Commentary on the Humble Remonstrance of the Company of Stationers 1643

A petition from the Company of Stationers to Parliament to introduce some form of legislative regulation of the press. The petition is significant in revealing the extent to which the Stationers depended upon the state to support the regulation of the book trade, as well as the nature of the various public and private interest arguments upon which they sought to base their claim. The commentary articulates the various arguments presented by the Stationers within their petition. The benefits of the legal regulation they suggested concerned not only the censorship and suppression of seditious and heretical texts, but also facilitated the advancement of learning and knowledge and the flourishing of the printing industry itself. In addition, the petition presents the figure of the ‘author' as reliant upon the benefit of his work, and that the ‘production of the Brain' was to be regarded as equivalent to any other commodity or chattel.

Commentary on Defoe's Essay on the Regulation of the Press (1704)

Treatise in which Daniel Defoe sets out his arguments concerning the importance of maintaining a free press, as well as the need to provide for a statutory protection to prevent the ‘press-piracy' of published books.
Defoe sets out various public interest arguments concerning the encouragement of learning, industry and the arts, in support of his case for the introduction of copyright legislation. The commentary describes part of the background to the passing of the Statute of Anne 1710 (uk_1710), in particular: the various unsuccessful attempts to reintroduce an alternative to the Licensing Act 1662 (uk_1662); Defoe's public writing on the need for, and social value of, copyright protection; and the influence of his writings in providing the Company of Stationers with a new rhetorical strategy with which to lobby parliament and secure the passing of the Statute of Anne.

Commentary on the Statute of Anne 1710

Legislation conferring exclusive rights upon the author of books not yet printed or published for a period of 14 years and for a further 14 years if the author was still alive at the end of the first period. The legislation also provided the same rights for the authors or owners of books already in print for a single 21 year term.
The commentary describes the background to the Act detailing the manner in which the legislation was amended as it passed through parliament, and highlights particular flaws in the drafting. The commentary argues that, although the Act sought to both secure the interests of the Stationers while at the same time regulating the general operation of the book trade, the primary concern of the legislature lay in the encouragement and advancement of learning.

Investigating high-achieving sixth grade students' erroneous answers on the angle concept in Yozgat

The angle concept is a multifaceted concept having static and dynamic definitions. The static definition of the angle refers to “the space between two rays” or “the intersection of two rays at the same end point” (Mitchelmore & White, 1998), whereas the dynamic definition of the angle concept highlights that the size of angle is the amount of rotation in direction (Fyhn, 2006). Since both definitions represent two diverse situations and have unique limitations (Henderson & Taimina, 2005), students may hold misconceptions about the angle concept. In this regard, the aim of this research was to explore high achievers’ knowledge regarding the definition of the angle concept as well as to investigate their erroneous answers on the angle concept.

104 grade 6 students drawn from four well-established elementary schools of Yozgat, Turkey were participated in this research. All participants were selected via a purposive sampling method and their mathematics grades were 4 or 5 out of 5, and. Data were collected through four questions prepared by considering the learning competencies set out in the grade 6 curriculum in Turkey and the findings of previous studies whose purposes were to identify students’ misconceptions of the angle concept. The findings were analyzed by two researchers, and their inter-rater agreement was calculated as 0.91, or almost perfect. Thereafter, coding discrepancies were resolved, and consensus was established.

The angle concept is a multifaceted concept having static and dynamic definitions.The static definition of the angle refers to “the space between two rays” or“the intersection of two rays at the same end point” (Mitchelmore & White, 1998), whereas the dynamicdefinition of the angle concept highlights that the size of angle is the amountof rotation in direction (Fyhn, 2006). Since both definitionsrepresent two diverse situations and have unique limitations (Henderson & Taimina, 2005), students may holdmisconceptions about the angle concept. In this regard, the aim of thisresearch was to explore high achievers’ knowledge regarding the definition ofthe angle concept as well as to investigate their erroneous answers on theangle concept.

Deep Corals, Deep Learning: Moving the Deep Net Towards Real-Time Image Annotation

The mismatch between human capacity and the acquisition of Big Data such as Earth imagery undermines commitments to Convention on Biological Diversity (CBD) and Aichi targets. Artificial intelligence (AI) solutions to Big Data issues are urgently needed as these could prove to be faster, more accurate, and cheaper. Reducing costs of managing protected areas in remote deep waters and in the High Seas is of great importance, and this is a realm where autonomous technology will be transformative.

Influence of Forecasting, Planning and Controlling on the performance of Small and Medium Enterprises

Production Planning and Control (PPC) systems have grown and changed because of the developments in planning tools and models as well as the use of computers and information systems in this area. Though so much is available in research journals, practice of PPC is lagging behind and does not use much from published research. The practices of PPC in SMEs lag behind because of many reasons, which need to be explored. This research work deals with the effect of identified variables such as forecasting, planning and control methods adopted, demographics of the key person, standardization practices followed, effect of training, learning and IT usage on firm performance. A model and framework has been developed based on literature. Empirical testing of the model has been done after collecting data using a questionnaire schedule administered among the selected respondents from Small and Medium Enterprises (SMEs) in India. Final data included 382 responses. Hypotheses linking SME performance with the use of forecasting, planning and controlling were formed and tested. Exploratory factor analysis was used for data reduction and for identifying the factor structure. High and low performing firms were classified using a Logistic Regression model. A confirmatory factor analysis was used to study the structural relationship between firm performance and dependent variables.

Learning at the Interstices; Locating Practical Philosophies for Understanding Physical/virtual Inter-spaces

Virtual worlds are relatively recent developments, and so it is tempting to believe that they need to be understood through newly developed theories and philosophies. However, humans have long thought about the nature of reality and what it means to be “real.” This paper examines the three persistent philosophical concepts of Metaxis, Liminality and Space that have evolved across more than 2000 years of meditation, contemplation and reflection. Our particular focus here is on the nature of the interface between the virtual and the physical: at the interstices, and how the nature of transactions and transitions across those interfaces may impact upon learning. This may, at first, appear to be an esoteric pursuit, but we ground our arguments in primary and secondary data from research studies in higher education.

Review into the Proposed Registration of Teachers and Others who Support Learning in the Independent Sector with the Education Workforce Council

During the passage of the Education (Wales) Bill, Assembly Members called for parity in the way the behaviour of practitioners within maintained schools and the independent sector are regulated. This study was therefore commissioned to gather the views of groups and individuals who work in the education sector in Wales, on whether: i) there should be a requirement for practitioners (both teaching and learning support staff) within independent schools and private FE institutions to register with the Council ii) employers should be legally required to refer cases of unacceptable professional conduct and serious professional incompetence to the Council It was also intended, through this process, to gather views on the potential implications associated with any such registration so that the resulting impact could be identified. The individuals and organisations consulted included head teachers, college principals, governing bodies, teaching staff, learning support staff, trade unions, registration bodies, independent sector representative bodies, inspectorates and teaching councils. Consultations took place between August and November 2015, with data gathered through an online survey, face-to-face interviews, telephone interviews and via email.

Shining a Light on the Dark Side: How the Global Financial Crisis Exposed the Dark Side of Leadership

The global financial crisis has had innumerate outcomes around the globe. Whilst most of these are generally perceived to be negative, there are outcomes which could be considered positive for society. One such outcome is the spotlight that the financial crisis has shone on corruption within organisations and in particular, the role that destructive leaders play in the promotion of negative behaviours within organisations. This interest in identifying so-called ‘dark-side’ traits in leaders is a positive step both academically and practically. Academically, there is a limited research examining individuals with ‘dark-traits’ within organisations (Mahmut, Homewood & Stevenson, 2008). Practically, most leader derailment can be attributed to ‘dark-side’ traits and leaders with such traits are implicated in a host of issues for organisations including poor staff morale and satisfaction, bullying, poor levels of productivity, high staff turnover, unethical behaviour and even white collar crime (e.g. Boddy,2010; 2011; Lesha & Lesha, 2012; O’Boyle, Forsyth, Banks & McDaniel, 2012; Sanecka, 2013). This paper focuses on one of the ‘dark-side’ traits; psychopathy. Psychopathy is a personality disorder characterised by guiltlessness, incapacity to experience love, impulsivity, shallow emotions, superficial charm and an inability to learn from experience (Cleckley, 1941, 1982). Research has found that individuals with high levels of psychopathy can be found working within organisations and experiencing some degree of career success (e.g. Babiak, Neumann & Hare, 2010; Board & Fritzon, 2005; Boddy, 2010; Lilienfeld, Latzman, Watts, Smith & Dutton, 2014). These individuals are theoretically thought to be attracted to careers which offer power, status and monetary rewards. In particular, the finance industry has been suggested as an ideal work place for the organisational psychopath. Some authors go as far as attribute organisational psychopaths a key role in the financial crisis (Boddy, 2011). However, little research has been conducted to explore whether levels of psychopathy in employees differ across industries and what careers might be most attractive to individuals with high levels of psychopathy. This paper presents the results of a large scale survey of 265 alumni of universities in the Central England region of the UK. The survey was conducted to assess the link between levels of three factors of psychopathy (Egotism, Callousness and Antisocialism) with occupation as defined by Holland’s RIASEC model. Participants completed Brinkley, Diamond, Magaletta & Heigel’s (2008) revision of Levenson’s Self-Report Psychopathy Scale and responded to questions regarding their current occupation. Logistic regression analyses were conducted to assess whether levels of Egotism, Callousness and Antisocialism were predictive of occupation. The results showed that when compared to individuals who occupy job roles within the Social sector of Holland’s model, individuals with higher levels of psychopathy were more likely to be employed within Realistic, Investigative, Enterprising and Conventional roles. When comparing Social and Realistic roles, more Egotistical individuals were likely to be employed within Realistic roles. When comparing those employed in Social roles to Investigative, Enterprising and Conventional roles, individuals with higher levels of Antisocialism were more likely to be employed within the latter three occupations than within Social roles. This suggests that individuals with psychopathy do gravitate towards certain career paths. Social roles where job incumbents are required to be caring and interact with others to a large extent appear to be unattractive to individuals with high levels of psychopathy. Social roles are also associated with lower monetary rewards and are generally less prestigious (Henley, 2001). These individuals instead seek out occupations where there are higher levels of risk, power and reward. Roles in the Realistic category include those which include high levels of risk e.g. fighter pilot, fireman etc., (Cohen, Meir, Segal & Amar, 2003). Investigative careers hold the highest level of prestige and ranking. Enterprising roles include management positions where power is wielded over subordinates and sales roles, where customers can be manipulated (ACT, 2009). Conventional roles include those within the finance industry, which include some of the most financially lucrative positive available (Babiak & Hare, 2006). The above suggests that individuals with higher levels of psychopathy may be seeking to satisfy their self-centred natures by selecting careers which provide them with high levels of reward in one way or another. Alternatively, these individuals may select roles where their traits can be accepted. The importance of Antisocialism in predicting occupation may be testament to the importance of finding a career which ‘fits’ such traits. Antisocialism is generally associated with negative outcomes in the workplace (Ettner, MacLean & French, 2010). Therefore, finding environments tolerant of antisocial tendencies may be a priority for individuals with high levels of these traits. The results suggest that Enterprising, Investigative and Conventional work environments may be tolerant of Antisocialism in employees and Realistic environments tolerant of Egotism. Academically, the results show that there is value in studying ‘dark-side’ characteristics in organisations. Individuals with higher levels of psychopathic traits, do not appear to randomly enter employment. Instead, they appear to gravitate to careers which meet their needs and/or tolerate their traits. It is important to further explore what industries and positions are particularly attractive to individuals with higher levels of psychopathy and what makes them attractive to these individuals. Such knowledge is important for practitioners to be able to advise organisations as to the likely level of risk they face of employing organisational psychopaths and to enable organisations which are particularly attractive to highly psychopathic employees to design selection systems which detect undesirable traits in candidates. Furthermore, organisations can examine their culture to assess whether traits such as antisocialism are tolerated (or even rewarded) and what the implications of this are.

Child Safety Signal Learning in the Context of Parental Worry, Overprotection, PTSD, and Depression

Thesis (Ph.D.)--University of Washington, 2016-08

Fallbasiertes E-Learning durch dynamische Verknüpfung von Fallstudien und Fachinhalten. Neue Diskussionsansätze zu einem vernachlässigten Konzept

Der Einsatz von Fallstudien kann als wichtiges Bindeglied zur Verknüpfung von Theorie und Praxis betrachtet werden. Fallstudien ermöglichen die Anwendung theoretischen Grundlagenwissens und die Entwicklung überfachlicher Kompetenzen. Damit können sie einen wichtigen Beitrag zur beruflichen Handlungskompetenz genau dort leisten, wo praktische Erfahrungen im Rahmen der Aus-und Weiterbildung nicht möglich sind. Der Einsatz von Fallstudien sollte aus diesem Grund nicht nur den „klassischen“ Anwendungsdisziplinen wie den Rechtswissenschaften, der Betriebswirtschaftslehre oder der Psychologie vorbehalten sein. Auch im Bereich der Informatik können sie eine wichtige Ergänzung zu den bisher eingesetzten Methoden darstellen. Das im Kontext des Projekts New Economy1 entwickelte und hier vorgestellte Konzept zur didaktischen und technischen Aufbereitung von Fallstudien am Beispiel der IT-Aus- und Weiterbildung soll diese Diskussion anregen. Mit Hilfe des vorgestellten Ansatzes ist es möglich, unterschiedliche methodische Zugänge zu einer Fallstudie für eine computerbasierte Präsentation automatisch zu generieren und mit fachlichen Inhalten zu verknüpfen. Damit ist ein entscheidender Mehrwert gegenüber den bisherigen statischen und in sich geschlossenen Darstellungen gegeben. Der damit zu erreichende Qualitätssprung im Einsatz von Fallstudien in der universitären und betrieblichen Aus- und Weiterbildung stellt einen wichtigen Beitrag zur praxisorientierten Gestaltung von Blended Learning-Ansätzen dar.(DIPF/Orig.)

Essays on the term structure of interest rates

This PhD thesis contains three main chapters on macro finance, with a focus on the term structure of interest rates and the applications of state-of-the-art Bayesian econometrics. Except for Chapter 1 and Chapter 5, which set out the general introduction and conclusion, each of the chapters can be considered as a standalone piece of work. In Chapter 2, we model and predict the term structure of US interest rates in a data rich environment. We allow the model dimension and parameters to change over time, accounting for model uncertainty and sudden structural changes. The proposed timevarying parameter Nelson-Siegel Dynamic Model Averaging (DMA) predicts yields better than standard benchmarks. DMA performs better since it incorporates more macro-finance information during recessions. The proposed method allows us to estimate plausible realtime term premia, whose countercyclicality weakened during the financial crisis. Chapter 3 investigates global term structure dynamics using a Bayesian hierarchical factor model augmented with macroeconomic fundamentals. More than half of the variation in the bond yields of seven advanced economies is due to global co-movement. Our results suggest that global inflation is the most important factor among global macro fundamentals. Non-fundamental factors are essential in driving global co-movements, and are closely related to sentiment and economic uncertainty. Lastly, we analyze asymmetric spillovers in global bond markets connected to diverging monetary policies. Chapter 4 proposes a no-arbitrage framework of term structure modeling with learning and model uncertainty. The representative agent considers parameter instability, as well as the uncertainty in learning speed and model restrictions. The empirical evidence shows that apart from observational variance, parameter instability is the dominant source of predictive variance when compared with uncertainty in learning speed or model restrictions. When accounting for ambiguity aversion, the out-of-sample predictability of excess returns implied by the learning model can be translated into significant and consistent economic gains over the Expectations Hypothesis benchmark.

Computerized Medical Diagnosis of Melanocytic Lesions based on the ABCD approach

Melanoma is a type of skin cancer and is caused by the uncontrolled growth of atypical melanocytes. In recent decades, computer aided diagnosis is used to support medical professionals; however, there is still no globally accepted tool. In this context, similar to state-of-the-art we propose a system that receives a dermatoscopy image and provides a diagnostic if the lesion is benign or malignant. This tool is composed with next modules: Preprocessing, Segmentation, Feature Extraction, and Classification. Preprocessing involves the removal of hairs. Segmentation is to isolate the lesion. Feature extraction is considering the ABCD dermoscopy rule. The classification is performed by the Support Vector Machine. Experimental evidence indicates that the proposal has 90.63 % accuracy, 95 % sensitivity, and 83.33 % specificity on a data-set of 104 dermatoscopy images. These results are favorable considering the performance of diagnosis by traditional progress in the area of dermatology

Effect of haptic guidance and error amplification robotic training interventions on the immediate improvement of timing among individuals that had a stroke

Abstract : Many individuals that had a stroke have motor impairments such as timing deficits that hinder their ability to complete daily activities like getting dressed. Robotic rehabilitation is an increasingly popular therapeutic avenue in order to improve motor recovery among this population. Yet, most studies have focused on improving the spatial aspect of movement (e.g. reaching), and not the temporal one (e.g. timing). Hence, the main aim of this study was to compare two types of robotic rehabilitation on the immediate improvement of timing accuracy: haptic guidance (HG), which consists of guiding the person to make the correct movement, and thus decreasing his or her movement errors, and error amplification (EA), which consists of increasing the person’s movement errors. The secondary objective consisted of exploring whether the side of the stroke lesion had an effect on timing accuracy following HG and EA training. Thirty-four persons that had a stroke (average age 67 ± 7 years) participated in a single training session of a timing-based task (simulated pinball-like task), where they had to activate a robot at the correct moment to successfully hit targets that were presented a random on a computer screen. Participants were randomly divided into two groups, receiving either HG or EA. During the same session, a baseline phase and a retention phase were given before and after each training, and these phases were compared in order to evaluate and compare the immediate impact of HG and EA on movement timing accuracy. The results showed that HG helped improve the immediate timing accuracy (p=0.03), but not EA (p=0.45). After comparing both trainings, HG was revealed to be superior to EA at improving timing (p=0.04). Furthermore, a significant correlation was found between the side of stroke lesion and the change in timing accuracy following EA (r[subscript pb]=0.7, p=0.001), but not HG (r[subscript pb]=0.18, p=0.24). In other words, a deterioration in timing accuracy was found for participants with a lesion in the left hemisphere that had trained with EA. On the other hand, for the participants having a right-sided stroke lesion, an improvement in timing accuracy was noted following EA. In sum, it seems that HG helps improve the immediate timing accuracy for individuals that had a stroke. Still, the side of the stroke lesion seems to play a part in the participants’ response to training. This remains to be further explored, in addition to the impact of providing more training sessions in order to assess any long-term benefits of HG or EA.

Essays on the term structure of interest rates

This PhD thesis contains three main chapters on macro finance, with a focus on the term structure of interest rates and the applications of state-of-the-art Bayesian econometrics. Except for Chapter 1 and Chapter 5, which set out the general introduction and conclusion, each of the chapters can be considered as a standalone piece of work. In Chapter 2, we model and predict the term structure of US interest rates in a data rich environment. We allow the model dimension and parameters to change over time, accounting for model uncertainty and sudden structural changes. The proposed time-varying parameter Nelson-Siegel Dynamic Model Averaging (DMA) predicts yields better than standard benchmarks. DMA performs better since it incorporates more macro-finance information during recessions. The proposed method allows us to estimate plausible real-time term premia, whose countercyclicality weakened during the financial crisis. Chapter 3 investigates global term structure dynamics using a Bayesian hierarchical factor model augmented with macroeconomic fundamentals. More than half of the variation in the bond yields of seven advanced economies is due to global co-movement. Our results suggest that global inflation is the most important factor among global macro fundamentals. Non-fundamental factors are essential in driving global co-movements, and are closely related to sentiment and economic uncertainty. Lastly, we analyze asymmetric spillovers in global bond markets connected to diverging monetary policies. Chapter 4 proposes a no-arbitrage framework of term structure modeling with learning and model uncertainty. The representative agent considers parameter instability, as well as the uncertainty in learning speed and model restrictions. The empirical evidence shows that apart from observational variance, parameter instability is the dominant source of predictive variance when compared with uncertainty in learning speed or model restrictions. When accounting for ambiguity aversion, the out-of-sample predictability of excess returns implied by the learning model can be translated into significant and consistent economic gains over the Expectations Hypothesis benchmark.