Search results for " Network"
showing 10 items of 6428 documents
It's Sad but I Like It The Neural Dissociation Between Musical Emotions and Liking in Experts and Laypersons
2016
Emotion-related areas of the brain, such as the medial frontal cortices, amygdala, and striatum, are activated during listening to sad or happy music as well as during listening to pleasurable music. Indeed, in music, like in other arts, sad and happy emotions might co-exist and be distinct from emotions of pleasure or enjoyment. Here we aimed at discerning the neural correlates of sadness or happiness in music as opposed those related to musical enjoyment. We further investigated whether musical expertise modulates the neural activity during affective listening of music. To these aims, 13 musicians and 16 non-musicians brought to the lab their most liked and disliked musical pieces with a …
Periferie interne siciliane
2020
Periferie interne della Sicilia, luoghi che spesso si attraversano senza soffermarsi a scoprirne le identit e i valori. Luoghi da cui sempre pi spesso si parte, che si abbandonano e si lasciano alle loro fragilit . L’immagine, con la linea della ferrovia in primo piano e il paesaggio visto in movimento dal treno, vuole evocare sia il senso del transito, del passaggio in queste “terre di mezzo”, sia il senso dell’abbandono, un abbandono triste perch comporta una sconfitta, ma anche speranzoso verso nuove prospettive.
Le periferie interne come luoghi di interconnessione e dinamismo reticolare
2020
I territori periferici risultano essere caratterizzati da una scarsa dotazione infrastrutturale, da un continuo decremento della popolazione e da insediamenti rur-urbani in precario stato di manutenzione. Ma non sono solo questo. I territori periferici, o meglio, le periferie interne sono dense di risorse paesaggistiche, naturali, culturali e portatrici di valori legati alle produzioni artigianali e agricole. Sono territori propensi al cambiamento e alla sperimentazione, capaci di generare straordinarie interrelazioni tra innovazione e tradizione, dove il capitale umano soprattutto negli ultimi anni sta dimostrando il suo potenziale e la capacit di adeguarsi alla sfida imposta dai pr…
Emerging Joint Expertise? Multiagency Collaboration Described in Local Integration Programmes in Finland
2016
Multiagency collaboration is seen as an essential way of working to promote the two-way integration of newcomers and a receiving society. The term multiagency collaboration underlines the diversity of actors in cooperation. Cross-sectorial networks are mentioned in higher strategies as well as in the local programmes or plans for action. But how is multiagency work structured at the local level? This article looks at the examples of multiagency collaboration in the written documents of local integration programmes in the Finnish context. The examples are chosen from different areas. It seems that collaboration is widely emphasized as a goal or a working method. Whereas expertise in integrat…
Automatic image‐based identification and biomass estimation of invertebrates
2020
Understanding how biological communities respond to environmental changes is a key challenge in ecology and ecosystem management. The apparent decline of insect populations necessitates more biomonitoring but the time-consuming sorting and expert-based identification of taxa pose strong limitations on how many insect samples can be processed. In turn, this affects the scale of efforts to map and monitor invertebrate diversity altogether. Given recent advances in computer vision, we propose to enhance the standard human expert-based identification approach involving manual sorting and identification with an automatic image-based technology. We describe a robot-enabled image-based identificat…
The Truth is Out There : Focusing on Smaller to Guess Bigger in Image Classification
2023
In Artificial Intelligence (AI) in general and in Machine Learning (ML) in particular, which are important and integral components of modern Industry 4.0, we often deal with uncertainty, e.g., lack of complete information about the objects we are classifying, recognizing, diagnosing, etc. Traditionally, uncertainty is considered to be a problem especially in the responsible use of AI and ML tools in the smart manufacturing domain. However, in this study, we aim not to fight with but rather to benefit from the uncertainty to improve the classification performance in supervised ML. Our objective is a kind of uncertainty-driven technique to improve the performance of Convolutional Neural Netwo…
Glottal Source Features for Automatic Speech-Based Depression Assessment
2017
Depression is one of the most prominent mental disorders, with an increasing rate that makes it the fourth cause of disability worldwide. The field of automated depression assessment has emerged to aid clinicians in the form of a decision support system. Such a system could assist as a pre-screening tool, or even for monitoring high risk populations. Related work most commonly involves multimodal approaches, typically combining audio and visual signals to identify depression presence and/or severity. The current study explores categorical assessment of depression using audio features alone. Specifically, since depression-related vocal characteristics impact the glottal source signal, we exa…
Multilayer perceptron training with multiobjective memetic optimization
2016
Machine learning tasks usually come with several mutually conflicting objectives. One example is the simplicity of the learning device contrasted with the accuracy of its performance after learning. Another common example is the trade-off that must often be made between the rate of false positive and false negative predictions in diagnostic applications. For computer programs that learn from data, these objectives are formulated as mathematical functions, each of which describes one facet of the desired learning outcome. Even functions that intend to optimize the same facet may behave in a subtly different and mutually conflicting way, depending on the task and the dataset being examined. Mul…
Node co-activations as a means of error detection : Towards fault-tolerant neural networks
2022
Context: Machine learning has proved an efficient tool, but the systems need tools to mitigate risks during runtime. One approach is fault tolerance: detecting and handling errors before they cause harm. Objective: This paper investigates whether rare co-activations – pairs of usually segregated nodes activating together – are indicative of problems in neural networks (NN). These could be used to detect concept drift and flagging untrustworthy predictions. Method: We trained four NNs. For each, we studied how often each pair of nodes activates together. In a separate test set, we counted how many rare co-activations occurred with each input, and grouped the inputs based on whether its class…
Performance Evaluation of EEG Based Mental Stress Assessment Approaches for Wearable Devices
2021
Mental stress has been identified as the root cause of various physical and psychological disorders. Therefore, it is crucial to conduct timely diagnosis and assessment considering the severe effects of mental stress. In contrast to other health-related wearable devices, wearable or portable devices for stress assessment have not been developed yet. A major requirement for the development of such a device is a time-efficient algorithm. This study investigates the performance of computer-aided approaches for mental stress assessment. Machine learning (ML) approaches are compared in terms of the time required for feature extraction and classification. After conducting tests on data for real-t…