Journal articles on the topic 'Adaptability metrics'
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van Haastrecht, Max, Bilge Yigit Ozkan, Matthieu Brinkhuis, and Marco Spruit. "Respite for SMEs: A Systematic Review of Socio-Technical Cybersecurity Metrics." Applied Sciences 11, no. 15 (July 27, 2021): 6909. http://dx.doi.org/10.3390/app11156909.
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Cybersecurity threats are on the rise, and small- and medium-sized enterprises (SMEs) struggle to cope with these developments. To combat threats, SMEs must first be willing and able to assess their cybersecurity posture. Cybersecurity risk assessment, generally performed with the help of metrics, provides the basis for an adequate defense. Significant challenges remain, however, especially in the complex socio-technical setting of SMEs. Seemingly basic questions, such as how to aggregate metrics and ensure solution adaptability, are still open to debate. Aggregation and adaptability are vital topics to SMEs, as they require the assimilation of metrics into an actionable advice adapted to their situation and needs. To address these issues, we systematically review socio-technical cybersecurity metric research in this paper. We analyse aggregation and adaptability considerations and investigate how current findings apply to the SME situation. To ensure that we provide valuable insights to researchers and practitioners, we integrate our results in a novel socio-technical cybersecurity framework geared towards the needs of SMEs. Our framework allowed us to determine a glaring need for intuitive, threat-based cybersecurity risk assessment approaches for the least digitally mature SMEs. In the future, we hope our framework will help to offer SMEs some deserved respite by guiding the design of suitable cybersecurity assessment solutions.
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Egilmez, M. Mert, Jong Min Park, Alparslan Emrah Bayrak, Bogdan I. Epureanu, and Panos Y. Papalambros. "Adaptability of modular vehicle fleets to changing supply route characteristics." Journal of Defense Modeling and Simulation: Applications, Methodology, Technology 17, no. 4 (September 10, 2019): 327–38. http://dx.doi.org/10.1177/1548512919874127.
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Modularity in vehicle systems can reduce total lifecycle cost and improve adaptability for ground military fleets. This paper quantifies the adaptability of vehicle fleets to changes in supply route characteristics defined by route distance, threat level, and damage probability. Each characteristic is discretized into three levels, and the adaptability analysis is performed over 27 scenarios with significantly different characteristics. Fleet adaptability is measured in terms of two fleet-level metrics, namely the total fleet mass (which is correlated to the total cost) and the personnel requirements. Results show that modularity improves adaptability in terms of total fleet mass compared with a conventional approach, while providing a comparable adaptability in terms of personnel requirements. A sensitivity analysis is also performed on module characteristics of the modular fleet. This analysis shows that changes in relatively small parts of the system can change the values of performance metrics substantially.
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Peng Ye, Youcong Ni, Linlin Zhang, Kai Zhao, and Ming Hu. "Adaptability Evaluation of Aspect-Oriented Software Architecture Using Quantitative Metrics." International Journal of Advancements in Computing Technology 5, no. 4 (February 28, 2013): 216–23. http://dx.doi.org/10.4156/ijact.vol5.issue4.27.
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Ismail, Suryani, Fatihah Mohd, Masita Abdul Jalil, and Wan M. N. Wan Kadir. "Development metrics measurement level for component reusability evaluation approach (CREA)." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 6 (December 1, 2019): 5428. http://dx.doi.org/10.11591/ijece.v9i6.pp5428-5435.
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The study of software component reuse is rising in software development field and one of the methods used to reduce the production cost and time. Among the problems faced by software developers in component reuse, is the difficulty to determine which set of components are suitable to use in new software development. Thus, this study was conducted with the purpose; to define the characteristics of software component reusability evaluation approach (CREA) based on experienced software developer’s feedback, and to estimate the measurement level for each of the predefined metric. Three characteristics and sub characteristics, namely understandability (documentation level and observality), adaptability (customizability), and portability (external dependency) were identified that have been used to develop the metrics for CREA. The result for all metrics will be used as an input to the fuzzy inference system (FIS) for measuring the reusability level of the component.
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Resick, Christian J., Toshio Murase, Wendy L. Bedwell, Elizabeth Sanz, Miliani Jiménez, and Leslie A. DeChurch. "Mental model metrics and team adaptability: A multi-facet multi-method examination." Group Dynamics: Theory, Research, and Practice 14, no. 4 (2010): 332–49. http://dx.doi.org/10.1037/a0018822.
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Amsallem, Myriam, Marie Aymami, William Hiesinger, Sanford Zeigler, Kegan Moneghetti, Michael Marques, Jeffrey Teuteberg, Richard Ha, Dipanjan Banerjee, and François Haddad. "Right ventricular load adaptability metrics in patients undergoing left ventricular assist device implantation." Journal of Thoracic and Cardiovascular Surgery 157, no. 3 (March 2019): 1023–33. http://dx.doi.org/10.1016/j.jtcvs.2018.08.095.
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French, Sarah, Myriam Amsallem, Nadia Ouazani, Shufeng Li, Kristina Kudelko, Roham T. Zamanian, Francois Haddad, and Lorinda Chung. "Non-invasive right ventricular load adaptability indices in patients with scleroderma-associated pulmonary arterial hypertension." Pulmonary Circulation 8, no. 3 (June 25, 2018): 204589401878826. http://dx.doi.org/10.1177/2045894018788268.
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Scleroderma-associated pulmonary arterial hypertension (SSc-PAH) is associated with worse outcome than idiopathic pulmonary arterial hypertension (IPAH), potentially due to worse right ventricular adaptation to load as suggested by pressure–volume loop analysis. The value of non-invasive load-adaptability metrics has not been fully explored in SSc-PAH. This study sought to assess whether patients with incident SSc-PAH have worse echocardiographic load-adaptability metrics than patients with IPAH. Twenty-two patients with incident SSc-PAH were matched 1:1 with IPAH based on pulmonary vascular resistance. Echocardiographic load-adaptability indices were divided into: surrogates of ventriculo-arterial coupling (e.g. right ventricular area change/end-systolic area), indices reflecting the proportionality of load adaptation (e.g. tricuspid regurgitation velocity-time integral normalized for average right ventricular radius), and simple ratios (e.g. tricuspid annular plane systolic excursion/right ventricular systolic pressure). The prognostic value of these indices for clinical worsening (i.e. death, transplant, or hospitalization for heart failure) at one year was explored. The two groups were comprised of patients of similar age, with similar cardiac index, pulmonary resistance, capacitance and NT-proBNP levels ( p > 0.10). There was no difference in baseline right ventricular dimension, function or load-adaptability indices. At one year, eight (36.4%) SSc-PAH patients had experienced clinical worsening (eight hospitalizations and two deaths) versus one hospitalization in the IPAH group. Load adaptation at one year in survivors was not worse in SSc-PAH ( p > 0.33). Patients with IPAH responded better to therapy than SSc-PAH in terms of reduction of right ventricular areas at one year ( p < 0.05). Right ventricular load-adaptability echocardiographic indices do not appear to capture the increased risk of negative outcomes at one year associated with SSc-PAH.
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Krause, Karolin Rose, Sophie Chung, Maria da Luz Sousa Fialho, Peter Szatmari, and Miranda Wolpert. "The challenge of ensuring affordability, sustainability, consistency, and adaptability in the common metrics agenda." Lancet Psychiatry 8, no. 12 (December 2021): 1094–102. http://dx.doi.org/10.1016/s2215-0366(21)00122-x.
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Krause, J., M. Cornelius, P. Goldsmith, M. Mzungu, C. Kambani-Banda, and C. Tamimie. "Soy dairy performance metrics." African Journal of Food, Agriculture, Nutrition and Development 21, no. 105 (December 24, 2021): 19016–39. http://dx.doi.org/10.18697/ajfand.105.21245.
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Soybean (Glycine max (L. Merr.) has been a crop of interest to address both poverty and malnutrition in the developing world because of its high levels of both protein and oil, and its adaptability to grow in tropical environments. Development practitioners and policymakers have long sought value added opportunities for local crops to move communities out of poverty by introducing processing or manufacturing technologies. Soy dairy production technologies sit within this development conceptual model. To the researchers’ knowledge, no research to date measures soy dairy performance, though donors and NGOs have launched hundreds of enterprises over the last 18 years. The lack of firm-level data on operations limits the ability of donors and practitioners to fund and site sustainable dairy businesses. Therefore, the research team developed and implemented a recordkeeping system and training program first, as a 14-month beta test with a network of five dairies in Ghana and Mozambique in 2016-2017. Learning from the initial research then supported a formal research rollout over 18 months with a network of six different dairies in Malawi and key collaboration from USAID’s Agricultural Diversification activity. None of the beta or rollout dairies kept records prior to the intervention. The formal rollout resulted in a unique primary dataset to address the soy dairy performance knowledge gap. The results of analysis show that the dairies, on average, achieve positive operating margins of 61%, yet cannot cover the fixed costs associated with depreciation, amortization of equipment and infrastructure, working capital, marketing and promotion, and regulatory compliance. The enterprises in our sample operate only at 9% of capacity, which limits their ability to cover the normal fixed costs associated with the business. The challenge is not the technology itself, as when operated, it produces a high-quality dairy product. The challenges involve a business that requires too much capital for normal operations relative to a nascent and small addressable market.
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Ghareb, Mazen Ismaeel, and Garry Allen. "An empirical evaluation of metrics on aspect-oriented programs." UHD Journal of Science and Technology 3, no. 2 (October 23, 2019): 74. http://dx.doi.org/10.21928/uhdjst.v3n2y2019.pp74-86.
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The quality evaluation of software metrics measurement is considered as the primary indicator of imperfection prediction and software maintenance in various empirical studies of software products. However, there is no agreement on which metrics are compelling quality pointers for new software development approaches such as aspect-oriented programming (AOP) techniques. AOP intends to enhance programming quality by providing fundamentally different parts of the systems, for example, pointcuts, advice, and intertype relationships. Hence, it is not evident if quality characteristics for AOP could be extracted from direct expansions of traditional object-oriented programming (OOP) measurements. Then again, investigations of AOP do regularly depend on established static and dynamic metrics measurement; notwithstanding the late research of AOP in empirical studies, few analyses been adopted using the International Organization for Standardization 9126 quality model as useful markers of flaw inclination in this context. This paper examination we have considered different programming quality models given by various authors every once in a while and distinguished that adaptability was deficient in the current model. We have testing 10 projects developed by AOP. We have used many applications to extract the metrics, but none of them could extract all AOP Metrics. It only can measure some of AOP Metrics, not all of them. This study investigates the suitable framework for extract AOP Metrics, for instance, static and dynamic metrics measurement for hybrid application systems (AOP and OOP) or only AOP application.
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Mori Junior, Renzo, Daniel M. Franks, and Saleem H. Ali. "Sustainability certification schemes: evaluating their effectiveness and adaptability." Corporate Governance 16, no. 3 (June 6, 2016): 579–92. http://dx.doi.org/10.1108/cg-03-2016-0066.
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Purpose New sustainability certification schemes (SCS) with different scope, governance structure and operating practice are fast emerging. This rapid growth and divergence in metrics has resulted in questions about the effectiveness of such schemes. Although this practice has been growing fast, to date, there are no reviews comprehensively synthesising the literature regarding SCS’ main flaws, challenges and improvement opportunities. This paper aims to identify what are the key components affecting effectiveness of SCS, highlighting their benefits, flaws and improvement opportunities. Design/methodology/approach An integrated literature review was conducted to identify and assess recent studies related to the benefits, flaws, effectiveness and improvement opportunities of SCS worldwide. Findings Key components affecting the effectiveness of SCS were identified (sustainability awareness; market access; management systems and productivity; social, environmental and economic impacts; monitoring outcomes; competition, overlapping and interoperability; stakeholder participation; and accountability and transparency). The authors argue that SCS to succeed have to be effective; provide accountability about their goals and achievements; and manage stakeholders’ expectations. Civil Society’s awareness of the scientific underpinnings of sustainability issues also contributes to the existence and improvement of such schemes. Research limitations/implications The limitations of this study are associated with the secondary material that was publicly available for our literature review. Originality/value This paper fulfils an identified need to explore the key components affecting effectiveness of SCS, their benefits, flaws and improvement opportunities. Such a synthesis also identifies the key areas where interoperability between SCS should be pursued by corporations and governments.
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Petersen, Kirstin H., Nils Napp, Robert Stuart-Smith, Daniela Rus, and Mirko Kovac. "A review of collective robotic construction." Science Robotics 4, no. 28 (March 13, 2019): eaau8479. http://dx.doi.org/10.1126/scirobotics.aau8479.
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The increasing need for safe, inexpensive, and sustainable construction, combined with novel technological enablers, has made large-scale construction by robot teams an active research area. Collective robotic construction (CRC) specifically concerns embodied, autonomous, multirobot systems that modify a shared environment according to high-level user-specified goals. CRC tightly integrates architectural design, the construction process, mechanisms, and control to achieve scalability and adaptability. This review gives a comprehensive overview of research trends, open questions, and performance metrics.
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Ren, Jiajia, Chunyu Peng, Shang Zheng, Haitao Zou, and Shang Gao. "An Approach to Improving Homogeneous Cross-Project Defect Prediction by Jensen-Shannon Divergence and Relative Density." Scientific Programming 2022 (October 20, 2022): 1–16. http://dx.doi.org/10.1155/2022/4648468.
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Homogeneous cross-project defect prediction (HCPDP) aims to apply a binary classification model built on source projects to a target project with the same metrics. However, there is still room for improvement in the performance of the existing HCPDP models. This study has proposed a novel approach, including one-to-one and many-to-one predictions. First, we apply the Jensen-Shannon divergence to select the most similar source project automatically. Second, relative density estimation is introduced to choose the suitable instance of the selected source project. Third, one-to-one and many-to-one prediction models are trained by the selected instances. Finally, two benchmark datasets are used to evaluate the proposed approach. Compared to the state-of-the-art methods, the experimental results demonstrated that the proposed approach could improve the prediction performance in the F1-score, AUC, and G-mean metrics and exhibit strong adaptability to the traditional classifiers.
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Baillargeon, Emma, Anisha Suri, Theodore Huppert, Ervin Sejdic, and Andrea Rosso. "DUAL-TASK CHANGES IN PREFRONTAL ACTIVATION AND GAIT QUALITY IN OLDER ADULTS." Innovation in Aging 6, Supplement_1 (November 1, 2022): 332. http://dx.doi.org/10.1093/geroni/igac059.1311.
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Abstract We compared the impact of performing dual-task walking on gait quality and prefrontal cortical activation assessed by functional near-infrared spectroscopy (fNIRS). We hypothesized a greater increase in fNIRS averaged over the left prefrontal cortex during dual-task walking would be associated with a greater decrease in gait quality (increased step-time variability; decreased gait speed, cadence, smoothness, and adaptability). In older adults (n=60, 75±5.8 years, 57% female), we quantified the change in fNIRS and gait metrics from single-task walking (even surface) to walking with attentional (reciting every-other letter of the alphabet) and physical (uneven surface) dual-task challenges using four 15m repetitions of each task. Gait metrics were computed from a tri-axial accelerometer at the lower-back. Changes in fNIRS from single to dual-task walking were not associated with changes in gait quality for both attentional and physical challenges (Spearman correlations, all p>0.08). Variability in response across individuals may contribute to our findings.
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Hu, Yu. "Some Technologies about Video Compression." Advanced Materials Research 393-395 (November 2011): 284–87. http://dx.doi.org/10.4028/www.scientific.net/amr.393-395.284.
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Many strategies can be developed into mature algorithms to compress video more efficiently than today’s standardized codecs. Future video compression algorithms may employ more adaptability, more refined temporal and spatial prediction models with better distortion metrics. The cost to users is the significant increase of implementation complexity at both the encoder and decoder. Fortunately, it seems that bitrates have a slower doubling time than computing power, so the disadvantage of increasing implementation complexity may one day be balanced with much improved processor capabilities. Development trends and perspectives of video compression analyzed in the following paper, highlighting problems and research directions are also analyzed.
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Bourbia, Salma, Daniel Le Guennec, Jacques Palicot, Khaled Grati, and Adel Ghazel. "Equalizer's Use Limitation for Complexity Reduction in a Green Radio Receiver." Journal of Computer Networks and Communications 2013 (2013): 1–15. http://dx.doi.org/10.1155/2013/794202.
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This work is about reducing energy consumption in the receiver chain by limiting the use of the equalizer. It is to make the radio receiver aware of its environment and able to take decision to turn on or off the equalizer according to its necessity or not. When the equalizer is off, the computational complexity is reduced and the rate of reduction depends on the percentage of time during which this component is disabled. In order to achieve this scenario of adapting the use of the equalizer, we need to develop a decision-making technique that provides the receiver with the capacities of awareness and adaptability to the state of its environment. For this, we improve a technique based on a statistical modeling of the environment by defining two metrics as channel quality indicators to evaluate the effect of the intersymbol interferences and the channel fading. The statistical modeling technique allows to take into account the impact of the uncertainties of the estimated metrics on the decision making.
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Zeng, Anxiang, Han Yu, Hualin He, Yabo Ni, Yongliang Li, Jingren Zhou, and Chunyan Miao. "Enhancing E-commerce Recommender System Adaptability with Online Deep Controllable Learning-To-Rank." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 17 (May 18, 2021): 15214–22. http://dx.doi.org/10.1609/aaai.v35i17.17785.
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In the past decade, recommender systems for e-commerce have witnessed significant advancement. Recommendation scenarios can be divided into different type (e.g., pre-, during-, post-purchase, campaign, promotion, bundle) for different user groups or different businesses. For different scenarios, the goals of recommendation are different. This is reflected by the different performance metrics employed. In addition, online promotional campaigns, which attract high traffic volumes, are also a critical factor affecting e-commerce recommender systems. Typically, prior to a promotional campaign, the Add-to-Cart Rate (ACR) is the target of optimization. During the campaign, this changes to Gross Merchandise Volumes (GMV). Immediately after the campaign, it becomes Click Through Rates CTR. Dynamically adapting among these potentially conflicting optimization objectives is an important capability for recommender systems deployed in real-world e-commerce platforms. In this paper, we report our experience designing and deploying the Deep Controllable Learning-To-Rank (DC-LTR) recommender system to address this challenge. It enhances the feedback controller in LTR with multi-objective optimization so as to maximize different objectives under constraints. Its ability to dynamically adapt to changing business objectives has resulted in significant business advantages. Since September 2019, DC-LTR has become a core service enabling adaptive online training and real-time deployment ranking models based on changing business objectives in AliExpress and Lazada. Under both everyday use scenarios and peak load scenarios during large promotional campaigns, DC-LTR has achieved significant improvements in satisfying real-world business objectives.
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Lee, Jangho, Jeffrey C. Mast, and Andrew E. Dessler. "The effect of forced change and unforced variability in heat waves, temperature extremes, and associated population risk in a CO<sub>2</sub>-warmed world." Atmospheric Chemistry and Physics 21, no. 15 (August 10, 2021): 11889–904. http://dx.doi.org/10.5194/acp-21-11889-2021.
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Abstract. This study investigates the impact of global warming on heat and humidity extremes by analyzing 6 h output from 28 members of the Max Planck Institute Grand Ensemble driven by forcing from a 1 % yr−1 CO2 increase. We find that unforced variability drives large changes in regional exposure to extremes in different ensemble members, and these variations are mostly associated with El Niño–Southern Oscillation (ENSO) variability. However, while the unforced variability in the climate can alter the occurrence of extremes regionally, variability within the ensemble decreases significantly as one looks at larger regions or at a global population perspective. This means that, for metrics of extreme heat and humidity analyzed here, forced variability in the climate is more important than the unforced variability at global scales. Lastly, we found that most heat wave metrics will increase significantly between 1.5 and 2.0 ∘C, and that low gross domestic product (GDP) regions show significantly higher risks of facing extreme heat events compared to high GDP regions. Considering the limited economic adaptability of the population to heat extremes, this reinforces the idea that the most severe impacts of climate change may fall mostly on those least capable of adapting.
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Charitopoulos, George, Ioannis Papaefstathiou, and Dionisios N. Pnevmatikatos. "Creating Customized CGRAs for Scientific Applications." Electronics 10, no. 4 (February 11, 2021): 445. http://dx.doi.org/10.3390/electronics10040445.
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Executing complex scientific applications on Coarse Grain Reconfigurable Arrays (CGRAs) offers improvements in the execution time and/or energy consumption when compared to optimized software implementations or even fully customized hardware solutions. In this work, we explore the potential of application analysis methods in such customized hardware solutions. We offer analysis metrics from various scientific applications and tailor the results that are to be used by MC-Def, a novel Mixed-CGRA Definition Framework targeting a Mixed-CGRA architecture that leverages the advantages of CGRAs and those of FPGAs by utilizing a customized cell-array along, with a separate LUT array being used for adaptability. Additionally, we present the implementation results regarding the VHDL-created hardware implementations of our CGRA cell concerning various scientific applications.
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Booch, Grady, Francesco Fabiano, Lior Horesh, Kiran Kate, Jonathan Lenchner, Nick Linck, Andreas Loreggia, et al. "Thinking Fast and Slow in AI." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 17 (May 18, 2021): 15042–46. http://dx.doi.org/10.1609/aaai.v35i17.17765.
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This paper proposes a research direction to advance AI which draws inspiration from cognitive theories of human decision making. The premise is that if we gain insights about the causes of some human capabilities that are still lacking in AI (for instance, adaptability, generalizability, common sense, and causal reasoning), we may obtain similar capabilities in an AI system by embedding these causal components. We hope that the high-level description of our vision included in this paper, as well as the several research questions that we propose to consider, can stimulate the AI research community to define, try and evaluate new methodologies, frameworks, and evaluation metrics, in the spirit of achieving a better understanding of both human and machine intelligence.
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Nassef, Omar, Toktam Mahmoodi, Foivos Michelinakis, Kashif Mahmood, and Ahmed Elmokashfi. "Optimising Performance for NB-IoT UE Devices through Data Driven Models." Journal of Sensor and Actuator Networks 10, no. 1 (March 5, 2021): 21. http://dx.doi.org/10.3390/jsan10010021.
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This paper presents a data driven framework for performance optimisation of Narrow-Band IoT user equipment. The proposed framework is an edge micro-service that suggests one-time configurations to user equipment communicating with a base station. Suggested configurations are delivered from a Configuration Advocate, to improve energy consumption, delay, throughput or a combination of those metrics, depending on the user-end device and the application. Reinforcement learning utilising gradient descent and genetic algorithm is adopted synchronously with machine and deep learning algorithms to predict the environmental states and suggest an optimal configuration. The results highlight the adaptability of the Deep Neural Network in the prediction of intermediary environmental states, additionally the results present superior performance of the genetic reinforcement learning algorithm regarding its performance optimisation.
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Collura, Thomas F. "The Quantitative Electroencephalogram and the Use of Normative Databases." Biofeedback 47, no. 2 (June 1, 2019): 26–35. http://dx.doi.org/10.5298/1081-5937-47.1.01.
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This report describes the scientific, technical, and clinical bases for the use of quantitative EEG (QEEG) in the assessment of clients and in treatment monitoring. Specific attention is directed toward the use of normative databases and z-scores as a form of standardized referencing for reporting and training purposes. Normative databases have general value and are of particular value when connectivity metrics are being used. It is shown that the use of z = 0 as an average over time corresponds to a state of optimum flexibility, adaptability, and readiness. The use of the inverse solution (LORETA) methods is also described, as well as use of those methods within the QEEG and normative model. Advantages as well as shortcomings of this approach are described and discussed.
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Ciyamala Kushbu, S., and T. M. Inbamalar. "Making Semi-Automatic Segmentation Method to be Automatic Using Deep Learning for Biventricular Segmentation." Journal of Medical Imaging and Health Informatics 12, no. 2 (February 1, 2022): 112–22. http://dx.doi.org/10.1166/jmihi.2022.3927.
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Ventricular Segmentation or Delineation of Cardiac Magnetic Resonance Imaging (CMRI) is significant in obtaining the cardiac contractile function, which in turn is taken as input for diagnosing Cardio Vascular Diseases (CVD). Many automatic and semi-automatic methods were evolved to meet the constraints of diagnosing CVDs. Among these, semi-automatic methods require user intervention for delineation of ventricles, which consumes time and leads to intra and inter-observability, as with manual delineation. Thus, the automatic method is suggested by most of the researchers to address the above-stated problem. We proposed Saliency-based Active contour U-Net (SACU-Net) for automatic bi-ventricular segmentation which is found to surpass the existing highest developed methods regarding closeness to the gold standard. Three schemes are used by our proposed algorithm, namely 1. Saliency Detection Scheme for Region of Interest (ROI) Localization to concentrate only on Object of Interest, 2. Drop-out embedded U-net for Initial Contour evolution that performs initial segmentation and 3. Local-Global-based Regional active Contour (LGRAC) to fine-tune and avoid leaking, merging of ventricles during Delineation. We used three datasets namely Automatic Cardiac Diagnosing Challenge (ACDC) of MICCAI 2017, Right Ventricular Segmentation Challenge (RVSC) of MICCAI 2012, and Sunny Brook (SB) of MICCAI 2009 dataset to test the adaptability nature of our algorithm over different scanner resolutions and protocols. 100 and 50 CMRI Images of ACDC were used for training and testing respectively which obtained average Dice Coefficient (DC) metric of 0.963, 0.934, and 0.948 for Left Ventricular Cavity (LVC), Left Ventricular Myocardium (LVM), and Right Ventricular Cavity (RVC) respectively. 32 and 16 CMRI Images of RVSC are used for preparing and experimenting respectively, which obtained an average DC metric of 0.95 for RVC.30 and 15 CMRI Images of SB are used for preparing and experimenting respectively, which obtained average DC metric of 0.96 and 0.97 for LVC and LVM, respectively. Hausdorff Distance (HD) Metrics are also calculated to learn the distance of proposed delineated ventricles to reach the gold standard. The above resultant metrics show the robustness of our proposed SACU-Net in the segmentation of ventricles of CMRI than previous methods.
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Ding, Bailu, Surajit Chaudhuri, Johannes Gehrke, and Vivek Narasayya. "DSB." Proceedings of the VLDB Endowment 14, no. 13 (September 2021): 3376–88. http://dx.doi.org/10.14778/3484224.3484234.
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We describe a new benchmark, DSB, for evaluating both workload-driven and traditional database systems on modern decision support workloads. DSB is adapted from the widely-used industrial-standard TPC-DS benchmark. It enhances the TPC-DS benchmark with complex data distribution and challenging yet semantically meaningful query templates. DSB also introduces configurable and dynamic workloads to assess the adaptability of database systems. Since workload-driven and traditional database systems have different performance dimensions, including the additional resources required for tuning and maintaining the systems, we provide guidelines on evaluation methodology and metrics to report. We show a case study on how to evaluate both workload-driven and traditional database systems with the DSB benchmark. The code for the DSB benchmark is open sourced and is available at https://aka.ms/dsb.
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Chen, Liang, and Benjamin F. Hobbs. "Robust Yellow River Delta Flood Management under Uncertainty." Water 13, no. 16 (August 16, 2021): 2226. http://dx.doi.org/10.3390/w13162226.
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A number of principles for evaluating water resources decisions under deep long-run uncertainty have been proposed in the literature. In this paper, we evaluate the usefulness of three widely recommended principles in the context of delta water and sedimentation management: scenario-based uncertainty definition, robustness rather than optimality as a performance measure, and modeling of adaptability, which is the flexibility to change system design or operations as conditions change in the future. This evaluation takes place in the context of an important real-world problem: flood control in the Yellow River Delta. The results give insight both on the physical function of the river system and on the effect of various approaches to modeling risk attitudes and adaptation on the long-term performance of the system. We find that the optimal decisions found under different scenarios differ significantly, while those resulting from using minimal expected cost and minmax regret metrics are similar. The results also show that adaptive multi-stage optimization has a lower expected cost than a static approach in which decisions over the entire time horizon are specified; more surprisingly, recognizing the ability to adapt means that larger, rather than smaller, first-stage investments become optimal. When faced with deep uncertainty in water resources planning, this case study demonstrates that considering scenarios, robustness, and adaptability can significantly improve decisions.
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Feizabadi, Javad, David M. Gligor, and Somayeh Alibakhshi. "Examining the synergistic effect of supply chain agility, adaptability and alignment: a complementarity perspective." Supply Chain Management: An International Journal 26, no. 4 (March 1, 2021): 514–31. http://dx.doi.org/10.1108/scm-08-2020-0424.
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Purpose Drawing on complementarity theory, this paper aims to examine the type and effect of interdependencies/interaction (i.e. complementarity or substitutability) between the supply chain capabilities of agility, adaptability and alignment. Design/methodology/approach A survey research design is adopted to collect primary and secondary data from 182 international firms. The complementarity (or substitutability) of three As (agile, adaptable and aligned) were analyzed in three-way and pairwise interactions; both, correlation and performance differences methods of testing the type of interactions among the system’s elements were used. Supply chain-centric and firm-centric performance metrics were used to examine the interaction types. Findings The study did not find empirical evidence of three-way complementarity between the three As. However, this paper did find evidence of complementarity in bivariate interactions for alignment and adaptability. Moreover, in the performance difference method, the study found a substitute relationship between all pairs of As. Practical implications The findings related to the substitutability between the three As offer managers guidance on how to allocate their limited resources to avoid unnecessary over-or under-investing in either one of the three As. Originality/value This study helps refine prior findings related to the three As by offering evidence that firms can still achieve their performance-related goals with reduced investment commitments by taking advantage of the substitutability relationship existent between these capabilities. That is, instead of concomitantly developing all three As as past studies have suggested, managers can use the findings to determine how to prioritize their resource allocation better. Furthermore, understanding the actual interaction among the supply chain variables generally provide insights for designing the supply chain, change management in the supply chain, developing supply chain strategy and adopting best practices in the supply chain.
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Bhandari, Khadak Singh, and Gi Hwan Cho. "A Resource Oriented Route Selection Framework Using Contextual Information Based on Fuzzy Logic." Electronics 8, no. 9 (September 12, 2019): 1023. http://dx.doi.org/10.3390/electronics8091023.
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Internet of Things (IoT) is expected to have a significant impact on city’s service provisioning and make a smart city more accessible and pragmatic since the deployment of heterogeneous smart devices in each infrastructure of cities is increasing. So far, the IPv6 routing protocol for low power and lossy networks (RPL) is considered to fit on IoT infrastructure for achieving the expected network requirements. While RPL meets the IoT network requirements quite well, there are some issues that need to be addressed, such as adaptability to network dynamics. This issue significantly limits the use of RPL in many smart city application scenarios, such as emergency alerts with high traffic flows. As part of a smart city vision, IoT applications are becoming more diverse, which requires context-awareness in routing protocols to support the behavior of the network. To address this issue, we design an objective function that performs the route selection based on fuzzy logic techniques while using contextual information from the application. For this, we present a new context-oriented objective function (COOF) that comprises both nodes as well as link metrics. Further, we suggest two new routing metrics, known as queue fluctuation index (QFI) and residual energy index (REI), which consider the status of queue utilization and remaining energy, respectively. The metrics used are designed to respond to the dynamic needs of the network. The proposed approach has been examined and evaluated in different scenarios when compared to other similar approach and default RPL objective functions. Simulation experiments are conducted in Cooja network simulator for Contiki OS. The evaluation results show that COOF can cope with network dynamics and IoT-based smart city application requirements.
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Khairi, Mutaz Hamed Hussien, Sharifah H. S. Ariffin, N. M. Abdul Latiff, and Kamaludin Mohamad Yusof. "Generation and collection of data for normal and conflicting flows in software defined network flow table." Indonesian Journal of Electrical Engineering and Computer Science 22, no. 1 (April 1, 2021): 307. http://dx.doi.org/10.11591/ijeecs.v22.i1.pp307-314.
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<a name="_Hlk31039004"></a><span lang="EN-US">In terms of network simplification and regulation, Software Defined Networking (SDN) is a new form of infrastructure that offers greater adaptability and flexibility. SDN, however, is an invention that is logically centralized. </span><span>In addition, the optimization of the control plane and data plane in SDN has become an area deserving of more attention. The flow in OpenFlow has been one of the essential parameters in the SDN standards, in which every individual flow includes packet matching fields, flow priority, separate counters, instructions for packet forwarding, flow timeouts and a cookie. This research work is conducted in order to produce and collect flows from the OpenFlow switch in two scenarios; in normal flows and when conflict policy rules are enforced in the network. In this article, the throughput is required to review and evaluate the conflict impact on two protocols as a performance metric; the Transmission Control Protocol (TCP) and the User Datagram Protocol (UDP) that flows via a forwarded plane. During the simulation of the SDN OpenFlow network, the metrics are tested using MININET. The results demonstrate that the existence of SDN conflict rules allows TCP and UDP to have a significant average change in bandwidth that eventually affects the network and operations performance.</span>
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Zhu, Linan, Yifei Xu, Zhechao Zhu, Yinwei Bao, and Xiangjie Kong. "Fine-Grained Sentiment-Controlled Text Generation Approach Based on Pre-Trained Language Model." Applied Sciences 13, no. 1 (December 26, 2022): 264. http://dx.doi.org/10.3390/app13010264.
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Sentiment-controlled text generation aims to generate texts according to the given sentiment. However, most of the existing studies focus only on the document- or sentence-level sentiment control, leaving a gap for finer-grained control over the content of generated results. Fine-grained control allows a generated review to express different opinions toward multiple aspects. Some previous works attempted to generate reviews conditioned on aspect-level sentiments, but they usually suffer from low adaptability and the lack of an annotated dataset. To alleviate these problems, we propose a novel pre-trained extended generative model that can dynamically refer to the prompt sentiment, together with an auxiliary classifier that extracts the fine-grained sentiments from the unannotated sentences, thus we conducted training on both annotated and unannotated datasets. We also propose a query-hint mechanism to further guide the generation process toward the aspect-level sentiments at every time step. Experimental results from real-world datasets demonstrated that our model has excellent adaptability in generating aspect-level sentiment-controllable review texts with high sentiment coverage and stable quality since, on both datasets, our model steadily outperforms other baseline models in the metrics of BLEU-4, METETOR, and ROUGE-L etc. The limitation of this work is that we only focus on fine-grained sentiments that are explicitly expressed. Moreover, the implicitly expressed fine-grained sentiment-controllable text generation will be an important puzzle for future work.
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Gil, Rafael Muñoz, Manuel de Buenaga Rodríguez, Fernando Aparicio Galisteo, Diego Gachet Páez, and Esteban García-Cuesta. "A Domain-Adaptable Heterogeneous Information Integration Platform: Tourism and Biomedicine Domains." Information 12, no. 11 (October 20, 2021): 435. http://dx.doi.org/10.3390/info12110435.
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In recent years, information integration systems have become very popular in mashup-type applications. Information sources are normally presented in an individual and unrelated fashion, and the development of new technologies to reduce the negative effects of information dispersion is needed. A major challenge is the integration and implementation of processing pipelines using different technologies promoting the emergence of advanced architectures capable of processing such a number of diverse sources. This paper describes a semantic domain-adaptable platform to integrate those sources and provide high-level functionalities, such as recommendations, shallow and deep natural language processing, text enrichment, and ontology standardization. Our proposed intelligent domain-adaptable platform (IDAP) has been implemented and tested in the tourism and biomedicine domains to demonstrate the adaptability, flexibility, modularity, and utility of the platform. Questionnaires, performance metrics, and A/B control groups’ evaluations have shown improvements when using IDAP in learning environments.
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Liu, Jinning, Zhiguo Shao, and Wei Wang. "Resilience Assessment and Critical Point Identification for Urban Water Supply Systems under Uncertain Scenarios." Water 13, no. 20 (October 19, 2021): 2939. http://dx.doi.org/10.3390/w13202939.
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The urban water supply system environment is becoming more complicated and unpredictable than ever before in the context of global climate change and expanding urbanization. Existing studies have adopted either static or dynamic approaches to assess the resilience of water supply systems without combining the two. Previous literature mostly establishes rigid quantitative metrics for resilience assessment, often without depicting the dynamics and adaptability of system resilience. For example, these studies usually fail to provide a critical point for identifying system resilience. To accurately describe the dynamics and adaptability of water supply system resilience under uncertain scenarios, in this study, we constructed a comprehensive framework based on the qualitative assessment of the input parameters, combining static and dynamic assessment, with the latter playing a dominant role based on the system perspective of pressure–state–influence–response. Taking Qingdao as a case study, we combined this framework with the system resilience theory, and statically assessed the five types of capitals and three attributes of resilience with the capital portfolio approach (CPA). Then, we dynamically assessed the resilience of urban water supply systems and identified critical points with the dynamic socio-technical model coupled with system resilience and the fitting analysis method. The results are as follows: (1) the static assessment results demonstrate an imbalanced development in the levels of the five types of capitals (financial capital, management efficiency, infrastructure, available water resources, and adaptation) and three attributes (robustness, recoverability, and adaptability) in the water supply systems of Qingdao. (2) The dynamic assessment results show that the current resilience trajectory of the water supply systems in Qingdao is that of a city in transition. (3) The fitting analysis shows that robustness (RB) has a linear relationship with resilience, recoverability (RE) has a non-linear relationship with resilience, and the critical points are RB = 0.70 and RE = 1.20. The research findings provide a reference for studying resilience mechanisms, internal attribute relationships, and resilience enhancement measures of urban water supply systems.
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Rusaniuk, Vasyl. "Metrics of efficiency indicators of state support for small entrepreneurship in the agricultural sector." Ekonomika APK 320, no. 6 (June 28, 2021): 117–27. http://dx.doi.org/10.32317/2221-1055.202106117.
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The purpose of the article is to reveal the essence and features of metrics of indicators of the effectiveness of state support for small entrepreneurship in the agricultural sector of the economy in modern conditions. Research methods. The methodological basis of the study was a set of methods of scientific knowledge of the system and mechanism of state support for small entrepreneurship in the agricultural sector. The achievement of the goal was facilitated by general scientific methods: empirical research (measurement, comparison, and observation), theoretical research (analysis and synthesis) as well as local (specific) analysis of situations (computational-constructive). Research results. It has been established that state support is one of the components of the state regulation mechanism; a system of preferential financing of priority industries and small entrepreneurship has been established; a system of measures to increase the adaptability and competitiveness of small entrepreneurship in the agricultural sector of the economy of a controlling, executive, legislative nature. It was found that the well-known methods for assessing the economic efficiency of state support for entrepreneurship in the agricultural sector could be combined into groups of methods: structural-territorial and structural-categorical; macroeconomic national; macroeconomic supranational. It has been substantiated that the set of indicators for achieving the goals of state support is reflected in the metric of indicators. Various researchers include various metrics of indicators in the system for assessing the effectiveness of state support for small business in the agricultural sector. Methods for assessing the effectiveness of state support for small entrepreneurship in the agricultural sector can be combined into groups of qualitative and quantitative assessment of budgetary, social, economic efficiency. Scientific novelty. The essence and features of metrics of indicators of the effectiveness of state support of small entrepreneurship in the agricultural sector of the economy in modern conditions is disclosed and a methodological approach to substantiating the main directions of modification of state support, which contributes to solving the problems of functioning of small entrepreneurship in the agricultural sector of the economy, is proposed. Attention is focused on the main components of expenditures for programs of state support for the development of entrepreneurship in the agricultural sector for 2021-2023. Practical significance. It is advisable to use the methodological approach as a base in the system for analyzing indicators of state support for small entrepreneurship in the agricultural sector according to the statistical reporting of business entities and macro indicators of the socio-economic state of the country. Tabl.: 2. Figs.: 1. Refs.: 27.
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Song, Zhiying, Huiyan Jiang, and Siqi Li. "A Novel Fusion Framework Based on Adaptive PCNN in NSCT Domain for Whole-Body PET and CT Images." Computational and Mathematical Methods in Medicine 2017 (2017): 1–9. http://dx.doi.org/10.1155/2017/8407019.
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The PET and CT fusion images, combining the anatomical and functional information, have important clinical meaning. This paper proposes a novel fusion framework based on adaptive pulse-coupled neural networks (PCNNs) in nonsubsampled contourlet transform (NSCT) domain for fusing whole-body PET and CT images. Firstly, the gradient average of each pixel is chosen as the linking strength of PCNN model to implement self-adaptability. Secondly, to improve the fusion performance, the novel sum-modified Laplacian (NSML) and energy of edge (EOE) are extracted as the external inputs of the PCNN models for low- and high-pass subbands, respectively. Lastly, the rule of max region energy is adopted as the fusion rule and different energy templates are employed in the low- and high-pass subbands. The experimental results on whole-body PET and CT data (239 slices contained by each modality) show that the proposed framework outperforms the other six methods in terms of the seven commonly used fusion performance metrics.
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Sankisa, Arun, Arjun Punjabi, and Aggelos K. Katsaggelos. "Optical Flow Prediction for Blind and Non-Blind Video Error Concealment Using Deep Neural Networks." International Journal of Multimedia Data Engineering and Management 10, no. 3 (July 2019): 27–46. http://dx.doi.org/10.4018/ijmdem.2019070102.
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A novel optical flow prediction model using an adaptable deep neural network architecture for blind and non-blind error concealment of videos degraded by transmission loss is presented. The two-stream network model is trained by separating the horizontal and vertical motion fields which are passed through two similar parallel pipelines that include traditional convolutional (Conv) and convolutional long short-term memory (ConvLSTM) layers. The ConvLSTM layers extract temporally correlated motion information while the Conv layers correlate motion spatially. The optical flows used as input to the two-pipeline prediction network are obtained through a flow generation network that can be easily interchanged, increasing the adaptability of the overall end-to-end architecture. The performance of the proposed model is evaluated using real-world packet loss scenarios. Standard video quality metrics are used to compare frames reconstructed using predicted optical flows with those reconstructed using “ground-truth” flows obtained directly from the generator.
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Jacobowitz, Ofer, Alan Schwartz, Eric Lovett, Giovanni Ranuzzi, and Atul Malhotra. "0761 Adaptability of the Treating Obstructive Sleep Apnea Using Targeted Hypoglossal Nerve Stimulation (OSPREY) Trial." Sleep 45, Supplement_1 (May 25, 2022): A331—A332. http://dx.doi.org/10.1093/sleep/zsac079.757.
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Abstract Introduction With few exceptions, clinical trials of hypoglossal nerve stimulation (HGNS) for obstructive sleep apnea (OSA) are single-arm, open-label studies sometimes followed by short-term, unblinded, randomized withdrawal. By contrast, the THN3 study was a parallel-arm, randomized, controlled trial (RCT) of targeted HGNS (THN) in moderate to severe OSA, and provided higher-level evidence of HGNS safety and efficacy.Despite generating strong evidence, conventional RCTs are risky due to their inherent inflexible designs. We therefore launched a confirmatory THN RCT (OSPREY) with an adaptive, Bayesian “Goldilocks” design that optimize its sample size dynamically, yet achieve high-confidence results. Methods Four scenarios were simulated within the OSPREY design framework (randomized 2:1 Treatment:Control) for the primary endpoint of apnea-hypopnea index (AHI) response rate (RR): nominal with results equal to those of THN3 (Treatment AHI RR 52%/Control AHI RR 20%), improved Treatment RR (63%/20%), worsened Treatment RR (41%/20%) and null [Treatment RR=Control RR] (20%/20%). Each scenario was simulated 10 times with 10,000 simulations of each interim analysis. Subject outcomes were determined by randomly drawing from a binomial distribution with the relevant AHI RR.Interim analyses in OSPREY begin at 50 randomized subjects and repeat every 20 additional subjects to the maximum sample size of 150, with opportunities for early success and futility at each milestone to generate high-confidence results from an optimal sample size. OSPREY assesses secondary endpoints including quality of life inventories (Epworth Sleepiness Scale; Functional Outcomes of Sleep Questionnaire; EQ-5D, SF-6D and PROMIS sleep questionnaires) and oximetry metrics (Oxygen Desaturation Index, %sleep time below 90% oxygen saturation). Previous results suggest secondary endpoints will be adequately powered at the final sample size determined by AHI RR. Results Simulations produced the following outcomes formatted as [scenario: randomized sample size, overall success rate, probability of early success, mean success probability]: null: 150, 0%, 0%, 2.47%; nominal: 130-150, 100%, 80%, 95.3%; improved: 90-130, 100%, 100%, 98.9%; worsened: 150, 100%, 0%, 68.6%. Conclusion OSPREY is uniquely able to adapt to various Treatment/Control response scenarios and should provide high-confidence confirmation of the safety and efficacy of THN therapy in moderate to severe OSA. Support (If Any) LivaNova
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Higueras-Ruiz, Diego R., Kiisa Nishikawa, Heidi Feigenbaum, and Michael Shafer. "What is an artificial muscle? A comparison of soft actuators to biological muscles." Bioinspiration & Biomimetics 17, no. 1 (December 23, 2021): 011001. http://dx.doi.org/10.1088/1748-3190/ac3adf.
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Abstract Interest in emulating the properties of biological muscles that allow for fast adaptability and control in unstructured environments has motivated researchers to develop new soft actuators, often referred to as ‘artificial muscles’. The field of soft robotics is evolving rapidly as new soft actuator designs are published every year. In parallel, recent studies have also provided new insights for understanding biological muscles as ‘active’ materials whose tunable properties allow them to adapt rapidly to external perturbations. This work presents a comparative study of biological muscles and soft actuators, focusing on those properties that make biological muscles highly adaptable systems. In doing so, we briefly review the latest soft actuation technologies, their actuation mechanisms, and advantages and disadvantages from an operational perspective. Next, we review the latest advances in understanding biological muscles. This presents insight into muscle architecture, the actuation mechanism, and modeling, but more importantly, it provides an understanding of the properties that contribute to adaptability and control. Finally, we conduct a comparative study of biological muscles and soft actuators. Here, we present the accomplishments of each soft actuation technology, the remaining challenges, and future directions. Additionally, this comparative study contributes to providing further insight on soft robotic terms, such as biomimetic actuators, artificial muscles, and conceptualizing a higher level of performance actuator named artificial supermuscle. In conclusion, while soft actuators often have performance metrics such as specific power, efficiency, response time, and others similar to those in muscles, significant challenges remain when finding suitable substitutes for biological muscles, in terms of other factors such as control strategies, onboard energy integration, and thermoregulation.
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Sánchez-Pérez, Ana, Francisco Oliva-Paterna, Fátima Amat-Trigo, and Mar Torralva. "Variability in Population Traits of a Sentinel Iberian Fish in a Highly Modified Mediterranean-Type River." Water 13, no. 6 (March 10, 2021): 747. http://dx.doi.org/10.3390/w13060747.
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Human pressures on water resources have been suggested as a driver of biological traits that induce changes in native fish populations. This study highlighted the interplay between environmental stress factors, mostly related to flow regulation, and the longitudinal river gradient in biological traits such as the growth, size structure and somatic condition of a sentinel fish, Luciobarbus sclateri. We found an increase in size-related metrics and somatic condition at population levels associated with downstream reaches, although fragmentation and habitat alteration, flow regime alteration and the abundance of non-native fish were also significantly involved in their variability. Age-related parameters and growth were only explained by flow regime alterations and the abundance of non-native fish species. The high plasticity observed in L. sclateri population traits suggests that this is a key factor in the species adaptability to resist in a strongly altered Mediterranean river basin. However, the interplay of multiple stressors plays an important role in fish population dynamics and could induce complex responses that may be essential for long-term monitoring in sentinel species.
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Ma, Yuqi, Yanqing Shi, Moyu Zhang, Wei Li, Chen Ma, and Yu Guo. "Design and Implementation of an Intelligent Assistive Cane for Visually Impaired People Based on an Edge-Cloud Collaboration Scheme." Electronics 11, no. 14 (July 20, 2022): 2266. http://dx.doi.org/10.3390/electronics11142266.
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Visually impaired people face many inconveniences in daily life, and there are problems such as high prices and single functions in the market of assistance tools for visually impaired people. In this work, we designed and implemented a low-cost intelligent assistance cane, particularly for visually impaired individuals, based on computer vision, sensors, and an edge-cloud collaboration scheme. Obstacle detection, fall detection, and traffic light detection functions have been designed and integrated for the convenience of moving for visually impaired people. We have also designed an image captioning function and object detection function with high-speed processing capability based on an edge-cloud collaboration scheme to improve the user experience. Experiments show that the performance metrics have an aerial obstacle detection accuracy of 92.5%, fall detection accuracy of 90%, and average image retrieval period of 1.124 s. It proves the characteristics of low power consumption, strong real-time performance, adaptability to multiple scenarios, and convenience, which can ensure the safety of visually impaired people when moving and can help them better perceive and understand the surrounding environment.
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Ficara, Annamaria, Francesco Curreri, Giacomo Fiumara, Pasquale De Meo, and Antonio Liotta. "Covert Network Construction, Disruption, and Resilience: A Survey." Mathematics 10, no. 16 (August 14, 2022): 2929. http://dx.doi.org/10.3390/math10162929.
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Covert networks refer to criminal organizations that operate outside the boundaries of the law; they can be mainly classified as terrorist networks and criminal networks. We consider how Social Network Analysis (SNA) is used to analyze such networks in order to attain a greater knowledge of criminal behavior. In fact, SNA allows examining the network structure and functioning by computing relevant metrics and parameters to identify roles, positions, features, and other network functioning that are not otherwise easily discovered at first glance. This is why Law Enforcement Agencies (LEAs) are showing growing interest in SNA, which is also used to identify weak spots and disrupt criminal groups. This paper provides a literature review and a classification of methods and real-case applications of disruption techniques. It considers covert network adaptability to such dismantling attempts, herein referred to as resilience. Critical problems of SNA in criminal studies are discussed, including data collection techniques and the inevitable incompleteness and biases of real-world datasets, with the aim of promoting a new research stream for both dismantling techniques and data collection issues.
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Wang, Hao, Xiaoqing Xian, Yujuan Gu, Cristina Castañé, Judit Arnó, Suran Wu, Fanghao Wan, Wanxue Liu, Guifen Zhang, and Yibo Zhang. "Similar Bacterial Communities among Different Populations of a Newly Emerging Invasive Species, Tuta absoluta (Meyrick)." Insects 13, no. 3 (March 3, 2022): 252. http://dx.doi.org/10.3390/insects13030252.
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Microorganisms in the guts of insects enhance the adaptability of their hosts with different lifestyles, or those that live in different habitats. Tuta absoluta is an invasive pest that is a serious threat to tomato production in China. It has quickly spread and colonized Xinjiang, Yunnan and other provinces and regions. We used Illumina HiSeq next generation sequencing of the 16S rRNA gene to study and analyze the composition and diversity of the gut microbiota of three geographical populations of T. absoluta. At the phylum level, the most common bacteria in T. absoluta across all three geographical populations were Proteobacteria and Firmicutes. An uncultured bacterium in the Enterobacteriaceae was the dominant bacterial genus in the T. absoluta gut microbiotas. There were no significant differences in alpha diversity metrics among the Spanish, Yunnan and Xinjiang populations. The structures of the gut microbiota of the three populations were similar based on PCoA and NMDS results. The results confirmed that the microbial structures of T. absoluta from different regions were similar.
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Kędziorek, Justyna, and Michalina Błażkiewicz. "Nonlinear Measures to Evaluate Upright Postural Stability: A Systematic Review." Entropy 22, no. 12 (November 30, 2020): 1357. http://dx.doi.org/10.3390/e22121357.
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Conventional biomechanical analyses of human movement have been generally derived from linear mathematics. While these methods can be useful in many situations, they fail to describe the behavior of the human body systems that are predominately nonlinear. For this reason, nonlinear analyses have become more prevalent in recent literature. These analytical techniques are typically investigated using concepts related to variability, stability, complexity, and adaptability. This review aims to investigate the application of nonlinear metrics to assess postural stability. A systematic review was conducted of papers published from 2009 to 2019. Databases searched were PubMed, Google Scholar, Science-Direct and EBSCO. The main inclusion consisted of: Sample entropy, fractal dimension, Lyapunov exponent used as nonlinear measures, and assessment of the variability of the center of pressure during standing using force plate. Following screening, 43 articles out of the initial 1100 were reviewed including 33 articles on sample entropy, 10 articles on fractal dimension, and 4 papers on the Lyapunov exponent. This systematic study shows the reductions in postural regularity related to aging and the disease or injures in the adaptive capabilities of the movement system and how the predictability changes with different task constraints.
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Ma, Xiaoyan, and Hong Fang. "Study on the Relationship between Climate and National Frailty." BCP Social Sciences & Humanities 19 (August 30, 2022): 229–35. http://dx.doi.org/10.54691/bcpssh.v19i.1609.
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In consequence of climate change, a country is faced with a series of economic, social and environmental problems. Which has affected the social and government stability in a country. First, in order to evaluate a country's fragility, we established a set of metrics including political economy, resources and society. Using space vector synthesis, we could calculate the score of vulnerability index. According to the principle of Natural fracture classification, finding that (0,0.37], (0.37,0.69], (0.69,1) is divided to stable, fragile and extreme state. Next, we selected Somalia, analyzing its' climate characters: On the one hand, droughts lead to water resources reducing, on the other hand, floods lead to city submerging. Assumption that two situations, including "adequate water resources" and "well-organized government ",compared with the present situation ,we concluded that these effect contributes to less vulnerability. Finally, we studied the adaptability of the model. In terms of a city, our model only needs to be adjusted in certain aspects. For a continent, we use the weighted average of the proportions of the countries in the continents and their vulnerabilities as the state's vulnerability index to improve our model.
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Dr. P. Prabhavathy, Nagalakshmi Vallabhaneni,. "The Analysis of the Impact of Yoga on Healthcare and Conventional Strategies for Human Pose Recognition." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 6 (April 5, 2021): 1772–83. http://dx.doi.org/10.17762/turcomat.v12i6.4032.
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Human pose estimation is a profound, established computer vision issue that has uncovered numerous past difficulties. Breaking down human exercise is advantageous in multiple fields like surveillance, biometrics, and many healthcare applications. Workout with yoga poses is famous these days since yoga activities can expand adaptability and muscular quality, and the respiration procedure will be improvised. The yoga postures evaluation is hard to check, so specialists will most likely be unable to benefit from the exercises ultimately. IoT-based yoga frameworks are required for individuals who need to rehearse Yoga at home. A few studies are recommended camera-oriented or wearable gadget-oriented yoga posture finding strategies with more precision. Nonetheless, camera-based plans have security and privacy issues, and the wearable device-based methods are illogical in the earlier applications. To build such systems, one must have a strong foundation and current research in pose estimation. In this paper, first, the impact of Yoga on humans with various stress levels is analysed on the real-time data. Second, the comprehensive review of yoga posture recognition systems from machine learning to deep learning strategies and evaluation metrics discussed
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Yin, Yuhua, Zhiliang Liu, Junhao Zhang, Enrico Zio, and Mingjian Zuo. "An Adaptive Sampling Framework for Life Cycle Degradation Monitoring." Sensors 23, no. 2 (January 14, 2023): 965. http://dx.doi.org/10.3390/s23020965.
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Data redundancy and data loss are relevant issues in condition monitoring. Sampling strategies for segment intervals can address these at the source, but do not receive the attention they deserve. Currently, the sampling methods in relevant research lack sufficient adaptability to the condition. In this paper, an adaptive sampling framework of segment intervals is proposed, based on the summary and improvement of existing problems. The framework is implemented to monitor mechanical degradation, and experiments are implemented on simulation data and real datasets. Subsequently, the distributions of the samples collected by different sampling strategies are visually presented through a color map, and five metrics are designed to assess the sampling results. The intuitive and numerical results show the superiority of the proposed method in comparison to existing methods, and the results are closely related to data status and degradation indicators. The smaller the data fluctuation and the more stable the degradation trend, the better the result. Furthermore, the results of the objective physical indicators are obviously better than those of the feature indicators. By addressing existing problems, the proposed framework opens up a new idea of predictive sampling, which significantly improves the degradation monitoring.
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Nguyen, Hoang Phuong, Nguyen Dang Khoa Pham, and Viet Duc Bui. "Technical-Environmental Assessment of Energy Management Systems in Smart Ports." International Journal of Renewable Energy Development 11, no. 4 (June 6, 2022): 889–901. http://dx.doi.org/10.14710/ijred.2022.46300.
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Shipping is facing huge pressure problems in this 21st century such as climate change and environmental pollution and the depletion of energy resources. Seaports are an important component of the shipping industry architecture. Although there is no common solution, seaports around the globe face the same challenge. Challenges raised include difficulties in integrating new technology into automation, traffic congestion, harmonizing residential communities around the port, quantifying and reducing CO2 emissions as well as planning for the energy transition. In addition, improving the adaptability of the port infrastructure in the context of increased pressure from market demand, labor shortage, and escalating prices should be considered. In that context, a smart port was born as a necessity. However, the understanding of smart ports is very limited. This review examines the recently published smart port literature to clarify the common concepts of smart ports and their development progress on the way to building a sustainable seaport ecosystem. Although smart port metrics and key port performance metrics are organized around four key performance areas including operations, environment, energy, and safety. However, a comprehensive review of all four key areas is very broad and difficult to cover in a review article. Therefore, this work focuses on analyzing and discussing the approaches and applications of the technology in smart port energy management systems. Our research has shown that different smart port founding perspectives play a decisive role in technology approaches to building a port energy management system including optimizing algorithms for energy consumption, balancing demand and energy production, and comprehensively integrating renewable energy. New findings in this study contribute to the elucidation of smart port concepts based on improving energy use and management efficiency with innovative technologies in the context of sustainable development of the shipping industry.
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Christopher, Obah Amechi, and Amah Edwinah. "Organizational Culture and Corporate Performance: A Review." Global Academic Journal of Economics and Business 4, no. 5 (October 26, 2022): 152–62. http://dx.doi.org/10.36348/gajeb.2022.v04i05.001.
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The study was to examine the relationship between organizational culture and corporate performance. It examines the way organizational culture influences corporate performance in companies. The study employs four elements of organizational culture mode (a) involvement (b) consistency (c) adaptability, and (d) mission. The establishment and upkeep of a successful organizational culture within the organization depends on the four components of the organizational culture model. The specific objective was to: evaluate the relationship between involvement and corporate performance and to assess the relationship between mission and corporate performance. The Denison model was used to examine the operational metrics for measuring organizational culture and corporate success. The research shows a statistically significant link between business performance and organizational culture. Additionally, engagement, adaptability, consistency, and mission impact the organization's non-financial performance. While training demonstrates the strongest association with organizational culture, involvement is the censorious aspect affecting how organizational culture affects corporate performance. This study concluded that lack of effective organizational culture is a primary cause of poor performance and productivity in the corporate organization. The relevance of an effective organizational culture must therefore be understood by company managers if they are to increase performance and productivity in the corporate setting. It was recommended among others that, there should be training for managers and employees on some principles that are important for effective performance. The conceptual underpinning for the investigation was provided by the Denison organizational culture model. The finding of the study included a well-defined mission that attribute to developing shared understanding between employees and managers and employee-focused leadership that contributed to motivating employees. The well-being of society through self-regulatory corporate social responsibility was one of the core corporate value findings. The finding single out in this study cloud have prospects for economic development in the local economy and may subscribe to social change with strategies business and improve the life standards of employees and the local community.
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Pérez-Castán, Javier A., Luis Pérez Sanz, Marta Fernández-Castellano, Tomislav Radišić, Kristina Samardžić, and Ivan Tukarić. "Learning Assurance Analysis for Further Certification Process of Machine Learning Techniques: Case-Study Air Traffic Conflict Detection Predictor." Sensors 22, no. 19 (October 10, 2022): 7680. http://dx.doi.org/10.3390/s22197680.
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Designing and developing artificial intelligence (AI)-based systems that can be trusted justifiably is one of the main issues aviation must face in the coming years. European Union Aviation Safety Agency (EASA) has developed a user guide that could be potentially transformed as means of compliance for future AI-based regulation. Designers and developers must understand how the learning assurance process of any machine learning (ML) model impacts trust. ML is a narrow branch of AI that uses statistical models to perform predictions. This work deals with the learning assurance process for ML-based systems in the field of air traffic control. A conflict detection tool has been developed to identify separation infringements among aircraft pairs, and the ML algorithm used for classification and regression was extreme gradient boosting. This paper analyses the validity and adaptability of EASA W-shaped methodology for ML-based systems. The results have identified the lack of the EASA W-shaped methodology in time-dependent analysis, by showing how time can impact ML algorithms designed in the case where no time requirements are considered. Another meaningful conclusion is, for systems that depend highly on when the prediction is made, classification and regression metrics cannot be one-size-fits-all because they vary over time.
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Rahman, MD Rashed, Kehinde Adedara, and Ashwin Ashok. "Enabling Multiple Access in Visible Light Communication Using Liquid Crystal Displays: A Proof-of-Concept Study." Electronics 9, no. 5 (May 16, 2020): 826. http://dx.doi.org/10.3390/electronics9050826.
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The directionality of optical signals provides an opportunity for efficient space reuse of optical links in visible light communication (VLC). Space reuse in VLC can enable multiple-access communication from multiple light emitting transmitters. Traditional VLC system design using photo-receptors requires at least one receiving photodetector element for each light emitter, thus constraining VLC to always require a light-emitter to light-receptor element pair. In this paper, we propose, design and evaluate a novel architecture for VLC that can enable multiple-access reception using a photoreceptor receiver that uses only a single photodiode. The novel design includes a liquid-crystal-display (LCD) based shutter system that can be automated to control and enable selective reception of light beams from multiple transmitters. We evaluate the feasibility of multiple access on a single photodiode from two light emitting diode (LED) transmitters and the performance of the communication link using bit-error-rate (BER) and packet-error-rate (PER) metrics. Our experiment and trace based evaluation through proof-of-concept implementation reveals the feasibility of multiple LED reception on a single photodiode. We further evaluate the system in controlled mobile settings to verify the adaptability of the receiver when the LED transmitter changes position.
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Wang, Huiping, and Yi Wang. "Estimating per Capita Primary Energy Consumption Using a Novel Fractional Gray Bernoulli Model." Sustainability 14, no. 4 (February 20, 2022): 2431. http://dx.doi.org/10.3390/su14042431.
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On the basis of the available gray models, a new fractional gray Bernoulli model (GFGBM (1,1,tα)) is proposed to predict the per capita primary energy consumption (PPEC) of major economies in the world. First, this paper introduces the modeling mechanism and characteristics of the GFGBM (1,1,tα). The new model can be converted to other gray models through parameter changes, so the new model has strong adaptability. Second, the predictive performance of the GFGBM (1,1,tα) is assessed by the four groups of PPEC. The optimal parameters of the model are solved by the moth flame optimization and gray wolf optimization algorithms, and the prediction results of the models are evaluated by two error metrics. The results show that the GFGBM (1,1,tα) is more feasible and effective than the other tested gray models. Third, the GFGBM (1,1,tα) is applied to forecast the PPEC of India, the world, the Organization for Economic Cooperation and Development (OECD) countries, and non-OECD countries over the next 5 years. The forecasting results indicate that the PPEC of the four economies will increase by 5.36 GJ, 42.09 GJ, 5.75 GJ, and 29.22 GJ, respectively, an increase of 51.53%, 55.61%, 3.22%, and 53.41%, respectively.
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Ji, Hao, and Yan Jin. "Evaluating the learning and performance characteristics of self-organizing systems with different task features." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 35, no. 4 (November 2021): 404–22. http://dx.doi.org/10.1017/s089006042100024x.
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AbstractSelf-organizing systems (SOS) are developed to perform complex tasks in unforeseen situations with adaptability. Predefining rules for self-organizing agents can be challenging, especially in tasks with high complexity and changing environments. Our previous work has introduced a multiagent reinforcement learning (RL) model as a design approach to solving the rule generation problem of SOS. A deep multiagent RL algorithm was devised to train agents to acquire the task and self-organizing knowledge. However, the simulation was based on one specific task environment. Sensitivity of SOS to reward functions and systematic evaluation of SOS designed with multiagent RL remain an issue. In this paper, we introduced a rotation reward function to regulate agent behaviors during training and tested different weights of such reward on SOS performance in two case studies: box-pushing and T-shape assembly. Additionally, we proposed three metrics to evaluate the SOS: learning stability, quality of learned knowledge, and scalability. Results show that depending on the type of tasks; designers may choose appropriate weights of rotation reward to obtain the full potential of agents’ learning capability. Good learning stability and quality of knowledge can be achieved with an optimal range of team sizes. Scaling up to larger team sizes has better performance than scaling downwards.