Why your job doesn't have to be your passion

This study reconstructs a technology-assisted inclusive mathematics design for marginalized Indonesian children in Malaysian community learning centers, focusing on basic geometry (points, lines, planes, space, angles) while cultivating Indonesian identity. Using Didactical Design Research with an interpretive–critical stance at the prospective stage, we analyzed initial conditions via Brousseau’s TDS (action–formulation–validation–institutionalization), phenomenological accounts of teachers and students, content–epistemic analysis of geometry, and socio-cultural contexts; data came from participant observation, interviews, FGDs, diagnostic–formative assessments, and learning artifacts, with expert validation, triangulation, and member checking. Findings show highly heterogeneous multigrade classes, scarce resources, and a definition–notation–drill routine lacking manipulatives and institutionalization, yielding declarative, authority-dependent, and fragile understanding with minimal differentiation. The resulting hypothetical design revitalizes the didactic cycle through concrete activities (string, acetate, cube nets, protractors) linked to low-bandwidth digital representations (GeoGebra, micro-videos, interactive sheets), dual-evidence validation (visual/kinesthetic plus symbolic), public class summaries as collective memory, and multilevel differentiation for combined Grades IV–VI using a “remote lead instructor + local facilitator” model. Targeted outcomes include reduced key misconceptions, stronger conceptual understanding and confidence, consistent enactment, low operational cost, and ease of replication across WNI studios, with constraints (legality, volunteer variability, connectivity) mitigated via flexible scheduling, asynchronous/offline content, print packets, and periodic synchronization.

A Game-based Analysis of Freight Paths Allocation with a Case Study on Great Britain Brighton Main Line

Modern real-time applications like avionics and Internet-of-Things are required to aggregate more features and functionality with less production costs. Future applications like CityAirbus and autonomous driving require large distributed systems to deliver expected services and performance. For such systems, scheduling large set of applications may lead to contradicting problems, e.g., resource scarcity and swap (size, weight and power). The time-triggered (TT) computation model has the potential to ease the way for solving all these issues. However, TT scheduling poses several challenges including complex network architectures, co-synthesis of allocation/scheduling and complex constraints (e.g., precedence, latency, reliability, etc.). Although state-of-the-art processor and network scheduling approaches can be used to generate TT schedules for small to medium sized systems, they fail to provide solutions for large distributed systems. In this paper, we discuss the design of a modular, scalable and flexible scheduler for large distributed TT networked systems. We introduce a novel search-space pruning technique, based on the response-times to generate schedules for large systems within reasonable time. Based on our modular scheduler design, we also provide an extension for TTEthernet networks. Through extensive evaluation, we demonstrate that our scheduler is capable of fulfilling the demands of modern and future real-time applications and that it dominates the state-of-the-art TT scheduling approaches in terms of schedulability and run-times.

Flexibility in course scheduling is an integral part of institutional strategies used to increase student engagement and success, yet little research exists that examines scheduling as a key factor that determines students’ experiences and educational outcomes. This study explored the undergraduate sport science students and their teachers at Jimma University, Ethiopia, regarding their experiences in semester-based and block scheduling formats as well as their reflections and perspectives on the effectiveness of these scheduling formats for teaching and learning. For this, the study used an exploratory mixed-methods design consisting of individual interviews with six teachers and focus group interviews with undergraduate sports sciences student sample (n = 40), and institutional archives of the sampled students’ cumulative grade point averages (GPAs). The study findings indicate divergent views regarding their perceptions and mixed experiences with the semester-based and block scheduled courses. Irrespective of these, the majority of participants reported that teachers’ missing scheduled classes, tending not to teach the full time of the class session, continual lecturing, and scarcity of instructional resources are the major challenges surrounding the implementation of both semester-based and block teaching. We discuss the implications of these findings for future research, implementation, and intervention design.

The goal of the Universal Mobile Telecommunication System (UMTS) is the delivery of multimedia services to the mobile user. Each different service requires its specific quality of service (QoS) to satisfy the mobile user. In this paper, a scheduling algorithm for the medium access control (MAC) is presented that satisfies these QoS requirements. The main task of a scheduler is the of logical channels to appropriate transport in accordance to service requirements. Considering packet based services, the traffic characteristic is very dynamic due to its interactive and bursty nature. In consequence, a highly dynamic and flexible scheduling is required since the scarce radio resource should be used most efficient. The paper introduces a scheduler with dynamic channel type switching and transport format (TF) selection in accordance to the service QoS requirements. To validate the scheduling concept a typical mobile user application mix is examined for performance analysis by simulations.

The scarcity of energy resources and spectrum resources has become an urgent problem with the exponential increase of communication devices. Meanwhile, unmanned aerial vehicle (UAV) is widely used to help communication network recently due to its maneuverability and flexibility. In this paper, we consider a UAV-assisted energy and spectrum harvesting (ESH) network to better solve the spectrum and energy scarcity problem, where nearby secondary users (SUs) harvest energy from the base station (BS) and perform data transmission to the BS, while remote SUs harvest energy from both BS and UAV but only transmit data to UAV to reduce the influence of near-far problem. We propose an unaligned time allocation scheme (UTAS) in which the uplink phase and downlink phase of nearby SUs and remote SUs are unaligned to achieve more flexible time schedule, including schemes (a) and (b) in remote SUs due to the half-duplex of energy harvesting circuit. In addition, maximum throughput optimization problems are formulated for nearby SUs and remote SUs respectively to find the optimal time allocation. The optimization problem can be divided into three cases according to the relationship between practical data volume and theoretical throughput to avoid the waste of time resource. The expressions of optimal energy harvesting time and data transmission time of each node are derived. Lastly, a successive convex approximation based iterative algorithm (SCAIA) is designed to get the optimal UAV trajectory in broadcast mode. Simulation results show that the proposed UTAS can achieve better performance than traditional time allocation schemes.

In this paper, we build on and extend Gartner and Kolisch (2014)’s hospital-wide patient scheduling problem. Their contribution margin maximising model decides on the patients’ discharge date and therefore the length of stay. Decisions such as the allocation of scarce hospital resources along the clinical pathways are taken. Our extensions which are modeled as a mathematical program include admission decisions and flexible patient-to-specialty assignments to account for multi-morbid patients. Another flexibility extension is that one out of multiple surgical teams can be assigned to each patient. Furthermore, we consider overtime availability of human resources such as residents and nurses. Finally, we include these extensions in the rolling-horizon approach and account for lognormal distributed recovery times and remaining resource capacity for elective patients. Our computational study on real-world instances reveals that, if overtime flexibility is allowed, up to 5% increase in contribution margin can be achieved by reducing length of stay by up to 30%. At the same time, allowing for overtime can reduce waiting times by up to 33%. Our model can be applied in and generalised towards other patient scheduling problems, for example in cancer care where patients may follow defined cancer pathways.

With the dense deployment of the satellite constellations, spectrum sharing among multiple satellite communication systems is a feasible way to alleviate the scarcity of spectrum resources. In order to improve the spectrum efficiency, we investigate the resource allocation in the spectrum sharing scenario of multiple beam-hopping (BH) based satellite systems. The BH technology enhances the scheduling flexibility and the reusability of the transmission resources, but it also makes the inter-system interference more complicated. Under the interference constraint, the resource allocation problem is formulated to maximize the throughput of the satellite system. Based on the set of feasible beam allocation patterns, the optimization problem is reformulated as a mixed integer linear programming problem to obtain the optimal solution. A greedy suboptimal algorithm is also proposed to solve the problem with low complexity. To further accelerate the resource allocation process, the inter-beam distance threshold is introduced to reduce the number of feasible beam allocation patterns. Simulation results show that the proposed resource allocation algorithms achieve higher system throughput and better adaptability to the uneven distribution of traffic demands. It is also shown that the suboptimal algorithm achieves desirable performance with lower computational complexity, which is more attractive for the real-time resource allocation in the satellite systems.

Dynamic scheduling problems are ubiquitous: traffic lights, elevators, planning of manufacturing plants, air traffic control, etc. Tasks have to be put on a timeline as smart as possible to reach certain goals. These goals may be related to production costs, the use of (scarce) resources, deadlines. These problems have often been regarded statically: a schedule is made that seems best for the situation as it is observed now. However, with dynamic problems, the situation changes continually. For example, you may assign passengers to elevators in a manner that seems optimal now, but a new passenger presses a button 3 seconds later, making you think: if I had known this before, I would have made a different schedule. This dissertation is about techniques to make schedules robust and/or flexible. A robust planning stands the tide of change: it only has to be modified slightly when change occurs. A flexible schedule makes it easy for future tasks to be inserted. Robustness and flexibility are two sides of the same medal. One is focused on currently known tasks, the other on future (yet unknown) tasks. The dissertation contains an elaborate case study on elevator dispatching. Various scheduling techniques have been tried, in simulation, on an existing building in Paris, of which detailed passenger data were available. Some of these techniques came out as promising. A remarkably successful technique involved advancing the scheduling horizon. Instead of focusing on individual passengers, this technique focused on elevators as a whole, making them finish whatever they're doing as soon as possible. On short term, this seemed worse for passengers (e.g., more stop overs), but on the long term, the average waiting and travelling times were significantly reduced.

The lack of airport capacity hinders the growth potential of global air travel, inflicting delays and economic losses to passengers, airlines, and airports. Airport Slot Allocation (ASA) is used in congested airports as a short-term measure for providing access to air-carriers to scarce airport resources. A rich literature has been developed during the last decade around the formulation and optimisation of the ASA problem using the IATA World Scheduling Guidelines (IATA WSG). However, existing models do not address airlines’ flight scheduling flexibility preferences which are expressed through the Timing Flexibility Indicator (TFI). Additionally, in considering the airport's capacity, existing ASA literature does not treat endogenously the allocation of the available airport capacity to match the demand's characteristics. This paper addresses these issues by proposing a novel modelling and solution framework that considers airlines’ flexibility preferences and its seamless integration with constraints that enable the dynamic allocation of the airport's resources. Our approach takes into account the number of rejected requests, the total, and maximum displacement objectives and addresses several primary and additional policy criteria of IATA WSG. The preferences of the airlines are introduced through the Timing Flexibility Indicator (TFI) which is incorporated in a weighted objective function considering the number of slot requests which fall within their specified TFI. The proposed framework benefits from valid tightening inequalities which reduce the required computational times. Our computational study using data from a coordinated airport suggests that the joint consideration of the TFI and the endogenous and dynamic capacity constraints, improves airport capacity utilisation, thus leading to improved airport slot schedules with reduced total and maximum displacement and significant improvements in terms of displaced slot requests and passengers.

The integrated satellite-terrestrial network (ISTN) provides a promising solution to achieve high-data-rate and ubiquitous connectivity in next-generation communication networks. Considering the scarce spectrum resources and unevenly distributed traffic demands, we investigate the resource allocation algorithms for ISTNs, where the beam-hopping (BH)-based satellite system and terrestrial systems share the same frequency band. Taking advantage of the scheduling flexibility of BH technology, the dynamical protection zones are constructed to avoid co-channel interference and improve the spectrum efficiency. Since both spectrum efficiency and user fairness are the key optimization indexes in practical systems, two resource allocation problems are formulated to maximize the weighted sum of capacity (MWSC) and maximize the minimum capacity-to-demand ratio (MMCDR) of ISTNs, respectively. By reformulating the problems as mixed-integer linear programming problems, optimal solutions are obtained. To reduce the computational complexity, two greedy suboptimal algorithms are proposed for the MWSC and MMCDR, respectively. The simulation results show that the proposed algorithms achieve higher spectrum efficiency and guarantee fairness between the satellite and terrestrial systems. It is also shown that both the greedy algorithms perform similarly to the optimal algorithms while having much lower complexity.

ABSTRACTLittle research has explored linkages between workplace policies and mental health in working-class, employed parents, creating a gap in our knowledge of work–family issues across social class levels. The current US study addresses this gap by employing hierarchical linear modeling techniques to examine how workplace policies and parental leave benefits predicted parents’ depressive symptoms and anxiety in a sample of 125, low income, dual-earner couples interviewed across the transition to parenthood. Descriptive analyses revealed that, on average, parents had few workplace policies, such as schedule flexibility or child care supports, available to them. Results revealed, however, that, when available, schedule flexibility was related to fewer depressive symptoms and less anxiety for new mothers. Greater child care supports predicted fewer depressive symptoms for fathers. In terms of crossover effects, longer maternal leave predicted declines in fathers’ anxiety across the first year. Results are discussed with attention to how certain workplace policies may serve to alleviate new parents’ lack of time and resources (minimize scarcity of resources) and, in turn, predict better mental health during the sensitive period of new parenthood.

Innovate or Evaporate: Coping with Budget Cuts

Providing employee benefits is costly for new ventures, yet offering such inducements is often essential to developing human capital. While a broad combination of employee benefits could yield synergistic effects, adopting a large number of benefits may not be feasible for resource constrained ventures. To ensure survival, while limiting misallocation of scarce resources towards benefits that have lower returns, entrepreneurs must be selective in choosing the benefits that generate the most ‘bang for the buck’. Our study assesses the effects of employee benefit offerings on venture survival odds. Based on a longitudinal sample of 1012 US-based ventures from the Kauffman Firm Survey and leveraging, signalling and motivation theories, we find that offering health insurance, flexible work schedules, paid vacation, or paid sick leave increase the odds of survival. However, offering employee stock ownership plans or tuition reimbursement has no significant influence on the odds of survival.