RooStats for Searches

The RooStats toolkit, which is distributed with the ROOT software package, provides a large collection of software tools that implement statistical methods commonly used by the High Energy Physics community. The toolkit is based on RooFit, a high-level data analysis modeling package that implements various methods of statistical data analysis. RooStats enforces a clear mapping of statistical concepts to C++ classes and methods and emphasizes the ability to easily combine analyses within and across experiments. We present an overview of the RooStats toolkit, describe some of the methods used for hypothesis testing and estimation of confidence intervals and finally discuss some of the latest developments.Comment: Contributed to "PHYSTAT 2011 Workshop on Statistical Issues Related to Discovery Claims in Search Experiments and Unfolding

Playing an Insecure Hand

For a growing number of families and workers in Western New York, low-wage work is the only—or the last—employment option. In 2009, one out of four jobs in the region were in occupations where the median annual wage fell below the poverty line for a family of four. This rising reliance on low-wage work is a discouraging change from the post-war economic boom when incomes and standards of living soared—a period that continues to shape our employment and lifestyle expectations. Actions by an array of individuals and groups—unbound by ideology—are essential for alleviating regional economic insecurity

Working Hours in Supply Chain Chinese and Thai Factories: Evidence From the Fair Labor Association’s ‘Soccer Project’

This paper examines the determinants of working excessive hours, defined as working in excess of 60 hours per week or for more than six consecutive days, in Chinese and Thai supply-chain factories. We use a matched employer-employee dataset collected from 15 Chinese and Thai footwear and sporting apparel supply-chain factories, which supply international brands. Matched employer-employee data allows us to examine the effect of worker and firm characteristics on hours worked. We find that in addition to the demographic and human capital characteristics of workers, firm-level characteristics and worker awareness of how to refuse overtime are important factors in explaining variation in hours worked.China, hours worked, supply chain factories

Global Manufacturing and Collaborative Tools

The project analyzes the current practices of Stanlok/REM and suggests means by which this corporation can increase global collaboration through the application of web-based engineering tools. Research was conducted in the field of software design, focusing on the communication between Java and SQL, along with preliminary study of relational databases. Proposed software was designed and implemented creating a server-based software tool which allows employees from any location to access and manage a manufacturing cost estimation dataset and deliver real-time simultaneous cost calculation

Information technology and the transformation of mass societies. Information technology today

International audienceThe goal is to analyze the formation and content of the notion of Information Society (Joho shakai). The point is that it needs to be understood not as a technology but as part of techno-industrial system in the sense of Bertrand Gille and Gilbert Simondon.La notion de "société de l'information" ne désigne pas une technologie générique qui en serait l'infrastructure mais l'émergence d'un nouveau système technique, tel que Bertrand Gille et Gilbert Simondon permettent de le penser et analyser

Old and new Italian multinational firms

After a quick profile of Italian foreign direct investments since 1900 and a short review of the main explanations of the lagged multinational growth by Italian manufacturing companies, a quick glimpse of business histories is given to the only two still today living "old protagonists" (Pirelli, Fiat) and to three old corporate groups (Olivetti, SNIA Viscosa, Montecatini-Montedison) who had also reached a significant degree of full internationalization early in the XX century, but during the second postwar period underwent profound dismantling of their original business mission. Finally the paper focuses on few cases of "new protagonists", mid-size family companies who undertook a true multinational strategy only in the most recent decades and today represent the core of the Italian "fourth capitalism".Italian industry-multinational companies

Knowledge graph for manufacturing cost estimation of gear shafts - a case study on the availability of product and manufacturing information in practice

Growing cost pressure forces companies to actively manage their product costs to secure profitability. Here, manufacturing cost estimation within product development estimates manufacturing and material costs. As most products are developed in generations, needed product and manufacturing information can origin from reference system elements (RSE), for example similar components of prior product generations. Problematically, this product and manufacturing information as well as the knowledge of its interrelation is often stored in an unstructured way, document based or at least not machine-readable. This makes manufacturing cost estimation an effortful, time consuming and mainly manual activity with low traceability, where a wide manufacturing knowledge is required. Trends in production, like new manufacturing processes and production systems further increase the need for manufacturing information and knowledge. Knowledge graphs as semantic technologies can improve the findability and reusability of reference system elements and enable automatic information processing. Within this research, cost estimation of research and development of a large automotive supplier was used as research environment. Guided by the model of PGE an ontology for the manufacturing cost estimation domain was developed. Then, a knowledge graph was instantiated based on product and manufacturing information from gear shafts of electric axles. A case study was carried out to evaluate process-specific cycle time calculation as exemplary use case of the knowledge graph. Process-specific cycle times are generally effortful estimated based on detailed manufacturing information and then used together with machine hourly rates to estimate manufacturing costs. Here, the structured and machine-readable manufacturing information of identified reference system elements is extracted from the knowledge graph to reduce the effort, increase the traceability and enable future automation. The case study shows exemplary, how a knowledge graph can support manufacturing cost estimation of gear shafts where product and manufacturing information is automatically identified using reference system elements

MECHANICAL ENGINEERING STUDENTS’ LEARNING STYLES AND THEIR PERCEPTION OF PROFESSION

In this study, it was aimed to explore learning styles of third year mechanical engineering students and also their perception of profession. Ninety-nine third year students studying mechanical engineering at a university located southwest of Turkey were the participants of this study. Data were collected through Kolb Learning Styles Inventory (KLSI) and a Word Association Test with the keyword “engineer” (WAT). Data obtained from KLSI were used in order to identify the participants’ learning styles and data gathered by WAT were used to obtain information about their perception of their future profession. Four groups, namely assimilators, accommodators, divergers, and convergers were formed according to analysis of KLSI and WAT’s of each group have examined separately. Conceptualizing of their future profession for each learning group was visualized by concept maps. It was found that majority of participants have assimilating and converging learning styles and learning styles have an effect on their perception of profession.   Article visualizations

Examining Students’ Covariational Reasoning Through Mathematical Modeling Activities Embedded in the Context of the Greenhouse Effect

The greenhouse effect is one of the most pressing environmental as well as social issues of the present age. In news media and weather reports, most of the essential information about the phenomenon is expressed in forms of graphs and pictures. However, the interpretation of such graphs is challenging for students; they often focus on the shape of the graphs, overlooking the covariational relationships between the concerned quantities. Building on the framework of critical mathematics literacy and social justice mathematics, in this study I aimed to explore the power of dynamic mathematical modeling activities for engaging students in covariational reasoning and developing their understanding about the greenhouse effect. More specifically, this study aimed to explore a) the extent to which students’ understanding of the greenhouse effect and covariational reasoning changed as a result of their engagement with the mathematical modeling activities, and b) the ways in which students may reason covariationally as they engage with mathematical modeling activities in the context of the greenhouse effect. To engage students in covariational reasoning in the context of the greenhouse effect, three NetLogo dynamic simulations and accompanied activities were developed and implemented in two sixth-grade classrooms in the form of a whole class design experiment. Both quantitative and qualitative data were collected in the form of pre- and post-assessments and video recordings of whole class discussions and small group interactions. The analysis of the quantitative data shows a significant improvement in post-assessment scores of the treatment group students compared to their peers in a control group. The qualitative analysis that followed helped me understand the meaning of the improved post-assessment scores by studying students’ reasoning as they interacted with the simulations. The analysis of the qualitative data indicates that the design of the three simulations and activities as well as the targeted questioning provided a productive space for students to engage in different levels of covariational reasoning according to Carlson et al.’s mental action framework and helped them identify the causes and the consequences of the greenhouse effect