Selection Of Slot Research Articles

Enhanced Time Slotted LoRaWAN for Node Mobility: A Joint Selection of Data Rate, Time Slot and Channel

Enhanced Time Slotted LoRaWAN for Node Mobility: A Joint Selection of Data Rate, Time Slot and Channel

Film cooling effectiveness from upstream purge slots of a turbine vane endwall: Experiment, modeling, and correlation

The design of an efficient cavity slot between assembled components, where purge air is injected, is especially crucial to the durability and efficiency of an aero-engine, since the purge air is relevant to sealing and film cooling of the hot component. In this paper, film cooling for purge flow injected from slots upstream the endwall of a turbine vane is systematically investigated in a linear cascade using Pressure-Sensitive Paint (PSP). The influence of the slot width (0.020−0.044 times vane axial chord length), position (0.11−0.24 times vane axial chord length in front of turbine passage inlets), and inclination angle (20−45°) is examined for coolant injection ratios of 0.3−2.0 %, with an attempt to develop a new correlation specifically for purge flow film cooling over a turbine endwall, since existing correlations in literature only work for slot injection on flat plates. The experimental tests are undertaken in extensive ranges of the slot geometry and the injection rate that are typically seen in a modern engine. For better understanding the impacts of the affecting parameters, five-hole probe and thermocouple measurements and numerical simulations were carried out as well to visualize the coolant-with-mainstream mixing flows. The measured local film coverage, pitchwise- and area-averaged cooling effectiveness are presented and discussed, in combination with the probe-detected and numerically-modeled flow structures to elaborate the experimental observations. The current results sufficiently reveal the changing tendency of purge flow film cooling caused by the variations of the slot geometry. Additionally, the newly-developed correlation is well validated using own experimental data and datasets in literature, proving the capability of the correlation to predict film cooling for purge flow injected from slots with such geometrical parameter ranges. The correlation can be a helpful tool to support the selection of an efficient slot in its preliminary design stage.

Efficient Prioritization and Processor Selection Schemes for HEFT Algorithm: A Makespan Optimizer for Task Scheduling in Cloud Environment

Cloud computing is one of the most commonly used infrastructures for carrying out activities using virtual machines known as processing units. One of the most fundamental issues with cloud computing is task scheduling. The optimal determination of scheduling criteria in cloud computing is a non-deterministic polynomial-time (NP)-complete optimization problem, and several procedures to manage this problem have been suggested by researchers in the past. Among these methods, the Heterogeneous Earliest Finish Time (HEFT) algorithm is recognized to produce optimal outcomes in a shorter time period for scheduling tasks in a heterogeneous environment. Literature shows that HEFT gives extraordinary results in terms of quality of schedule and execution time. However, in some cases, the average computation cost and selection of the first idle slot may not produce a good solution. Therefore, here we propose modified versions of the HEFT algorithm that can obtain improved results. In the rank generation phase, we implement different methodologies for calculating ranks, while in the processor selection phase, we modify the way of selecting idle slots for scheduling the tasks. This paper suggests enhanced versions of the HEFT algorithm under user-required financial constraints to minimize the makespan of a specified workflow submission on virtual machines. Our findings also suggest that enhanced versions of the HEFT algorithm perform better than the basic HEFT method in terms of lesser schedule length of the workflow problems running on various virtual machines.

Resource Allocation in Multicore Elastic Optical Networks: A Deep Reinforcement Learning Approach

A deep reinforcement learning approach is applied, for the first time, to solve the routing, modulation, spectrum and core allocation (RMSCA) problem in dynamic multicore fiber elastic optical networks (MCF-EONs). To do so, a new environment - compatible with OpenAI's Gym - was designed and implemented to emulate the operation of MCF-EONs. The new environment processes the agent actions (selection of route, core and spectrum slot) by considering the network state and physical-layer-related aspects. The latter includes the available modulation formats and their reach and the inter-core crosstalk (XT), an MCF-related impairment. If the resulting quality of the signal is acceptable, the environment allocates the resources selected by the agent. After processing the agent's action, the environment is configured to give the agent a numerical reward and information about the new network state. The blocking performance of four different agents was compared through simulation to 3 baseline heuristics used in MCF-EONs. Results obtained for the NSFNet and COST239 network topologies show that the best-performing agent achieves, on average, up to a four-times decrease in blocking probability concerning the best-performing baseline heuristic methods.

Customer Preferences for Delivery Service Attributes in Attended Home Delivery

Retailers face increasing competitive pressure to determine how best to deliver products purchased on-line to the end customer. As online retailing grows, so does the need for retailers to establish an appropriate fulfillment strategy. This is particularly true in grocery where the customer must be present to receive perishable goods from the retailer. Attended home delivery requires the retailer and the customer to agree upon a delivery time slot that works for both parties. Customers may exhibit different preferences for the selection of a delivery time slot. Using data from a grocery retailer that performs attended home deliveries, we evaluate customer responses to three delivery attributes, namely, speed, precision, and flexibility. We define speed as the expected time between the placement of an order and delivery, precision as the duration of the offered time slot, and flexibility as the availability of choices across times of the day and days of the week. Our results demonstrate that customers not only value speed as an attribute of delivery service but that precision and flexibility are also key drivers of the customer’s time slot selection process. In fact, under many conditions, customers prefer precision and flexibility over speed. We also explore the willingness of customers to pay for time slots with various attributes and find substantial and significant heterogeneity among customers. Customers that differ in their loyalty to the retailer, basket value, basket size, and basket composition exhibit differences in their willingness to pay. Understanding customer preferences towards the attributes of delivery time slots and how the willingness of customers to pay for a given time slot differs across customers is important for practitioners seeking to design competitive fulfillment strategies. Moreover, our findings enable academics to refine their assumptions of customer behavior when modeling the attended home delivery context.

Braking Torque Due to Cross Magnetization in Unsaturated IPM BLDC Machines and Its Mitigation

Cross magnetization (CM) is an inevitable phenomenon in electrical machines. It is more prominent in interior permanent magnet (IPM) brushless dc (BLDC) machines. This is because PMs demagnetize in overloaded and saturated conditions. It leads to cross coupling between the direct and quadrature-axes quantities, and a decrease in the resultant air-gap flux-density distribution under saturated conditions. In this paper, it is shown that CM leads to braking torque even in unsaturated IPM BLDC machines. Furthermore, the effect of CM on flux linkage, electromotive force, and dynamic torque is presented. Its mitigation using suitable selection of slot–pole combination is presented. It is observed that odd slot–pole combinations are least affected, and even slot–pole combinations are severely affected by CM. Furthermore, it is found that the overlap area of rotor pole arc with the stator pole arc influences the severity of CM, more particularly in fractional slot–pole combination machines. To verify these claims, finite-element method is used for modeling and analyzing various slot–pole combinations of a spoke-type IPM BLDC motor. The results obtained from these simulations are validated with a fabricated reference prototype, which support the claims.

Time-slot management in digital portable radio systems

The problem of assigning a time slot to a user in a frequency-reuse time-division multiplexed digital portable radio system is considered. Time-slot assignment algorithms are studied using a discrete-event stochastic computer simulation that models many concurrent two-way radio links. Three time-slot assignment algorithms were modeled: random selection of an idle time slot, selection of the idle time slot with the least interference power, and selection of the idle time slot with the largest signal-to-interference ratio not exceeding a given threshold. It is shown that under heavy traffic loads, measurement-based assignment of time slots yields improvements in transmission quality of 8 dB (local mean) to 15 dB (instantaneous) over random assignment for 99% of the users. As a result, the amount of radio spectrum needed is halved according to local mean performance.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>