Indicators of School Crime and Safety: 2015

Our nation's schools should be safe havens for teaching and learning, free of crime and violence. Any instance of crime or violence at school not only affects the individuals involved, but also may disrupt the educational process and affect bystanders, the school itself, and the surrounding community (Brookmeyer, Fanti, and Henrich 2006; Goldstein, Young, and Boyd 2008).Establishing reliable indicators of the current state of school crime and safety across the nation and regularly updating and monitoring these indicators are important in ensuring the safety of our nation's students. This is the aim of Indicators of School Crime and Safety.This report is the 18th in a series of annual publications produced jointly by the National Center for Education Statistics (NCES), Institute of Education Sciences (IES), in the U.S. Department of Education, and the Bureau of Justice Statistics (BJS) in the U.S. Department of Justice. This report presents the most recent data available on school crime and student safety. The indicators in this report are based on information drawn from a variety of data sources, including national surveys of students, teachers, principals, and postsecondary institutions. Sources include results from the School-Associated Violent Deaths Study, sponsored by the U.S. Department of Education, the Department of Justice, and the Centers for Disease Control and Prevention (CDC); the National Crime Victimization Survey and School Crime Supplement to that survey, sponsored by BJS and NCES, respectively; the Youth Risk Behavior Survey, sponsored by the CDC; the Schools and Staffing Survey, School Survey on Crime and Safety, Fast Response Survey System, ED Facts , and High School Longitudinal Study of 2009, all sponsored by NCES; the Supplementary Homicide Reports, sponsored by the Federal Bureau of Investigation; the Campus Safety and Security Survey and Civil Rights Data Collection, both sponsored by the U.S. Department of Education; and the Census of Juveniles in Residential Placement, sponsored by the U.S. Department of Justice. The most recent data collection for each indicator varied by survey, from 2009 to 2014. Each data source has an independent sample design, data collection method, and questionnaire design, or is the result of a universe data collection. Findings described in this report with comparative language (e.g., higher, lower, increase, and decrease) are statistically significant at the .05 level. Additional information about methodology and the datasets analyzed in this report may be found in appendix A.This report covers topics such as victimization, teacher injury, bullying and cyber-bullying, school conditions, fights, weapons, availability and student use of drugs and alcohol, student perceptions of personal safety at school, and criminal incidents at postsecondary institutions. Indicators of crime and safety are compared across different population subgroups and over time. Data on crimes that occur away from school are offered as a point of comparison where available

Indicators of School Crime and Safety: 2014

A joint effort by the Bureau of Justice Statistics and National Center for Education Statistics, this annual report examines crime occurring in schools and colleges. This report presents data on crime at school from the perspectives of students, teachers, principals, and the general population from an array of sources--the National Crime Victimization Survey, the School Crime Supplement to the National Crime Victimization Survey, the Youth Risk Behavior Survey, the School Survey on Crime and Safety, the Schools and Staffing Survey, EDFacts, and the Campus Safety and Security Survey. The report covers topics such as victimization, bullying, school conditions, fights, weapons, the presence of security staff at school, availability and student use of drugs and alcohol, student perceptions of personal safety at school, and criminal incidents at postsecondary institutions

Indicators of School Crime and Safety: 2016

Our nation's schools should be safe havens for teaching and learning, free of crime and violence. Any instance of crime or violence at school not only affects the individuals involved, but also may disrupt the educational process and affect bystanders, the school itself, and the surrounding community (Brookmeyer, Fanti, and Henrich 2006; Goldstein, Young, and Boyd 2008).Establishing reliable indicators of the current state of school crime and safety across the nation and regularly updating and monitoring these indicators are important in ensuring the safety of our nation's students. This is the aim of Indicators of School Crime and Safety.This report is the 19th in a series of annual publications produced jointly by the National Center for Education Statistics (NCES), Institute of Education Sciences (IES), in the U.S. Department of Education, and the Bureau of Justice Statistics (BJS) in the U.S. Department of Justice. This report presents the most recent data available on school crime and student safety. The indicators in this report are based on information drawn from a variety of data sources, including national surveys of students, teachers, principals, and postsecondary institutions. Sources include results from the School-Associated Violent Death Surveillance System, sponsored by the U.S. Department of Education, the Department of Justice, and the Centers for Disease Control and Prevention (CDC); the National Crime Victimization Survey and School Crime Supplement to that survey, sponsored by BJS and NCES, respectively; the Youth Risk Behavior Survey, sponsored by the CDC; the Schools and Staffing Survey, School Survey on Crime and Safety, Fast Response Survey System, ED Facts , and Early Childhood Longitudinal Study, Kindergarten Class of 2010–11, all sponsored by NCES; the Supplementary Homicide Reports, sponsored by the Federal Bureau of Investigation; the Campus Safety and Security Survey and Civil Rights Data Collection, both sponsored by the U.S. Department of Education; and the Trends in International Mathematics and Science Study, sponsored by the International Association for the Evaluation of Educational Achievement. The most recent data collection for each indicator varied by survey, from 2009 to 2015. Each data source has an independent sample design, data collection method, and questionnaire design, or is the result of a universe data collection. Findings described in this report with comparative language (e.g., higher, lower, increase, and decrease) are statistically significant at the .05 level. Additional information about methodology and the datasets analyzed in this report may be found in appendix A.This report covers topics such as victimization, teacher injury, bullying and cyber-bullying, school conditions, fights, weapons, availability and student use of drugs and alcohol, student perceptions of personal safety at school, and criminal incidents at postsecondary institutions. Indicators of crime and safety are compared across different population subgroups and over time. Data on crimes that occur away from school are offered as a point of comparison where available

Driving Big Data : A First Look at Driving Behavior via a Large-Scale Private Car Dataset

The increasing number of privately owned vehicles in large metropolitan cities has contributed to traffic congestion, increased energy waste, raised CO2 emissions, and impacted our living conditions negatively. Analysis of data representing citizens' driving behavior can provide insights to reverse these conditions. This article presents a large-scale driving status and trajectory dataset consisting of 426,992,602 records collected from 68,069 vehicles over a month. From the dataset, we analyze the driving behavior and produce random distributions of trip duration and millage to characterize car trips. We have found that a private car has more than 17% probability to make four trips per day, and a trip has more than 25% probability to last 20-30 minutes and 33% probability to travel 10 Kilometers during the trip. The collective distributions of trip mileage and duration follow Weibull distribution, whereas the hourly trips follow the well known diurnal pattern and so the hourly fuel efficiency. Based on these findings, we have developed an application which recommends the drivers to find the nearby gas stations and possible favorite places from past trips. We further highlight that our dataset can be applied for developing dynamic Green maps for fuel-efficient routing, modeling efficient Vehicle-to-Vehicle (V2V) communications, verifying existing V2V protocols, and understanding user behavior in driving their private cars.Peer reviewe

Entrepreneurial growth in digital business ecosystems: an integrated framework blending the knowledge-based view of the firm and business ecosystems

Digitalisation is shaping the contemporary technological context of entrepreneurial activities, where firms grow through interacting with digital ecosystem stakeholders. This study investigates how incumbent firms seek entrepreneurial growth by re-configurating their knowledge bases in digital business ecosystems. We propose and develop a conceptual framework that blends the digital business ecosystem perspective and the knowledge-based view of the firm. Through a longitudinal case study of a Chinese textile manufacturing firm, we identify three pathways for entrepreneurial growth. The results contribute to the entrepreneurship literature by demonstrating how digital technologies foster corporate entrepreneurship in incumbent firms. The proposed framework extends the analytical power of the knowledge-based view by incorporating ecosystem elements into the firm’s internal and external knowledge management. The findings also generate relevant and actionable managerial implications for entrepreneurs, managers, and policymakers that are applicable in the context of digital business ecosystems

How does the media frame the legitimacy of multinationals in the context of geopolitical rivalry? A study of Chinese multinationals in developed countries

Chinese multinational enterprises are facing almost continuous negative media coverage in many Western countries, given the rising geopolitical tensions between the China and the West. This thesis aims to scrutinize this phenomenon to examine why and how Chinese multinationals are suffering from negative media coverage, and how firms can deal with such challenges when facing geopolitical complexities. To examine the phenomenon of interest, this thesis takes a cross-disciplinary approach by combining the subjects of international business, mass communication, and international relations. The research problem that this thesis aims to address is: How can Chinese multinationals interpret and respond to media-framed legitimacy challenges when facing intensive geopolitical tensions? This research problem leads the author to develop three concrete research questions: How are liabilities of origin framed by the media, thereby posing legitimacy challenges for Chinese multinationals? How are the voices of different stakeholders framed by the media in constructing the legitimacy of Chinese multinationals? How can Chinese multinationals form voice strategies to mitigate legitimacy challenges in the geopolitical context? The research design in this thesis contains three independent yet related studies in dealing with the general research problem. The first case study focuses on the legitimacy challenges of Huawei in the UK. The second case study focuses on the legitimacy challenges of TikTok in the US. The third study supplements the previous two case studies and explores Chinese multinationals’ voice strategies through semi-structured interviews with public relations managers. This thesis extends knowledge and makes contributions to three theoretical gaps regarding multinationals’ legitimacy challenges in the geopolitical rivalry, media framing of multinationals’ legitimacy, and multinationals’ voice strategies as part of the nonmarket strategy. Besides, it responds to the call for methodological pluralism in case study work. Finally, it generates both managerial and policy implications for multinationals and governments to consider the impact of geopolitical rivalry on multinational enterprises

The legitimacy defeat of Huawei in the media: Cause, context, and process

Emerging market multinational enterprises (EMNEs) seem to face almost continuous negative media coverage in many Western countries. Our study scrutinizes this phenomenon to examine why and how EMNEs are confronting increasing negative media coverage. We empirically examine how the British newspaper media reported on the governmental banning of Huawei from fifth-generation network development in the UK. Our findings suggest that liabilities of origin (LOR) trigger negative media coverage of EMNEs, and that the geopolitical context and media framing make LOR more salient and harmful for EMNEs in developed countries. We propose a contextualized explanation for EMNEs’ legitimacy defeats in the media by identifying the cause (i.e., LOR), context (i.e., geopolitical rivalry), and process (i.e., media framing) in such a de-legitimization mechanism. Indeed, we crystalize the matter of how the media frames LOR and de-legitimizes EMNEs. We also examine EMNEs’ voice strategies for mitigating negative media coverage and defending legitimacy

Indicators of School Crime and Safety: 2017

This report covers topics such as victimization, teacher injury, bullying and cyberbullying, school conditions, fights, weapons, availability and student use of drugs and alcohol, student perceptions of personal safety at school, and criminal incidents at postsecondary institutions. Indicators of crime and safety are compared across different population subgroups and over time. Data on crimes that occur away from school are offered as a point of comparison where available

Design of a Machine Vision-Based Automatic Digging Depth Control System for Garlic Combine Harvester

The digging depth is an important factor affecting the mechanized garlic harvesting quality. At present, the digging depth of the garlic combine harvester (GCH) is adjusted manually, which leads to disadvantages such as slow response, poor accuracy, and being very dependent on the operator’s experience. To solve this problem, this paper proposes a machine vision-based automatic digging depth control system for the original garlic digging device. The system uses the improved YOLOv5 algorithm to calculate the length of the garlic root at the front end of the clamping conveyor chain in real-time, and the calculation result is sent back to the system as feedback. Then, the STM32 microcontroller is used to control the digging depth by expanding and contracting the electric putter of the garlic digging device. The experimental results of the presented control system show that the detection time of the system is 30.4 ms, the average accuracy of detection is 99.1%, and the space occupied by the model deployment is 11.4 MB, which suits the design of the real-time detection of the system. Moreover, the length of the excavated garlic roots is shorter than that of the system before modification, which represents a lower energy consumption of the system and a lower rate of impurities in harvesting, and the modified system is automatically controlled, reducing the operator’s workload