Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Machine learning

Building Leadership Effectiveness This program encourages leaders to develop practices that transform values into action, vision into realities, obstacles into innovations, and risks into rewards. Participants will be introduced to the five practices of exemplary leadership: modeling the way, inspiring a shared vision, challenging the process, enabling others to act, and encouraging the heart Coaching & Communicating for Performance Coaching & Communicating for Performance is a highly interactive program that will give supervisors and managers the opportunity to build skills that will enable them to share expectations and set objectives for employees, provide constructive feedback, more effectively engage in learning conversations, and coaching opportunities. Skillful Conflict Management for Leaders As a leader, it is important to understand conflict and be effective at conflict management because the way conflict is resolved becomes an integral component of our university’s culture. This series of conflict management sessions help leaders learn and put into practice effective strategies for managing conflict.

기독교 사역과 Leadership

The Social Psychology of Organizations.

Ethical leadership: A social learning perspective for construct development and testing

\"What are your assumptions (implicit as well as explicit) about the most effective way to manage people?\" So began Douglas McGregor in this 1960 management classic. It was a seemingly simple question he asked, yet it led to a fundamental revolution in management. Today, with the rise of the global economy, the information revolution, and the growth of knowledge-driven work, McGregor's simple but provocative question continues to resonate-perhaps more powerfully than ever before. Heralded as one of the most important pieces of management literature ever written, a touchstone for scholars and a handbook for practitioners, The Human Side of Enterprise continues to receive the highest accolades nearly half a century after its initial publication. Influencing such major management gurus such as Peter Drucker and Warren Bennis, McGregor's revolutionary Theory Y-which contends that individuals are self-motivated and self-directed-and Theory X-in which employees must be commanded and controlled-has been widely taught in business schools, industrial relations schools, psychology departments, and professional development seminars for over four decades. In this special annotated edition of the worldwide management classic, Joel Cutcher-Gershenfeld, Senior Research Scientist in MIT's Sloan School of Management and Engineering Systems Division, shows us how today's leaders have successfully incorporated McGregor's methods into modern management styles and practices. The added quotes and commentary bring the content right into today's debates and business models. Now more than ever, the timeless wisdom of Douglas McGregor can light the path towards a management style that nurtures leadership capability, creates effective teams, ensures internal alignment, achieves high performance, and cultivates an authentic, value-driven workplace--lessons we all need to learn as we make our way in this brave new world of the 21st century.

The Human Side of Enterprise.

Personality and charismatic leadership: a matter of context

Trust plays a pivotal role in the development and maintenance of effective working relationships. In this paper we offer a critical review of the conceptualization and operationalization of cognition-based and affect-based trust. While definitions and measures of trust are abundant, the view of trust as a concept with cognitive and affective bases is well established. Nevertheless, the validity of this approach has rarely been examined. Our theoretical and empirical review (content validity study, systematic review and meta-analysis) of the literature reveals a failure to fully capture cognition or affect in current trust theory and measurement. We find the construct of affect-based trust to be particularly problematic in its current form. Resolving these issues is critical to advancing our understanding of the differentiating roles of these two important bases of trust. We detail areas for future research on the conceptualization and measurement of trust to stimulate theoretical exploration and methodological advances. 

A critical review of the conceptualisation, operationalisation, and empirical literature on cognition‐based and affect‐based trust

Background: Immediate total-body CT (iTBCT) is often used for screening of potential severely injured patients. Patients requiring emergency bleeding control interventions benefit from fast and optimal trauma screening. The aim of this study was to assess whether an initial trauma assessment with iTBCT is associated with lower mortality in patients requiring emergency bleeding control interventions. Methods: In the REACT-2 trial, patients who sustained major trauma were randomized for iTBCT or for conventional imaging and selective CT scanning (standard workup; STWU) in five trauma centers. Patients who underwent emergency bleeding control interventions following their initial trauma assessment with iTBCT were compared for mortality and clinically relevant time intervals to patients that underwent the initial trauma assessment with the STWU. Results: In the REACT-2 trial, 1083 patients were enrolled of which 172 (15.9%) underwent emergency bleeding control interventions following their initial trauma assessment. Within these 172 patients, 85 (49.4%) underwent iTBCT as primary diagnostic modality during the initial trauma assessment. In trauma patients requiring emergency bleeding control interventions, in-hospital mortality was 12.9% (95% CI 7.2–21.9%) in the iTBCT group compared to 24.1% (95% CI 16.3–34.2%) in the STWU group (p = 0.059). Time to bleeding control intervention was not reduced; 82 min (IQR 5–121) versus 98 min (IQR 62–147), p = 0.108. Conclusions: Reduction in mortality in trauma patients requiring emergency bleeding control interventions by iTBCT could not be demonstrated in this study. However, a potentially clinically relevant absolute risk reduction of 11.2% (95% CI − 0.3 to 22.7%) in comparison with STWU was observed. Trial registration: ClinicalTrials.gov: NCT01523626.

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Emergency Bleeding Control Interventions After Immediate Total-Body CT Scans in Trauma Patients

This study focuses on culturally endorsed implicit theories of leadership (CLTs). Although cross-cultural research emphasizes that different cultural groups likely have different conceptions of what leadership should entail, a controversial position is argued here: namely that attributes associated with charismatic/transformational leadership will be universally endorsed as contributing to outstanding leadership. This hypothesis was tested in 62 cultures as part of the Global Leadership and Organizational Behavior Effectiveness (GLOBE) Research Program. Universally endorsed leader attributes, as well as attributes that are universally seen as impediments to outstanding leadership and culturally contingent attributes are presented here. The results support the hypothesis that specific aspects of charismatic/transformational leadership are strongly and universally endorsed across cultures.

Culture Specific and Cross-Culturally Generalizable Implicit Leadership Theories: Are Attributes of Charismatic/Transformational Leadership Universally Endorsed?

Dutch GLOBE data are presented in this chapter with an overview of the history of Holland
and later the Netherlands. From the Middle Ages onward, Dutch cities had substantial local
autonomy, which led their educated citizens and merchants to rule themselves to a large
extent. This relative autonomy stimulated independent thought and judgment, a climate that
helped Protestantism to gain much ground. Foreign trade facilitated the rise of a liberal culture. Later on, religious denomination became an important societal organization principle.
After the Second World War industrial relations were characterized by an economic order that
emphasized mixed capitalism (in which the government has a strong role), consultation
among major parties, and a welfare state.

Deanne N. Den Hartog

Papers

Personality and charismatic leadership: a matter of context

A critical review of the conceptualisation, operationalisation, and empirical literature on cognition‐based and affect‐based trust

Emergency Bleeding Control Interventions After Immediate Total-Body CT Scans in Trauma Patients

Culture Specific and Cross-Culturally Generalizable Implicit Leadership Theories: Are Attributes of Charismatic/Transformational Leadership Universally Endorsed?

Culture and Leadership in a Flat Country: The Case of the Netherlands