87 research outputs found

    年官制度の本質

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    Uppsatsens syfte är att utreda hur företag i form av aktiebolag skall kostnadsföra organisationskostnader av olika slag. Organisationskostnader är kostnader som är kopplade till företagets organisation och förvaltning och det kan till exempel vara fråga om utredningskostnader, flyttningskostnader och förvaltningskostnader. I uppsatsen behandlas inte organisationskostnader i form av utgifter för forskning och utveckling. Uppsatsens fokus ligger på den skatterättsliga behandlingen där omfångs- och periodiseringsfrågan för organisationskostnader enligt gällande rätt diskuteras. Även den redovisningsrättsliga behandlingen diskuteras kortfattat. Idag är kostnadsföringen av de flesta organisationskostnaderna fastställd men det finns fortfarande en del frågetecken där det saknas lagrum och där det fortfarande råder osäkerhet i rättspraxis hur kostnaden skall behandlas. Avslutningsvis ges förslag på förändringar som enligt min mening skulle förenkla hanteringen av organisationskostnader för företaget. Framförallt skulle det underlätta för företaget om samtliga utredningskostnader blev omedelbart avdragsgilla

    Simulation of Information Spreading on Twitter Concerning Radiation After the Fukushima Nuclear Power Plant Accident

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    Information spreading on social media is a crucial issue to build a safe society. In particular, during emergencies, misinformation and uncertain information can lead to social disruption and cause significant damage to our lives. Here we built a retweet network from 24 million radiation-related tweets by 1.3 million accounts in the immediate aftermath of the Fukushima nuclear power plant accident in 2011. Then we simulated the information spreading on the network to explore ways to spread scientifically accurate information. Our simulation replicated the reality in which the number of scientific evidence-based tweets experienced a gradual decline while the number of emotional tweets increased. We also showed that increasing new direct retweets from the influencers could effectively spread scientific evidence-based information in our hypothetical simulations

    A visual analytics system to support the formation of a hypothesis from calcium wave data

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    In most species, calcium waves in the oocyte are considered common phenomena in the activation of eggs. However, the mechanism of calcium waves has not yet been clarified. By collaborating with biologists studying Caenorhabditis elegans (C. elegans), which is widely used as a model organism, we observed that the following requirements must be satisfied to form a useful hypothesis based on calcium waves captured using high-speed in vivo imaging: (1) the ability to obtain an overview of how the calcium waves are propagated and (2) the ability to understand the propagation of waves in a narrow region. However, conventional visualization methods cannot satisfy these requirements simultaneously. Therefore, we propose a visual analytics system that allows users to understand and explore calcium wave images using cross-correlation analysis of the time-series data of the Ca²⁺ fluorescence intensity at each point. The interface of this system comprises an overview visualization, a detail visualization, and user interactions to satisfy these requirements and realize exploratory visualization. Some views present an overview visualization that displays the clustering results of a directed graph calculated using cross-correlation analysis. These views enable the users to understand the overview of wave propagation, thereby helping users find a region of interest. The detail visualization shows the relationship between the region of interest and other areas. Furthermore, users can use the proposed system with overview-detail and brush-link exploration to assign meaning to the region of interest and construct a hypothesis for its role. In this paper, we demonstrate how the proposed visual analytics approach works and how new hypotheses can be formed using the analysis of C. elegans calcium waves

    Visualization of Topic Transitions in SNSs Using Document Embedding and Dimensionality Reduction

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    Visualizing Text Structure of Scientific Articles Using AI

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