Kouakou A.K.,University of Economic Sciences
Energy Policy | Year: 2011
This paper examines the causal relationship between the electric power industry and the economic growth of Cote d'Ivoire. Using the data from 1971 to 2008, a test was conducted for the cointegration and Granger causality within an error correction model. Results from these tests reveal a bidirectional causality between per capita electricity consumption and per capita GDP. A unidirectional causality running from electricity consumption to industry value added appears in the short run. Economic growth is found to have great effects on electricity consumption and a reverse causality from electricity to economic growth may also appear. In the long run, there is a unidirectional causality between electricity and both GDP and industry value added. From these findings, we conclude that the country will be energy dependent in the long run and must therefore secure the production network from shortfalls to ensure a sustainable development path. Accordingly, government should adopt policies aimed at increasing the investment in the sector by stepping up electricity production from existing and new energy sources. © 2011 Elsevier Ltdl.
Amri F.,University of Economic Sciences
Renewable and Sustainable Energy Reviews | Year: 2016
The current study inspects the nexus amongst energy consumption, FDI inflows and output in 75 countries meantime the period 1990–2010. We further examine this relationship with regard to developed as well as developing countries assembled from diverse geographic regions from the world. The present results display that there is proof of bidirectional linkage concerning FDI and output per capita, concerning renewable energy consumption and gross domestic product per capita and concerning non-renewable energy and gross domestic product per capita in the three groups of countries (developed, all, and developing). In addition, the judgments detect a bidirectional linkage concerning renewable energy consumption and FDI in developed countries. An increase of 1% rate in renewable energy participates to improving FDI by 0.185 % and at the same time an increase of FDI contributes to enhancing renewable energy by 0.292%. Nevertheless, in the case of all and developing countries, the results discover unidirectional link moving from foreign inflows to both sorts of energy. In conclusion, the policy recommendations of our empirical results are taken into consideration. © 2016 Elsevier Ltd
Wagner U.,University of Economic Sciences
Quality Management in Health Care | Year: 2010
Objective: The more complex a medical device is, the more difficult it is to control the hazards associated with its use. A substantial percentage of harm or injuries to patients resulting from treatment can be attributed to errors. No one knows exactly how many victims have been claimed by medical errors. Studies from the United States and other countries show that 3% to 4% of all hospital patients suffer harm or injuries. This text is intended to provide a practice-oriented approach to the discussion of targeted improvement opportunities in connection with a superficial consideration of the sociotechnical system comprising the manufacturers, the medical devices, and the users in the health facilities. Method: Analysis of the risk reports received by the Federal Institute for Drugs and Medical Devices (Bundesinstitut für Arzneimittel und Medizinprodukte) in connection with undesirable events involving the use of medical devices. Supplementary consideration of additional data from previous human factors research in the field of medicine. The evaluation period for the primary data focuses on the years 2005 to 2008. A differentiation is made between the error causal factors, man, and device. Results: A substantial percentage of the incidents that occurred can be attributed to human blunders. Within the scope of an evaluation of more than 16 000 risk reports in connection with medical devices, 5000 risk reports could not be directly attributed to the failure of a medical device. The lack of an error culture seems to be a considerable problem. Conclusion: The safe and reliable development and use of medical devices requires efficient and consistent risk management. Until now, human factors are not sufficiently considered when identifying sources of errors in sociotechnical systems. The useful data required for an extensive risk assessment are missing. An interface-overlapping method of solution is required which permits system-analytical and unbiased error handling and integrates all stakeholders. © 2010 Wolters Kluwer Health | Lippincott Williams & Wilkins.
Huebner T.,University of Economic Sciences
German medical science : GMS e-journal | Year: 2010
Electrocardiographic methods still provide the bulk of cardiovascular diagnostics. Cardiac ischemia is associated with typical alterations in cardiac biosignals that have to be measured, analyzed by mathematical algorithms and allegorized for further clinical diagnostics. The fast growing fields of biomedical engineering and applied sciences are intensely focused on generating new approaches to cardiac biosignal analysis for diagnosis and risk stratification in myocardial ischemia. To present and review the state of the art in and new approaches to electrocardiologic methods for non-invasive detection and risk stratification in coronary artery disease (CAD) and myocardial ischemia; secondarily, to explore the future perspectives of these methods. In follow-up to the Expert Discussion at the 2008 Workshop on "Biosignal Analysis" of the German Society of Biomedical Engineering in Potsdam, Germany, we comprehensively searched the pertinent literature and databases and compiled the results into this review. Then, we categorized the state-of-the-art methods and selected new approaches based on their applications in detection and risk stratification of myocardial ischemia. Finally, we compared the pros and cons of the methods and explored their future potentials for cardiology. Resting ECG, particularly suited for detecting ST-elevation myocardial infarctions, and exercise ECG, for the diagnosis of stable CAD, are state-of-the-art methods. New exercise-free methods for detecting stable CAD include cardiogoniometry (CGM); methods for detecting acute coronary syndrome without ST elevation are Body Surface Potential Mapping, functional imaging and CGM. Heart rate variability and blood pressure variability analyses, microvolt T-wave alternans and signal-averaged ECG mainly serve in detecting and stratifying the risk for lethal arrythmias in patients with myocardial ischemia or previous myocardial infarctions. Telemedicine and ambient-assisted living support the electrocardiological monitoring of at-risk patients. There are many promising methods for the exercise-free, non-invasive detection of CAD and myocardial ischemia in the stable and acute phases. In the coming years, these new methods will help enhance state-of-the-art procedures in routine diagnostics. The future can expect that equally novel methods for risk stratification and telemedicine will transition into clinical routine.
Tavana M.,Philadelphia University |
Tavana M.,University of Paderborn |
Abtahi A.-R.,University of Economic Sciences |
Khalili-Damghani K.,Islamic Azad University at Tehran
Expert Systems with Applications | Year: 2014
Considering the trade-offs between conflicting objectives in project scheduling problems (PSPs) is a difficult task. We propose a new multi-objective multi-mode model for solving discrete time-cost-quality trade-off problems (DTCQTPs) with preemption and generalized precedence relations. The proposed model has three unique features: (1) preemption of activities (with some restrictions as a minimum time before the first interruption, a maximum number of interruptions for each activity, and a maximum time between interruption and restarting); (2) simultaneous optimization of conflicting objectives (i.e., time, cost, and quality); and (3) generalized precedence relations between activities. These assumptions are often consistent with real-life projects. A customized, dynamic, and self-adaptive version of a multi-objective evolutionary algorithm is proposed to solve the scheduling problem. The proposed multi-objective evolutionary algorithm is compared with an efficient multi-objective mathematical programming technique known as the efficient ε-constraint method. The comparison is based on a number of performance metrics commonly used in multi-objective optimization. The results show the relative dominance of the proposed multi-objective evolutionary algorithm over the ε-constraint method. © 2013 Elsevier Ltd. All rights reserved.