Directional Decision Lists

In this paper we introduce a novel family of decision lists consisting of highly interpretable models which can be learned efficiently in a greedy manner. The defining property is that all rules are oriented in the same direction. Particular examples of this family are decision lists with monotonically decreasing (or increasing) probabilities. On simulated data we empirically confirm that the proposed model family is easier to train than general decision lists. We exemplify the practical usability of our approach by identifying problem symptoms in a manufacturing process.Comment: IEEE Big Data for Advanced Manufacturin

Attraction and Retention of Generations X, Y and Z in the Workplace

Abstract Human Resource Management has been challenged with maximizing production and increasing the bottom line since its introduction to the work place. Various techniques have been utilized over the years, customized to the values and beliefs of the generations making up the work force. Now that we are in recovery from the recession it has become an employee’s market and human resource departments find themselves in what is now being described as a war for talent. During our history, attraction and retention of quality employees has been accomplished by offering a higher wage, better benefits package, or pension plan. Employees were motivated to do well in the hopes of keeping their job for a lifetime and therefore enjoying the retirement benefits provided by their employer. Loyalty to employers was high and it was not uncommon for an individual to spend their entire career with one corporation. Generations of late have seen these opportunities all but disappear. Money is no longer the motivating factor it once was. Work life balance, schedule flexibility, freedom to express ideas, team atmosphere, and personal beliefs meshing with those of the company you work for, have become more important. Individuals want to work in a place whose beliefs and values mirror their own; they want to work for companies that exhibit social responsibility, and have a reputation of operating with fairness and integrity. Companies who are able to establish themselves as a great place to work will have the competitive advantage in the marketplace of the future

Why are the stayers staying with “No Excuses” Charter Management Organizations (CMOs)? : a qualitative study on teacher retention at “No Excuses” CMOs

Teacher retention at “No Excuses” Charter Management Organizations (NECMOs) lags behind traditional and public charter schools. This study focused on three NECMO schools in a Texas urban area with higher than normal teacher retention rates. Nine teacher “stayers” with at least three years of experience at their specific school were interviewed as well as six administrators. Key findings were that teacher stayers at these schools made their decision to stay or leave their school based on the quality of their direct managers, e.g. assistant principal, the caliber of their relationship with their colleagues on their teaching team, the short- and long-term relationships they developed with students, opportunities to engage in leadership roles, and their commute to work. Policy implications include a focus on these social constructs over other teacher retention initiatives and a review of the effectiveness of Teacher Career Pathway programs on teacher retention.Educational Leadership and Polic

Noir ontology : existing in the fragmented spaces of Los Angeles.

Noir Ontology: Existing in the Fragmented Urban Spaces of Los Angeles explores the role of decentered urban geography within the body of noir texts set within Los Angeles. By focusing on the development of the idea of Los Angeles in early to mid-Twentieth century literature and film, this essay argues that Alain Badiou\u27s system of ontology provides a critical apparatus for investigating the many ways in which the Los Angeles sunshine myth organizes the relations between individuals within particular urban spaces. Through an analysis of the city\u27s early cultural history, Roman Polanski and Robert Towne\u27s film Chinatown, and Chester Himes\u27s novel If He Hollers Let Him Go, this project develops the concept of an LA noir ontology that expresses a suspicion towards post-industrial urban development and the modifications that it makes to everyday life while echoing Badiou\u27s contemporary critique of the role capitalism in contemporary globalized society

Sea-ice deformation forecasts for the MOSAiC Arctic drift campaign in the SIDFEx database

The Sea Ice Drift Forecast Experiment (SIDFEx) database comprises more than 180,000 forecasts for trajectories of single sea-ice buoys in the Arctic and Antarctic, collected since 2017. SIDFEx is a community effort originating from the Year Of Polar Prediction. Forecasts are provided by various forecast centres and collected, and archived by the Alfred Wegener Institute (AWI). AWI provides a dedicated software package and an interactive online platform for analysing the forecasts. Their lead times range from daily to seasonal scales. Among the buoys targeted by SIDFEx are the buoys of the Distributed Network (DN) array which was deployed during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. In this contribution, we show to what extent the deformation (divergence, shear and vorticity) of the DN can be forecasted by the SIDFEx forecasts. We investigate the performance of single models as well as a consensus forecast which merges the single forecasts to a seamless best-guess forecast

Spatial Damped Anomaly Persistence of the sea ice edge as a benchmark for dynamical forecast systems

Accelerated loss of the sea-ice cover and increased human activities in the Arctic emphasize the need for skillful prediction of sea-ice conditions at subseasonal to seasonal (S2S) timescales. To assess the quality of predictions, dynamical forecast systems can be benchmarked against reference forecasts based on present and past observations of the ice edge. However, the simplest types of reference forecasts—persistence of the present state and climatology—do not exploit the observations optimally and thus lead to an overestimation of forecast skill. For spatial objects such as the ice-edge location, the development of damped-persistence forecasts that combine persistence and climatology in a meaningful way poses a challenge. We have developed a probabilistic reference forecast method that combines the climatologically derived probability of ice presence with initial anomalies of the ice-edge location, both derived from satellite sea-ice concentration data. No other observations, such as sea-surface temperature or sea-ice thickness, are used. We have tested and optimized the method based on minimization of the Spatial Probability Score. The resulting Spatial Damped Anomaly Persistence forecasts clearly outperform both simple persistence and climatology at subseasonal timescales. The benchmark is about as skillful as the best-performing dynamical forecast system in the S2S database. Despite using only sea-ice concentration observations, the method provides a challenging benchmark to assess the added value of dynamical forecast systems