Academic literature on the topic 'Previous performance'

Purpose This study aims to investigate how new CEOs’ previous experiences in other organizations and other industries create value in acquisitions. Drawing on the upper echelon perspective, this study theorizes that the multiorganizational experience of new CEOs is positively associated with acquisition performance and, in particular, that the multi-industry experience of new CEOs leads to better performance in diversifying acquisitions than in related acquisitions. While new CEOs without multiorganizational experience undergo a cognitive entrenchment in firm-specific experience, new CEOs with multiorganizational experience can lead acquisitions with more flexibility and agility. Design/methodology/approach Acquisition and organizational data were drawn from the US manufacturing industries (SIC 20-39) between 2008 and 2010. The event study method was used to test hypotheses. In 346 acquisitions made by 139 firms, acquisition performance was measured according to cumulative abnormal returns. Findings Consistent with the hypotheses, the multiorganizational experience of new CEOs was positively associated with acquisition performance and, in particular, the multi-industry experience of new CEOs led to better performance in diversifying acquisitions than in related acquisitions. Originality/value This paper contributes to the CEO literature and acquisition literature by suggesting that the multiorganizational experience of new CEOs can be a valuable source of competitive advantages, particularly when implementing corporate strategies involving interorganizational integration processes.

Thesis (M.A.)--West Virginia University, 2001.
Title from document title page. Document formatted into pages; contains vi, 93 p. : ill. Includes abstract. Includes bibliographical references (p. 69-76).

This paper examines the performance and performance persistence of South African bond mutual funds. To my knowledge, this paper is among the first research papers to focus on South African bond mutual funds. I utilize the Sharpe Ratio, the modified Sharpe ratio, Jensen's alpha and the multi-index models to examine whether peformance is influenced by the performance measure used. In addition, I examine the impact of conditioning information variables on performance by further measuring performance using the conditional single-index and conditional multi-index models. To test for persistence, I use the contigency tables and crosssectional regressions. I find empirical evidence to suggest that South African bond funds are not able to outperform the market. These findings are consistent across the Sharpe ratio, the unconditional single-index alphas and the unconditional multi-index alphas. When I consider the modified and conditional versions of these models, I conclude that the modified Sharpe ratio improves fund performance when compared to the original Sharpe ratio. Additionally, I conclude that incorporating conditional information variables does not offer significant improvements on the results. However, despite the observed underperformance, I note the improvement on alphas when these conditioning variables are considered. In examining performance persistence, I find evidence to suggest that, in the short-term, persistence is not sensitive to the persistence methodology used. However, I observe that persistence is rather sensitive to the performance model used. Over the longer-term, I find evidence to conclude that persistence is greatly sensitive to both the performance model used as well as the methodology used to test such persistence. My results suggest that the South African bond market is efficient and thereby in support of a passive management investment strategy. Nonetheless, my results urge for a need for bond funds to pay special attention to their trading costs in order to maximise returns for their investmens

Abstract

Purpose

The purpose of this paper is to find out which personal-related factors are influencing on the task performance and the contextual performance of expatriate managers.

Design/Methodology/Approach

This research adopts a qualitative approach, using semi-structured interviews with key-information from the managers taking international assignments.

Findings

The findings indicate that there is a series of significant associations between personal-related factors (personality traits, competences/skills, self-willingness and previous experience) and the performance of expatriates’ assignments.

Research limitations/implications

One suggestion for further research is to explore deeper and more comprehensive on other less important factors or the important factors which we are overlooking; it also could be more comprehensive on the factors that relate to the performance of expatriates.

Practical implications

We present a table of the relationship between personality traits, competences/skills, self-willingness, previous experience and the job performance of expatriates’ assignments. Thus, HR departments can follow this guidance when selecting expatriates to manage overseas assignments. Furthermore, individuals can take this model as a reference when making decisions for their career lives.

Keywords

Expatriate assignments, personality traits, self-willingness, competences/skills, previous experience, job performance, task performance, contexture performance

Paper type

Master Thesis

Practitioners are obligated to identify cost-effective, worthwhile practices for improving student learning. With the current climate of pressure to quickly improve student performance on the Virginia Standards of Learning assessments, the use of Brain Gym® is an idea that has begun to pique the interest of teachers as an innovative instructional strategy. The value in conducting this research was to attempt to objectively analyze whether the use of this specific activity-based intervention in an educational setting affects children's skill acquisition. Intact kindergarten classes from two relatively matched schools within the same southeastern Virginia school division were randomly assigned to the treatment and control groups. A total of 126 kindergarten students in eight classes were involved. All of the classes were administered the Phonological Awareness Literacy Screening test in October as part of the system-wide pre-assessment of kindergarten students. In addition to regular instruction, the treatment group then followed a prescribed set of six Brain Gym® exercises for 8-10 minutes twice each school day until the PALS posttest was given in late spring. The classroom teachers received in-service training from the researcher to enable them to lead the treatment group in the daily performance of the Brain Gym® exercises. The treatment began after the completion of PALS pre-testing. The control group received regular instruction and did not participate in any Brain Gym® exercises. Following a t-test for differences in previous performance, a four-way analysis of variance was performed on the total PALS scores. Using the Statistical Package for the Social Sciences and a predetermined alpha level of .05, the four-way ANOVA yielded a significant main effect for previous performance and non-significant main effects for Brain Gym® participation, socioeconomic status, and gender. A significant interaction effect was found only among Brain Gym® participation, socioeconomic status, and gender. The data were examined another way using a three-way analysis of covariance. After adjusting for previous performance, no significant main effects or interaction effects were found across the variables.
Ed. D.

In recent years, the application of Information Technologies has fostered a tremendous growth in e-learning courses at colleges and universities in the United States. Subsequently, some colleges and universities have reported dropout rates of over 60% in e-learning courses. Therefore, the persistence of identifiable groups of students enrolled in e-learning courses has garnered increased attention and research. Information Systems researchers suggested that studies of persistence e-learning courses identify and investigate specific constructs as well as identifiable target populations. Furthermore, as a separate and identifiable group, the college student athlete has received extensive coverage in the research literature, however, limited attention for their dropout in e-learning courses. Therefore, this research investigated persistence in e-learning courses of an identified population of college student athletes. In order to predict the persistence of college student athletes enrolled in e-learning courses, this research an empirically assessed a conceptual model, e-Learning Persistence Model (e-LPM). e-LPM was based on selected constructs that have previously shown tendencies to persistence in e-learning courses. This research, therefore, empirically assessed the constructs of e-LPM in the predication of persistence in a population of 187 college student athletes enrolled in e-learning courses. The constructs of e-LPM includes, student's attitude toward computers, student's intrinsic and extrinsic motivation, student's perceived satisfaction from the e-learning system, and student's previous academic performance measures (high school GPA and SAT score). The e-LPM constructs were empirically assessed and weighted in order to evaluate their contribution to persistence in e-learning courses. Survey response data from college student athletes at the beginning and at the end of e-learning courses were quantitatively analyzed using Ordinal Logistic Regression, ANOVA, chi-square, and t-test statistical techniques. Results of this research showed that e-LPM was able to predict persistence in e-learning course 81.4% of the time. The previous academic performance measure of GPA was shown to significantly predict e-learning course persistence in the research population. In the analysis of gender, female college student athletes exhibited higher intrinsic and extrinsic motivation than their male counterparts.

The lack of the visible and practical involvement of parents in schools that are in previously disadvantaged communities is not only depriving the present learners and their parents of their democratic right to participate in shaping their future, but that of the coming generation and leaders of tomorrow as well. South Africa as a country is about twenty years into democracy and already the education system has been chopped and changed about four times but with no success. The schooling system in previously black communities is deteriorating. The government of the day has been prioritising education for about fifteen years now, the budget for education is equal to the budget for the whole country in some of the neighbouring countries like Zimbabwe but the quality and standard are far worse than in those countries. The cost of the current problems in education mostly in previously black township schools is far too much to imagine. The main challenge seems to be the nature, character, skills and capabilities of parents serving in school governing bodies. This study is so important because of the situation that exists in schools that are situated in historically disadvantaged communities where the parents who get elected to school governing bodies are still, despite workshops and training offered by the Department of Education, unable to manage and govern schools and thus render the school governing body ineffective. The Department of Education through its programmes does conduct governance, financial management and policy formulation workshops. These efforts from the government side do not seem to bear any fruit because parents, after attending the training and workshops are still unable to create well-managed and properly governed schools. The primary objective of this study is to improve the organisational performance of schools in previously disadvantaged communities in the Uitenhage District of the Department of Education situated in the Nelson Mandela Metropolitan Municipality by investigating how effective school governing body governance could contribute to such performance. More specifically, the study investigates the relationship between effective school governing body management, as a dependent variable, and parental/community involvement, finance and resource management, school governance, learner discipline/conduct, and quality education as independent variables. The population of the study was high school principals and school management team (SMT) members in the Nelson Mandela Metropolitan Municipality focusing mainly on historically or previously disadvantaged schools in the Uitenhage district of the Department of Education. The study used convenience sampling where seventeen (17) high schools were selected. In each school, school management team members and a principal were requested to fill in a questionnaire. In total 105 questionnaires were distributed and 85 were fully completed and returned. Questionnaires were collected, data captured and analysed and a report was written. The empirical results revealed the following weaknesses in the SGBs of high schools in the Uitenhage District of the Department of Education in the Nelson Mandela Bay Municipality: the SGBs do not effectively formulate school policies; the SGBs do not effectively provide support to educators in performing their professional duties; the SGBs are not fully involved in supplementing resources supplied by the state in order to improve quality of teaching and learning; and the schools are weak on community engagement. On the other hand, the following positive elements of SGBs were highlighted in the empirical results; the schools are rated good regarding the following variables/issues: quality of teaching and learning, utilisation of school resources, school governance, professionalism of staff and extra-mural activities; the SGBs know and participate in the academic and extra-mural programmes of the schools; the SGBs successfully prepare the annual budget for the schools; the SGBs are effectively governing the schools; the SGBs do appoint auditors to audit the school's books and financial statements; the schools have achieved audited financial statements without a disclaimer; the schools have a disciplinary committee that deals with the learner code of conduct and attends to disciplinary problems. The study highlights areas in school governance that should be improved, as well as recommendations on how to improve them. Recommendations for future research are also provided.

Research has shown conflicting results involving interference of strength development with combined resistance and endurance training. Purpose: To examine if endurance training and resistance training performed concurrently would produce different performance and physiological results when compared to each type of training alone. Methods: Forty-five untrained males were recruited and randomly assigned to one of three 12 wk training groups. An endurance training (ET, N=12) group trained by running (2-3 days/week, 20-40 min, 65- 80% HRR), a resistance training (RT, N=13) group performed a resistance training program (2-3 days/week, 3 sets/8 exercises, 6-10 reps, 75-85% 1RM), and a concurrent training (CT, N=16) group performed both the endurance and resistance training programs (5 days/week, even # week 3 endurance/2 resistance workouts, odd # week 3 resistance/2 endurance workouts). All groups were tested for all the following variables prior to and following training: percent body fat, VO2max, isokinetic-maximal torque and avg. power at two speeds, 1RM leg press, 1 RM bench press, vertical jump, lower body power (as calculated by the Lewis formula) and 40-yard dash time. Results: Percent body fat was significantly (p≤.05) decreased in both the ET and CT groups. Only the ET group significantly improved VO2max (+8.24%). Minimal changes were found for any of the isokinetic measurements. The ET, RT, and CT groups demonstrated significant improvements in leg press (20.4, 40.8, and 39.4%) and bench press (7.5, 30.5 and 21.2%) 1 RM. RT and CT 1 RM improvements were similar and significantly greater than the ET group. Only the RT group significantly increased power. No group showed a significant change in vertical jump or 40-yard dash time. Conclusions: Findings indicate that endurance training does not interfere with strength development, but resistance training appears to hinder development of maximal aerobic capacity.

Sistemas de Aprendizagem Adaptativos e Inteligentes, tema de pesquisa recente no mundo, são ambientes com arquitetura e algoritmos específicos, que consideram as características individuais de cada estudante para selecionar o objeto de aprendizagem mais adequado a ser oferecido ao aluno. O rápido desenvolvimento da infraestrutura sem fio e o amplo uso de dispositivos móveis na vida diária das pessoas motivam as pesquisas relativas ao uso desses dispositivos na educação, proporcionando o m-learning. Assim, relacionado a essas linhas de pesquisa, este trabalho propõe a arquitetura AdaptMLearning, elaborada para prover a aprendizagem em plataformas móveis e não móveis, considerando a seleção de objetos de aprendizagem que melhor se adaptam a diversos aspectos, tais como: dados sobre a tecnologia utilizada para acesso; informações sobre o estilo de aprendizagem de um estudante; desempenho e tempo associados à interação do estudante com o objeto de aprendizagem; conhecimentos adquiridos pelo estudante em consonância ao conteúdo do curso; e a garantia de que não só o professor possa configurar as adaptações a serem oferecidas ao seu curso, como também o aluno tenha a possibilidade de informar sua preferência pelos tipos de mídia. Essa arquitetura é baseada no modelo de referência AHAM para sistemas adaptativos AEHS, contemplando a quádrupla: espaço do conhecimento, modelo do usuário, observações e modelo de adaptação, referente à definição lógica desses sistemas. Na AdaptMLearning, foram desenvolvidos alguns algoritmos, utilizando-se o modelo FSLSM, relacionado aos estilos de aprendizagem de um estudante e o padrão IEEE 1484 para catalogação dos objetos de aprendizagem e uso de alguns atributos de suas categorias, associados às dimensões dos estilos de aprendizagem do modelo FSLSM. O algoritmo calcula um peso para um objeto catalogado em cada dimensão e permite uma busca pelo objeto mais adequado ao estilo do estudante, além de usar a computação fuzzy, para avaliar se o estudante pode sofrer mudanças no seu estilo, deve receber reforço ou necessita de um reestudo em determinado assunto de um curso, por meio de resultados obtidos com o tempo de estudo e desempenho. Também, este trabalho apresenta o desenvolvimento e a avaliação de um simulador para a arquitetura AdaptMLearning e seus algoritmos, realizada utilizando diversos cenários de simulação, envolvendo estudantes, cursos e tecnologias com diferentes configurações. Assim sendo, com base nos resultados obtidos por meio da avaliação, foi possível discutir, analisar e identificar o potencial de uso da AdaptMLearning e de seus algoritmos em uma situação real para elaboração de um ambiente de aprendizagem ou agregação a um ambiente existente.
Intelligent and Adaptive Learning Systems, subject of recent research in the world, are environments with specific architectures and algorithms, designed considering the individual characteristics of each student. The rapid development of wireless infrastructures and wide use of mobile devices in people\'s everyday life encourage research about the use of these devices in education, providing the mlearning. In the context of such research, this work proposes the AdaptMLearning architecture that was designed to be a learning infrastructure for mobile and nonmobile platforms. This architecture provides a selection of learning objects that takes into account as adaptation criteria the following data: the mobile device\'s technological specification; the student\'s learning style information, his/her performance and spent time associated to the student\'s interaction with the learning object; previously acquired knowledge by the student related to the course\'s content. In addition, it also allows the teacher to interfere in the adaptation criteria used during the study simulation, and allows the student to indicate his/her preferences for media types. This architecture is based on AHAM reference model for adaptive systems AEHS and uses the quadruple: the knowledge space, the user model, the observations and the model adaptation, referring to the logical definition of these systems. To implement the AdaptMLearning architecture some algorithms using the FSLSM model related to the student\'s learning styles were developed. The algorithms use the IEEE 1484 for cataloging learning objects and some of its categories and attributes associated with dimensions of learning styles FSLSM model, are used to compute a weight of an object in each dimension allowing a search of the most appropriate object according to the student\'s learning styles; and the use of fuzzy computing, considering that the student\'s learning style can change, determines if the student has to receive reinforcement or need a new study in a particular subject of a course, when the student gets unsatisfactory results in terms of timing and performance in a course\'s subject. Also, this work also presents the development and evaluation of a simulator for the AdaptMLearning architecture and their algorithms. The evaluation of the simulator was done by means of many simulations scenarios, considering students, courses and technologies with different settings. Based on the results obtained from the evaluation it was possible to discuss, analyze and identify the potential use of AdaptMLearning architecture and their algorithms in a real situation for developing a learning environment or its aggregation to an existing environment.

碩士
國立成功大學
國際企業研究所碩博士班
94
In the past decades, acquisition is a frequently used strategy. Researchers are interested in the post-acquisition performance. But most of the empirical results are disappointing. We try to propose an approach to bring bidders the better performance. Previous studies indicated that the alliances provide an opportunity for company to learn from partners. Therefore, we propose that the previous bidder and target’s alliances could cut down the information asymmetry and positively influence the acquisition performance. Whether the acquisition is non-horizontal or not is adopted as the moderator in the analysis. Non-horizontal acquisitions usually involve more information asymmetry, thus we expect prior alliances experiences are more influential in non-horizontal acquisition. Since we expect the alliances experiences with target could reduce the risk from information asymmetry, we suggest that the acquirers which face high level of information asymmetry are more likely to make alliances with target before acquisition. In this paper, we collect the US domestic acquisitions events between 1993 and 2000, and alliances events are between 1989 and 2000 from SDC. We use the post-acquisition 3-year buy-and-hold return in stock to measure the bidders’ performance, and to test our arguments. Our results support that the bidder-target alliances experiences let the bidders get better performance. The bidders possibly have prior bidder-target alliance when acquiring a nonpublic target firm. In contrast, we find the different industry background doesn’t have obvious moderating effect, and the bidders don’t tend to make alliances prior acquisitions as acquiring high technology or service target firms.

There are several features that we have come to expect from an expert performance: technical mastery, confidence, originality, flexibility, and a true understanding of the musical style. Yet the feature that both performers and listeners appear to regard as the most important is that the performer is expressive. The most-loved artists are commonly the ones that are able to express and evoke emotions in listeners. Previous studies have mainly concerned how performers express emotions, and this article focuses on this question. The article first provides working definitions of key concepts (e.g. expression, communication), and considers how performers conceive of these issues. It then reviews up-to-date evidence on how performers express emotions. Finally, the article proposes directions for future research.

This chapter draws on previous research to consider how HRM practices are used to manage human and social capital to generate superior performance in professional service firms. Previous research indicates that PSFs rely on both human capital (knowledge and skills) and social capital (relationships inside and outside the PSF) to manage their performance outputs. In this context the authors review the existing research on strategic HRM practices in PSFs which is predominantly categorized into expertise- and efficiency-orientated HRM systems. They draw on their own research to outline two models of HRM practices which are used to manage human and social capital and discuss the link to innovation. The first of these emphasizes the protection of human capital and therefore has centripetal properties, whereas the second is more client-focused and therefore displays centrifugal properties. Finally, they consider the managerial challenges that these models present and point to avenues for future research.

This chapter discusses the character Apu, exploring how his appearance on the television show The Simpsons in the 1990s was a departure from previous Hollywood and television representations of South Asians in the United States. Whereas South Asians were previously depicted as brief visitors or exotic foreigners, Apu symbolizes a permanent Indian immigrant presence in the United States. Yet, his brown-voice performance racializes and differentiates him from other Americans. The chapter theorizes the use of brown voice and discusses how animated characters, in particular, become a significant subject to study vocal accents and voiceovers. Animated characters are unique because one of their most important defining features is their voice, and, thus, animation emphasizes the voice as a site of interest in thinking about racial performance.

This is the final chapter of this book, and it brings together some of the thoughts that have been discussed previously. It explores the importance of moving on in the process, every experience good and bad contributes to an improved performance for the future. It then looks at the value of embracing the positive, having dealt with anxiety in previous chapters, and the importance of balancing the two. It considers upgrading skills, each interview itself being an upgrade, and makes suggestions for effecting change. The chapter finally reflects on our new set of psychological skills available for us in this charged and challenging process.

Chapter 4 returns to the temple arena with the account of an event in which either Alexander Janneus (Josephus) or an anonymous priest (Mishnah, Tosefta) is pelted with citrons in the temple. In Josephus this etiological story explains the circumstances underlying Janneus’s erection of a wooden barrier in the temple and, as in the previous chapter, evidences tension between Janneus and the people. The rabbinic tradition also concerns the history of the temple and its laws, but from a different direction, a conflict over the performance of the water libation. As opposed to the legends treated in the previous chapters, we cannot definitely state that these two versions derived from a single Ur-text.

AbstractThe Finnish education system has gone through an exciting developmental path from a follower into a role model. Also on the two-decade history of PISA studies, Finland’s performance has provided years of glory as of the world’s top-performing nation, but also a substantial decline. This chapter examines Finland’s educational outcomes in recent PISA-study and the trends across previous cycles. Boys’ more unsatisfactory performance and the increasing effect of students’ socio-economic background are clear predictors of the declining trend, but they can explain it only partly. Some of the other possible factors are discussed.

Previous research on teaching and learning in the design disciplines has demonstrated the complex set of factors which need to be aligned in order for our students to be prepared for professional practice in teamwork. This chapter reports on ongoing work to extend this previous research, including integration with an institutional learning outcomes framework, incorporation of insights from beyond the design disciplines to engage student motivation in capability development, and a specific interest in the ways team teaching in design studios can contribute to the development of students' teamwork capability (in addition to advancing their development of design capability).

Performance testing (PT) is not to be construed as features testing even though it has a definite link with the latter. In fact, PT begins from where the feature testing ends. It presupposes successful completion of features testing, meaning that all the desired functional requirements expected from the system are fully met. However, it is worth noting that conducting PT without features testing is often fraught with great difficulties. This is because the residual defects in the system, which otherwise would have been known in features testing, would give misleading results about the performance. Previous chapters emphasized the need for PT and various factors that have impact the performance of Web-based applications. This chapter provides an insight about the technology aspects, including the software languages, necessary for Web development. Needless to add, that technology as well as software languages have a critical impact on the performance of the system.

The knowledge embedded in organizational processes has been difficult to codify and make available to other members who need access to this knowledge either because they perform complementary processes or may need to take over the processes in question. Previous approaches to the codification of such knowledge have recognized the difficulties of capturing the context within which the knowledge is utilized. In this design-science based work, the authors propose a work process knowledge template (WPKT) which follows a systems' approach to capturing work processes that balances complexity of the template with capturing relevant context. The template was pilot tested during development, and empirically evaluated for usability, ease of use and learnability in multiple real world settings.

The present work evaluates the performance of step drills, new and after regrinding. The tools were made of P20 cemented carbide coated with TiAlN. The routine of re-coating them after regrinding were varied (no recoating, recoating over the previous coating and recoating after removing the previous coating). The output parameters considered for determining the machining performance were: tool life, thrust force, torque, form errors (roundness and cylindricity) and surface roughness (Ra and Rz parameters). The results generated with the resharpened tools were compared to those obtained with a new tool (first time used). The results showed that in general the reground tools showed worse performance than the new tools, regardless the parameter considered. Only the tools that have undergone the process of cleanness of the previous coating and then reground and recoated (with the same type of coating) showed results similar to the new tools. The tools with no recoating and those that received the recoating over the previous showed, practically in all tests, higher thrust force and torque, larger form errors and worse surface roughness than the new tools.

<p>This study was conducted on the seismic performance of the new DPT 1301/1302 - 61 earthquake design standard in Thailand, the ACI 318-11:2014, and the ASCE 7-16 Standard. The selected sample structure for the case study was an existing five-storey building located in Bangkok. It was designed as a shopping mall having a length of 350 m, a width of 35 m, and a height of 26 m, resulting in a total constructed usable area of 62,000 m2, and consists of shops, restaurants and car-park spaces. Construction started on 15th February 2013, and it was opened on 31st August 2019. Bangkok is situated on a large plain underlain by the thick alluvial and deltaic sediments of the Chao Phraya Basin. The design spectral accelerations, as specified in the previous DPT standard 1302 - 52, were established based on the data of the site characteristics available from the past. However, recent studies have revealed several key features of the site characteristics that are essential for improvement of the previous standard. The structural analysis and design of this building were performed by using computer software programs so as to comply with the previous standard. This paper presents a comparison between the previous and the newly revised standards and examines the design differences by using the selected building as a case study on the structural design of typical existing low-rise buildings in Bangkok.</p>

Abstract Reuse of prior design experience allows an engineer to save design time, by leveraging off previous work-out solutions, and to avoid repeating past mistakes, by accessing information on manufacturing or field failures. Indexing and retrieving of design cases is efficiently done based on qualitative descriptions of the behavior specification of a device. Qualitative influences has been used for behavior representation and reasoning since they allow behavior decomposition and synthesis of design parts taken from different contexts. Thus, innovative new designs are generated. However, a drawback of this kind of high-level abstractions is that important performance information contained in design specifications is not taken into account. In this article, performance information such as ranges of operation and types of response are added to the qualitative behavior representation. Higher-order behavior representations are also studied. Reasoning mechanisms are accordingly extended for index generation and retrieval of previous designs. As a result of considering performance information, the number of synthesized designs not performing according to specification can be reduced. Analysis and simulation time spent in design verification is, thereby, also reduced.

Pedestrian safety is an important concern when evaluating intersections. Previous literature has shown that exclusive pedestrian phases improve safety, but at the expense of imposing greater pedestrian and motorist delay. However, outside of crash data, there are no easily implementable performance measures for pedestrians at traffic signals. This study proposes two performance metrics: (1) a time-to-jaywalk measure, and (2) the Conflict Occupancy Ratio (COR) for evaluating concurrent pedestrian signal phasing with turning vehicles. The COR quantifies conflicts between turning vehicles and pedestrians in the crosswalk. The COR is based upon a commercially deployed video detection system that correctly identified the presence of pedestrians to within two per cycle in this study. This performance is likely sufficient for the current application, but as the technology matures it will provide a scalable screening tool to identify intersections that have opportunities for capacity adjustments or warrant further direct field investigation.

This paper presents advancements in a surrogate-based, rotor blade design optimization framework for improved helicopter performance. The framework builds on previous successes by allowing multiple airfoil sections to designed simultaneously to minimize required rotor power in multiple flight conditions. Rotor power in hover and forward flight, at advance ratio 𝜇 = 0.3, are used as objective functions in a multi-objective genetic algorithm. The framework is constructed using Galaxy Simulation Builder with optimization provided through integration with Dakota. Three independent airfoil sections are morphed using ParFoil and aerodynamic coefficients for the updated airfoil shapes (i.e., lift, drag, moment) are calculated using linear interpolation from a database generated using C81Gen/ARC2D. Final rotor performance is then calculated using RCAS. Several demonstrative optimization case studies were conducted using the UH-60A main rotor. The degrees of freedom for this case are limited to the airfoil camber, camber crest position, thickness, and thickness crest position for each of the sections. The results of the three-segment case study show improvements in rotor power of 4.3% and 0.8% in forward flight and hover, respectively. This configuration also yields greater reductions in rotor power for high advance ratios, e.g., 6.0% reduction at 𝜇 = 0.35, and 8.8% reduction at 𝜇 = 0.4.

The rate of fatalities at signalized intersections involving heavy vehicles is nearly five times higher than for passenger vehicles in the US. Previous studies in the US have found that heavy vehicles are twice as likely to violate a red light compared with passenger vehicles. Current technologies leverage setback detection to extend green time for a particular phase and are based upon typical deceleration rates for passenger cars. Furthermore, dilemma zone detectors are not effective when the max out time expires and forces the onset of yellow. This study proposes the use of connected vehicle (CV) technology to trigger force gap out (FGO) before a vehicle is expected to arrive within the dilemma zone limit at max out time. The method leverages position data from basic safety messages (BSMs) to map-match virtual waypoints located up to 1,050 ft in advance of the stop bar. For a 55 mph approach, field tests determined that using a 6 ft waypoint radius at 50 ft spacings would be sufficient to match 95% of BSM data within a 5% lag threshold of 0.59 s. The study estimates that FGOs reduce dilemma zone incursions by 34% for one approach and had no impact for the other. For both approaches, the total dilemma zone incursions decreased from 310 to 225. Although virtual waypoints were used for evaluating FGO, the study concludes by recommending that trajectory-based processing logic be incorporated into controllers for more robust support of dilemma zone and other emerging CV applications.

This report addresses the general matter of optimisation under uncertainties, following a previous report on stochastic sensitivities (deliverable 6.2). It describes several theoretical methods, as well their application into implementable algorithms. The specific case of the conditional value at risk chosen as risk measure, with its challenges, is prominently discussed. In particular, the issue of smoothness – or lack thereof – is addressed through several possible approaches. The whole report is written in the context of high-performance computing, with concern for parallelisation and cost-efficiency.

The multiple schema for the classification of soils rely on differing criteria but the major soil science systems, including the United States Department of Agriculture (USDA) and the international harmonized World Reference Base for Soil Resources soil classification systems, are primarily based on inferred pedogenesis. Largely these classifications are compiled from individual observations of soil characteristics within soil profiles, and the vast majority of this pedologic information is contained in nonquantitative text descriptions. We present initial text mining analyses of parsed text in the digitally available USDA soil taxonomy documentation and the Soil Survey Geographic database. Previous research has shown that latent information structure can be extracted from scientific literature using Natural Language Processing techniques, and we show that this latent information can be used to expedite query performance by using syntactic elements and part-of-speech tags as indices. Technical vocabulary often poses a text mining challenge due to the rarity of its diction in the broader context. We introduce an extension to the common English vocabulary that allows for nearly-complete indexing of USDA Soil Series Descriptions.

This report details both the process undertaken to develop an evaluation instrument that can collect feedback from children in the Love of Learning program and feedback the children have provided. A total of 178 children who are beneficiaries of the program completed the survey, and 91% confirmed the program was positively supporting them. They provided their feedback using a 20-question survey which measured four protective factors that previous research suggests supports children to engage with and enjoy learning, helping them to thrive in school and life. The protective factors are known to foster social, emotional, and academic development and success. There is a strong positive association between these factors, and the results of the survey suggest the Love of Learning program is influencing children's attitude towards learning and school. This report highlights some of the design challenges and complexities when engaging children in participatory evaluation. Importantly, to ensure children are given an opportunity to provide feedback, they must be supported by their foster carer who need to also feel informed and confident to be part of the evaluation process and empower children to speak up. Further research will now be conducted to implement the evaluation process more widely and ascertain if the protective factors improve a child’s health, educational engagement, and performance.

We present Any-Precision Deep Neural Networks (Any- Precision DNNs), which are trained with a new method that empowers learned DNNs to be flexible in any numerical precision during inference. The same model in runtime can be flexibly and directly set to different bit-width, by trun- cating the least significant bits, to support dynamic speed and accuracy trade-off. When all layers are set to low- bits, we show that the model achieved accuracy compara- ble to dedicated models trained at the same precision. This nice property facilitates flexible deployment of deep learn- ing models in real-world applications, where in practice trade-offs between model accuracy and runtime efficiency are often sought. Previous literature presents solutions to train models at each individual fixed efficiency/accuracy trade-off point. But how to produce a model flexible in runtime precision is largely unexplored. When the demand of efficiency/accuracy trade-off varies from time to time or even dynamically changes in runtime, it is infeasible to re-train models accordingly, and the storage budget may forbid keeping multiple models. Our proposed framework achieves this flexibility without performance degradation. More importantly, we demonstrate that this achievement is agnostic to model architectures. We experimentally validated our method with different deep network backbones (AlexNet-small, Resnet-20, Resnet-50) on different datasets (SVHN, Cifar-10, ImageNet) and observed consistent results.

1.1 Macroeconomic summary Economic recovery has consistently outperformed the technical staff’s expectations following a steep decline in activity in the second quarter of 2020. At the same time, total and core inflation rates have fallen and remain at low levels, suggesting that a significant element of the reactivation of Colombia’s economy has been related to recovery in potential GDP. This would support the technical staff’s diagnosis of weak aggregate demand and ample excess capacity. The most recently available data on 2020 growth suggests a contraction in economic activity of 6.8%, lower than estimates from January’s Monetary Policy Report (-7.2%). High-frequency indicators suggest that economic performance was significantly more dynamic than expected in January, despite mobility restrictions and quarantine measures. This has also come amid declines in total and core inflation, the latter of which was below January projections if controlling for certain relative price changes. This suggests that the unexpected strength of recent growth contains elements of demand, and that excess capacity, while significant, could be lower than previously estimated. Nevertheless, uncertainty over the measurement of excess capacity continues to be unusually high and marked both by variations in the way different economic sectors and spending components have been affected by the pandemic, and by uneven price behavior. The size of excess capacity, and in particular the evolution of the pandemic in forthcoming quarters, constitute substantial risks to the macroeconomic forecast presented in this report. Despite the unexpected strength of the recovery, the technical staff continues to project ample excess capacity that is expected to remain on the forecast horizon, alongside core inflation that will likely remain below the target. Domestic demand remains below 2019 levels amid unusually significant uncertainty over the size of excess capacity in the economy. High national unemployment (14.6% for February 2021) reflects a loose labor market, while observed total and core inflation continue to be below 2%. Inflationary pressures from the exchange rate are expected to continue to be low, with relatively little pass-through on inflation. This would be compatible with a negative output gap. Excess productive capacity and the expectation of core inflation below the 3% target on the forecast horizon provide a basis for an expansive monetary policy posture. The technical staff’s assessment of certain shocks and their expected effects on the economy, as well as the presence of several sources of uncertainty and related assumptions about their potential macroeconomic impacts, remain a feature of this report. The coronavirus pandemic, in particular, continues to affect the public health environment, and the reopening of Colombia’s economy remains incomplete. The technical staff’s assessment is that the COVID-19 shock has affected both aggregate demand and supply, but that the impact on demand has been deeper and more persistent. Given this persistence, the central forecast accounts for a gradual tightening of the output gap in the absence of new waves of contagion, and as vaccination campaigns progress. The central forecast continues to include an expected increase of total and core inflation rates in the second quarter of 2021, alongside the lapse of the temporary price relief measures put in place in 2020. Additional COVID-19 outbreaks (of uncertain duration and intensity) represent a significant risk factor that could affect these projections. Additionally, the forecast continues to include an upward trend in sovereign risk premiums, reflected by higher levels of public debt that in the wake of the pandemic are likely to persist on the forecast horizon, even in the context of a fiscal adjustment. At the same time, the projection accounts for the shortterm effects on private domestic demand from a fiscal adjustment along the lines of the one currently being proposed by the national government. This would be compatible with a gradual recovery of private domestic demand in 2022. The size and characteristics of the fiscal adjustment that is ultimately implemented, as well as the corresponding market response, represent another source of forecast uncertainty. Newly available information offers evidence of the potential for significant changes to the macroeconomic scenario, though without altering the general diagnosis described above. The most recent data on inflation, growth, fiscal policy, and international financial conditions suggests a more dynamic economy than previously expected. However, a third wave of the pandemic has delayed the re-opening of Colombia’s economy and brought with it a deceleration in economic activity. Detailed descriptions of these considerations and subsequent changes to the macroeconomic forecast are presented below. The expected annual decline in GDP (-0.3%) in the first quarter of 2021 appears to have been less pronounced than projected in January (-4.8%). Partial closures in January to address a second wave of COVID-19 appear to have had a less significant negative impact on the economy than previously estimated. This is reflected in figures related to mobility, energy demand, industry and retail sales, foreign trade, commercial transactions from selected banks, and the national statistics agency’s (DANE) economic tracking indicator (ISE). Output is now expected to have declined annually in the first quarter by 0.3%. Private consumption likely continued to recover, registering levels somewhat above those from the previous year, while public consumption likely increased significantly. While a recovery in investment in both housing and in other buildings and structures is expected, overall investment levels in this case likely continued to be low, and gross fixed capital formation is expected to continue to show significant annual declines. Imports likely recovered to again outpace exports, though both are expected to register significant annual declines. Economic activity that outpaced projections, an increase in oil prices and other export products, and an expected increase in public spending this year account for the upward revision to the 2021 growth forecast (from 4.6% with a range between 2% and 6% in January, to 6.0% with a range between 3% and 7% in April). As a result, the output gap is expected to be smaller and to tighten more rapidly than projected in the previous report, though it is still expected to remain in negative territory on the forecast horizon. Wide forecast intervals reflect the fact that the future evolution of the COVID-19 pandemic remains a significant source of uncertainty on these projections. The delay in the recovery of economic activity as a result of the resurgence of COVID-19 in the first quarter appears to have been less significant than projected in the January report. The central forecast scenario expects this improved performance to continue in 2021 alongside increased consumer and business confidence. Low real interest rates and an active credit supply would also support this dynamic, and the overall conditions would be expected to spur a recovery in consumption and investment. Increased growth in public spending and public works based on the national government’s spending plan (Plan Financiero del Gobierno) are other factors to consider. Additionally, an expected recovery in global demand and higher projected prices for oil and coffee would further contribute to improved external revenues and would favor investment, in particular in the oil sector. Given the above, the technical staff’s 2021 growth forecast has been revised upward from 4.6% in January (range from 2% to 6%) to 6.0% in April (range from 3% to 7%). These projections account for the potential for the third wave of COVID-19 to have a larger and more persistent effect on the economy than the previous wave, while also supposing that there will not be any additional significant waves of the pandemic and that mobility restrictions will be relaxed as a result. Economic growth in 2022 is expected to be 3%, with a range between 1% and 5%. This figure would be lower than projected in the January report (3.6% with a range between 2% and 6%), due to a higher base of comparison given the upward revision to expected GDP in 2021. This forecast also takes into account the likely effects on private demand of a fiscal adjustment of the size currently being proposed by the national government, and which would come into effect in 2022. Excess in productive capacity is now expected to be lower than estimated in January but continues to be significant and affected by high levels of uncertainty, as reflected in the wide forecast intervals. The possibility of new waves of the virus (of uncertain intensity and duration) represents a significant downward risk to projected GDP growth, and is signaled by the lower limits of the ranges provided in this report. Inflation (1.51%) and inflation excluding food and regulated items (0.94%) declined in March compared to December, continuing below the 3% target. The decline in inflation in this period was below projections, explained in large part by unanticipated increases in the costs of certain foods (3.92%) and regulated items (1.52%). An increase in international food and shipping prices, increased foreign demand for beef, and specific upward pressures on perishable food supplies appear to explain a lower-than-expected deceleration in the consumer price index (CPI) for foods. An unexpected increase in regulated items prices came amid unanticipated increases in international fuel prices, on some utilities rates, and for regulated education prices. The decline in annual inflation excluding food and regulated items between December and March was in line with projections from January, though this included downward pressure from a significant reduction in telecommunications rates due to the imminent entry of a new operator. When controlling for the effects of this relative price change, inflation excluding food and regulated items exceeds levels forecast in the previous report. Within this indicator of core inflation, the CPI for goods (1.05%) accelerated due to a reversion of the effects of the VAT-free day in November, which was largely accounted for in February, and possibly by the transmission of a recent depreciation of the peso on domestic prices for certain items (electric and household appliances). For their part, services prices decelerated and showed the lowest rate of annual growth (0.89%) among the large consumer baskets in the CPI. Within the services basket, the annual change in rental prices continued to decline, while those services that continue to experience the most significant restrictions on returning to normal operations (tourism, cinemas, nightlife, etc.) continued to register significant price declines. As previously mentioned, telephone rates also fell significantly due to increased competition in the market. Total inflation is expected to continue to be affected by ample excesses in productive capacity for the remainder of 2021 and 2022, though less so than projected in January. As a result, convergence to the inflation target is now expected to be somewhat faster than estimated in the previous report, assuming the absence of significant additional outbreaks of COVID-19. The technical staff’s year-end inflation projections for 2021 and 2022 have increased, suggesting figures around 3% due largely to variation in food and regulated items prices. The projection for inflation excluding food and regulated items also increased, but remains below 3%. Price relief measures on indirect taxes implemented in 2020 are expected to lapse in the second quarter of 2021, generating a one-off effect on prices and temporarily affecting inflation excluding food and regulated items. However, indexation to low levels of past inflation, weak demand, and ample excess productive capacity are expected to keep core inflation below the target, near 2.3% at the end of 2021 (previously 2.1%). The reversion in 2021 of the effects of some price relief measures on utility rates from 2020 should lead to an increase in the CPI for regulated items in the second half of this year. Annual price changes are now expected to be higher than estimated in the January report due to an increased expected path for fuel prices and unanticipated increases in regulated education prices. The projection for the CPI for foods has increased compared to the previous report, taking into account certain factors that were not anticipated in January (a less favorable agricultural cycle, increased pressure from international prices, and transport costs). Given the above, year-end annual inflation for 2021 and 2022 is now expected to be 3% and 2.8%, respectively, which would be above projections from January (2.3% and 2,7%). For its part, expected inflation based on analyst surveys suggests year-end inflation in 2021 and 2022 of 2.8% and 3.1%, respectively. There remains significant uncertainty surrounding the inflation forecasts included in this report due to several factors: 1) the evolution of the pandemic; 2) the difficulty in evaluating the size and persistence of excess productive capacity; 3) the timing and manner in which price relief measures will lapse; and 4) the future behavior of food prices. Projected 2021 growth in foreign demand (4.4% to 5.2%) and the supposed average oil price (USD 53 to USD 61 per Brent benchmark barrel) were both revised upward. An increase in long-term international interest rates has been reflected in a depreciation of the peso and could result in relatively tighter external financial conditions for emerging market economies, including Colombia. Average growth among Colombia’s trade partners was greater than expected in the fourth quarter of 2020. This, together with a sizable fiscal stimulus approved in the United States and the onset of a massive global vaccination campaign, largely explains the projected increase in foreign demand growth in 2021. The resilience of the goods market in the face of global crisis and an expected normalization in international trade are additional factors. These considerations and the expected continuation of a gradual reduction of mobility restrictions abroad suggest that Colombia’s trade partners could grow on average by 5.2% in 2021 and around 3.4% in 2022. The improved prospects for global economic growth have led to an increase in current and expected oil prices. Production interruptions due to a heavy winter, reduced inventories, and increased supply restrictions instituted by producing countries have also contributed to the increase. Meanwhile, market forecasts and recent Federal Reserve pronouncements suggest that the benchmark interest rate in the U.S. will remain stable for the next two years. Nevertheless, a significant increase in public spending in the country has fostered expectations for greater growth and inflation, as well as increased uncertainty over the moment in which a normalization of monetary policy might begin. This has been reflected in an increase in long-term interest rates. In this context, emerging market economies in the region, including Colombia, have registered increases in sovereign risk premiums and long-term domestic interest rates, and a depreciation of local currencies against the dollar. Recent outbreaks of COVID-19 in several of these economies; limits on vaccine supply and the slow pace of immunization campaigns in some countries; a significant increase in public debt; and tensions between the United States and China, among other factors, all add to a high level of uncertainty surrounding interest rate spreads, external financing conditions, and the future performance of risk premiums. The impact that this environment could have on the exchange rate and on domestic financing conditions represent risks to the macroeconomic and monetary policy forecasts. Domestic financial conditions continue to favor recovery in economic activity. The transmission of reductions to the policy interest rate on credit rates has been significant. The banking portfolio continues to recover amid circumstances that have affected both the supply and demand for loans, and in which some credit risks have materialized. Preferential and ordinary commercial interest rates have fallen to a similar degree as the benchmark interest rate. As is generally the case, this transmission has come at a slower pace for consumer credit rates, and has been further delayed in the case of mortgage rates. Commercial credit levels stabilized above pre-pandemic levels in March, following an increase resulting from significant liquidity requirements for businesses in the second quarter of 2020. The consumer credit portfolio continued to recover and has now surpassed February 2020 levels, though overall growth in the portfolio remains low. At the same time, portfolio projections and default indicators have increased, and credit establishment earnings have come down. Despite this, credit disbursements continue to recover and solvency indicators remain well above regulatory minimums. 1.2 Monetary policy decision In its meetings in March and April the BDBR left the benchmark interest rate unchanged at 1.75%.

An approach to increasing sensor performance and detection reliability for buried objects is to better understand which physical processes are dominant under certain environmental conditions. The present effort (Phase 2) builds on our previously published prior effort (Phase 1), which examined methods of determining the probability of detection and false alarm rates using thermal infrared for buried-object detection. The study utilized a 3.05 × 3.05 m test plot in Hanover, New Hampshire. Unlike Phase 1, the current effort involved removing the soil from the test plot area, homogenizing the material, then reapplying it into eight discrete layers along with buried sensors and objects representing targets of inter-est. Each layer was compacted to a uniform density consistent with the background undisturbed density. Homogenization greatly reduced the microscale soil temperature variability, simplifying data analysis. The Phase 2 study spanned May–November 2018. Simultaneous measurements of soil temperature and moisture (as well as air temperature and humidity, cloud cover, and incoming solar radiation) were obtained daily and recorded at 15-minute intervals and coupled with thermal infrared and electro-optical image collection at 5-minute intervals.