Happening in Plain Sight: An Evaluation of Sexual Harassment in Municipal Government Through A Case Study of Newark, New Jersey

In the city of Newark, New Jersey, Sebrevious Scott, a participant in the New Jersey Reentry program was hired as part-time office assistant in the city\u27s re-entry office. After being transferred to the city’s Parks and Grounds Departments, she started being sexually harassed, inappropriately touched and propositioned by her supervisor, Richard Kirkland. Scott made repeated attempts to report these actions through the appropriate channels. She was met with dismissal, resistance, and later retaliation. While working in this hostile environment she was also pursuing a full-time employment opportunity with the city upon the completion of the reentry program. Unfortunately, this never came to fruition due to the behavior of her supervisor and other city staff. Scott eventually filed a gender discrimination complaint with the Equal Employment Opportunity Commission (EEOC). Following this filing and after two leaves of absences, Scott was notified that she had been terminated from her job. In performing this case study, the goal is to address the pervasive incidents of harassment taking place in municipal government. It will illustrate the challenges that victims face when trying to seek relief and how for vulnerable populations, e.g., part time, low wage, minority, and women employees the challenges are far greater. A discussion on how power dynamics play a major role along with workplace culture and male-dominated leadership teams contribute to this problem. An emphasis on strengthening policies and procedures will be reviewed, as well as a focus on the job environment and diversifying employees. Not only are these cases costly to municipalities regarding legal fees and other related expenditures, but it also has an adverse effect on employee morale, public trust in government, and general safety

Multidimensional Data Visual Exploration by Interactive Information Segments

Visualization techniques provide an outstanding role in KDD process for data analysis and mining. However, one image does not always convey successfully the inherent information from high dimensionality, very large databases. In this paper we introduce VSIS (Visual Set of Information Segments), an interactive tool to visually explore multidimensional, very large, numerical data. Within the supervised learning, our proposal approaches the problem of classification by searching of meaningful intervals belonging to the most relevant attributes. These intervals are displayed as multi–colored bars in which the degree of impurity with respect to the class membership can be easily perceived. Such bars can be re–explored interactively with new values of user–defined parameters. A case study of applying VSIS to some UCI repository data sets shows the usefulness of our tool in supporting the exploration of multidimensional and very large data

Machine-Part cell formation through visual decipherable clustering of Self Organizing Map

Machine-part cell formation is used in cellular manufacturing in order to process a large variety, quality, lower work in process levels, reducing manufacturing lead-time and customer response time while retaining flexibility for new products. This paper presents a new and novel approach for obtaining machine cells and part families. In the cellular manufacturing the fundamental problem is the formation of part families and machine cells. The present paper deals with the Self Organising Map (SOM) method an unsupervised learning algorithm in Artificial Intelligence, and has been used as a visually decipherable clustering tool of machine-part cell formation. The objective of the paper is to cluster the binary machine-part matrix through visually decipherable cluster of SOM color-coding and labelling via the SOM map nodes in such a way that the part families are processed in that machine cells. The Umatrix, component plane, principal component projection, scatter plot and histogram of SOM have been reported in the present work for the successful visualization of the machine-part cell formation. Computational result with the proposed algorithm on a set of group technology problems available in the literature is also presented. The proposed SOM approach produced solutions with a grouping efficacy that is at least as good as any results earlier reported in the literature and improved the grouping efficacy for 70% of the problems and found immensely useful to both industry practitioners and researchers.Comment: 18 pages,3 table, 4 figure

Microcellular Electrode Material for Microbial Bioelectrochemical Systems Synthesized by Hydrothermal Carbonization of Biomass Derived Precursors

V.F. acknowledges a UQ Postdoctoral Fellowship. This work was supported by the Australian Research Council Grant DP110100539. The authors acknowledge the facilities and the scientific and technical assistance of the Australian Microscopy & Microanalysis Research Facility at the Centre for Microscopy and Microanalysis (The University of Queensland). The Ghent University Special Research Fund (BOF) is acknowledged for the postdoctoral grant of M.N.B

A computational study on outliers in world music

The comparative analysis of world music cultures has been the focus of several ethnomusicological studies in the last century. With the advances of Music Information Retrieval and the increased accessibility of sound archives, large-scale analysis of world music with computational tools is today feasible. We investigate music similarity in a corpus of 8200 recordings of folk and traditional music from 137 countries around the world. In particular, we aim to identify music recordings that are most distinct compared to the rest of our corpus. We refer to these recordings as ‘outliers’. We use signal processing tools to extract music information from audio recordings, data mining to quantify similarity and detect outliers, and spatial statistics to account for geographical correlation. Our findings suggest that Botswana is the country with the most distinct recordings in the corpus and China is the country with the most distinct recordings when considering spatial correlation. Our analysis includes a comparison of musical attributes and styles that contribute to the ‘uniqueness’ of the music of each country