3,263 research outputs found
Contrasting activity profile of two distributed cortical networks as a function of attentional demands
No full textThe original publication is available at http://www.jneurosci.orgThis work was supported by R01 grant MH-073610 from the National Institutes of Health to Denis Paré
Mining Segmentation Patterns Using e-Commerce Retail Data: An Experience Report
No full textPart 8: Customer Behavior and E-businessInternational audienceThe goal of this experience report is to study and advance our understanding on visit and shopper segmentation in retail. Current segmentation studies mainly use customers as unit of analysis to identify shopper segments and mine patterns in their behaviors. Another stream of studies utilizes shopper baskets or visits to perform basket/visit segmentation and elicit shopping patterns. However, given the fact that we live in the era of personalization focusing solely on visits leads on neglecting the shopper. On the other hand, focusing solely on shoppers and their behavior over time, leads on losing his/her daily purchasing behavior. In this study we combine shopper and visit segmentation and we apply data mining to identify purchase patterns using data from an e-commerce grocery retailer
A Review of AI in the Supply Chain Industry: Preliminary Findings
No full textPart 7: Digitised Supply ChainsInternational audienceArtificial Intelligence (AI) has been claimed to provide transformational powers in developing efficient and sustainable supply chains. Despite this, the supply chain industry is grappling with a number of challenges related to the implementation of AI. Additionally, AI and supply chain research to date has largely focused on the technical elements or different functions of AI, rather than AI as a whole. In order to provide a consolidated view of AI in the context of supply chains, we synthesis this dispersed knowledge by conducting a systematic literature review of AI research in supply chains that have been published in 3* and 4* ranked journals between 2000 and 2020. The search strategy resulted in 468 studies, of which 56 were identified as primary papers relevant to this research. This research adds to aggregation of knowledge by providing a state-of-the-art of AI and supply chain research, synthesising the reported challenges of the supply chain industry and the claimed benefits of AI
Adopting Artificial Intelligence in the Saudi Arabian Public Sector: Preliminary Findings
No full textPart 1: Adopting AI for Digital Transformation and Public GoodInternational audienceArtificial Intelligence (AI) has received significant attention in recent years, with claims of unlimited potential across sectors and industries. Despite the media hype about AI, there is limited understanding of how governments can utilize AI for the delivery of value to citizens and what are the barriers and trade-offs that need to be addressed to lead to value realization. AI has the potential to bring transformative benefits to society, but first we need to understand the current state of play in the public sector through an appropriate theoretical lens. We adopt the attention-based view of the organization to identify key challenges in terms of organizational attention. This study draws on a single case study in Saudi Arabia to identify key challenges associated with the adoption of AI
Analysis of the drivers of industry 4.0 technology deployment to achieve agri-food supply chain sustainability: a hybrid approach
No full textAgri-food supply chains (AFSCs) are struggling toachieve sustainability in the face of increasing social,environmental, and economic challenges. Industry 4.0technologies are widely deployed to monitor, assess, and analyzetheir operational process, and thereby drive sustainable value.This study adopts a hybrid approach to analyze the drivers ofindustry 4.0 technology deployment to achieve AFSCsustainability. Thematic analysis of 24 interviews was carried outto identify 13 drivers, and these were used as inputs into the fuzzyanalytic hierarchy process (AHP), total interpretive structuralmodeling (TISM), and fuzzy cross-impact matrix multiplicationsapplied to classification (MICMAC). The results show thatenhancing efficiency of water and fertilizer use, reducing carbonemissions, and reducing work intensity contribute significantly toeconomic, environmental, and social aspects of sustainability. Wealso identify that government subsidies for agricultural facilitiesand strengthening of farmers’ agri-tech skills are key drivers thatshould be given priority
Developing Machine Learning Model for Predicting Social Media Induced Fake News
No full textPart 11: Social Media and AnalyticsInternational audienceFake news has been associated with major global events such as Covid-19 and the political polarisation of the US presidential election in 2016. This paper investigates how fake news has affected society and advance understanding of the nature of its impact in the future of democratic societies. Taken from large datasets consisting of over 23,000 fake news story words and over 21,000 true news story words we use descriptive and predictive analytics, partly analysing more than 350 words during the selected period of October 2016 to April 2017. The findings show that Trump was the most popular word for both true and fake news. In this study, we compare and contrast the words used and the volume of true versus fake news stories related to the election and the inauguration. This study makes an important contribution as it develops a predictive model that highlights the severity of political polarization and its consequences in democratic societies, which inevitably have implications for inclusive societies in the 21st century
Understanding the Drivers of Industry 4.0 technologies to enhance supply chain sustainability: insights from the agri-food industry
No full textThe sustainability of agri-food supply chains (AFSC) has been under significant threat from regional and global events (e.g., conflict, natural and human-made disasters, climate crises). In response to these sustained threats, the AFSC industry is seeking digital solutions using Industry 4.0 (I4.0) technologies to enhance the resilience and efficiency of supply chains. Despite the transformational potential of I4.0, there is limited understanding to why its adoption remains stubbornly low in the agri-food industry. To address this gap, this study draws on middle-range theory (MRT) and builds on nine selected case studies located in China, each of whom have invested in I4.0 technologies to improve the sustainability of their AFSC. Data is examined using thematic analysis, the fuzzy analytic hierarchy process, total interpretive structural modelling, and fuzzy cross-impact matrix multiplication applied to classification. This study identifies several new drivers of I4.0 that are unique to the agri-food industry and how I4.0 can contribute to the environmental, economic, and social dimensions of AFSC sustainability. The results have implications for AFSC researchers and practitioners with an interest in supply chain sustainability
Is Tolerance Political? An Interview with Denis Lacorne
No full textcontribution à un site webDenis Lacorne is the author of "The Limits of Tolerance. Enlightenment Values and Religious Fanaticism" (Columbia University Press, 2019), the English translation of "Les limites de la tolérance" (Gallimard, awarded the Prix Montyon by the Académie Française). In his book, which is intellectually very inspiring because of the many questions it addresses and raises, Denis Lacorne traces the emergence of the notion of tolerance from its early thinkers to the Age of Enlightenment and finally questions the notion and its various understandings through more recent events in France and the United States. What is tolerance? Is tolerance political? Interview by Miriam Périer, CER
Timing of impulses from the central amygdala and bed nucleus of the stria terminalis to the brainstem
No full textThe amygdala and bed nucleus of the stria terminalis (BNST) are thought to subserve distinct functions with the former mediating rapid fear responses to discrete sensory cues and the latter longer “anxiety-like” states in response to diffuse environmental contingencies. Yet, these structures are reciprocally connected and their projection sites overlap extensively. To shed light on the significance of BNST-amygdala connections, we compared the antidromic response latencies of BNST and central amygdala (CE) neurons to brainstem stimulation. Whereas the frequency distribution of latencies was unimodal in BNST neurons (~10 ms mode), that of CE neurons was bimodal (~10 and ~30 ms modes). However, after stria terminalis (ST) lesions, only short-latency antidromic responses were observed, suggesting that CE axons with long conduction times course through the ST. Compared to the direct route, the ST greatly lengthens the path of CE axons to the brainstem, an apparently disadvantageous arrangement. Since BNST and CE share major excitatory basolateral amygdala (BL) inputs, lengthening the path of CE axons might allow synchronization of BNST and CE impulses to brainstem when activated by BL. To test this, we applied electrical BL stimuli and compared orthodromic response latencies in CE and BNST neurons. The latency difference between CE and BNST neurons to BL stimuli approximated that seen between the antidromic responses of BNST cells and CE neurons with long-conduction times. These results point to a hitherto unsuspected level of temporal coordination between the inputs and outputs of CE and BNST neurons, supporting the idea of shared functions.The original publication is available at: http://jn.physiology.org/cgi/content/full/100/6/342
Rehab Depot de la Plaine Saint-Denis
No full textRedesign for workshop Atelier Revision Intermediaire at the Depot de la Plaine Saint-Denis with a rehabilitation center as new functionRMITArchitecture and The Built Environmen
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