Building Renovation Cost Optimization with the Support of Fuzzy Signature State Machines

2015 ◽  
pp. 129-138
Author(s):  
Gergely I. Molnárka ◽  
László Tamás Kóczy
Keyword(s):  
Cost Optimization ◽  
State Machines

Basel III: In quest for criteria and scenarios of the banking regulation reform advancement

2016 ◽  
pp. 77-93 ◽  
Author(s):  
E. Dzhagityan
Keyword(s):  
Financial Regulation ◽  
Cost Optimization ◽  
Spillover Effect ◽  
Regulatory Reform ◽  
Banking Regulation ◽  
Capital Adequacy ◽  
Basel Iii ◽  
Eurasian Economic Union ◽  
Downward Pressure ◽  
Crisis Recovery

The article looks into the spillover effect of the sweeping overhaul of financial regulation, also known as Basel III, for credit institutions. We found that new standards of capital adequacy will inevitably put downward pressure on ROE that in turn will further diminish post-crisis recovery of the banking industry. Under these circumstances, resilience of systemically important banks could be maintained through cost optimization, repricing, and return to homogeneity of their operating models, while application of macroprudential regulation by embedding it into new regulatory paradigm would minimize the effect of risk multiplication at micro level. Based on the research we develop recommendations for financial regulatory reform in Russia and for shaping integrated banking regulation in the Eurasian Economic Union (EAEU).

Cost Optimization in Manufacturing of toys using Linear Programming

2011 ◽  
Vol 3 (2) ◽  
pp. 118-120
Author(s):  
Salma Shaheen ◽  
◽  
Tazyeen Ahmad
Keyword(s):  
Linear Programming ◽  
Cost Optimization

“PIRAMIDA TINGGI, A State of the Art to Fulfill Obligation of Forestry Permit on Watershed Rehabilitation at PT Pertamina Hulu Mahakam”

2020 ◽  
Author(s):  
P. Sarwanto
Keyword(s):  
Land Tenure ◽  
Management System ◽  
Web Application ◽  
Local Community ◽  
Oil And Gas ◽  
Cost Optimization ◽  
Field Work ◽  
Development Goals ◽  
Potential Risks ◽  
Oil And Gas Sector

Among other obligations imposed under the forestry permit, watershed rehabilitation planting is perceived by the upstream oil and gas sector as the most complex challenge to conquer. Despite its poor track in fulfilling timeline and required result, there are also other challenges to consider, for instance lack of critical location, weather, fire, land tenure, community habit and capability, and cost optimization. In attempt to respond these challenges, an innovation in management system is constructed at PT Pertamina Hulu Mahakam, embracing and tailoring all related challenges, difficulties, and complexities, escalating the activity to be beyond compliance. So that it will be able to deliver more than merely avoid the identified potential risks towards company. The management system, called PIRAMIDA TINGGI (Pemberdayaan Masyarakat untuk Melestarikan Hutan di Dunia demi Ketahanan Energi Nasional), actively involves government, community, and business sector as equilateral triangle that work together to perform watershed rehabilitation planting. Developed using ISO 9001:2015 process approach namely PDCA (Plan-Do-Check-Act), the PIRAMIDA TINGGI system is in line as well with NAWACITA (President Joko Widodo’s vision, mission and program). To encounter other issue found during field work, this system is equipped as well with another innovation tool named PARIDA, a geospatial mobile-desk top-web application that easily able to map and identify vegetation in real time for further geo-analyzing multi-purposes, to be operated by local community. Full set implementation of this system has benefitted all parties. To Company in form of significant cost efficiency around 13.9 MUSD and 7 days’ faster result delivery besides obligation fulfillment, for others in form of broader advantage of proven sustainability project that has gave contribution to 5P (People, Planet, Prosperity, Partnership and Peace), objectives required by UN Sustainable Development Goals 2030.

ERROR LOCALIZATION DIAGNOSTIC MODEL OPTIMIZATION IN DIGITAL STATE MACHINES NETWORKS

2019 ◽  
Author(s):  
Irina Bystrova ◽  
E. Danil'chuk ◽  
Boris Podkopaev
Keyword(s):  
Single Component ◽  
Diagnostic Model ◽  
State Machines ◽  
Model Optimization ◽  
Error Localization ◽  
Diagnostic Models

The problem of constructing a diagnostic model for a network S consisting of a number of digital automata is considered, provided that the diagnostic models of all network components are known. It is assumed that these models are given by systems of logical equations, and the errors to be detected are localized in any but a single component of the network.

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