Returns from Self-Employment: Using Human Capital Theory to Compare U.S. Natives and Immigrants

The focus of this paper is to examine the economic returns from self-employment when comparing natives and immigrants. I hypothesize that returns from self-employment will increase with age and education, and that immigrants from China, India, and the Philippines will have higher returns while immigrants from Mexico will have lower returns than natives. I also hypothesize that immigrants with high levels of education will earn more than natives with the same amount of education. The OLS regressions show that human capital variables explain the differences in self-employed income between natives and immigrants, as the literature suggests

ExploitingDMAto enablenon-blockingexecution inDecoupledThreadedArchitecture

DTA (Decoupled Threaded Architecture) is designed to exploit fine/medium grained Thread Level Parallelism (TLP) by using a distributed hardware scheduling unit and relying on existing simple cores (in-order pipelines, no branch predictors, no ROBs). In DTA, the local variables and synchronization data are communicated via a fast frame memory. If the compiler can not remove global data accesses, the threads are excessively fragmented. Therefore, in this paper, we present an implementation of a pre-fetching mechanism (for global data) that complements the original DTA pre-load mechanism (for consumer-producer data patterns) with the aim of improving non-blocking execution of the threads. Our implementation is based on an enhanced DMA mechanism to prefetch global data. We estimated the benefit and identified the required support of this proposed approach, in an initial implementation. In case of longer latency to access memory, our idea can reduce execution time greatly (i.e.,11xforthezoombenchmarkon8processors)compared to the case of no-prefetching. 1

On-photo Restitution and Management of an Angular Size-Illusion\u27s Behaviour Experienced in Architectural/Urban Spaces

An angular size-illusion refers to a contradictory effect related to a seeming size-decrease of focused objects as the observer approaches them. This paper continues the research in this field, trying to establish fundamental principles of how to: (a) efficiently perform an on-photo restitution of an illusion\u27s behaviour (expressed by illusion descriptors) when it is experienced in architectural/urban spaces during movement under the influence of available triggers (represented by illusion determinants of physical nature), and (b) manage it computationally so as to be sustainable for contemporary professional practice. To explain that conceptually, one simple architectural/urban matrix is chosen and digitally photographed. Images are photogrammetrically processed and determinants-related data obtained. Subsequently, descriptors-related outputs are calculated by applying derived mathematical equations (expressed in function of those determinants-related data). Then, behaviour-charts are created and corresponding illusion-characteristics read-off. Finally, it is illustrated how to manage (intentionally modify) the restituted behaviour by varying values of acquired determinants-related data. Given results allow also to "design a new illusion" (to programme and control it) by simulating in digital VR/AR environments. Thus, any cause of unwanted/unpredictable visual impression degradations of important architectural/urban structures can be prevented or minimized (by planning and performing adequate spatial/physical interventions on existing/reconstructed/newly designed matrices)

Neural Radiance Fields for Manhattan Scenes with Unknown Manhattan Frame

Novel view synthesis and 3D modeling using implicit neural field representation are shown to be very effective for calibrated multi-view cameras. Such representations are known to benefit from additional geometric and semantic supervision. Most existing methods that exploit additional supervision require dense pixel-wise labels or localized scene priors. These methods cannot benefit from high-level vague scene priors provided in terms of scenes' descriptions. In this work, we aim to leverage the geometric prior of Manhattan scenes to improve the implicit neural radiance field representations. More precisely, we assume that only the knowledge of the indoor scene (under investigation) being Manhattan is known -- with no additional information whatsoever -- with an unknown Manhattan coordinate frame. Such high-level prior is used to self-supervise the surface normals derived explicitly in the implicit neural fields. Our modeling allows us to group the derived normals and exploit their orthogonality constraints for self-supervision. Our exhaustive experiments on datasets of diverse indoor scenes demonstrate the significant benefit of the proposed method over the established baselines

Rating the Relevant Factors of Business Conditions for Entrepreneurs in Serbia

In this paper were processed and analyzed the attitudes and opinions of potential entrepreneurs regarding to starting their own businesses, in order to scan favorable conditions for development of entrepreneurship in Serbia. As a basic research instrument, a questionnaire with questions about the possibilities and limitations of entrepreneurial business was designed, with the task of identification and assessment of relevant factors that condition the operations of entrepreneurs in Serbia. Throughout the conducted research, it was concluded there are numerous obstacles to business start-ups and successful growth and development of entrepreneurship in Serbia. Participants of the survey believe they have competencies for starting their own business, but due to the unfavorable market conditions and the lack of financial resources, do not see themselves as employers. Analyzing of efforts and time, as well as the risks they take, it is concluded that most of them are not motivated to engage in entrepreneurship and does not plan a professional career in that field