scholarly journals Multi-Modal Adaptive Fusion Transformer Network for the Estimation of Depression Level

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4764
Author(s):  
Hao Sun ◽  
Jiaqing Liu ◽  
Shurong Chai ◽  
Zhaolin Qiu ◽  
Lanfen Lin ◽  
...  
Keyword(s):  
State Of The Art ◽  
Estimation Accuracy ◽  
Temporal Context ◽  
Context Information ◽  
Main Task ◽  
Visual Data ◽  
Sequence Modeling ◽  
Adaptive Fusion ◽  
Depression Level

Depression is a severe psychological condition that affects millions of people worldwide. As depression has received more attention in recent years, it has become imperative to develop automatic methods for detecting depression. Although numerous machine learning methods have been proposed for estimating the levels of depression via audio, visual, and audiovisual emotion sensing, several challenges still exist. For example, it is difficult to extract long-term temporal context information from long sequences of audio and visual data, and it is also difficult to select and fuse useful multi-modal information or features effectively. In addition, how to include other information or tasks to enhance the estimation accuracy is also one of the challenges. In this study, we propose a multi-modal adaptive fusion transformer network for estimating the levels of depression. Transformer-based models have achieved state-of-the-art performance in language understanding and sequence modeling. Thus, the proposed transformer-based network is utilized to extract long-term temporal context information from uni-modal audio and visual data in our work. This is the first transformer-based approach for depression detection. We also propose an adaptive fusion method for adaptively fusing useful multi-modal features. Furthermore, inspired by current multi-task learning work, we also incorporate an auxiliary task (depression classification) to enhance the main task of depression level regression (estimation). The effectiveness of the proposed method has been validated on a public dataset (AVEC 2019 Detecting Depression with AI Sub-challenge) in terms of the PHQ-8 scores. Experimental results indicate that the proposed method achieves better performance compared with currently state-of-the-art methods. Our proposed method achieves a concordance correlation coefficient (CCC) of 0.733 on AVEC 2019 which is 6.2% higher than the accuracy (CCC = 0.696) of the state-of-the-art method.

scholarly journals Documentary data and the study of past droughts: a global state of the art

2018 ◽  
Vol 14 (12) ◽  
pp. 1915-1960 ◽  
Author(s):  
Rudolf Brázdil ◽  
Andrea Kiss ◽  
Jürg Luterbacher ◽  
David J. Nash ◽  
Ladislava Řezníčková
Keyword(s):  
Large Scale ◽  
State Of The Art ◽  
Drought Indices ◽  
Documentary Evidence ◽  
Climatic Trends ◽  
Instrumental Observations ◽  
Spatio Temporal ◽  
Epigraphic Evidence ◽  
Administrative Evidence

Abstract. The use of documentary evidence to investigate past climatic trends and events has become a recognised approach in recent decades. This contribution presents the state of the art in its application to droughts. The range of documentary evidence is very wide, including general annals, chronicles, memoirs and diaries kept by missionaries, travellers and those specifically interested in the weather; records kept by administrators tasked with keeping accounts and other financial and economic records; legal-administrative evidence; religious sources; letters; songs; newspapers and journals; pictographic evidence; chronograms; epigraphic evidence; early instrumental observations; society commentaries; and compilations and books. These are available from many parts of the world. This variety of documentary information is evaluated with respect to the reconstruction of hydroclimatic conditions (precipitation, drought frequency and drought indices). Documentary-based drought reconstructions are then addressed in terms of long-term spatio-temporal fluctuations, major drought events, relationships with external forcing and large-scale climate drivers, socio-economic impacts and human responses. Documentary-based drought series are also considered from the viewpoint of spatio-temporal variability for certain continents, and their employment together with hydroclimate reconstructions from other proxies (in particular tree rings) is discussed. Finally, conclusions are drawn, and challenges for the future use of documentary evidence in the study of droughts are presented.

scholarly journals Diagnostic Challenges on the Laboratory Detection of Lupus Anticoagulant

Biomedicines ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 844
Author(s):  
Armando Tripodi
Keyword(s):  
Lupus Anticoagulant ◽  
Clinical Laboratory ◽  
External Quality Assessment ◽  
State Of The Art ◽  
Diagnostic Procedures ◽  
External Quality ◽  
Glycoprotein I ◽  
Current State ◽  
Clinical Laboratories

Lupus anticoagulant (LA) is one of the three laboratory parameters (the others being antibodies to either cardiolipin or β2-glycoprotein I) which defines the rare but potentially devastating condition known as antiphospholipid syndrome (APS). Testing for LA is a challenging task for the clinical laboratory because specific tests for its detection are not available. However, proper LA detection is paramount for patients’ management, as its persistent positivity in the presence of (previous or current) thrombotic events, candidate for long term anticoagulation. Guidelines for LA detection have been established and updated over the last two decades. Implementation of these guidelines across laboratories and participation to external quality assessment schemes are required to help standardize the diagnostic procedures and help clinicians for appropriate management of APS. This article aims to review the current state of the art and the challenges that clinical laboratories incur in the detection of LA.

Rose Fitzgerald Kennedy bridge over the River Barrow. Design and Construction of a long span extrados bridge

2021 ◽  
Author(s):  
Marcos Sanchez Sanchez ◽  
John Iliff
Keyword(s):  
State Of The Art ◽  
Single Plane ◽  
Robust Approach ◽  
Analysis Techniques ◽  
Long Span ◽  
The World ◽  
Art Analysis ◽  
Concrete Deck ◽  
Design And Construction

<p>This paper describes the key elements from early planning to completion of a new bridge over the River Barrow which is part of the New Ross bypass in the south of Ireland. The structure has a total length of 887m, with a span arrangement of 36-45-95-230-230-95-70-50-36m. The two central twin spans are the longest of its kind in the world (extrados with a full concrete deck). The bridge carries a dual carriageway with a cable arrangement consisting of a single plane of cables located in the central axis of the deck. The design and construction focused in providing a structure with long term durability, resilience, and a robust approach to design scenarios using the Eurocodes and state of the art analysis techniques, including extreme events such as fire and ship impact<i>.</i></p>

Bistability of somatic pattern memories: stochastic outcomes in bioelectric circuits underlying regeneration

2021 ◽  
Vol 376 (1821) ◽  
pp. 20190765 ◽  
Author(s):  
Giovanni Pezzulo ◽  
Joshua LaPalme ◽  
Fallon Durant ◽  
Michael Levin
Keyword(s):  
Large Scale ◽  
Computational Models ◽  
State Of The Art ◽  
Memory Representation ◽  
Theme Issue ◽  
Evolutionary Innovation ◽  
New Interpretation ◽  
The Brain

Nervous systems’ computational abilities are an evolutionary innovation, specializing and speed-optimizing ancient biophysical dynamics. Bioelectric signalling originated in cells' communication with the outside world and with each other, enabling cooperation towards adaptive construction and repair of multicellular bodies. Here, we review the emerging field of developmental bioelectricity, which links the field of basal cognition to state-of-the-art questions in regenerative medicine, synthetic bioengineering and even artificial intelligence. One of the predictions of this view is that regeneration and regulative development can restore correct large-scale anatomies from diverse starting states because, like the brain, they exploit bioelectric encoding of distributed goal states—in this case, pattern memories. We propose a new interpretation of recent stochastic regenerative phenotypes in planaria, by appealing to computational models of memory representation and processing in the brain. Moreover, we discuss novel findings showing that bioelectric changes induced in planaria can be stored in tissue for over a week, thus revealing that somatic bioelectric circuits in vivo can implement a long-term, re-writable memory medium. A consideration of the mechanisms, evolution and functionality of basal cognition makes novel predictions and provides an integrative perspective on the evolution, physiology and biomedicine of information processing in vivo . This article is part of the theme issue ‘Basal cognition: multicellularity, neurons and the cognitive lens’.

I Know What You Need: Investigating Document Retrieval Effectiveness with Partial Session Contexts

2022 ◽  
Vol 40 (3) ◽  
pp. 1-30
Author(s):  
Procheta Sen ◽  
Debasis Ganguly ◽  
Gareth J. F. Jones
Keyword(s):  
Relevant Information ◽  
Document Retrieval ◽  
Context Information ◽  
Information Need ◽  
Search System ◽  
Query Log ◽  
Sequence Modeling ◽  
Joint Embedding ◽  
One Step ◽  
A Current

Reducing user effort in finding relevant information is one of the key objectives of search systems. Existing approaches have been shown to effectively exploit the context from the current search session of users for automatically suggesting queries to reduce their search efforts. However, these approaches do not accomplish the end goal of a search system—that of retrieving a set of potentially relevant documents for the evolving information need during a search session. This article takes the problem of query prediction one step further by investigating the problem of contextual recommendation within a search session. More specifically, given the partial context information of a session in the form of a small number of queries, we investigate how a search system can effectively predict the documents that a user would have been presented with had he continued the search session by submitting subsequent queries. To address the problem, we propose a model of contextual recommendation that seeks to capture the underlying semantics of information need transitions of a current user’s search context. This model leverages information from a number of past interactions of other users with similar interactions from an existing search log. To identify similar interactions, as a novel contribution, we propose an embedding approach that jointly learns representations of both individual query terms and also those of queries (in their entirety) from a search log data by leveraging session-level containment relationships. Our experiments conducted on a large query log, namely the AOL, demonstrate that using a joint embedding of queries and their terms within our proposed framework of document retrieval outperforms a number of text-only and sequence modeling based baselines.

Disparate Entwicklung der Wohnungsmärkte fordert die Politik

2014 ◽  
Vol 63 (1) ◽  
Author(s):  
Oliver Arentz
Keyword(s):  
Housing Policy ◽  
Low Income ◽  
Conflicts Of Interest ◽  
Housing Allowance ◽  
Main Task ◽  
Trading System ◽  
The Public ◽  
Site Development ◽  
High Level

AbstractThe regional differences in the housing markets are enormous and will continue to exacerbate in the future. The main task for the housing policy is to take appropriate long term measures depending on the market structure. A central aspect of future housing policy is the site development. Potential conflicts of interest with other social objectives must be detected and resolved. Creating a trading system for development rights appears to be promising. In order to secure housing for low income households, the housing allowance (Wohngeld) must be promptly adjusted to the market conditions. The public housing sector should be seen as an instrument for the stabilization of neighborhoods. Appropriate market rents secure a housing supply at a high level.

scholarly journals Correlation Tracking via Self-Adaptive Fusion of Multiple Features

Information ◽  
2018 ◽  
Vol 9 (10) ◽  
pp. 241 ◽  
Author(s):  
Zhi Chen ◽  
Peizhong Liu ◽  
Yongzhao Du ◽  
Yanmin Luo ◽  
Wancheng Zhang
Keyword(s):  
State Of The Art ◽  
Correlation Filter ◽  
Multiple Features ◽  
Multi Scale ◽  
Tracking Algorithms ◽  
Model Update ◽  
Adaptive Fusion ◽  
Tracking Model ◽  
Update Strategy ◽  
Self Adaptive

Correlation filter (CF) based tracking algorithms have shown excellent performance in comparison to most state-of-the-art algorithms on the object tracking benchmark (OTB). Nonetheless, most CF based tracking algorithms only consider limited single channel feature, and the tracking model always updated from frame-by-frame. It will generate some erroneous information when the target objects undergo sophisticated scenario changes, such as background clutter, occlusion, out-of-view, and so forth. Long-term accumulation of erroneous model updating will cause tracking drift. In order to address problems that are mentioned above, in this paper, we propose a robust multi-scale correlation filter tracking algorithm via self-adaptive fusion of multiple features. First, we fuse powerful multiple features including histogram of oriented gradients (HOG), color name (CN), and histogram of local intensities (HI) in the response layer. The weights assigned according to the proportion of response scores that are generated by each feature, which achieve self-adaptive fusion of multiple features for preferable feature representation. In the meantime the efficient model update strategy is proposed, which is performed by exploiting a pre-defined response threshold as discriminative condition for updating tracking model. In addition, we introduce an accurate multi-scale estimation method integrate with the model update strategy, which further improves the scale variation adaptability. Both qualitative and quantitative evaluations on challenging video sequences demonstrate that the proposed tracker performs superiorly against the state-of-the-art CF based methods.

scholarly journals Humanitarian Diplomacy

2018 ◽  
pp. 382-392
Author(s):  
Antonio Gazzanti Pugliese di Cotrone
Keyword(s):  
International Law ◽  
International Federation ◽  
Decision Makers ◽  
Red Cross ◽  
Main Task ◽  
Disadvantaged Groups ◽  
Socially Disadvantaged ◽  
Open Borders

The article describes humanitarian diplomacy that has to break a potential ideological ice between belligerent parties, establish a network of diplomatic connections in a skillful way, and use every opportunity available to support victims of war. An indisputable fact is that the higher the reputation and the stronger the trust to those using humanitarian diplomacy strategies, the better results will be achieved. The combination of diplomacy and humanitarian activities may lead to the emergence of unexpected interactions. The International Federation of Red Cross mentions that the goal humanitarian diplomacy seeks to achieve is the provision of better care for socially disadvantaged groups of society from governments; establishment of closer ties with decision-makers to generate opportunities to influence them; maintenance of a permanent dialogue at both national and international levels; engagement to a discussion of those who work in the field of humanitarian diplomacy; increase in transparency of such discussion; enhancement of the ability to govern all the useful resources; cooperation with other actors pursuing the same humanitarian goals. Humanitarian diplomacy has to direct its actions at all crises and to both governmental and non-governmental entities of international law; take into account that its aim is to open borders and establish humanitarian corridors ensuring the provision of direct assistance to refugees. The main task is to guarantee long-term actions, while avoiding temporary and fragile alternatives. That is the basis for humanitarian diplomacy of the Sovereign Military Order of Malta with all its peculiarities. Keywords: the Sovereign Military Order of Malta, Red Cross, international law, humanitarian diplomacy, crises.

scholarly journals "A survey on the most important internet of things technologies "

2019 ◽  
Vol 6 (2) ◽  
pp. 1-12
Author(s):  
Gesoon j.k Al-Abass ◽  
Huda R. ALkifaey
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Recent Work ◽  
State Of The Art ◽  
Long Term Evolution ◽  
Network Layers ◽  
Term Evolution ◽  
Domain Importance ◽  
The World

"Internet of things (IoT) domain targets human with smart resolutions through the connection of “M2M” in all over the world, effectively. It was difficult to ignore domain importance field of IoT with the new deployment of applications such as smartphone in recent days. The most important layer in architecture of IoT is network layer, because of various systems (perform of cloud computing, switching, hub, gateway, so on), different technologies of connection (Long-Term Evolution (LTE), WIFI, Bluetooth, etc.) gathered in layer. Network layers should transfer the information from or to various applications/objects, via gateways/interfaces between networks that are heterogeneous, therefore utilizing different connection technologies, protocols. Recent work highlighted IoT technologies state-of-the-art utilized in architectures of IoT, some variations among them in addition to the applications of them in life."

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