Zoekresultaten

Resource-Efficient Image Buffer Architecture for Neighborhood Processors

Neighborhood image processing operations on Field Programmable Gate Array (FPGA) are considered as memory intensive operations. A large memory bandwidth is required to transfer the required pixel data from external memory to the processing unit. On-chip image buffers are employed to reduce this data transfer rate. Conventional image buffers, implemented either by using FPGA logic resources or embedded memories are resource inefficient. They exhaust the limited FPGA resources quickly. Consequently, hardware implementation of neighborhood operations becomes expensive, and integrating them in resource constrained devices becomes unfeasible. This paper presents a resource efficient FPGA based on-chip buffer architecture. The proposed architecture utilizes full capacity of a single Xilinx BlockRAM (BRAM36 primitive) for storing multiple rows of input image. To get multiple pixels/clock in a user defined scan order, an efficient duty-cycle based memory accessing technique is coupled with a customized addressing circuitry. This accessing technique exploits switching capabilities of BRAM to read 4 pixels in a single clock cycle without degrading system frequency. The addressing circuitry provides multiple pixels/clock in any user defined scan order to implement a wide range of neighborhood operations. With the saving of 83% BRAM resources, the buffer architecture operates at 278 MHz on Xilinx Artix-7 FPGA with an efficiency of 1.3 clock/pixel. It is thus capable to fulfill real time image processing requirements for HD image resolution (1080 × 1920) @103 fcps.

Gate me if you can: the impact of gating mechanics on retention and revenues in Jelly

Neighbours at the Gate: Exploration of Alternative Approaches to Refugee (Re)settlement and Integration in the Netherlands

In the Netherlands and Europe, there exist approaches to refugee (re)settlement where asylum seekers face long waiting periods, in large-scale centres often isolated from Dutch society, with little-to-no opportunity to structure their day or participate in activities which bring meaning to their lives. These activities, which bring meaning people’s lives are termed occupations in the occupational therapy and occupation science literature. When the context hinders the opportunity to engage in these meaningful occupations, one experiences a situation of occupational injustice. These approaches taken in the Netherland and internationally creates the state of occupation injustice, this lack of ability to engage in meaningful activities, and this is turn has been documented to have negative effects on refugees health, well-being, identity and eventual inclusion in society.Parallel to these standard approaches in the Netherlands, are alternative approaches to refugee resettlement and integration. These alternatives are oftenbeing facilitated by charities, community-based organizations and citizen initiatives. Alternative programs currently aim to counter the government programs and focus on safe passages, for vulnerable populations, with an emphasis on early inclusion in society, community placement, sponsorship, and integration from the time of arrival. These alternative programs claim to address the issues of lack of meaningful engagement and isolation as currently seen in standard procedures, thereby claiming to improve integration, inclusion and wellbeing.This research aims to explore the lives and experiences of both the individuals living in, as well as the individuals facilitating these alternative programs. The research will explore how these programs are situated in and/or actively negotiating the broader context of refugee programs and policies in the Netherlands. This exploration will include the perspectives of the multiple actors involved, including service users and service providers, using a participatory methodology.Through exploring the perspectives on alternative programs through a participatory evaluation format, we are able to explore these programs as they are described, evaluated and experienced by theservices users themselves. This allows for a grounded understanding of the programs and their further potential.

Neighbours at the Gate

Enhancing a simulation-based Allocator Software with machine learning and genetic algorithms for improving the gate assignment problem

Assigning gates to flights considering physical, operational, and temporal constraints is known as the Gate Assignment Problem. This article proposes the novelty of coupling a commercial stand and gate allocation software with an off-the-grid optimization algorithm. The software provides the assignment costs, verifies constraints and restrictions of an airport, and provides an initial allocation solution. The gate assignment problem was solved using a genetic algorithm. To improve the robustness of the allocation results, delays and early arrivals are predicted using a random forest regressor, a machine learning technique and in turn they are considered by the optimization algorithm. Weather data and schedules were obtained from Zurich International Airport. Results showed that the combination of the techniques result in more efficient and robust solutions with higher degree of applicability than the one possible with the sole use of them independently.

Opt-Sim approach for the gate allocation problem in covid-19 times

This study tackles the gate allocation problem (GAP) at the airport terminal, considering the current covid-19 pandemic restrictions. The GAP has been extensively studied by the research community in the last decades, as it represents a critical factor that determines an airport's capacity. Currently, the airport passenger terminal operations have been redesigned to be aligned and respect the covid-19 regulation worldwide. This provides operators with new challenges on how to handle the passengers inside the terminal. The purpose of this study is to come up with an efficient gate allocator that considers potential issues derived by the current pandemic, i.e., avoid overcrowded areas. A sim-opt approach has been developed where an evolutionary algorithm (EA) is used in combination with a dynamic passenger flow simulation model to find a feasible solution. The EA aims to find a (sub)optimal solution for the GAP, while the simulation model evaluates its efficiency and feasibility in a real-life scenario. To evaluate the potential of the Opt-Sim approach, it has been applied to a real airport case study.