software developers are often using instant messaging platforms to communicate with each other and other stakeholders. Among these platforms, Gitter has emerged as a popular choice and the messages it contains can rev...
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software developers are often using instant messaging platforms to communicate with each other and other stakeholders. Among these platforms, Gitter has emerged as a popular choice and the messages it contains can reveal important information to researchers studying open-source software systems. Uncovering what developers are communicating about through Gitter is an essential first step towards successfully understanding and leveraging this information. This paper builds upon our previously published paper (Parra et al. 2020), which introduced GitterCom for the first time and presented a study of the messages it contains with the goal of observing how developers and other stakeholders communicate about software using Gitter in the context of Gitter communities dedicated to the active development of open source software systems on GitHub.
As the level of intelligence in agricultural consumer electronics continues to advance, data-driven devices are often faced with challenges such as resource shortages, high real-time requirements, and complex data pro...
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Most software systems have different stakeholders with a variety of *** process of collecting requirements from a large number of stakeholders is vital but *** propose an efficient,automatic approach to collecting req...
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Most software systems have different stakeholders with a variety of *** process of collecting requirements from a large number of stakeholders is vital but *** propose an efficient,automatic approach to collecting requirements from different stakeholders’responses to a specific *** use natural language processing techniques to get the stakeholder response that represents most other stakeholders’*** study improves existing practices in three ways:Firstly,it reduces the human effort needed to collect the requirements;secondly,it reduces the time required to carry out this task with a large number of stakeholders;thirdly,it underlines the importance of using of data mining techniques in various softwareengineering *** approach uses tokenization,stop word removal,and word lemmatization to create a list of frequently accruing *** then creates a similarity matrix to calculate the score value for each response and selects the answer with the highest *** experiments show that using this approach significantly reduces the time and effort needed to collect requirements and does so with a sufficient degree of accuracy.
Drug-drug interactions (DDIs) are a significant focus in biomedical research and clinical practice due to their potential to compromise treatment outcomes or cause adverse effects. While deep learning approaches have ...
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Drug-drug interactions (DDIs) are a significant focus in biomedical research and clinical practice due to their potential to compromise treatment outcomes or cause adverse effects. While deep learning approaches have advanced DDI extraction, challenges such as severe class imbalance and the complexity of biomedical relationships persist. This study introduces BioFocal-DDI, a framework combining BioGPT for data augmentation, BioBERT and BiLSTM for contextual and sequential feature extraction, and Relational Graph Convolutional Networks (ReGCN) for relational modeling. To address class imbalance, a Focal Loss-based Attention mechanism is employed to enhance learning on underrepresented and challenging instances. Evaluated on the DDI Extraction 2013 dataset, BioFocal-DDI achieves a precision of 86.75%, recall of 86.53%, and an F1 Score of 86.64%. These results suggest that the proposed method is effective in improving DDI extraction.
On several e-commerce platforms, internet users share opinions. Understanding people's sentiments and opinions is necessary. GloVe, which uses word contexts and matrix vectorization, is an effective word vector le...
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Dynamic voltage and frequency scaling (DVFS) is commonly used for the balance of performance and power of mobile processors. Conventional DVFS regulators take the processor cores with the same power and performance we...
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ISBN:
(数字)9798350350821
ISBN:
(纸本)9798350350838
Dynamic voltage and frequency scaling (DVFS) is commonly used for the balance of performance and power of mobile processors. Conventional DVFS regulators take the processor cores with the same power and performance weight showing their inability in the regulation of heterogeneous processors. This paper proposes a core-aware frequency-power evaluation scheme that utilizes a multilayer perceptron (MLP) to assess the efficacy of DVFS regulation actions. Additionally, a ResNet-based DVFS regulator, trained with the assistance of the MLP, is developed for heterogeneous multi-core processors. Evaluated on Xiaomi 13 Pro powered by a Qualcomm Snapdragon 8 Gen 2, the proposed DVFS approach achieves an up to ×1.47 improvement in FPS Performance Per Watt (FPPW) compared with the Qualcomm's default DVFS governor in video recording scenario.
Medical data processing has grown into a prominent topic in the latest decades with the primary goal of maintaining patient data via new information technologies, including the Internet of Things (IoT) and sensor tech...
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Medical data processing has grown into a prominent topic in the latest decades with the primary goal of maintaining patient data via new information technologies, including the Internet of Things (IoT) and sensor technologies, which generate patient indexes in hospital data networks. Innovations like distributed computing, Machine Learning (ML), blockchain, chatbots, wearables, and pattern recognition can adequately enable the collection and processing of medical data for decision-making in the healthcare era. Particularly, to assist experts in the disease diagnostic process, distributed computing is beneficial by digesting huge volumes of data swiftly and producing personalized smart suggestions. On the other side, the current globe is confronting an outbreak of COVID-19, so an early diagnosis technique is crucial to lowering the fatality rate. ML systems are beneficial in aiding radiologists in examining the incredible amount of medical images. Nevertheless, they demand a huge quantity of training data that must be unified for processing. Hence, developing Deep Learning (DL) confronts multiple issues, such as conventional data collection, quality assurance, knowledge exchange, privacy preservation, administrative laws, and ethical considerations. In this research, we intend to convey an inclusive analysis of the most recent studies in distributed computing platform applications based on five categorized platforms, including cloud computing, edge, fog, IoT, and hybrid platforms. So, we evaluated 27 articles regarding the usage of the proposed framework, deployed methods, and applications, noting the advantages, drawbacks, and the applied dataset and screening the security mechanism and the presence of the Transfer Learning (TL) method. As a result, it was proved that most recent research (about 43%) used the IoT platform as the environment for the proposed architecture, and most of the studies (about 46%) were done in 2021. In addition, the most popular utilized DL
In model-driven engineering, textual domain-specific languages (DSLs) are constructed using a meta-model and a grammar and artifacts for parsing can be generated from this *** designing such a DSL, it is often necessa...
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In this paper experimental result of prediction of a moving object in a net of discrete points is presented. The prediction is done by autoregressive model of X-axis and Y-axis independently. Such kind of prediction c...
In this paper experimental result of prediction of a moving object in a net of discrete points is presented. The prediction is done by autoregressive model of X-axis and Y-axis independently. Such kind of prediction could be valuable for prediction of moving of autonomous robots, drones and other similar artificial objects which can have implemented some kind of intelligent behavior. Thus the moving object can predict reaching a dangerous area or erupting points in its path. The results are analyzed and conclusions are summarized.
Index tracking is a popular passive investment strategy aimed at optimizing portfolios, but fully replicating an index can lead to high transaction costs. To address this, partial replication have been proposed. Howev...
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