Kinetika Fotodegradasi Remazol Yellow Menggunakan Fotokatalis ZnO dan ZnO-Ag

Telah dilakukan penelitian tentang kinetika fotodegradasi remazol yellow dengan menggunakan ZnO dan ZnO yang disisipi 1%, 3%, 5%, 7%, dan 9% Ag yang disintesis dengan metode kopresipitasi. Eksperimen kinetika dilakukan melalui penentuan konsentrasi remazol yellow yang tersisa setelah interaksi ZnO dan ZnO-Ag dengan larutan remazol yellow yang disinari UV selama 0, 20, 40, 60, 80, 100, 120 dan 140 menit. Selanjutnya data dianalisis mengikuti model kinetika reaksi orde pertama. Hasil penelitian menunjukkan bahwa laju reaksi fotodegradasi oleh ZnO meningkat dengan penambahan konsentrasi dopan AgA research on photodegradation kinetics of remazol yellow using ZnO and Ag-doped ZnO (1, 3, 5, 7 and 9 wt% Ag) synthesized by co-precipitation method had been studied. Kinetics experiment was performed by determining the concentration of remazol yellow remained after interaction of ZnO and ZnO-Ag with remazol yellow solution that were irradiated by UV-light at 0, 20, 40, 60, 80, 100, 120 and 140 minutes. Data obtained was analyzed using firs-order kinetics model. The results showed that photodegradation rate was increased with the increasing Ag concentration

Information-Theoretic Properties of Auditory Sequences Dynamically Influence Expectation and Memory

EPSRC. Grant Number: EP/D038855/

Re-Representing Metaphor: Modelling metaphor perception using dynamically contextual distributional semantics

In this paper, we present a novel context-dependent approach to modelling word meaning, and apply it to the modelling of metaphor. In distributional semantic approaches, words are represented as points in a high dimensional space generated from co-occurrence statistics; the distances between points may then be used to quantifying semantic relationships. Contrary to other approaches which use static, global representations, our approach discovers contextualised representations by dynamically projecting low-dimensional subspaces; in these \textit{ad hoc} spaces, words can be re-represented in an open-ended assortment of geometrical and conceptual configurations as appropriate for particular contexts. We hypothesise that this context-specific re-representation enables a more effective model of the semantics of metaphor than standard static approaches. We test this hypothesis on a dataset of English word dyads rated for degrees of metaphoricity, meaningfulness, and familiarity by human participants. We demonstrate that our model captures these ratings more effectively than a state-of-the-art static model, and does so via the amount of contextualising work inherent in the re-representational process

Melody Generation using an Interactive Evolutionary Algorithm

Music generation with the aid of computers has been recently grabbed the attention of many scientists in the area of artificial intelligence. Deep learning techniques have evolved sequence production methods for this purpose. Yet, a challenging problem is how to evaluate generated music by a machine. In this paper, a methodology has been developed based upon an interactive evolutionary optimization method, with which the scoring of the generated melodies is primarily performed by human expertise, during the training. This music quality scoring is modeled using a Bi-LSTM recurrent neural network. Moreover, the innovative generated melody through a Genetic algorithm will then be evaluated using this Bi-LSTM network. The results of this mechanism clearly show that the proposed method is able to create pleasurable melodies with desired styles and pieces. This method is also quite fast, compared to the state-of-the-art data-oriented evolutionary systems.Comment: 5 pages, 4 images, submitted to MEDPRAI2019 conferenc

Conflict of Interest Policies at Canadian Universities: Clarity and Content

[À l'origine dans / Was originally part of : ESPUM - Dép. médecine sociale et préventive - Travaux et publications]Abstract Discussions of conflict of interest (COI) in the university have tended to focus on financial interests in the context of medical research; much less attention has been given to COI in general or to the policies that seek to manage COI. Are university COI policies accessible and understandable? To whom are these policies addressed (faculty, staff, students)? Is COI clearly defined in these policies and are procedures laid out for avoiding or remedying such situations? To begin tackling these important ethical and governance questions, our study examines the COI policies at the Group of Thirteen (G13) leading Canadian research universities. Using automated readability analysis tools and an ethical content analysis, we begin the task of comparing the strengths and weaknesses of these documents, paying particular attention to their clarity, readability, and utility in explaining and managing COI.This study was supported by a grant from the Institute of Genetics of the Canadian Institutes of Health Researc

Accelerated Multi-Organization Conflict Resolution

In this paper, we discuss two situations where two organizations with different aims recognized the dysfunctionality of their relationship. In each of these cases, which were long running (6–8 months), the organizations had worked hard to resolve this dysfunctionality, and conflict, by organizing off-site meetings designed to resolve the conflict. These 1-day meetings failed. Subsequently Group Support System workshops were used for 1 day workshops and in each case the conflict was essentially resolved within 55 min. The research reported in this paper seeks to answer the question: what happened in these cases that led to a resolution of the conflict in such a short time period, given other attempts had failed? Specifically the paper explores the impact of the GSS used to facilitate two organizations seeking to resolve a conflictual situation

NnAudio: An on-the-Fly GPU Audio to Spectrogram Conversion Toolbox Using 1D Convolutional Neural Networks

10.1109/ACCESS.2020.3019084IEEE Access8161981-16200

Harmonic Structure Predicts the Enjoyment of Uplifting Trance Music

This research is an expansion of the extended abstract of Agres et al. (2016). It is supported by the project Lrn2Cre8 which is funded by the Future and Emerging Technologies (FET) programme within the Seventh Framework Programme for Research of the European Commission, under FET grant number 610859. This project also received funding from the European Unions Horizon 2020 research and innovation programme under grant agreement number 658914