American University of Phnom Penh

Cet article explore la complexité clinique d’états dissociatifs observés chez des sujets réfugiés en France qui interprètent leurs expériences psychiques à travers la croyance d’être victime de transe de possession par des Djinns. S’appuyant sur une approche interculturelle et une méthodologie mixte, cette recherche vise à identifier les étiologies sous-jacentes de ces phénomènes et leur articulation possible avec le traumatisme ou la psychose, en tenant compte des référentiels culturels propres aux sujets. Trois hypothèses sont explorées : une origine psychotraumatique, une structure psychotique à thème mystique et la nécessité d’une lecture contextuelle intégrant les croyances culturelles dans l’analyse clinique. Cet article met ainsi en lumière la complexité des processus de subjectivation chez ces patients, entre altération du sentiment d’agentivité, élaboration narrative du trauma et recours à une cosmologie culturelle signifiante.

The rise of social media and the internet has significantly increased the amount and speed of shared information, posing challenges for verifying content. Automated veracity checking has become essential in quickly and accurately evaluating claims due to the overwhelming volume of data. The reliability of these systems depends on their ability to access and evaluate substantial evidence, which is crucial for authenticating assertions and preventing the spread of misinformation. This study proposes a new method that integrates rationales from evidentiary texts to address the issue of insufficient evidence in automated veracity checking. By using contextual coherence and relevance as metrics when direct evidence is limited, our technique aims to assess evidence sufficiency comprehensively. Furthermore, it goes beyond identifying evidence sufficiency by examining supporting or refuting rationales, enhancing our understanding of claim veracity. Our research introduces a preservation technique focused on maintaining contextual consistency and logical validity to overcome limitations in existing veracity-checking systems. This approach prioritizes alignment between claims and their evidence, effectively addressing issues related to evidence insufficiency by capturing subtle semantic connections while assessing contextually implied meanings often overlooked in traditional methods of evidence evaluation

The aim of this chapter is to examine the perception towards implementation of AI in the recruitment and selection process in MNC companies. AI has become our present and future and has dominated our lives and businesses in this competitive world. By implementing AI, MNCs can increases their recruiting and selection efficiency and have access to a wider candidate pool. Digitization has played a prominent role in redesigning the different human resource functions and processes. AI in recruitment and selection processes has been glorified for being cost-effective, time-saving, fair, and unbiased, building greater diversity into the workforce. In particular, it helps to eradicate time-consuming activities, so that recruitment professionals can focus more on strategic issues. Investing in AI and more explicitly in sophisticated algorithms may be the way forward in recruitment and selection. This chapter aims to explore the under-researched area of recruiters' perceptions of AI in recruitment and a selection of several MNCs who hire candidates with different AI-enabled recruitment tools.

To build intelligent model learning in conventional architecture, the local data are required to be transmitted toward the cloud server, which causes heavy backhaul congestion, leakage of personalization, and insufficient use of network resources. To address these issues, federated learning (FL) is introduced by offering a systematical framework that converges the distributed modeling process between local participants and the parameter server. However, the challenging issues of insufficient participant scheduling, aggregation policies, model offloading, and resource management still remain within conventional FL architecture. In this survey article, the state-of-the-art solutions for optimizing the orchestration in FL communications are presented, primarily querying the deep reinforcement learning (DRL)-based autonomy approaches. The correlations between the DRL and FL mechanisms are described within the optimized system architectures of selected literature approaches. The observable states, configurable actions, and target rewards are inquired into to illustrate the applicability of DRL-assisted control toward self-organizing FL systems. Various deployment strategies for Internet of Things applications are discussed. Furthermore, this article offers a review of the challenges and future research perspectives for advancing practical performances. Advanced solutions in these aspects will drive the applicability of converged DRL and FL for future autonomous communication-efficient and privacy-aware learning.

Voluntourism has always been portrayed as a crucial role in developing economies. However, as voluntourism evolves and expands, a question of sustainability arises. The majority of populaces served by short-term volunteer trips are predisposed communities. Thus, this raises ethical questions such as voluntourism as a savior or impediment to communities. This study examines the attractiveness of volunteer tourists in recent years in Cambodia and India and how it contributes to future sustainable tourism research. The paper uses KH Coder to collect primary data for the quantitative analysis of text data. Moreover, the paper applies an exploratory approach using content analysis of participant reviews to identify the critical dimensions of experiences. Based on the analysis of trends in voluntourism and their ecosystem, an approach to the sustainable development strategy of voluntourism actors is proposed. First, voluntourism operators and host organizations, a pivotal element of the development strategy of voluntourism infrastructure, are considered. It was revealed that there is a nexus between the well-being of the community/business opportunities and experienced voluntourists. Consequently, these voluntourism activities may provide intrinsic gains for them and the targeted communities, plus its support toward corporate social responsibility. Acknowledgment This study received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

ou représentation de cet article, notamment par photocopie, n'est autorisée que dans les limites des conditions générales d'utilisation du site ou, le cas échéant, des conditions générales de la licence souscrite par votre établissement.Toute autre reproduction ou représentation, en tout ou partie, sous quelque forme et de quelque manière que ce soit, est interdite sauf accord préalable et écrit de l'éditeur, en dehors des cas prévus par la législation en vigueur en France.Il est précisé que son stockage dans une base de données est également interdit.

SummaryThis article assesses the impact of economic integration on Tanzania's sociometabolic profile for the years 1970–2011, which witnessed an opening and further integration of Tanzania's economy through increased trade and foreign investment, through a time‐series economy‐wide material flows analysis (EW‐MFA). The EW‐MFA results show that contrary to the trade patterns of many developing countries, increased economic integration has resulted in Tanzania becoming a net importer of resources across all material categories when measured by the physical trade balance indicator. Additionally, the article discusses the conceptual and empirical challenges of measuring ecologically unequal exchange with EW‐MFAs for developing countries whose export profiles are dominated by lightweight, high‐value precious stones and metals. It also assesses the degree to which the Tanzanian economy has undergone dematerialization over the past 40 years of economic integration.