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With the prevalence of hardware accelerators as an integral part of the modern systems on chip (SoCs), the ability to model accelerators quickly and accurately within the system in which it operates is critical. This paper presents gem5-SALAMv2 as a novel system architecture for LLVM-based modeling and simulation of custom hardware accelerators integrated into the gem5 framework. It overcomes the inherent limitations of state-of-the-art trace-based pre-register-transfer level (RTL) simulators by offering a truly "execute-in-execute" LLVM-based model. It enables scalable modeling of multiple dynamically interacting accelerators with full-system simulation support. To create long-term sustainable expansion compatible with the gem5 system framework, gem5-SALAM offers a general-purpose and modular communication interface and memory hierarchy integrated into the gem5 ecosystem, streamlining designing and modeling accelerators for new and emerging applications. gem5-SALAMv2 expands upon the framework established in gem5-SALAMv1 with improved LLVM-based elaboration and simulation, improved and more extensible system integration, and new automations to simplify rapid prototyping and design space exploration. 1 1 Conference Paper Extension: This work extends the work presented in gem5-SALAM: A System Architecture for LLVM-based Accelerator Modeling from MICRO 2020 (Rogers et al., 2020). This work expands on the aforementioned work by revamping the gem5-SALAM internals to provide more robust and extensible simulations, introducing new automation tools for expanding and simplifying design space exploration, and demonstrates the new capabilities of gem5-SALAMv2 by exploring multiple configurations of simple neural network architectures. Validation on the MachSuite (Reagen et al., 2014) benchmarks presents a timing estimation error of less than 1% against the Vivado High-Level Synthesis (HLS) tool. Results also show less than a 4% area and power estimation error against Synopsys Design Compiler. Additionally, system validation against implementations on an Ultrascale+ ZCU102 shows an average end-to-end timing error of less than 2%. Lastly, we demonstrate the upgraded capabilities of gem5-SALAMv2 by exploring accelerator platforms for two deep neural networks, LeNet5 and MobileNetv2. In these explorations, we demonstrate how gem5-SALAMv2 can simulate such systems and guide architectural optimizations for these types of accelerator-rich architectures. 2 2 The most up-to-date version of gem5-SALAMv2 is available at https://github.com/TeCSAR-UNCC/gem5-SALAM.. [ABSTRACT FROM AUTHOR]

• The characteristics that can revolutionize Blockchain technology are thoroughly described. • The WoS literature is being explored with a systematic review on Blockchain. • The current state of Blockchain technology is thoroughly investigated. • Findings of the study highlight some significant implications to the Blockchain community. • A mapping of the major open issues for Blockchain to possible solutions is tabulated. At present times, Blockchain technology is gaining more attraction with every passing day, as it has revolutionized the traditional trade due to its distributed ledger feature, every record in this ledger is secured by rules of cryptography which makes it more secure and tamper-free. This naturally led to the emergence of various types of cryptocurrency, such as Bitcoin, which builds on a technology commonly known as Blockchain. The rapid evolution of research on Blockchain calls for more research studies for investigating and analyzing the current knowledge in this field through a systematic technical study that shows the impact and significance of the related literature since the inception of the technology in 2013. From this point, in this paper, a state-of-the-art review is conducted on the most influential articles, conference papers, and review papers related to Blockchain published from 2013 to 2020 and indexed by the Web of Science Core CollectionTM (WoS) world's literature database. To attain the desired objective, after presenting an inevitable, brief overview of Blockchain technology, the collected papers have closely been analyzed along seven key research questions. Subsequently, vital valuable findings, such as the top 10 influential papers, yearly publications and citation trends, the favorite publication venues, the hottest research areas, and the most supportive funding bodies are reported, which may offer several implications about the status quo and emerging trends and frontiers of Blockchain, to guide towards establishing a baseline for both fresh and experienced researchers and practitioners before initiating a future research project on Blockchain. Furthermore, a rigorous discussion is provided on Blockchain application in diversified domains, along with different versatile use cases. Lastly, a brief insight is presented into open challenges and potential future advancements in the field of Blockchain. Summing up, this paper is meant to assist newbies in exploring and designing new Blockchain solutions, bearing in mind existing demands and challenges. [ABSTRACT FROM AUTHOR]

Generative artificial intelligence (GAI) is a rapidly growing field with a wide range of applications. In this paper, a thorough examination of the research landscape in GAI is presented, encompassing a comprehensive overview of the prevailing themes and topics within the field. The study analyzes a corpus of 1319 records from Scopus spanning from 1985 to 2023 and comprises journal articles, books, book chapters, conference papers, and selected working papers. The analysis revealed seven distinct clusters of topics in GAI research: image processing and content analysis, content generation, emerging use cases, engineering, cognitive inference and planning, data privacy and security, and Generative Pre-Trained Transformer (GPT) academic applications. The paper discusses the findings of the analysis and identifies some of the key challenges and opportunities in GAI research. The paper concludes by calling for further research in GAI, particularly in the areas of explainability, robustness, cross-modal and multi-modal generation, and interactive co-creation. The paper also highlights the importance of addressing the challenges of data privacy and security in GAI and responsible use of GAI. [ABSTRACT FROM AUTHOR]

A comprehensive study of the Earth System and its different environments requires understanding of multi-dimensional data acquired with a multitude of different sensors or produced by various models. Here we present a component-wise scalable web-based framework for simultaneous visualisation of multiple data sources. It helps contextualise mixed observation and simulation data in time and space. This work is an extended version of the conference paper (Buck et al., 2021). [Display omitted] • Open-source (EUPL) hybrid application for realtime visualisation of 4D geoscientific data. • Split into native server and web client to utilize the strengths of both platforms. • Desktop builds are released for Windows, Linux, and MacOS. • Viewer used on expedition cruises to plan underwater exploration missions • Presentation and data validation capabilities used by GLODAP [ABSTRACT FROM AUTHOR]

Academic networks express the academic relationships among authors, papers and conferences, which offer perspectives and tools to rethink and solve traditional problems in the academic field. Among them, conference ranking is a problem which normally produced by collecting information from different sources and considering many factors. Not like most of the existed ranking methods that based on subjective evaluation, in this paper, we develop a Conference Ranking method based on Academic Network Embedding (CRANE) algorithm to simultaneously rank authors and conferences which improving the accuracy of ranking by embedding the Academic Network. The CRANE uses both conference features like internationality, citations and co-authors, and structure in Academic Network to evaluate the ranking of certain conferences. The theoretical analysis and convergence analysis were provided in this paper. Experiments on datasets of the Digital Bibliography & Library Project (DBLP) and AMiner academic platforms also be conducted. The experimental results show that the CRANE algorithm is superior to other algorithms by comparing with the public academic ranking like the China Computer Federation (CCF) ranking. [ABSTRACT FROM AUTHOR]

Digital platform ecosystem governance refers to a platform owner's decisions and mechanisms that seek to influence complementors and users to build and sustain an ecosystem. The relevance of digital platform ecosystem governance is broadly acknowledged by researchers. However, the extant body of research is fragmented, and varied terminologies are employed, leading to challenges in identifying and recognizing results across different fields. This article provides a multidisciplinary and systematic literature review with the aim of consolidating knowledge on this important topic. Based on an analysis of 103 journal articles and conference papers, this review synthesizes the literature into a conceptual model with five building blocks of platform ecosystem governance. The model aims to create a robust foundation for researchers approaching the topic for the first time and conducting subsequent research. The conceptual model also offers practical guidance for governing ecosystems in a structured manner. Finally, this article provides a research agenda with five areas for future investigation. • Multidisciplinary, systematic literature review on platform ecosystem governance. • Synthesis of the literature into a conceptual model with five building blocks. • Robust foundation for understanding the topic and for future research. • Research agenda with five areas and questions for future investigation. [ABSTRACT FROM AUTHOR]

Given a set A ⊆ S n of m permutations of { 1 , 2 , ... , n } and a distance function d , the median problem consists of finding a permutation π ∗ that is the "closest" of the m given permutations. Here, we study the problem under the Kendall- τ distance which counts the number of order disagreements between pairs of elements of two permutations. This problem has been proved to be NP-hard when m ≥ 4 , m even. In this article, which is a full version of the conference paper Milosz and Hamel (2016), we investigate new theoretical properties of A that solve the relative order between pairs of elements in median permutations of A , thus drastically reducing the search space of the problem. The resulting preprocessing of the problem is implemented with a Branch-and-Bound solving algorithm. We analyze its performance on randomly generated data and on real data. [ABSTRACT FROM AUTHOR]

In applications of AI systems where exact definitions of the important notions of the application domain are hard to come by, the use of traditional logic-based knowledge representation languages such as Description Logics may lead to very large and unintuitive definitions, and high complexity of reasoning. To overcome this problem, we define new concept constructors that allow us to define concepts in an approximate way. To be more precise, we present a family τ EL (m) of extensions of the lightweight Description Logic EL that use threshold constructors for this purpose. To define the semantics of these constructors we employ graded membership functions m , which for each individual in an interpretation and concept yield a number in the interval [ 0 , 1 ] expressing the degree to which the individual belongs to the concept in the interpretation. Threshold concepts C ⋈ t for ⋈ ∈ { < , ≤ , > , ≥ } then collect all the individuals that belong to C with degree ⋈ t. The logic τ EL (m) extends EL with threshold concepts whose semantics is defined relative to a function m. To construct appropriate graded membership functions, we show how concept measures ∼ (which are graded generalizations of subsumption or equivalence between concepts) can be used to define graded membership functions m ∼. Then we introduce a large class of concept measures, called simi-d , for which the logics τ EL (m ∼) have good algorithmic properties. Basically, we show that reasoning in τ EL (m ∼) is NP/coNP-complete without TBox, PSpace-complete w.r.t. acyclic TBoxes, and ExpTime-complete w.r.t. general TBoxes. The exception is the instance problem, which is already PSpace-complete without TBox w.r.t. combined complexity. While the upper bounds hold for all elements of simi-d , we could prove some of the hardness results only for a subclass of simi-d. This article considerably improves on and generalizes results we have shown in three previous conference papers and it provides detailed proofs of all our results. [ABSTRACT FROM AUTHOR]

• Estimated battery SOH using CNN model based on the raw data. • A high tolerance to the partial charging condition. • Introduced transfer learning method to reduce the offline training data. • Satisfied generality to different types of batteries. State of health (SOH) estimation is essential to the health diagnostic of lithium-ion battery. The data-driven approach with charging feature extraction is promising for online SOH estimation and has been widely explored over years. However, their deployment can be barriered by the lack of complete charging data in real-world applications. Motivated by this, this paper proposes an artificial intelligence-based SOH estimator using the transient phase between constant current (CC) and constant voltage (CV) charging, which is easily obtained in real-world charging scenarios. Specifically, a convolutional neural network (CNN) model is proposed to explain the relationship between the charging data and the SOH. Following this endeavor, the transfer learning is exploited for model mitigation and SOH estimation on different battery types, relying on much reduced amount of data for efficient CNN model re-training. The validation experiments are conducted based on the aging data obtained on LiNiCoAlO 2 (NCA) and LiCoO 2 (LCO) cells. Results suggest that the proposed method realizes accurate SOH estimation requiring only a short segment from the CC-CV transient phase, so that can meet a broad range of real-world charging scenarios. Moreover, the efficient model transfer promises expected performance with different battery types. The short version of the paper was presented at ICAE2021, Nov 29 - Dec 5, 2021. This paper is a substantial extension of the short version of the conference paper. [ABSTRACT FROM AUTHOR]

Knowledge discovery for data streaming requires online feature selection to reduce the complexity of real-world datasets and significantly improve the learning process. This is achieved by selecting highly relevant subsets and minimising irrelevant and redundant features. However, researchers have difficulties in addressing various forms of data. The goal of this article is to present a state-of-the-art review of feature subset selection based on the data form for the high-dimensional data used in online streaming. Through a systematic literature review assessing journal and conference papers from the past five years, detailed discussions on traditional feature selection and online feature selection were presented. Subsequently, a taxonomy of the challenges related to OFS provides a comprehensive review of state-of-the-art OFS and the benchmark methods. Several data forms were identified based on the extensive review: group stream, multi-label, capricious, imbalance, and feature drift. Using critical analysis, the evaluation metrics of online feature selection methods were compared from the perspectives of threshold initialisation, accuracy, high dimensionality, running time, relevancy, and redundancy for the optimal feature subset. An online feature selection framework was derived to illustrate the relationship between the application area, data form, online feature selection methods, evaluation metrics, and tools. Finally, the findings and potential directions for future research were thoroughly discussed. It is suggested that future researchers explore the derived framework and aim to advance each method. • Online feature selection methods for high dimensional online streaming data according to data forms and correlation measures. • A taxonomy of OFS challenges and the OFS framework was derived to illustrate the relationship of its ecosystems. • Significant findings in the adjustment of threshold dimensionality of data, relevancy and redundancy state. [ABSTRACT FROM AUTHOR]

• Electricity, the most direct and effective use of RES, is in center of energy transition. • An interdisciplinary procedure suitable for the planning of RES is presented. • Key points and procedures for the assessment of large-scale RES installation is presented. • Simulation on Eygiption case shows the technical and economical viability. Due to the environmental impacts brought by current energy schemes, the energy transition, a new paradigm shift from fossil fuels to renewable energy, has been widely accepted and is being realized through collective international, regional, and local efforts. Electricity, as the most direct and effective use of renewable energy sources (RES), plays a key role in the energy transition. In this paper, we first discuss a viable pathway to energy transition through the electricity triangle, highlighting the role of RES in electricity generation. Further, we propose methodologies for the planning of wind and solar PV, as well as how to address their uncertainty in generation expansion problems. Finally, by using a web-based tool, "RES-PLAT" 1 1 https://res-plat.est.polito.it. , we demonstrate the scheme in a case study in Egypt, which evaluates the impacts and benefits of a large-scale RES expansion. 2 2 The short version of the paper was presented at Applied Energy Symposium: MIT A+ B, August 13–14, Boston. This paper is a substantial extension of the short version of the conference paper. [ABSTRACT FROM AUTHOR]

Ever since California experienced its energy crisis two decades ago, dynamic pricing of electricity has been the topic of discussion in numerous conferences and papers. Scores of pilots involving some 400 treatments of time-varying rates have been done to assess customer response to dynamic pricing around the globe, beginning with California's Statewide Pricing Pilot that ran from 2003 to 04. In the past few years, we are witnessing large scale deployment of static time-varying rates in states such as California and Michigan. Colorado is about to embark on that journey. However, other than OG&E's deployment of dynamic pricing, we have not seen much deployment of dynamic pricing in North America. California's power outages in August 2002 have rekindled interest in the topic. But almost all of the discussion about dynamic pricing has focused on summer peaking utilities. In this paper, we discuss the experience of Hydro Quebec, a winter peaking utility in Canada. Hydro Quebec has tested both critical-peak pricing and peak-time rebates. The results are very encouraging and quite consistent with results from summer peaking utilities. The article is based on a question and answer format with Frederic Pelletier, who advises Hydro Quebec on tariff strategy. He had posted some results from their dynamic pricing deployment on LinkedIn in response to some results I had posted from three-pilots with TOU rates that had been carried out in Maryland. I put a few questions to Frederic and this article evolved out of that conversation. In the article that follows, the questions are mine and the answers are exclusively his. [ABSTRACT FROM AUTHOR]

Abstract: This article investigates and discusses 3D property research, as evidenced by conference papers and other publications written in English, to analyze the distribution of interest areas and the occurrence of legal aspects and trends within 3D property research occurring between 2001 and 2011. A total of 156 publications on 3D property were examined. The publications were classified in four different categories, which represent different aspects of 3D property: legal, technical, registration and organizational. More 3D property research has been conducted on technical aspects and registration than legal aspects. In the legal category, most studies addressed national legislation and the practical use of (national) legislation. The authors believe that further fundamental legal research on 3D property is needed. The quantity of research could be increased, for example, by promoting international discussion and increasing the number of comparative legal studies on 3D property rights. Additional and more focused attention should be given to international matters, such as comparative studies on the use of 3D property concepts, the development of (international) 3D property terminology and cooperation between 3D property unit owners. [Copyright &y& Elsevier]

The present article reviews and compares the immunomodulatory activities of Crocus sativus (C. sativus) and Nigella sativa (N. sativa) and their main bioactive compounds. Immunomodulatory effects of these plants, especially with respect to Th1 and Th2 cytokines, are discussed based on relevant articles, books, and conference papers published in English until the end of April 2020, that were retrieved from Web of Science, PubMed, Scopus and Google Scholar databases. C. sativus and its constituents increase immunoglobulin (Ig-)G, interleukin 2 (IL)-2, interferon gamma (IFN-γ), and IFN-γ/IL-4 ratio, but decreased IgM, IL-10 and IL-4 secretion. N. sativa extract and thymoquinone reduce the levels of IL-2, -4, -10, and -12, while enhance IFN-γ and serum IgG1 and 2a. The reviewed articles indicate that C. sativus and N. sativa and their constituents could be potentially considered promising treatments for disorders associated with immune-dysregulation such as asthma and cancer. [Display omitted] • Immunomodulatory activities of Crocus sativus , Nigela sativa and their compounds were presented. • C. sativus and its ingredients increased levels of Ig-G, IL-2, and IFN-γ. • C. sativus and its constituents decreased IgM, IL-10 and IL-4 secretion. • N. sativa extract and thymoquinone (TQ) reduced the levels of IL-2, -4, -10, and -12. • N. sativa extract and TQ enhanced the level of IFN-γ, and serum levels of IgG1 and 2a. [ABSTRACT FROM AUTHOR]

There are multiple ways of defining nonmonotonic inference relations based on a conditional knowledge base. While the axiomatic system P is an important standard for such plausible nonmonotonic reasoning, inference relations obtained from system Z or from c-representations have been designed which go beyond system P by selecting preferred models for inference. For any class of models M , we propose the notion of weakly skeptical inference, first introduced in an ECAI conference paper this article revises and extends, that lies between skeptical and credulous inference with respect to M. Weakly skeptical c-inference properly extends skeptical c-inference, but avoids disadvantages of a too liberal credulous c-inference. We extend the concepts of skeptical, weakly skeptical, and credulous c-inference modes by taking models obtained from different minimality criteria into account. We illustrate the usefulness of the obtained inference relations and show that they fulfill various desirable properties put forward for nonmonotonic reasoning. Furthermore, we elaborate in detail the interrelationships among the inference relations when taking the different inference modes and various classes of minimal models into account. [ABSTRACT FROM AUTHOR]

Open innovation (OI) has received considerable attention since its introduction and has positive and negative characteristics. To offer an overview for future research, this article produces a comprehensive review by combining bibliometric analysis and content analysis. A total of 4463 journal articles and 3061 conference papers on OI were extracted from Web of Science (WOS). The synthesized networks were constructed and visualized through CiteSpace software to aid analytical studies. After the descriptive bibliometric analysis of all publications, a content analysis of 213 articles was carried out to develop the conceptual framework of OI. The results reveal that OI still confined itself to limited disciplines and innovation-centric journals but is beginning to put more effort into becoming a more open ecosystem by influencing other disciplines. We also find some gaps in the extant research and provide some research directions in the OI field: empirical studies in various contexts could enrich the external validity of OI, other theoretical perspectives could provide novel views, and OI is on its way to becoming mature but has a long way to go. [ABSTRACT FROM AUTHOR]

Reviewers play a significant role in academic peer review activities, including conference paper assignment and funding selection, because their evaluation of proposals impacts the final decision. Several studies have proposed reviewer selection strategies or reviewer evaluation methods for solving the problem of selecting appropriate reviewers. Identifying reviewers who are familiar with the proposals to be reviewed is the objective of the reviewer assignment problem. However, the majority of the existing studies ignore quantitative constraints with respect to the articles assigned to the reviewers during the review process. In this study, we propose a novel optimization model with several review condition constraints to address the reviewer assignment problem. In the proposed model, the expertise and research areas of the candidate reviewers and proposals are identified using semantic topic models, which are demonstrated to be effective when measuring the relevance of the reviewers with respect to the proposals to be reviewed; further, the computational efficiency is improved owing to the reduced representation dimensionality. Herein, an improved heuristic algorithm is proposed to match reviewers and papers based on specific topic areas, and candidate reviewers are assigned to each proposal under the global optimum condition based on their overall performance values. Subsequently, an empirical test is conducted using a conference reviewer dataset. The obtained results show that the proposed model can help the managers to efficiently and effectively select reviewers in terms of the convergence rate and convergence level when compared with several classic benchmarks. • A novel optimization model is proposed to address the reviewer assignment problem. • The expertise and profiles are identified with the semantic topic models. • An improved heuristic algorithm is proposed to assign reviewer with global optimum. • The effectiveness and robustness is validated in three stages of experiments. [ABSTRACT FROM AUTHOR]

Since its inception in 1969, Chemico-Biological Interactions (CBI) has persistently published high quality research articles. As part of the journal's golden anniversary (50 years), we performed an electronic search on Scopus to get all publications details. Based on citescore, ranking & percentile, CBI holds 21st position in the top 113 relevant journals (in 2018). CBI also completed publications of 8005 manuscripts in March 2020. The highest documents were articles (6972/87.09%) followed by conference papers (588/7.34%) and reviews (252/3.14%). The maximum number of publications (385) was recorded in 2019, followed by 366 (in 2010) and 336 in 2016. Furthermore, details of the top 50 countries, top 50 authors and top 20 institutes with total publications, h-index, total citations and without selfcitations (WSC) are provided. USA (2371), China (786) and United Kingdom (658) are the top three countries, O'Brien, P.J (48), Maser, E. (45) and Lockridge, O. (35) are the top three authors and Karolinska Institutet (144), Stockholm University (102) & Ministry of Education China (94) are the top three institutes involved in research publications. More than eighty-four thousand (84,000) key words were amassed from scopus and after critical analysis we proposed a common sequence and connectivity. The top 200 articles, 200 reviews and 200 conference papers were analyzed by Vosviewer for various parameters. While, the top three (3) research articles and reviews are briefly described. The bibliometric analyses confirm a noteworthy growth of CBI in research publications and scientometric performance. • The 1st bibliometric study of chemico-biological interactions. • The data about top authors, universities and countries are provided. • The top 200 articles, reviews and conference papers were analyzed by Vosviewer. [ABSTRACT FROM AUTHOR]

This work follows up a previous paper at conference Cyberworlds 2018 for automatic border approximation of cutaneous melanoma and other skin lesions from macroscopic medical images. Given a set of feature points on the boundary of the skin lesion obtained by a dermatologist, we introduce a new method for automatic least-squares B-spline curve fitting of such feature points. The method is based on the original cuckoo search algorithm used in the conference paper but with three major modifications: (1) we use an enhanced version of the algorithm in which the parameters change dynamically with the generations; (2) this improved method is coupled with the Luus-Jaakola local search heuristics for better performance; (3) the original Bézier curves are now replaced by the more powerful and more general B-spline curves, providing extra flexibility and lower polynomial degree. The new method (called memetic improved cuckoo search algorithm) has been applied to a benchmark comprised of ten medical images of skin lesions. The computer results show that it performs very well and yields a border curve enclosing the lesion and fitting the feature points with good accuracy. Furthermore, a comparison with ten alternative methods in the literature (six standard mathematical methods for B-spline fitting, two state-of-the art methods in medical imaging, the method in our conference paper and the non-memetic version of our new method) shows that it outperforms all these methods in terms of numerical accuracy for the instances in our reference benchmark. [ABSTRACT FROM AUTHOR]

The rapid development of information and communication technologies (ICT) has enabled the prevailing digital transformation (i.e. digitalization), where physical products can be readily digitized in the virtual space and seamlessly interconnected. Meanwhile, industries are ever increasingly adopting service business models (i.e. servitization), so as to offer not only physical products but also services as a solution bundle to meet individual customer needs. Such convergence of both digitalization and servitization (i.e. digital servitization) has triggered an emerging IT-driven business paradigm, smart product-service systems (Smart PSS). As a novel paradigm coined in 2014, to the authors' knowledge, only 2 conference papers have provided some literature review to date, and many issues remain uncovered or not comprehensively investigated. Aiming to fill this gap, this paper has conducted a systematic review of Smart PSS or related papers published ever since its first brought up to date (30/06/2019), and selected 97 representative items together with other 37 supplementary works to summarize the tendency towards Smart PSS, its business and technical aspects, current challenges, and future perspectives. From the survey, it is found that several hybrid concerns are the key challenges faced, and self-adaptiveness with sustainability, advanced IT infrastructure, human-centric perspectives, and circular lifecycle management are the core future perspectives to explore. It is hoped that this work can attract more open discussions and provide useful insights to both academics and industries in their exploration and implementation of Smart PSS. [ABSTRACT FROM AUTHOR]