scholarly journals Towards a Generalised Metaheuristic Model for Continuous Optimisation Problems

Mathematics ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. 2046
Author(s):  
Jorge M. Cruz-Duarte ◽  
José C. Ortiz-Bayliss ◽  
Iván Amaya ◽  
Yong Shi ◽  
Hugo Terashima-Marín ◽  
...  
Keyword(s):  
Building Blocks ◽  
Proof Of Concept ◽  
Proposed Model ◽  
The Future ◽  
Simple Heuristics

Metaheuristics have become a widely used approach for solving a variety of practical problems. The literature is full of diverse metaheuristics based on outstanding ideas and with proven excellent capabilities. Nonetheless, oftentimes metaheuristics claim novelty when they are just recombining elements from other methods. Hence, the need for a standard metaheuristic model is vital to stop the current frenetic tendency of proposing methods chiefly based on their inspirational source. This work introduces a first step to a generalised and mathematically formal metaheuristic model, which can be used for studying and improving them. This model is based on a scheme of simple heuristics, which perform as building blocks that can be modified depending on the application. For this purpose, we define and detail all components and concepts of a metaheuristic (i.e., its search operators), such as heuristics. Furthermore, we also provide some ideas to take into account for exploring other search operator configurations in the future. To illustrate the proposed model, we analyse search operators from four well-known metaheuristics employed in continuous optimisation problems as a proof-of-concept. From them, we derive 20 different approaches and use them for solving some benchmark functions with different landscapes. Data show the remarkable capability of our methodology for building metaheuristics and detecting which operator to choose depending on the problem to solve. Moreover, we outline and discuss several future extensions of this model to various problem and solver domains.

PoGB-Pred: Prediction of Antifreeze Proteins Sequences using Amino Acid Composition with Feature Selection followed by a Sequential based Ensemble Approach

2020 ◽  
Vol 15 ◽  
Author(s):  
Affan Alim ◽  
Abdul Rafay ◽  
Imran Naseem
Keyword(s):  
Amino Acid ◽  
Dimension Reduction ◽  
Protein Identification ◽  
Cold Water ◽  
Genomic Sequence ◽  
Sequence Data ◽  
Antifreeze Proteins ◽  
Building Blocks ◽  
Gradient Boosting ◽  
Proposed Model

Background: Proteins contribute significantly in every task of cellular life. Their functions encompass the building and repairing of tissues in human bodies and other organisms. Hence they are the building blocks of bones, muscles, cartilage, skin, and blood. Similarly, antifreeze proteins are of prime significance for organisms that live in very cold areas. With the help of these proteins, the cold water organisms can survive below zero temperature and resist the water crystallization process which may cause the rupture in the internal cells and tissues. AFP’s have attracted attention and interest in food industries and cryopreservation. Objective: With the increase in the availability of genomic sequence data of protein, an automated and sophisticated tool for AFP recognition and identification is in dire need. The sequence and structures of AFP are highly distinct, therefore, most of the proposed methods fail to show promising results on different structures. A consolidated method is proposed to produce the competitive performance on highly distinct AFP structure. Methods: In this study, we propose to use machine learning-based algorithms Principal Component Analysis (PCA) followed by Gradient Boosting (GB) for antifreeze protein identification. To analyze the performance and validation of the proposed model, various combinations of two segments composition of amino acid and dipeptide are used. PCA, in particular, is proposed to dimension reduction and high variance retaining of data which is followed by an ensemble method named gradient boosting for modelling and classification. Results: The proposed method obtained the superfluous performance on PDB, Pfam and Uniprot dataset as compared with the RAFP-Pred method. In experiment-3, by utilizing only 150 PCA components a high accuracy of 89.63 was achieved which is superior to the 87.41 utilizing 300 significant features reported for the RAFP-Pred method. Experiment-2 is conducted using two different dataset such that non-AFP from the PISCES server and AFPs from Protein data bank. In this experiment-2, our proposed method attained high sensitivity of 79.16 which is 12.50 better than state-of-the-art the RAFP-pred method. Conclusion: AFPs have a common function with distinct structure. Therefore, the development of a single model for different sequences often fails to AFPs. A robust results have been shown by our proposed model on the diversity of training and testing dataset. The results of the proposed model outperformed compared to the previous AFPs prediction method such as RAFP-Pred. Our model consists of PCA for dimension reduction followed by gradient boosting for classification. Due to simplicity, scalability properties and high performance result our model can be easily extended for analyzing the proteomic and genomic dataset.

Forecast of the efficiency confidence interval of decision-making units in data envelopment analysis

2020 ◽  
Vol 33 (02) ◽  
pp. 431-445
Author(s):  
Azarnoosh Kafi ◽  
Behrouz Daneshian ◽  
Mohsen Rostamy-Malkhalifeh ◽  
Mohsen Rostamy-Malkhalifeh
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Confidence Interval ◽  
Data Envelopment ◽  
Data Set ◽  
Interval Model ◽  
Time Period ◽  
Proposed Model ◽  
The Future ◽  
Decision Making Units

Data Envelopment Analysis (DEA) is a well-known method for calculating the efficiency of Decision-Making Units (DMUs) based on their inputs and outputs. When the data is known and in the form of an interval in a given time period, this method can calculate the efficiency interval. Unfortunately, DEA is not capable of forecasting and estimating the efficiency confidence interval of the units in the future. This article, proposes a efficiency forecasting algorithm along with 95% confidence interval to generate interval data set for the next time period. What’s more, the manager’s opinion inserts and plays its role in the proposed forecasting model. Equipped with forecasted data set and with respect to data set from previous periods, the efficiency for the future period can be forecasted. This is done by proposing a proposed model and solving it by the confidence interval method. The proposed method is then implemented on the data of an automotive industry and, it is compared with the Monte Carlo simulation methods and the interval model. Using the results, it is shown that the proposed method works better to forecast the efficiency confidence interval. Finally, the efficiency and confidence interval of 95% is calculated for the upcoming period using the proposed model.

scholarly journals An economic analysis of ransomware and its welfare consequences

2020 ◽  
Vol 7 (3) ◽  
pp. 190023
Author(s):  
J. Hernandez-Castro ◽  
A. Cartwright ◽  
E. Cartwright
Keyword(s):  
Economic Analysis ◽  
Price Discrimination ◽  
Proof Of Concept ◽  
Welfare Costs ◽  
Pilot Survey ◽  
Uniform Pricing ◽  
The Future ◽  
Welfare Consequences ◽  
New Form

We present in this work an economic analysis of ransomware, a relatively new form of cyber-enabled extortion. We look at how the illegal gains of the criminals will depend on the strategies they use, examining uniform pricing and price discrimination. We also explore the welfare costs to society of such strategies. In addition, we present the results of a pilot survey which demonstrate proof of concept in evaluating the costs of ransomware attacks. We discuss at each stage whether the different strategies we analyse have been encountered already in existing malware, and the likelihood of them being implemented in the future. We hope this work will provide some useful insights for predicting how ransomware may evolve in the future.

scholarly journals Facing the Future: A Blueprint for a Resilient and Equitable Society: Connecting the Functional Building Blocks

2018 ◽  
Vol 2 (1) ◽  
pp. 1-37
Author(s):  
F. Bocken ◽  
E. Brennan ◽  
N. Claessens ◽  
D. Claeys ◽  
S. Debeaussaert ◽  
...  
Keyword(s):  
Political Representation ◽  
Full Range ◽  
Building Blocks ◽  
Bank Loans ◽  
Ageing Population ◽  
Individual Level ◽  
The Future ◽  
Range Of Functions ◽  
The Individual ◽  
The Unemployed

Abstract Contemporary society is plagued by a number of issues and inconsistencies on both an environmental and a socio-economic level. Reliance on bank loans forces debtors to seek means to repay their debts, thus facilitating the current boundless economic growth in which long-term, environmental considerations typically come second. On the individual level, since virtually nothing is free, everyone has to ensure his or her own livelihood, mostly in the form of wage labour. For fear of poverty, the unemployed must adjust to the needs of the job market and risk not being able to fully explore their potential. Other socio-economic groups also face stigmatisation, and inequality is rampant as a result of the pervasive market-based pricing mechanisms. In view of these issues, it seems unjustified to accept these terms and conditions in the future, especially since the West has to cater to its ageing population and the ensuing pressure this will exert on welfare systems. Therefore, as a transdisciplinary team assisted by various experts and armed with insights from a wide <target target-type="page-num" id="p-2"/>variety of sources, we propose an alternative model of society based on the values of fairness, inclusion and transparency, with the goal of developing a representative systems map for a future, resilient and equitable society. The exact workings of this society are captured by several building blocks, which together endeavour to cover the full range of functions and responsibilities associated with society today, and jointly promote democratisation while guaranteeing equal political representation for all members of society.

scholarly journals A Novel Approach for Forest Fragmentation Susceptibility Mapping and Assessment: A Case Study from the Indian Himalayan Region

2021 ◽  
Vol 13 (20) ◽  
pp. 4090
Author(s):  
Amit Kumar Batar ◽  
Hideaki Shibata ◽  
Teiji Watanabe
Keyword(s):  
Forest Fragmentation ◽  
Integrated Model ◽  
Himalayan Region ◽  
Geographical Information ◽  
Susceptibility Map ◽  
Forest Landscape ◽  
Indian Himalayan Region ◽  
Proposed Model ◽  
Causative Factors ◽  
The Future

An estimation of where forest fragmentation is likely to occur is critically important for improving the integrity of the forest landscape. We prepare a forest fragmentation susceptibility map for the first time by developing an integrated model and identify its causative factors in the forest landscape. Our proposed model is based upon the synergistic use of the earth observation data, forest fragmentation approach, patch forests, causative factors, and the weight-of-evidence (WOE) method in a Geographical Information System (GIS) platform. We evaluate the applicability of the proposed model in the Indian Himalayan region, a region of rich biodiversity and environmental significance in the Indian subcontinent. To obtain a forest fragmentation susceptibility map, we used patch forests as past evidence of completely degraded forests. Subsequently, we used these patch forests in the WOE method to assign the standardized weight value to each class of causative factors tested by the Variance Inflation Factor (VIF) method. Finally, we prepare a forest fragmentation susceptibility map and classify it into five levels: very low, low, medium, high, and very high and test its validity using 30% randomly selected patch forests. Our study reveals that around 40% of the study area is highly susceptible to forest fragmentation. This study identifies that forest fragmentation is more likely to occur if proximity to built-up areas, roads, agricultural lands, and streams is low, whereas it is less likely to occur in higher altitude zones (more than 2000 m a.s.l.). Additionally, forest fragmentation will likely occur in areas mainly facing south, east, southwest, and southeast directions and on very gentle and gentle slopes (less than 25 degrees). This study identifies Himalayan moist temperate and pine forests as being likely to be most affected by forest fragmentation in the future. The results suggest that the study area would experience more forest fragmentation in the future, meaning loss of forest landscape integrity and rich biodiversity in the Indian Himalayan region. Our integrated model achieved a prediction accuracy of 88.7%, indicating good accuracy of the model. This study will be helpful to minimize forest fragmentation and improve the integrity of the forest landscape by implementing forest restoration and reforestation schemes.

scholarly journals Site-Selective [2+2+n] Cycloadditions for Rapid, Scalable Access to Alkynylated Polycyclic Aromatic Hydrocarbons

2019 ◽  
Author(s):  
Gavin R. Kiel ◽  
Harrison Bergman ◽  
T. Don Tilley
Keyword(s):  
Polycyclic Aromatic Hydrocarbons ◽  
Aromatic Hydrocarbons ◽  
Structural Complexity ◽  
Building Blocks ◽  
Synthetic Methods ◽  
Proof Of Concept ◽  
Site Selectivity ◽  
Polycyclic Aromatic ◽  
Site Selective ◽  
Nanometer Regime

Polycyclic aromatic hydrocarbons (PAHs) are attractive synthetic building blocks for more complex conjugated nanocarbons, but their use for this purpose requires appreciable quantities of a PAH with reactive functional groups. Despite tremendous recent advances, most synthetic methods cannot satisfy these demands. Here we present a general and scalable [2+2+n] (n = 1 or 2) cycloaddition strategy to access PAHs that are decorated with synthetically versatile alkynyl groups and its application to seven structurally diverse PAH ring systems (thirteen new alkynylated PAHs in total). The critical discovery is the site-selectivity of an Ir-catalyzed [2+2+2] cycloaddition, which preferentially cyclizes tethered diyne units with preservation of other (peripheral) alkynyl groups. The potential for generalization of the site-selectivity to other [2+2+n] reactions is demonstrated by identification of a Cp<sub>2</sub>Zr-mediated [2+2+1] / metallacycle transfer sequence for synthesis of an alkynylated, selenophene-annulated PAH. The new PAHs are excellent synthons for macrocyclic conjugated nanocarbons. As a proof of concept, four were subjected to Mo catalysis to afford large, PAH-containing arylene ethylene macrocycles, which possess a range of cavity sizes reaching well into the nanometer regime. More generally, this work is a demonstration of how site-selective reactions can be harnessed to rapidly build up structural complexity in a practical, scalable fashion.

Towards Implementing a Collaborative Manufacturing Cloud Platform: Experimenting Testbeds Aiming Asset Efficiency

2020 ◽  
Author(s):  
Nuno Santos ◽  
Paula Monteiro ◽  
Francisco Morais ◽  
Jaime Pereira ◽  
Daniel Dias ◽  
...  
Keyword(s):  
Supply Chain ◽  
Internet Of Things ◽  
Proof Of Concept ◽  
Cloud Platform ◽  
Industrial Internet Of Things ◽  
Manufacturing Environment ◽  
Collaborative Manufacturing ◽  
Manufacturing Operations ◽  
Industrial Internet ◽  
The Future

Abstract Developing Industrial Internet of Things (IIoT) systems requires addressing challenges that range from acquiring data at the level of the shopfloor, integrated at the edge level and managing it at the cloud level. Managing manufacturing operations at the cloud level arose the opportunity for extending decisions to entities of the supply chain in a collaborative way. Not only it has arisen many challenges due to several interoperability needs; but also in properly defining an effective way to take advantage of the available data, leading to Industrial Digital Thread (IDT) and Asset Efficiency (AE) implementing. This paper discusses implementation concerns for a collaborative manufacturing environment in an IIoT system in order to monitor equipment’s AE. Each concern was addressed in a separate proof of concept testbed. The demonstration is based in a project for the IIoT domain called PRODUTECH-SIF (Solutions for the Industry of the Future).

Identify project corporate behavioral risks to support long-term sustainable cooperative partnerships.

2021 ◽  
Author(s):  
marco nunes ◽  
Antônio José de Abreu Pina
Keyword(s):  
Social Network ◽  
Project Management ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Building Blocks ◽  
Two Dimensions ◽  
Corporate Behavior ◽  
Proposed Model ◽  
Project Lifecycle

Projects can be seen as the crucial building blocks whereby organizations execute and implement their short, and long-term strategic vision. Projects are thought to solve problems, drive change, satisfy unique needs, add value, or exploit opportunities, just to name a few. In order to successful deliver projects, project management tools and techniques are applied throughout a project´s lifecycle, essentially to efficiently and in a timely manner, identify and manage project risks. However, according to latest reviewed literature, projects keep failing at an impressive rate. Although research in the project management field argues that such failure rate is due to a huge variety of reasons, it highlights particular importance to a still underexplored and not quite well understood (regarding how it emerges and evolves) risk type, that may lead projects to failure. This risk type, called as corporate behavioral risks, usually emerge, and evolve as organizations work together across a finite period of time (for example, across a project lifecycle) to deliver projects, and is characterized by the mix of countless formal and informal dynamic interactions between the different elements that constitute the different organizations. Understanding the extent to which such corporate behavior influences project´s outcomes, is a breakthrough of high importance that positively impacts two dimensions; first, enables organizations that deliver projects (but not only), to increase the chances of project success, which in turn is a driver of sustainable business, because it allows the development and implementation of effective, and timely corrective measures to project´s tasks and activities, and second, it contributes to the scientific community (on the organizations field), to generate valuable and actionable new knowledge regarding the emergence and evolution of such cooperative risks, which can lead to the development of new theories and approaches on how to manage them. In this work, we propose a heuristic model to efficiently identify and analyze how corporate behavioral risks may influence project´s outcomes. The proposed model in this work, lays its foundations on four fundamental fields ((1) project management, (2) risk management, (3) corporate behavior, and (4) social network analysis), and will quantitatively measure four critical project social networks ((1) communication, (2) problem-solving, (3) advice, and (4) trust) that usually emerge as projects are being delivered, by applying the theory of social network analysis (SNA), more concretely, SNA centrality metrics. The proposed model in this work is supported with a case study to illustrate its implementation across a project lifecycle, and how organizations can benefit from its application.

Use of 3-(Pentafluorosulfanyl)phenol to Access to Advanced Substituted Pentafluorosulfanylphenol/anisole: Application to the Synthesis of 2-(Arylpentafluorosulfanyl)indanedione

2021 ◽  
Vol 18 ◽  
Author(s):  
Antoine Michaut ◽  
Sabrina Quatrevaux ◽  
Laurence Queguiner ◽  
Sandrine Gaurrand ◽  
Jérôme Guillemont
Keyword(s):  
Carboxylic Acid ◽  
Building Blocks ◽  
The Future

Abstract: The synthesis of advanced substituted 3-pentafluorosulfanylphenol/anisole was accomplished starting from the easy to access and commercially available 3-pentafluorosulfanylphenol. These products bear diverse substitutions such as ester, aldehyde, halogens, alcohol, nitrile and carboxylic acid and could be in the future used as high value building blocks for the synthesis of various scaffolds. For our part, this intermediate had been used to synthetize a library of 2-arylindadiones substituted by a pentafluorosulfanyl group.

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