An integrated portfolio optimisation procedure based on data envelopment analysis,artificial bee colony algorithm and genetic programming

Portfolio optimisation is an important issue in the field of investment/financial decision-making and has received considerable attention from both researchers and practitioners. However, besides portfolio optimisation, a complete investment procedure should also include the selection of profitable investment targets and determine the optimal timing for buying/selling the investment targets. In this study, an integrated procedure using data envelopment analysis (DEA), artificial bee colony (ABC) and genetic programming (GP) is proposed to resolve a portfolio optimisation problem. The proposed procedure is evaluated through a case study on investing in stocks in the semiconductor sub-section of the Taiwan stock market for 4 years. The potential average 6-month return on investment of 9.31% from 1 November 2007 to 31 October 2011 indicates that the proposed procedure can be considered a feasible and effective tool for making outstanding investment plans, and thus making profits in the Taiwan stock market. Moreover, it is a strategy that can help investors to make profits even when the overall stock market suffers a loss.     

A STOCHASTIC ANALYSIS OF COKE DEPOSITION

The phenomenon of coke deposition on catalyst surface is analyzed stochastically. In contrast to a conventional deterministic approach, derivation of the governing equations of the phenomenon is based on probability laws. The resulting representation provides the information on both the mean or macroscopic and the fluctuating characteristics about the system under consideration. The deposition of coke is assumed to be reversible, i.e., deposited coke has a certain probability of escaping the surface. The applicability of the model developed is justified through analyzing available experimental data appeared in the literature.     

Examining the role of perceived value in virtual communities continuance: its antecedents and the influence of experience

Although perceived value has long been recognised as an influential means of affecting continuance intention in information systems (IS), little attention has been devoted to explore its antecedents, which constitutes an important research issue. This study, building on prior literature on continued usage in IS as well as the resource-based view, proposed a model to address this gap. Our model suggests that perceived value, a major driving force for members’ satisfaction and continuance intention, is affected by four kinds of resources embedded in virtual communities, which are relationship resources, technology infrastructure, knowledge resources and human resources. To provide additional insights on the pivotal role of perceived value, we also postulate that experience moderates the link between perceived value and its antecedents. Data collected from 235 members of a professional virtual community provide strong support for the research model. It was found that perceived value exerts a great effect on both satisfaction and continuance intention. In addition, when different levels of experience are taken into consideration, relationship resources, knowledge resources and human resources were found to be more salient to high-experience members, whereas technology infrastructure was found to be more salient to low-experience members. Finally, this study discusses the implications of these findings and offers direction for future research.     

A Truncated Sum of Processing‐Times–Based Learning Model for a Two‐Machine Flowshop Scheduling Problem

Scheduling with learning effects has gained increasing attention in recent years. A well‐known learning model is called “sum‐of‐processing‐times‐based learning” in which the actual processing time of a job is a nonincreasing function of the jobs already processed. However, the actual processing time of a given job drops to zero precipitously when the normal job processing times are large. Moreover, the concept of learning process is relatively unexplored in a flowshop environment. Motivated by these observations, this article addresses a two‐machine flowshop problem with a truncated learning effect. The objective is to find an optimal schedule to minimize the total completion time. First, a branch‐and‐bound algorithm incorporating with a dominance property and four lower bounds is developed to derive the optimal solution. Then three simulated annealing algorithms are also proposed for near‐optimal solution. The experimental results indicated that the branch‐and‐bound algorithm can solve instances up to 18 jobs, and the proposed simulated annealing algorithm performs well in item of CPU time and error percentage. © 2011 Wiley Periodicals, Inc.     

Engineering Analysis and Design with ALE-VMS and Space–Time Methods

Flow problems with moving boundaries and interfaces include fluid–structure interaction (FSI) and a number of other classes of problems, have an important place in engineering analysis and design, and offer some formidable computational challenges. Bringing solution and analysis to them motivated the Deforming-Spatial-Domain/Stabilized Space–Time (DSD/SST) method and also the variational multiscale version of the Arbitrary Lagrangian–Eulerian method (ALE-VMS). Since their inception, these two methods and their improved versions have been applied to a diverse set of challenging problems with a common core computational technology need. The classes of problems solved include free-surface and two-fluid flows, fluid–object and fluid–particle interaction, FSI, and flows with solid surfaces in fast, linear or rotational relative motion. Some of the most challenging FSI problems, including parachute FSI, wind-turbine FSI and arterial FSI, are being solved and analyzed with the DSD/SST and ALE-VMS methods as core technologies. Better accuracy and improved turbulence modeling were brought with the recently-introduced VMS version of the DSD/SST method, which is called DSD/SST-VMST (also ST-VMS). In specific classes of problems, such as parachute FSI, arterial FSI, ship hydrodynamics, fluid–object interaction, aerodynamics of flapping wings, and wind-turbine aerodynamics and FSI, the scope and accuracy of the FSI modeling were increased with the special ALE-VMS and ST FSI techniques targeting each of those classes of problems. This article provides an overview of the core ALE-VMS and ST FSI techniques, their recent versions, and the special ALE-VMS and ST FSI techniques. It also provides examples of challenging problems solved and analyzed in parachute FSI, arterial FSI, ship hydrodynamics, aerodynamics of flapping wings, wind-turbine aerodynamics, and bridge-deck aerodynamics and vortex-induced vibrations.     

Digital evidence discovery of networked multimedia smart devices based on social networking activities

Unquestionably, networked multimedia smart devices are commonly adopted in contemporary ubiquitous wireless computing era with unprecedented evolving pace in terms of mobility, portability, and pervasiveness. Regrettably, those technology-oriented gadgets are phenomenally exploited by cyber criminals or get involved in computer-related incidents unknowingly. Substantively, the detection, prevention, and the related digital forensics of the above scenarios are becoming tremendously urgent both in public and private sectors. Therefore, in this research, we investigate the scenario when state-of-the-art wireless communication technologies are integrated with the networked smart devices where digital evidences may exist and they could be disclosed when appropriate standard operating procedures are suitably applied. Accordingly, in this paper, a PDA with the built-in GPS navigation functionality via the ubiquitous Wi-Fi connection to a popular social networking platform (facebook) is cross examined concerning the related digital evidence collecting and discovering in terms of revealing previous facebook user accounts on the mobile device without shutting off the power. The research provides a generic framework for the digital forensics specialists to contemplate when the networked smart devices are involved in the related criminal investigation cases especially when omnipresent social networking platforms are becoming the new avenue for the escalating, stringent, and heinous cybercrimes.     

Multi-user web service selection based on multi-QoS prediction

In order to find best services to meet multi-user’s QoS requirements, some multi-user Web service selection schemes were proposed. However, the unavoidable challenges in these schemes are the efficiency and effect. Most existing schemes are proposed for the single request condition without considering the overload of Web services, which cannot be directly used in this problem. Furthermore, existing methods assumed the QoS information for users are all known and accurate, and in real case, there are always many missing QoS values in history records, which increase the difficulty of the selection. In this paper, we propose a new framework for multi-user Web service selection problem. This framework first predicts the missing multi-QoS values according to the historical QoS experience from users, and then selects the global optimal solution for multi-user by our fast match approach. Comprehensive empirical studies demonstrate the utility of the proposed method.     

Dehydrogenation of Cyclohexene on Platinum Nanoclusters on a Thin Film of Al2O3/NiAl(100)

Using a scanning-tunneling microscope, reflection high-energy electron diffraction and photoelectron spectra with synchrotron radiation, we investigated the temperature dependence of the dehydrogenation of cyclohexene (C₆H₁₀) adsorbed on Pt nanoclusters supported on an ultra-thin film of Al₂O₃/NiAl(100). The Pt clusters, grown by vapor deposition, are structurally ordered and exhibit a mean diameter 2.2 nm and height 0.4 nm. The progress of dehydrogenation was monitored through the temporal variation of C 1s photoelectron spectra; analysis of these features revealed that the dehydrogenation of cyclohexene with increasing sample temperature occurs as a sequential process beginning around 150 K, a temperature significantly less than that for Pt single-crystal surfaces. The dehydrogenation behavior, particularly the decomposition into elemental carbon, is found to vary with Pt coverage.     

Crystallization of Li2O · Al2O3· 6SiO2 Glasses Containing Niobium Pentoxide as Nucleating Dopant

Niobium pentoxide (T form, orthorhombic system) was utilized to promote devitrification in Li₂O · Al₂O₃· 6SiO₂ glasses. Two or more mole percentage of this nucleating dopant enhanced crystallization in these glasses. Glasses containing 4.0 and 8.0 mol% T-Nb₂O₅ exhibited a high tendency to form dispersed TT-Nb₂O₅ (monoclinic system) precipitates during the glass quenching process. The crystallization process in glasses containing 2.0 or 4.0 mol% T-Nb₂O₅ occurred as microphase separation, followed by the formation of dispersed TT-Nb₂O₅ crystalline precipitates (760°C), followed by β-quartz solid-solution ( ss ) formation (850° to 900°C) heterogeneously nucleated from the precipitates. β-quartz( ss ) transformed to β-spodumene( ss ), along with a polymorphic transition from the TT-Nb₂O₅ to M-Nb₂O₅ (tetragonal system) crystalline phase.     

Behavior of high strength concrete with and without steel fiber reinforcement in triaxial compression

Based on an extensive experimental program, this paper studies the behavior of high strength concrete and steel fiber reinforced high strength concrete under uniaxial and triaxial compression. Triaxial stress-strain relations and failure criteria are used to evaluate the effect of steel fiber reinforcement on the mechanical properties of high strength concrete in triaxial compression, which is found to be insignificant.