Nadir compromise programming: A model for optimization of multi-objective portfolio problem

In problem of portfolio selection, financial Decision Makers (DMs) explain objectives and investment purposes in the frame of multi-objective mathematic problems which are more consistent with decision making realities. At present, various methods have introduced to optimize such problems. One of the optimization methods is the Compromise Programming (CP) method. Considering increasing importance of investment in financial portfolios, we propose a new method, called Nadir Compromising Programming (NCP) by expanding a CP-based method for optimization of multi-objective problems. In order to illustrate NCP performance and operational capability, we implement a case study by selecting a portfolio with 35 stock indices of Iran stock market. Results of comparing the CP method and proposed method under the same conditions indicate that NCP method results are more consistent with DM purposes.     

Iran atlas of offshore renewable energies

The aim of the present study is to provide an Atlas of IRAN Offshore Renewable Energy Resources (hereafter called ‘the Atlas’) to map out wave and tidal resources at a national scale, extending over the area of the Persian Gulf and Sea of Oman. Such an Atlas can provide necessary tools to identify the areas with greatest resource potential and within reach of present technology development.To estimate available tidal energy resources at the site, a two-dimensional tidally driven hydrodynamic numerical model of Persian Gulf was developed using the hydrodynamic model in the MIKE 21 Flow Model (MIKE 21HD), with validation using tidal elevation measurements and tidal stream diamonds from Admiralty charts. The results of the model were used to produce a time series of the tidal stream velocity over the simulation period.Moreover, to assess the potential of the wave energy in this site, a model was developed based on six-hourly data from a third generation ocean wave model (ISWM-Iranian Sea Wave Model) covering the period 1992–2003.To ensure the information provided to the Atlas is managed and maintained most effectively, all the derived marine resource parameters have been captured in a structured database, within a Geographical Information System (GIS), so enabling effective data management, presentation and interrogation.     

A modified thermodynamic insight to deliquescence of a void‐containing nanocrystal confirmed by MD simulation

Existence of voids in crystalline structures can affect their physical and chemical properties considerably. When the size of the crystal reaches to nanoscale, experimental determination of its void fraction is difficult. In this work, a molecular dynamics approach is introduced to find equilibrium void fractions of a simple cubic (CsCl) and fcc (KCl) nanocrystals by determination of their deliquescence relative humidity (DRH) for different sizes and void fractions and extrapolation of the results to the bulk limit. To confirm the simulation results, the size dependency of DRH to the nanoparticle size was studied thermodynamically by inclusion of size‐dependent density of water nanodroplet which leads to a simple homographic equation. This method proposes the equilibrium void percents of CsCl and KCl nanoparticles to be 10 and 15%, respectively, which are obtained by extrapolation of the results to the bulk limit. The success of obtained Möbius function was also confirmed by fitting it to experimental data for deliquescence of NaCl nanoparticles which implies the importance of considering density of water nanodroplet as a size dependent quantity. Also, using the mentioned thermodynamic approach, void dependency of deliquescence for the nanoparticles was found to be as a quasi‐linear trend which is compatible with the simulation results. It is noticeable that the approach used this work for determination of equilibrium void fraction is only valid if the utilized force fields are accurate. © 2016 American Institute of Chemical Engineers AIChE J, 62: 4066–4077, 2016     

Simultaneous minimization of total tardiness and waiting time variance on a single machine by genetic algorithms

This paper considers a single machine scheduling problem, with the objective of minimizing a linear combination of total tardiness and waiting time variance in which the idle time is not allowed. Minimizing total tardiness is always regarded as one of the most significant performance criteria in practical systems to avoid penalty costs of tardiness, and waiting time variance is an important criterion in establishing quality of service (QoS) in many systems. Each of these criteria is known to be non-deterministic polynomial-time hard (NP-hard); therefore, the linear combination of them is NP-hard too. For this problem, we developed a genetic algorithm (GA) by applying its general structure that further improves the initial population, utilizing some of heuristic algorithms. The GA is shown experimentally to perform well by testing on various instances.     

Prioritizing Long-term Watershed Management Strategies Using Group Decision Analysis

There is a growing consensus that an effective way of enhancing long-term water resources management and environmental sustainability is through locally based planning at the watershed scale. Managing watershed resources for particular uses requires interactive dialogue among all stakeholders who have different objectives. Therefore, the resolution of inter-group conflict should be an acknowledged task of the planning process. In this paper, an integrated framework for prioritizing watershed management strategies is proposed. A case study is employed to highlight the challenges of using group decision analysis in strategic planning and to illustrate the interaction between different stakeholders on watershed issues. In particular, two group decision-making approaches are used to assess and analyse different stakeholders' preferences for various strategies and alternatives. Professional experts, government agencies and community leaders constitute the different parties included in the framework. The main focus is on the application of group decision analysis in the long-term watershed planning process. The results of the overall preference analysis show that water resources development is the most important strategy followed by agricultural and range management.     

Statistical modeling of global geogenic arsenic contamination in groundwater

Contamination of groundwaters with geogenic arsenic poses a major health risk to millions of people. Although the main geochemical mechanisms of arsenic mobilization are well understood, the worldwide scale of affected regions is still unknown. In this study we used a large database of measured arsenic concentration in groundwaters (around 20,000 data points) from around the world as well as digital maps of physical characteristics such as soil, geology, climate, and elevation to model probability maps of global arsenic contamination. A novel rule-based statistical procedure was used to combine the physical data and expert knowledge to delineate two process regions for arsenic mobilization: "reducing" and "high-pH/ oxidizing". Arsenic concentrations were modeled in each region using regression analysis and adaptive neuro-fuzzy inferencing followed by Latin hypercube sampling for uncertainty propagation to produce probability maps. The derived global arsenic models could benefit from more accurate geologic information and aquifer chemical/physical information. Using some proxy surface information, however, the models explained 77% of arsenic variation in reducing regions and 68% of arsenic variation in high-pH/oxidizing regions. The probability maps based on the above models correspond well with the known contaminated regions around the world and delineate new untested areas that have a high probability of arsenic contamination. Notable among these regions are South East and North West of China in Asia, Central Australia, New Zealand, Northern Afghanistan, and Northern Mali and Zambia in Africa.     

CCVNet: A Modified Content-Centric Approach to Enable Multiple Types of Applications in Vehicular Networks

Wireless Personal Communications - Intelligent transportation systems and connected vehicles, by utilization of new facilities and technologies, have a significant role in improving the quality of...     

Exergoeconomic and environmental investigation of an innovative poly-generation plant driven by a solid oxide fuel cell for production of electricity,cooling, desalinated water,and hydrogen

Fuel cell and renewable-based poly-generation plants (PGPs) are proven as advanced technologies for multiple generation purposes. To limit the greenhouse gas emissions, an innovative PGP generating electricity, cooling, desalinated water, and hydrogen is proposed in the current study. The system consists of a solid oxide fuel cell as a prime mover integrated with a gas turbine, a biomass combustion chamber, an organic Rankine cycle, an ejector refrigeration cycle, a desalination unit, and a proton exchange membrane electrolyzer integrated with solar collectors. As the most effective tools for performance evaluation, exergoeconomic, and environmental analyses have been applied. The system produces electricity of 4.4 MW, refrigeration capacity of 0.16 MW, and desalinated water of 0.96 kg/s. The attained freshwater enters the electrolyzer during 12 daylight hours, leading to hydrogen and sanitary water generation with the values of 1.55 g/s and 0.94 kg/s, respectively. The cost per unit exergy and the total cost rate of the products are 11.28 $/GJ, 223 $/h, correspondingly. Carbon dioxide emission of the system is estimated to be 10.79 kmol/MWh. According to the evaluation, the total cost rate increases with increasing current density and fuel cell inlet temperature and decreasing fuel utilization factor.     

Modeling of thermodynamic properties of carrot product using ALO,GWO, and WOA algorithms under multi-stage semi-industrial continuous belt dryer

Engineering with Computers - In this paper, multi-stage continuous belt (MSCB) dryer was used for carrot slices drying. Experiments were performed at three air speeds (1, 1.5, and 2 m/s)...     

On the resilience of P2P botnet footprints in the presence of legitimate P2P traffic

Botnet is a distributed platform for illegal activities severely threaten the security of the Internet. Fortunately, although their complicated nature, bots leave some footprints during the C&C communication that have been utilized by security researchers to design detection mechanisms. Nevertheless, botnet designers are always trying to evade detection systems by leveraging the legitimate P2P protocol as C&C channel or even mimicking legitimate peer‐to‐peer (P2P) behavior. Consequently, detecting P2P botnet in the presence of normal P2P traffic is one of the most challenging issues in network security. However, the resilience of P2P botnet detection systems in the presence of normal P2P traffic is not investigated in most proposed schemes. In this paper, we focused on the footprint as the most essential part of a detection system and presented a taxonomy of footprints utilized in behavioral P2P botnet detection systems. Then, the resilience of mentioned footprints is analyzed using three evaluation scenarios. Our experimental and analytical investigations indicated that the most P2P botnet footprints are not resilient to the presence of legitimate P2P traffic and there is a pressing need to introduce more resilient footprints.