Detection of iOS Malware apps based on Significant Services Identification using Borda count

2021 ◽  
Author(s):  
Neetu Sardana ◽  
Arpita Jadhav Bhatt
Keyword(s):  
Borda Count

Aiming for a Standardized Protocol for Preparing a Process Green Synthesis Report and for Ranking Multiple Synthesis Plans to a Common Target Product

2019 ◽  
Author(s):  
john andraos
Keyword(s):  
Green Synthesis ◽  
Block Diagram ◽  
Computational Method ◽  
Borda Count ◽  
Target Product ◽  
Material Efficiency ◽  
Synthesis Report ◽  
Common Target ◽  
Greenness Index ◽  
Multiple Synthesis

This paper proposes a standardized format for the preparation of process green synthesis reports that can be applied to chemical syntheses of active pharmaceutical ingredients (APIs) of importance to the pharmaceutical industry. Such a report is comprised of the following eight sections: a synthesis scheme, a synthesis tree, radial pentagons and step E-factor breakdowns for each reaction step, a tabular summary of key material efficiency step and overall metrics for a synthesis plan, a mass process block diagram, an energy consumption audit based on heating and cooling reaction and auxiliary solvents, a summary of environmental and safety-hazard impacts based on organic solvent consumption using the Rowan solvent greenness index, and a cycle time process schedule. Illustrative examples of process green synthesis reports are given for the following pharmaceuticals: 5-HT2B and 5-HT7 receptors antagonist (Astellas Pharma), brivanib (Bristol-Myers Squibb), and orexin receptor agonist (Merck). Methods of ranking synthesis plans to a common target product are also discussed using 6 industrial synthesis plans of apixaban (Bristol-Myers Squibb) as a working example. The Borda count method is suggested as a facile and reliable computational method for ranking multiple synthesis plans to a common target product using the following 4 attributes obtained from a process green synthesis report: process mass intensity, mass of sacrificial reagents used per kg of product, input enthalpic energy for solvents, and Rowan solvent greenness index for organic solvents.<br>

scholarly journals Aiming for a standardized protocol for preparing a process green synthesis report and for ranking multiple synthesis plans to a common target product

2019 ◽  
Vol 8 (1) ◽  
pp. 787-801
Author(s):  
John Andraos
Keyword(s):  
Green Synthesis ◽  
Block Diagram ◽  
Computational Method ◽  
Borda Count ◽  
Target Product ◽  
Material Efficiency ◽  
Synthesis Report ◽  
Common Target ◽  
Greenness Index ◽  
Multiple Synthesis

Abstract This paper proposes a standardized format for the preparation of process green synthesis reports that can be applied to chemical syntheses of active pharmaceutical ingredients (APIs) of importance to the pharmaceutical industry. Such a report is comprised of the following eight sections: a synthesis scheme, a synthesis tree, radial pentagons and step E-factor breakdowns for each reaction step, a tabular summary of key material efficiency step and overall metrics for a synthesis plan, a mass process block diagram, an energy consumption audit based on heating and cooling reaction and auxiliary solvents, a summary of environmental and safety-hazard impacts based on organic solvent consumption using the Rowan solvent greenness index, and a cycle time process schedule. Illustrative examples of process green synthesis reports are given for the following pharmaceuticals: 5-HT2B and 5-HT7 receptors antagonist (Astellas Pharma), brivanib (Bristol-Myers Squibb), and orexin receptor agonist (Merck). Methods of ranking synthesis plans to a common target product are also discussed using 6 industrial synthesis plans of apixaban (Bristol-Myers Squibb) as a working example. The Borda count method is suggested as a facile and reliable computational method for ranking multiple synthesis plans to a common target product using the following 4 attributes obtained from a process green synthesis report: process mass intensity, mass of sacrificial reagents used per kg of product, input enthalpic energy for solvents, and Rowan solvent greenness index for organic solvents.

Exploring the Uncertainty Space of Ensemble Classifiers in Face Recognition

2015 ◽  
Vol 29 (03) ◽  
pp. 1556002 ◽  
Author(s):  
Juan Luis Fernández-Martínez ◽  
Ana Cernea
Keyword(s):  
Face Recognition ◽  
Nearest Neighbor ◽  
Learning Algorithm ◽  
Majority Voting ◽  
Borda Count ◽  
Discrete Wavelet ◽  
Final Decision ◽  
Ensemble Classifiers ◽  
Classification Problems ◽  
Uncertainty Space

In this paper, we present a supervised ensemble learning algorithm, called SCAV1, and its application to face recognition. This algorithm exploits the uncertainty space of the ensemble classifiers. Its design includes six different nearest-neighbor (NN) classifiers that are based on different and diverse image attributes: histogram, variogram, texture analysis, edges, bidimensional discrete wavelet transform and Zernike moments. In this approach each attribute, together with its corresponding type of the analysis (local or global), and the distance criterion (p-norm) induces a different individual NN classifier. The ensemble classifier SCAV1 depends on a set of parameters: the number of candidate images used by each individual method to perform the final classification and the individual weights given to each individual classifier. SCAV1 parameters are optimized/sampled using a supervised approach via the regressive particle swarm optimization algorithm (RR-PSO). The final classifier exploits the uncertainty space of SCAV1 and uses majority voting (Borda Count) as a final decision rule. We show the application of this algorithm to the ORL and PUT image databases, obtaining very high and stable accuracies (100% median accuracy and almost null interquartile range). In conclusion, exploring the uncertainty space of ensemble classifiers provides optimum results and seems to be the appropriate strategy to adopt for face recognition and other classification problems.

Rank Level Fusion

2013 ◽  
pp. 69-79
Keyword(s):  
Information Aggregation ◽  
Regression Method ◽  
Borda Count ◽  
Fusion Method ◽  
Advantages And Disadvantages ◽  
Current State ◽  
Fusion Methods ◽  
Logistic Regression Method ◽  
Level Fusion ◽  
Voting Method

Rank level fusion is one of the after matching fusion methods used in multibiometric systems. The problem of rank information aggregation has been raised before in various fields. This chapter extensively discusses the rank level fusion methodology, starting with existing literature from the last decade in different application scenarios. Several approaches of existing biometric rank level fusion methods, such as plurality voting method, highest rank method, Borda count method, logistic regression method, and quality-based rank fusion method, are discussed along with their advantages and disadvantages in the context of the current state-of-the-art in the discipline.

Multicriteria Models for E-Health Service Evaluation

2011 ◽  
pp. 1976-1993
Author(s):  
Gulcin Buyukozkan ◽  
Ufuk Bilsel
Keyword(s):  
Health Service ◽  
Health Services ◽  
Information Technologies ◽  
Healthcare Services ◽  
Service Evaluation ◽  
Service Planning ◽  
Alternative Methods ◽  
Borda Count ◽  
Provider Perspectives ◽  
Multiple Criteria Evaluation

The use of advanced telecommunication and information technologies has been investigated for several decades as an effort in improving healthcare services. Over the last ten years, in particular, efforts have been centered on telemedicine, which has become an increasingly attractive field of research in healthcare service delivery. This chapter discusses multiple criteria evaluation of electronic healthcare (e-health) services, a branch of telemedicine, with both users’ and practitioners’ (service provider) perspectives. The proposed approach integrates several analytical decision making techniques and can be helpful in increasing the flexibility and efficiency of e-health service planning. Several different discrete alternative methods, namely AHP, Borda Count, LINMAP, and PROMETHEE are utilized to prioritize different e-health services and to evaluate preferences of both users and practitioners.

Three Social Choice Rules

2017 ◽  
pp. 54-71
Author(s):  
Andrei Marius Vlăducu
Keyword(s):  
Social Choice ◽  
Status Quo ◽  
Choice Rule ◽  
Borda Count ◽  
Social Choice Rule ◽  
Status Quo Bias ◽  
Approval Voting ◽  
The People ◽  
Viable Solution ◽  
Social Choice Rules

The authors analyze three social choice rules (plurality voting, approval voting and Borda count) from a behavioral economics perspective aiming three objectives: 1) if it is a viable solution to use these procedures during mass elections; 2) why individuals prefer a specific social choice rule and not another; 3) how status quo bias and framing effect influence the preference of individuals for a certain social choice rule. The research is conducted with 87 participants to a lab experiment and data suggest that for using approval voting and Borda count during mass elections is necessary to increase the people level of information about their benefits. When making a decision in a political or economic context seem that people tend to prefer simple plurality rule do to its availability and maybe because of its strong reliance with status quo bias.

scholarly journals A proposed sustainability index for synthesis plans based on input provenance and output fate: application to academic and industrial synthesis plans for vanillin as a case study

2020 ◽  
Vol 16 ◽  
pp. 2346-2362
Author(s):  
John Andraos
Keyword(s):  
Renewable Energy ◽  
Mass Fraction ◽  
Renewable Energy Sources ◽  
Quantitative Measure ◽  
Borda Count ◽  
Energy Sources ◽  
Target Product ◽  
Energy Fraction ◽  
Waste Products ◽  
Sustainability Index

This paper describes a sustainability index (SI) as a quantitative measure of “sustainability” applicable to synthesis plans based on the provenance of input materials and energy sources and the fate of output waste products. The index is computed as the root-mean-square average of the following four parameters: mass fraction of valorized inputs (F VI ), mass fraction of valorized outputs (F VO ), mass fraction of valorized target product (F VP ), and input enthalpic energy fraction arising from renewable energy sources (F RE ). Valorized input materials originate from renewable, recycled, or reclaimed sources. Valorized output materials are destined for recycling or reclaiming so that they may be used in the same or other chemical processes. Valorized target product refers to that portion of the target product that is actually used for its intended purpose. Renewable energy sources are defined as originating from hydroelectric, wind, solar, geothermal, and biomass sources. The computation of SI is illustrated for 22 synthesis plans of the high commodity flavour ingredient vanillin from biofermentation, chemical synthesis, and solvent extraction processes. In addition, these plans are compared and ranked according to Borda count and poset (partially ordered set) pairwise dominance analyses using the following attributes: process mass intensity (PMI), sacrificial reagent (SR) consumption, input enthalpic energy (IEE) consumption, Rowan solvent greenness index (RSGI), and sustainability index (SI).

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