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In our earlier work, Network-Centric Optimal Hybrid Mobility for IPv6 wireless sensor networks, in which the work sought to control mobility of sensor nodes from an external network was proposed. It was a major improvement on earlier works such as Cluster Sensor Proxy Mobile IPv6 (CSPMIPv6) and Network of Proxies (NoP). In this work, the Network-Centric optimal hybrid mobility scenario was used to detect and fill sensing holes occurring as a result damaged or energy depleted sensing nodes. Various sensor networks self-healing and recovery, and deployment algorithms such as Enhanced Virtual Forces Algorithm with Boundary Forces (EVFA-B); Coverage - Aware Sensor Automation protocol (CASA); Sensor Self-Organizing Algorithm (SSOA); VorLag and the use of the use of anchor and relay nodes were reviewed. With node density thresholds set for various scenarios, the recovery efficiency using various parameters were measured. Comparably, our method provides the most efficient node relocation and self-healing mechanism for sensor networks. Compared to Sensor Self-Organizing Algorithm (SSOA), Hybrid Mobile IP showed superiority in coverage, shorter period of recovery, less computational cost and lower energy depletion. With processing and mobility costs shifted to the external network, Hybrid Mobile IP extends the life span of the network., Comment: 18 pages, 13 figures

Maize farming is a major livelihood activity for many farmers in Ghana. Unfortunately, farmers usually do not obtain the expected returns on their investment due to reliance on rudimentary, labor-intensive, and inefficient methods of production. Using cross-sectional data from 359 maize farmers, this study investigates the profitability and determinants of the use of tractor services for maize production in Ejura-Sekyedumase, Ashanti Region of Ghana. Results from descriptive and profitability analyses reveal that tractor services such as ploughing and shelling are widely used, but their profitability varies significantly among farmers. Key factors influencing profitability include farm size, fertilizer quantity applied, and farmer experience. Results from a multivariate probit analysis also showed that farming experience, fertilizer quantity, and profit per acre have a positive influence on tractor service use for shelling, while household size, farm size, and FBO have a negative influence. Farming experience, fertilizer quantity, and profit per acre positively influence tractor service use for ploughing, while farm size has a negative influence. A t-test result reveals a statistically significant difference in profit between farmers who use tractor services and those who do not. Specifically, farmers who utilize tractor services on their maize farm had a return to cost of 9 percent more than those who do not (p-value < 0.05). The Kendall's result showed a moderate agreement among the maize farmers (first ranked being financial issues) in their ability to access/utilize tractor services on their farm.

What does work and career success mean for those who secure their work using digital labor platforms? Traditional research on success predominantly relies on organizationally-centric benchmarks, such as promotions and income. These measures provide limited insights into the evolving nature of work and careers shaped at the intersection of digital labor platform technologies and workers' evolving perspectives. Drawing on data from a longitudinal study of 108 digital labor platform workers on Upwork, we (1) identify seven dimensions of success indicators that reflect workers' definitions of success in platform-mediated work and careers, (2) delineate three dimensions of digital labor platforms mediating workers' experiences of success and (3) examine the shifting perspectives of these workers relative to success. Based on these findings, we discuss the implications of platform-mediated success in workers' labor experiences, marked by platformic management, standardization, precarity and ongoing evolution. Our discussion intertwines CSCW scholarship with career studies, advancing a more nuanced understanding of the evolving perspectives on success in platform-mediated work and careers., Comment: PAPER WAS ACCEPTED AT CSCW ON SEPTEMBER 2024

Numerical computations and methods have become increasingly crucial in the study of spin foam models across various regimes. This paper adds to this field by introducing new algorithms based on tensor network methods for computing amplitudes, focusing on topological SU(2) BF and Lorentzian EPRL spin foam models. By reorganizing the sums and tensors involved, vertex amplitudes are recast as a sequence of matrix contractions. This reorganization significantly reduces computational complexity and memory usage, allowing for scalable and efficient computations of the amplitudes for larger representation labels on standard consumer hardware--previously infeasible due to the computational demands of high-valent tensors. We apply these tensor network algorithms to analyze the characteristics of various vertex configurations, including Regge and vector geometries for the SU(2) BF theory, demonstrating consistent scaling behavior and differing oscillation patterns. Our benchmarks reveal substantial improvements in computational time and memory allocations, especially for large representation labels. Additionally, these tensor network methods are applicable to generic 2-complexes with multiple vertices, where we introduce partial-coherent vertex amplitudes to streamline the computations. The implementation of these algorithms is available on GitHub for further exploration and use., Comment: 31 pages, 8 figures, 3 tables

A fourth-order exponential time differencing (ETD) Runge-Kutta scheme with dimensional splitting is developed to solve multidimensional non-linear systems of reaction-diffusion equations (RDE). By approximating the matrix exponential in the scheme with the A-acceptable Pad\'e (2,2) rational function, the resulting scheme (ETDRK4P22-IF) is verified empirically to be fourth-order accurate for several RDE. The scheme is shown to be more efficient than competing fourth-order ETD and IMEX schemes, achieving up to 20 times speed in CPU time. Inclusion of up to three pre-smoothing steps of a lower order L-stable scheme facilitates efficient damping of spurious oscillations arising from problems with non-smooth initial/boundary conditions., Comment: 41 pages, 5 figures

Area variables are intrinsic to connection formulations of general relativity, in contrast to the fundamental length variables prevalent in metric formulations. Within 4D discrete gravity, particularly based on triangulations, the area-length system establishes a relationship between area variables associated with triangles and the edge length variables. This system is comprised of polynomial equations derived from Heron's formula, which relates the area of a triangle to its edge lengths. Using tools from numerical algebraic geometry, we study the area-length systems. In particular, we show that given the ten triangular areas of a single 4-simplex, there could be up to 64 compatible sets of edge lengths. Moreover, we show that these 64 solutions do not, in general, admit formulae in terms of the areas by analyzing the Galois group, or monodromy group, of the problem. We show that by introducing additional symmetry constraints, it is possible to obtain such formulae for the edge lengths. We take the first steps toward applying our results within discrete quantum gravity, specifically for effective spin foam models., Comment: 15 pages, 9 figures, 4 tables: New Version matches published article on Class. Quant. Grav. Journal

Generative AI is changing the way that many disciplines are taught, including computer science. Researchers have shown that generative AI tools are capable of solving programming problems, writing extensive blocks of code, and explaining complex code in simple terms. Particular promise has been shown in using generative AI to enhance programming error messages. Both students and instructors have complained for decades that these messages are often cryptic and difficult to understand. Yet recent work has shown that students make fewer repeated errors when enhanced via GPT-4. We extend this work by implementing feedback from ChatGPT for all programs submitted to our automated assessment tool, Athene, providing help for compiler, run-time, and logic errors. Our results indicate that adding generative AI to an automated assessment tool does not necessarily make it better and that design of the interface matters greatly to the usability of the feedback that GPT-4 provided., Comment: Accepted to CHI 2024

We introduce the n-th Heron variety as the realization space of the (squared) volumes of faces of an n-simplex. Our primary goal is to understand the extent to which Heron's formula, which expresses the area of a triangle as a function of its three edge lengths, can be generalized. Such a formula for one face volume of an n-simplex in terms of other face volumes expresses a dependence in the algebraic matroid of the Heron variety. Whether the volume is expressible in terms of radicals is controlled by the monodromy groups of the coordinate projections of the Heron variety onto coordinates of bases. We discuss a suite of algorithms, some new, for determining these matroids and monodromy groups. We apply these algorithms toward the smaller Heron varieties, organize our findings, and interpret the results in the context of our original motivation., Comment: 25 pages, 11 figures