic variability. The main idea is to transform the hypothesis making use of extensive semantic knowledge from sources like DIRT, WordNet, Wikipedia, acronyms database. Additionally, we built a system to acquire the extra background knowledge needed and applied complex grammar rules for rephrasing in English.
Non-Rigid Spectral Correspondence of Triangle Meshes

We present an algorithm for finding a meaningful vertex-to-vertex correspondence between two triangle meshes, which is designed to handle general non-rigid transformations. Our algorithm operates on embeddings of the two shapes in the spectral domain so as to normalize them with respect to uniform scaling and rigid-body transformation. Invari-ance to shape bending is achieved by relying on approximate geodesic point proximities on a mesh to capture its shape. To deal with moderate stretching, we first raise the issue of “eigenmode switching” and discuss heuristics to bring the eigenmodes to alignment. For additional non-rigid discrepancies in the spectral embeddings, we propose to use non-rigid alignment via thin-plate splines. This is combined with a refinement step based on geodesic proximities to improve dense correspondence. We show empirically that our algorithm outperforms previous spectral methods, as well as schemes that compute correspondence in the spatial domain via non-rigid iterative closest points or the use of local shape descriptors, e.g., 3D shape context. Finally, to speed up our algorithm, we examine the effect of using subsampling and Nystrom method.
Implementing and an empirical study of rank aggregation approaches based on real world instances

Rank aggregation is an essential approach for aggregating the preferences of multiple agents. One rank aggregation rule of particular interest is the Kemeny rule, which maximises the number of pairwise agreements between the final ranking and the existing rankings, and has an important interpretation as a maximum likelihood estimator. However, Kemeny rankings are NP-hard to compute. This has resulted in the development of various algorithms for computing Kemeny rankings. Fortunately, NP-hardness may not reflect the difficulty of solving problems that arise in practice. As a result, we aim to demonstrate that the Kemeny consensus can be computed efficiently when aggregating different rankings in real case. In this paper, we describe a dynamic programming model for aggregating university rankings. We also provide details on the implementation of the model. Finally, we present results obtained from an empirical comparison of different approach models based on real world and randomly generated problem instances, and show that the dynamic programming approach has comparable performance as other approaches.
Managing extensibility and maintainability of industrial robotics software

As neither the set of robotics devices nor the operations they can execute is fixed, a software framework for robotics should be extensible. Moreover, as the environment the robots work in changes, the application controlling them must be easily adaptable to changing requirements. When this can be achieved at run-time, it leads to a continuous evolution of robotics software. This paper presents an object-oriented software framework, the Java-based Robotics API, that facilitates extensibility with code reuse. By integrating the framework into the dynamic module system OSGi, it is possible to continuously evolve a robotics application (including its real-time capable parts).
Risk-Sensitive Learning and Pricing for Demand Response

We consider the setting in which an electric power utility seeks to curtail its peak electricity demand by offering a fixed group of customers a uniform price for reductions in consumption relative to their predetermined baselines. The underlying demand curve, which describes the aggregate reduction in consumption in response to the offered price, is assumed to be affine and subject to unobservable random shocks. Assuming that both the parameters of the demand curve and the distribution of the random shocks are initially unknown to the utility, we investigate the extent to which the utility might dynamically adjust its offered prices to maximize its cumulative <italic>risk-sensitive payoff</italic> over a finite number of <inline-formula> <tex-math notation="LaTeX">${T}$ </tex-math></inline-formula> days. In order to do so effectively, the utility must design its pricing policy to balance the tradeoff between the need to learn the unknown demand model (exploration) and maximize its payoff (exploitation) over time. In this paper, we propose such a pricing policy, which is shown to exhibit an expected payoff loss over <inline-formula> <tex-math notation="LaTeX">${T}$ </tex-math></inline-formula> days that is at most <inline-formula> <tex-math notation="LaTeX">${O(\sqrt {T}\log (T))}$ </tex-math></inline-formula>, relative to an oracle pricing policy that knows the underlying demand model. Moreover, the proposed pricing policy is shown to yield a sequence of prices that converge to the oracle optimal prices in the mean square sense.
Acquisition of Generic Problem Solving Knowledge through Information Extraction and Pattern Mining

In many technical domains, the generic problem-solving knowledge is scarce even hough a large number of concrete resolutions exist and are well documented. This makes the machine learning from resolution traces approach facing a number of challenges, not least among them the complexity of the underlying domain (concepts, relationships, events, processes, etc.) and the machine-readability of the documented resolution. We tackle here the acquisition of expertise in phylogeny, which is a notoriously rich and prolific field where hundreds, if not thousands, concrete cases are reported in the literature, yet tools to assist the phylogenist in analyzing a new dataset are virtually absent. Thus, we propose an approach that amounts to ontology-based workflow mining: Our T-GROWLer system abstracts general patterns from event sequences previously extracted from texts. It comprises two modules -- a workflow extractor and a pattern miner -- both relying on a pair of ontologies (a domain one and a procedural one).
New efficient clustering quality indexes

This paper deals with a major challenge in clustering that is optimal model selection. It presents new efficient clustering quality indexes relying on feature maximization, which is an alternative measure to usual distributional measures relying on entropy, Chi-square metric or vector-based measures such as Euclidean distance or correlation distance. First Experiments compare the behavior of these new indexes with usual cluster quality indexes based on Euclidean distance on different kinds of test datasets for which ground truth is available. This comparison clearly highlights altogether the superior accuracy and stability of the new method on these datasets, its efficiency from low to high dimensional range and its tolerance to noise. Further experiments are then conducted on “real life” textual data extracted from a multisource bibliographic database for which ground truth is unknown. These experiments show that the accuracy and stability of these new indexes allow to deal efficiently with diachronic analysis, when other indexes do not fit the requirements for this task.
Surgical specimen extraction via a prophylactic ileostomy procedure: A minimally invasive technique for laparoscopic rectal cancer surgery

AIM To retrospectively evaluate the safety and feasibility of surgical specimen extraction via a prophylactic ileostomy procedure in patient with rectal cancer. METHODS We systematically reviewed 331 consecutive patients who underwent laparoscopic anterior resection for rectal cancer and prophylactic ileostomy in our institution from June 2010 to October 2016, including 155 patients who underwent specimen extraction via a prophylactic ileostomy procedure (experimental group), and 176 patients who underwent specimen extraction via a small lower abdominal incision (control group). Clinical data were collected from both groups and statistically analyzed. RESULTS The two groups were matched in clinical characteristics and pathological outcomes. However, mean operative time was significantly shorter in the experimental group compared to the control group (161.3 ± 21.5 min vs 168.8 ± 20.5 min; P = 0.001). Mean estimated blood loss was significantly less in the experimental group (77.4 ± 30.7 mL vs 85.9 ± 35.5 mL; P = 0.020). The pain reported by patients during the first two days after surgery was significantly less in the experimental group than in the control group. No wound infections occurred in the experimental group, but 4.0% of the controls developed wound infections (P = 0.016). The estimated 5-year disease-free survival and overall survival rate were similar between the two groups. CONCLUSION Surgical specimen extraction via a prophylactic ileostomy procedure represents a secure and feasible approach to laparoscopic rectal cancer surgery, and embodies the principle of minimally invasive surgery.
XPIR : Private Information Retrieval for Everyone

Abstract A Private Information Retrieval (PIR) scheme is a protocol in which a user retrieves a record from a database while hiding which from the database administrators. PIR can be achieved using mutuallydistrustful replicated databases, trusted hardware, or cryptography. In this paper we focus on the later setting which is known as single-database computationally- Private Information Retrieval (cPIR). Classic cPIR protocols require that the database server executes an algorithm over all the database content at very low speeds which impairs their usage. In [1], given certain assumptions, realistic at the time, Sion and Carbunar showed that cPIR schemes were not practical and most likely would never be. To this day, this conclusion is widely accepted by researchers and practitioners. Using the paradigm shift introduced by lattice-based cryptography, we show that the conclusion of Sion and Carbunar is not valid anymore: cPIR is of practical value. This is achieved without compromising security, using standard crytosystems, and conservative parameter choices.