RealText-asg: A Model to Present Answers Utilizing the Linguistic Structure of Source Question

Recent trends in Question Answering (QA) have led to numerous studies focusing on pre-senting answers in a form which closely re-sembles a human generated answer. These studies have used a range of techniques which use the structure of knowledge, generic lin-guistic structures and template based ap-proaches to construct answers as close as pos-sible to a human generate answer, referred to as human competitive answers. This paper re-ports the results of an empirical study which uses the linguistic structure of the source ques-tion as the basis for a human competitive answer. We propose a typed dependency based approach to generate an answer sen-tence where linguistic structure of the ques-tion is transformed and realized into a sen-tence containing the answer. We employ the factoid questions from QALD-2 training ques-tion set to extract typed dependency patterns based on the root of the parse tree. Using iden-tified patterns we generate a rule set which is used to generate a natural language sentence containing the answer extracted from a knowl-edge source, realized into a linguistically cor-rect sentence. The evaluation of the approach is performed using QALD-2 testing factoid questions sets with a 78.84 % accuracy. The top-10 patterns extracted from training dataset were able to cover 69.19 % of test questions.

Selecting Contextual Peripheral Information for Answer Presentation: The Need for Pragmatic Models

This paper explores the possibility of pre-senting additional contextual information as a method of answer presentation Question An-swering. In particular the paper discusses the result of employing Bag of Words (BoW) and Bag of Concepts (BoC) models to retrieve contextual information from a Linked Data resource, DBpedia. DBpedia provides struc-tured information on wide variety of entities in the form of triples. We utilize the QALD question sets consisting of a 100 instances in the training set and another 100 in the testing set. The questions are categorized into single entity and multiple entity questions based on the number of entities mentioned in the ques-tion. The results show that both BoW (syn-tactic models) and BoC (semantic models) are not capable enough to select contextual infor-mation for answer presentation. The results further reveals that pragmatic aspects, in par-ticular, pragmatic intent and pragmatic infer-ence play a crucial role in contextual informa-tion selection in the answer presentation.

SECURE COMMUNICATION USING PFS IN A DISTRIBUTED ENVIRONMENT

Today millions of ordinary citizens are using networks for banking, shopping and filing their tax return. Network security has become a massive problem. All this requires network to identify its legal users for providing services. An authentication protocol used is Kerberos which uses strong secret key for user authentication but it is vulnerable in case of weak passwords. Authentication  & key distribution protocols requires sharing secret key(s) with a view that only the concerned users know to derive the information from it. These protocols are vulnerable to key guessing attacks. Another important consideration is perfect forward secrecy in which our proposed scheme cover cases with application servers, authentication servers or clients key are revealed & their combination. In this paper our proposed scheme deal with key guessing attacks, perfect forward secrecy and protocols for few combinations of keys. All these protocols are based on the fact that the keys are weak & can be exploited easily

Lexicalizing DBpedia with Realization Enabled Ensemble Architecture: RealText lex2 Approach

Abstract. DBpedia encodes massive amounts of open domain knowledge and is growing by accumulating more triples at the same rate as Wikipedia. However, the applications often require natural language formulations of these triples to present the information as a natural text. The RealText lex2 framework offers a scalable platform to transform these triples to natural language sentences using lexicalization patterns. The framework has evolved from its previous version (RealText lex ) and is comprised of four lexicalization pattern mining modules which derive patterns from a training triple collection. These patterns can be then applied on the new triples given that they satisfy a defined set of constraints

An Organic Acid-induced Synthesis and Characterization of Selenium Nanoparticles

A simple wet chemical method has been developed to synthesize selenium nanoparticles (size 40–100 nm), by the reaction of sodium selenosulphate precursor with different organic acids in aqueous medium, under ambient conditions. Polyvinyl alcohol has been used to stabilize the selenium nanoparticles. The synthesized nanoparticles can be separated from its sol by using a high-speed centrifuge and can be redispersed in aqueous medium with a sonicator. UV-visible optical absorption spectroscopy, X-ray diffraction, energy dispersive X-rays, differential scanning calorimetry, atomic force microscopy, and transmission electron microscopy techniques have been employed to characterize the synthesized selenium nanoparticles

A "NOTCH" deeper into the epithelial-to-mesenchymal transition (EMT) program in breast cancer

Notch signaling is a primitive signaling pathway having various roles in the normal origin and development of each multicellular organisms. Therefore, any aberration in the pathway will inevitably lead to deadly outcomes such as cancer. It has now been more than two decades since Notch was acknowledged as an oncogene in mouse mammary tumor virus-infected mice. Since that discovery, activated Notch signaling and consequent up-regulation of tumor-promoting Notch target genes have been observed in human breast cancer. Moreover, consistent over-expression of Notch ligands and receptors has been shown to correlate with poor prognosis in human breast cancer. Notch regulates a number of key processes during breast carcinogenesis, of which, one key phenomenon is epithelial–mesenchymal transition (EMT). EMT is a key process for large-scale cell movement during morphogenesis at the time of embryonic development. Cancer cells aided by transcription factors usurp this developmental program to execute the multi-step process of tumorigenesis and metastasis. In this review, we recapitulate recent progress in breast cancer research that has provided new perceptions into the molecular mechanisms behind Notch-mediated EMT regulation during breast tumorigenesis

Advances in pulmonary drug delivery targeting microbial biofilms in respiratory diseases

The increasing burden of respiratory diseases caused by microbial infections poses an immense threat to global health. This review focuses on the various types of biofilms that affect the respiratory system and cause pulmonary infections, specifically bacterial biofilms. The article also sheds light on the current strategies employed for the treatment of such pulmonary infection-causing biofilms. The potential of nanocarriers as an effective treatment modality for pulmonary infections is discussed, along with the challenges faced during treatment and the measures that may be implemented to overcome these. Understanding the primary approaches of treatment against biofilm infection and applications of drug-delivery systems that employ nanoparticle-based approaches in the disruption of biofilms are of utmost interest which may guide scientists to explore the vistas of biofilm research while determining suitable treatment modalities for pulmonary respiratory infections. </jats:p