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For the ultrasensitive determination of 244Pu by accelerator mass spectrometry, a suitable methodology was developed at the IFIN-HH AMS laboratory. Alpha spectrometry was used to verify the performance of the radiochemical procedure for plutonium extraction, including preparation of alpha sources by electrodeposition and microprecipitation. The chemical yield for plutonium extraction from environmental samples was found to be reasonable (∼86%) for our purposes. The 244Pu AMS measurements were performed using two AMS systems, 1 MV (IFIN-HH) and 3 MV (CIRCE) accelerators. The spectra collected using chemical blanks clearly show the zero background when measuring mass 244, while a total measurement efficiency for both systems of the order of 10−4 was estimated. Regarding the concentration of 244Pu per gram of sediment, we obtained hundreds of atto-grams per gram for the sediment of Bikini Atoll, while for the sediment of the Pacific Ocean the level is of the order of several tens of atto-grams per gram. In addition, we determined isotopic ratios for 240Pu/239Pu and 244Pu/239Pu for both certified reference materials, and they are in fine agreement within the 2σ limits when comparing the two AMS systems used in this work as well as compared to other published results. [ABSTRACT FROM AUTHOR]

While trying to fill in empty positions in a short time frame, struggling to find the best candidates while competing with other recruiters for them, nowadays, HR personnel need to consider innovative ways for reaching faster the IT professionals. Manually searching across professional networks is no longer an option. This study introduces the prototype of a system that automatically screens the candidates in the IT field. Its main goal is to provide a valuable support in the first stage of the personnel selection by decreasing the number of errors that can occur when thousands of CVs/profiles are manually filtered to pick candidates for an interview. Our proposed system consists in a mobile application that automatically selects online profiles from professional websites (like Indeed, LinkedIn, Monster) and ranks them, to finally display the eligible candidates for a particular open position to the recruiter. We developed an ontology to support the matching between the knowledge in the candidate's resume and the requirements in the job description. While developing the ontology our primary focus was on the skills that are encompassed in a resume, as these are the key abilities when searching for the ideal candidate. The knowledge a job seeker should possess, respectively a job description requires, is divided in the following categories: programming languages, databases, frameworks, integrated development environments, methodologies and operating systems. First part of the implementation, automatically extracting the skills from unstructured resumes, was achieved using Apache Tika and GATE. [ABSTRACT FROM AUTHOR]

Nowadays, the continuous demand for qualified candidates in the IT domain has empowered the use of e-Recruitment tools, which are becoming more and more exploited at the expense of the traditional methods. This study focuses on the use of ontologies in developing a job recommender system, which helps to automatically match job offers with the candidates' profiles and in reverse. In order to design the IT e-Recruitment ontology we have gathered a list with all the features a platform of this kind should provide, for both the job seeker and the recruiter. Based on the selected requirements, we developed the ontology that offers all the necessary means to implement such a job recommender system, designed to connect people with job opportunities and backwards. The second part of the paper proposes a Java based architecture to implement the e-Recruitment platform. To convert the users' input into RDF description, RDF2Go and RDFBeans APIs are employed. Storing and retrieving the data make use of the Jena Framework, which provides dedicated interfaces for accessing the Fuseki2 Server over HTTP. Finally, the prototype of the e-Recruitment platform is presented, together with its core functionalities. [ABSTRACT FROM AUTHOR]