No description available.

El siguiente plan de negocios contempla la creación de DIVERSITAS CONSULTORAS: Consultora estratégica DirCom para la adecuada gestión de la comunicación organizacional en temas de Diversidad e Inclusión, basada en 3 campos de acción: equidad de género, comunidad LGBTIQ+ y discapacidad y habilidades distintas. La consultora pretende diagnosticar el estado de las organizaciones, identificar oportunidades, planificar las estrategias de comunicación y darle acompañamiento a la implementación de las mismas; monitoreando los resultados de manera continua, por medio de información en tiempo real. El plan contempla un benchmark y análisis del mercado de consultoría en el Perú, donde hemos explorado el entorno, la competencia, las necesidades de las organizaciones y los retos frente al nuevo contexto de la emergencia sanitaria que estamos viviendo; descubriendo que existen nichos de mercado desatendidos y deseosos de implementar estrategias comunicacionales de Diversidad e Inclusión. Nuestra propuesta de valor resalta la creación de la plataforma “Diversitas Digital”, una herramienta 100% online que permitirá transformar la forma en cómo las organizaciones vienen trabajando, democratizando los contenidos y obteniendo indicadores de medición en tiempo real; más ahora que la digitalización en las organizaciones ha tomado un rol importante a causa de la pandemia mundial del COVID-19. Finalmente, el análisis financiero nos muestra la viabilidad del negocio, con una proyección de crecimiento sostenible y una utilidad neta del 14% en el segundo año, donde el Valor Actual Neto (VAN) es de S/ 10, 569,709 soles y la Tasa Interna de Retorno (TIR) es de 83%. / The following business plan contemplates the creation of DIVERSITAS CONSULTANTS: DirCom strategic consultant for the proper management of organizational communication on Diversity and Inclusion issues, based on 3 lines of action: gender equality, LGBTIQ + community and disability and different skills. The consulting firm aims to diagnose the state of organizations, identify opportunities, plan communication strategies and provide support for their implementation; monitoring the results continuously through information in real time. The plan includes a benchmark and analysis of the consulting market in Peru, where we have explored the environment, the competition, the needs of the organizations and the challenges facing the new context of the health emergency that we are experiencing; discovering that there are neglected market niches willing to implement Inclusion and Diversity communication strategies. Our value proposition highlights the creation of the “Diversitas Digital” platform, a 100% online tool that will allow us to transform the way organizations are working, democratizing content and obtaining measurement indicators in real time; more so now that digitalization in organizations has taken an important role, especially taking into account scenarios such as the current pandemic caused by COVID-19. Finally, the financial analysis shows us the viability of the business, with a projection of sustainable growth and a net profit of 14% in the second year, where the Net Present Value (NPV) is S/ 10, 569,709 soles and the Internal Rate of Return (IRR) is 83%. / Trabajo de investigación

Reading competency is related to individuals' success at school and in their careers. Students who experience significant problems with reading may be at risk of long-term academic and social problems. High-quality measures that determine student progress toward curricular goals are needed for early identification and interventions to improve reading abilities and ultimately prevent subsequent failure in reading. The purpose of this quantitative nonexperimental ex post facto research study was to determine whether a correlation existed amongst student achievement scores on the Fountas and Pinnell Reading Benchmark Assessment and reading comprehension scores on the Criterion Reference Competency Test (CRCT). The item response theory served as the conceptual framework for examining whether a relationship exists between Fountas and Pinnell Benchmark Instructional Reading Levels and the reading comprehension scores on the CRCT of students in Grades 3, 4, and 5 in the year 2013-2014. Archival data for 329 students in Grades 3-5 were collected and analyzed through Spearman's rank-order correlation. The results showed positive relationships between the scores. The findings promote positive social change by supporting the use of benchmark assessment data to identify at-risk reading students early.

Effects of Interactive Read-Aloud and Literature Discussion on Reading Comprehension for First-Grade Students With Language Impairments in a Title 1 School. Elizabeth Vultaggio Salah, 2014: Applied Dissertation, Nova Southeastern University, Abraham S. Fischler School of Education. Language Impaired, First-Grade, Title 1 Schools, Reading Comprehension, Interactive Read-Aloud, Literature Discussion, Fountas and Pinnell. This applied dissertation was designed to determine the effects of the interactive read-aloud and literature discussion on reading comprehension for first-grade students with language impairments in a Title 1 School. This study was conducted as an embedded case study design using a quantitative method for data collection and analysis. The de-identified data was collected and analyzed from two consecutive school years (i.e., 2012-2013, 2013-2014). Data on the students' overtime (i.e., from kindergarten to first-grade) was collected and analyzed based upon a multiple case study design. Data points were collected using the A-B design, a two phase, basic signal-subject design. The A in the A-B design was the individual student's baseline data point; whereas B, was the data point after the intervention. The researcher observed and measured individual student data from the kindergarten school year (A). The researcher administered the read-aloud intervention, and observed and measured multiple data points after the intervention (B). The students' scores were determined using ongoing data collection. Since the overall design was to measure improvement in the four students overtime, no comparison groups were used. An analysis of the de-identified data revealed how individual language impaired students responded to the intervention. The researcher concluded that interactive read-aloud coupled with literature discussions improved reading comprehension of first-grade language impaired students based on results of the Oral Language Assessment and the Comprehension Conversation Assessment of the Fountas and Pinnell Benchmark System 1. Recommendations were made for future research.

<p>This dissertation studies the impact of mutual fund managers' beliefs on fund performance in the first chapter and focuses on the impact of firm behavior on stock performance in the second chapter. </p> <p><br></p> <p>In the first chapter, I utilize the Revealed Preference Theory to recover fund manager belief formation directly from their actual trading activities. By relating stock holdings in a fund's portfolio to past factor returns, I document three facts about managers' belief formation: 1. In contrast to belief extrapolation, a substantial fraction of mutual fund managers act as contrarian investors who expect lower factor returns after a good factor performance; 2. Whether a fund trades in an extrapolative or contrarian way is due to its managers' expectation biases rather than fund style investment strategy, fund catering strategy or fund risk preference; and 3. Contrarian managers generate superior performance, are more experienced investors, charge higher expense ratios, and manage smaller US equity funds. The top (contrarian) managers significantly outperform the bottom (extrapolative) managers by a return of 3.4% per annum after adjusting by FFC4 factor models.</p> <p><br></p> <p>The second chapter is co-authored paper with Yan Liu and Feng Zhang. In this chapter, we systematically replicate the bulk of long-run event studies conducted in the last three decades from 1990 to 2020 using extended samples and four long-run performance measures. The final sample contains 62 papers of long-run event studies and 148 corporate events. Our findings suggest that long-run return anomalies documented in the last three decades are not robust, and firms do not earn long-run abnormal returns following various types of corporate events. Only 2% of the 148 corporate events we replicate earn post-event abnormal returns that are statistically significant at the 5% level based on all the four performance measures, and the fraction further shrinks to 0% at the 1% significance level. Viewed together, our findings suggest that these long-run abnormal returns after corporate events are likely the result of data mining or "p-hacking".</p>

The Information and Communication Technology (ICT) industry and network researchers use traffic generator tools to a large extent to test their systems. The industry uses reliable and rigid hardware-based platform tools for high-performance network testing. The research community commonly uses software-based tools in, for example, experiments because of economic and flexibility aspects. As a result, it is possible to run these tools on different systems and hardware. In this thesis, we examine the software traffic generators Iperf, Mausezahn, Ostinato in a closed loop physical and virtual environment to evaluate the applicability of the tools and find sources of inaccuracy for a given traffic profile. For each network tool, we measure the throughput from 64- to 4096-byte in packet sizes. Also, we encapsulate each tool with container technology using Docker to reach a more reproducible and portable research. Our results show that the CPU primarily limits the throughput for small packet sizes, and saturates the 1000 Mbps link for larger packet sizes. Finally, we suggest using these tools for simpler and automated network tests. / IT-branschen och nätverksforskare använder sig av trafikgeneratorer till stor del för att testa sina system. Industrin använder sig av stabila och pålitliga hårdvaruplattformar för högpresterande nätverkstester. Forskare brukar använda mjukvarubaserade verktyg i till exempel experiment på grund av ekonomiska och flexibilitet skäl. Det är därför möjligt att använda dessa verktyg på olika system och hårdvaror. I denna avhandling undersöker vi mjukvarutrafikgeneratorerna Iperf, Mausezahn, Ostinato i en isolerad fysisk och virtuell miljö, det vill säga för att utvärdera användbarheten av verktygen och hitta felkällor för en given trafikprofil. För varje nätverksverktyg mäter vi genomströmningen från 64 till 4096 byte i paketstorlekar. Dessutom paketerar vi varje verktyg med molnteknologin Docker för att nå ett mer reproducerbart och portabelt arbete. Våra resultat visar att processorn begränsar genomströmningen för små paketstorlekar och saturerar 1000 Mbps-länken för större paketstorlekar. Slutligen föreslår vi att man kan använda dessa verktyg för enklare och automatiserade nätverkstester.

Feature selection is the process of automatically selecting important features from data. It is an essential part of machine learning, artificial intelligence, data mining, and modelling in general. There are many feature selection algorithms available and the appropriate choice can be difficult. The aim of this thesis was to compare feature selection algorithms in order to provide an experimental basis for which algorithm to choose. The first phase involved assessing which algorithms are most common in the scientific community, through a systematic literature study in the two largest reference databases: Scopus and Web of Science. The second phase involved constructing and implementing a benchmark pipeline to compare 31 algorithms’ performance on 50 data sets.The selected features were used to construct classification models and their predictive performances were compared, as well as the runtime of the selection process. The results show a small overall superiority of embedded type algorithms, especially types that involve Decision Trees. However, there is no algorithm that is significantly superior in every case. The pipeline and data from the experiments can be used by practitioners in determining which algorithms to apply to their respective problems. / Variabelselektion är en process där relevanta variabler automatiskt selekteras i data. Det är en essentiell del av maskininlärning, artificiell intelligens, datautvinning och modellering i allmänhet. Den stora mängden variabelselektionsalgoritmer kan göra det svårt att avgöra vilken algoritm som ska användas. Målet med detta examensarbete är att jämföra variabelselektionsalgoritmer för att ge en experimentell bas för valet av algoritm. I första fasen avgjordes vilka algoritmer som är mest förekommande i vetenskapen, via en systematisk litteraturstudie i de två största referensdatabaserna: Scopus och Web of Science. Den andra fasen bestod av att konstruera och implementera en experimentell mjukvara för att jämföra algoritmernas prestanda på 50 data set. De valda variablerna användes för att konstruera klassificeringsmodeller vars prediktiva prestanda, samt selektionsprocessens körningstid, jämfördes. Resultatet visar att inbäddade algoritmer i viss grad är överlägsna, framför allt typer som bygger på beslutsträd. Det finns dock ingen algoritm som är signifikant överlägsen i varje sammanhang. Programmet och datan från experimenten kan användas av utövare för att avgöra vilken algoritm som bör appliceras på deras respektive problem.

In recent years, developers have wanted to design more complex and advanced embedded processors. The feasibility of developed processors must be verified before the actual application. However, the process of verification always needs high costs and time. Quick Emulator (QEMU), a virtual platform emulator, can help in this situation. It can emulate different processors and hardware environments and build a unique platform according to the designers wishes. Many people have used QEMU to emulate advanced Reduced Instruction Set Computing (RISC) processors (like ARM) or the X86 architectures. Still, there is little research on RISC-V processors. Therefore, studying the QEMU to emulate the RISC-V processor is important. This thesis aims to evaluate the performance of the RISC-V processor using QEMU. Ten different benchmarks are designed, and their results are compared to reflect the performance of the RISC-V as well as the simulator. These results provide a reference when these benchmarks are run on the RISC-V processor that is on the actual hardware development board. / De senaste åren har utvecklarna alltid velat utveckla mer komplexa och avancerade funktioner på inbyggda utvecklingskort. Men de nya funktionerna måste verifieras innan man gör kretskortet. Å andra sidan så kostar verifieringsprocessen mycket tid och pengar. Quick Emulator (QEMU), en virtuell plattformsemulator, kan hjälpa till för att lösa detta problem. Den kan emulera olika processorer och hårdvarumiljöer och bygga en unik plattform allt enligt designernas önskemål. Många människor har använt QEMU för att emulera avancerade Reduced Instruction Set Computing (RISC)-processorer (som ARM), eller X86-arkitekturerna, men det finns mycket lite forskning om RISC-V processorer. Därför är det viktigt att studera QEMU för att emulera RISC-V-processorn. Denna avhandling syftar till att utvärdera prestandan för RISC-V processorer genom att använder QEMU. Tio olika benchmarks konstrueras för att användas för att spegla prestandan hos processorn såväl som simulatorn. Dessa resultat kan sedan användas som referens när benchmarken körs på de RISC-V-processorer som finns på det aktuella hårdvaruutvecklingskortet.

The growth of distributed applications stand on a foundation of containers and their communication and have seen the rise and fall of many implementations throughout the years with a mix of proprietary and open sources. Today there are two implementations widely used as a result of the popularity of the huge project Kubernetes: CRI-O and Containerd. Both with the edge responsibility of managing containers using similar underlying software raising the question; do they have any implications on the containers they spawn? This thesis investigate these implementations from a performance perspective with a custom developed tool for direct communication to them and run a suite of benchmarks within the containers created by each. The suite consists of tests for throughput, latency, cpu, memory, random file read/write and sequential file read/write. Results conclude they perform similarly in all, but the file tests which showed overall CRI-O dominating in write speed and Containerd dominating the read speed.

No description available.