Heuristic algorithms for the Longest Filled Common Subsequence Problem

At CPM 2017, Castelli et al. define and study a new variant of the Longest Common Subsequence Problem, termed the Longest Filled Common Subsequence Problem (LFCS). For the LFCS problem, the input consists of two strings $A$ and $B$ and a multiset of characters $\mathcal{M}$. The goal is to insert the characters from $\mathcal{M}$ into the string $B$, thus obtaining a new string $B^*$, such that the Longest Common Subsequence (LCS) between $A$ and $B^*$ is maximized. Casteli et al. show that the problem is NP-hard and provide a 3/5-approximation algorithm for the problem. In this paper we study the problem from the experimental point of view. We introduce, implement and test new heuristic algorithms and compare them with the approximation algorithm of Casteli et al. Moreover, we introduce an Integer Linear Program (ILP) model for the problem and we use the state of the art ILP solver, Gurobi, to obtain exact solution for moderate sized instances.Comment: Accepted and presented as a proceedings paper at SYNASC 201

USING MANAGEMENT CONTROL TO ALIGN ORGANIZATIONAL STARTEGIES AND TO MEASURE PERFORMANCES

Practice shows that, in order to improve internal and external communication, managers need to increase the request of information about their business administration. So, for this, they need a complementary system which assures them this kind of informa

Car-to-Smartphone Interactions: Experimental Setup, Risk Analysis and Security Technologies

International audienceVehicle access control and in particular access to in-vehicle functionalities from smart mobile devices, e.g., phones or watches, has become an increasingly relevant topic. Security plays a critical part, due to both a long history of car keys that succumbed to attacks and recently reported intrusions that use various vehicle communication interfaces to further gain access to in-vehicle safety-critical components. In this work we discuss existing technologies and functionalities that should be embedded in an experimental setup that addresses such a scenario. We make emphasis on existing cryptographic technologies, from symmetric to asymmetric primitives, identity-based cryptography and group signatures. We also discuss risks associated with in-vehicle functionalities and mitigation, e.g., intrusion detection systems

Watermark Text Pattern Spotting in Document Images

Watermark text spotting in document images can offer access to an often unexplored source of information, providing crucial evidence about a record's scope, audience and sometimes even authenticity. Stemming from the problem of text spotting, detecting and understanding watermarks in documents inherits the same hardships - in the wild, writing can come in various fonts, sizes and forms, making generic recognition a very difficult problem. To address the lack of resources in this field and propel further research, we propose a novel benchmark (K-Watermark) containing 65,447 data samples generated using Wrender, a watermark text patterns rendering procedure. A validity study using humans raters yields an authenticity score of 0.51 against pre-generated watermarked documents. To prove the usefulness of the dataset and rendering technique, we developed an end-to-end solution (Wextract) for detecting the bounding box instances of watermark text, while predicting the depicted text. To deal with this specific task, we introduce a variance minimization loss and a hierarchical self-attention mechanism. To the best of our knowledge, we are the first to propose an evaluation benchmark and a complete solution for retrieving watermarks from documents surpassing baselines by 5 AP points in detection and 4 points in character accuracy

Anti-IL-15 monoclonal antibody for the treatment of coeliac disease: the light at the end of the gluten free diet tunnel?

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Efficient generation of neural stem cell-like cells from adult human bone marrow stromal cells

Clonogenic neural stem cells (NSCs) are self-renewing cells that maintain the capacity to differentiate into brain-specific cell types, and may also replace or repair diseased brain tissue. NSCs can be directly isolated from fetal or adult nervous tissue, or derived from embryonic stem cells. Here, we describe the efficient conversion of human adult bone marrow stromal cells (hMSC) into a neural stem cell-like population (hmNSC, for human marrow-derived NSC-like cells). These cells grow in neurosphere-like structures, express high levels of early neuroectodermal markers, such as the proneural genes NeuroD1, Neurog2, MSl1 as well as otx1 and nestin, but lose the characteristics of mesodermal stromal cells. In the presence of selected growth factors, hmNSCs can be differentiated into the three main neural phenotypes: astroglia, oligodendroglia and neurons. Clonal analysis demonstrates that individual hmNSCs are multipotent and retain the capacity to generate both glia and neurons. Our cell culture system provides a powerful tool for investigating the molecular mechanisms of neural differentiation in adult human NSCs. hmNSCs may therefore ultimately help to treat acute and chronic neurodegenerative diseases