Thank you for sharing this story! However, please do so in a way that respects the copyright of this text. If you want to share or reproduce this full text, please ask permission from Innovation Origins (partners@innovationorigins.com) or become a partner of ours! You are of course free to quote this story with source citation. Would you like to share this article in another way? Then use this link to the article: https://innovationorigins.com/en/silicon-sampling-ai-powered-personas-offer-new-insights-for-market-research-but-have-limitations/ n the rapidly evolving field of marketing and communication, staying ahead means embracing technological innovations. The latest breakthrough, silicon sampling, leverages AI to revolutionize market research by creating synthetic personas that mimic human responses. This method, which utilizes large language models (LLMs) like GPT-4o, offers a cost-efficient and less time-consuming alternative to traditional market research. Roberta Vaznyte and Marieke van Vliet (Fontys University of Applied Science) have explored the promise and challenges of silicon sampling, highlighting key findings from recent experiments and the implications for the future of market research.
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Background: Only a few papers are published on the safety and effectiveness of acute burn care in low-income countries. A cohort study was therefore carried out to determine such outcomes.Methods: The study was conducted in a rural Tanzanian hospital in 2017-2018. All patients admitted with burns were eligible. Complications were scored during admission as an indication for safety. Survivors of severe burn injuries were evaluated for time of reepithelialization, graft take, disability (WHODAS2.0) and quality of life (EQ5D-3L) up to 3 months post-injury, as an indication of effectiveness.Results: Patients presented on average at 5 days after injury (SD 11, median 1, IQR 0-4). Three patients died at admission. The remaining 79 were included in the cohort. Their median age was 3 years (IQR 2-9, range 0.5-49), mean TBSA burned 12% (SD10%) and mortality rate 11.4%. No surgery-related mortality or life-threatening complications were observed. Skin grafting was performed on 29 patients at a delayed stage (median 23 days, IQR 15-47). Complications of skin grafts included partial (25% of procedures) and complete graft necrosis (8% of procedures). The mean time to reepithelialization was 52 (SD 42) days after admission. Disability and quality of life improved from admission to 3 months after injury (p<0.001, p<0.001, respectively).Conclusion: In this resource-limited setting patients presented after a delay and with multiple complications. The mortality during the first two weeks after admission was high. Surgery was found to be safe and effective. A significant improvement in disability and quality of life was observed.
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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.
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Met de opkomst van digitale diensten en de impact van digitale technologie is het vraagstuk van privacy hoog op de maatschappelijke agenda beland. Burgers gebruiken steeds vaker apps en andere online services, met als keerzijde dat we steeds meer informatie over onszelf moeten delen om optimaal gebruik te kunnen maken van deze faciliteiten. Dit kan leiden tot schending van onze privacy. Ook voor de meeste (mkb-)bedrijven is het lastig om inzicht te krijgen in de privacy implicaties van hun online services en in de privacy-eisen om deze implicaties te verzachten. Het privacyvraagstuk is voor deze doelgroepen grijpbaar te maken door de privacy-eisen waar online diensten aan moeten voldoen op een beknopte, overzichtelijke en duidelijke manier te communiceren. Privacy labels, in navolging van energielabels en voedingslabels, zijn hiervoor een veelbelovende methode. Binnen het, door NWO gefinancierde, SERIOUS project is een prototype ontwikkeld om privacy-eisen te visualiseren middels een multidimensionaal privacy label (Barth, Ionita en Hartel, 2020). Op basis van een vragenlijst met betrekking op datacollectie, dataverwerking en datadisseminatie kan de mate van privacy borging en bescherming worden vastgesteld. Het huidige prototype van dit privacy label is generiek. Echter is het mogelijk dat bepaalde elementen van privacy in de praktijk binnen sommige domeinen veel zwaarder wegen dan binnen anderen. Kenniscentrum Creating 010 onderzoekt, naar aanleiding van de vraag vanuit de samenwerkingspartijen van het SERIOUS project, binnen dit project hoe het SERIOUS prototype kan worden doorontwikkeld naar een volwaardig privacy label. Hierbij wordt nagegaan of en hoe het prototype in en voor verschillende sectoren werkt, deze zijn: retail, media en cultuur. Het doel van dit project is om middels een haalbaarheidsstudie de richtlijnen voor een domein-specifiek label te achterhalen en op te stellen die dienen als uitgangspunt voor een vervolgproject voor een domein-specifieke privacy tool.
