Text-to-picture tools,systems, and approaches: a survey

Multimedia Tools and Applications - Text-to-picture systems attempt to facilitate high-level, user-friendly communication between humans and computers while promoting understanding of natural...     

Use of genetic algorithms to solve production and operations management problems: A review

Operations managers and scholars in their search for fast and good solutions to real-world problems have applied genetic algorithms to many problems. While genetic algorithms are promising tools for problem solving, future research will benefit from a review of the problems that have been solved and the designs of the genetic algorithms used to solve them. This paper provides a review of the use of genetic algorithms to solve operations problems. Reviewed papers are classified according to the problems they solve. The basic design of each genetic algorithm is described, the shortcomings of the current research are discussed and directions for future research are suggested.     

Effects of time-inconsistent preferences on information technology infrastructure investments with growth options

Increasing information technology (IT) infrastructure spending and the capability of such projects to provide a platform for a firm to realize value from IT marks their importance. Effective management of IT infrastructure investments includes identification of embedded growth options in the infrastructure, and exercising them in a timely manner. Extant research has recognized that while managers could use real options thinking in IT investment management, managerial bias could affect the timing of option exercise and their realized value. We analyze the effect of time-inconsistent preferences of present-biased managers on the exercise time of real growth options and the realized value using a discrete time option valuation model. The results show that present-biased managers are more likely to exercise options early when the net payoffs are low, the option payoffs have high volatility, and the risk free discount rate is small. In addition, present biased managers are more likely to exercise a growth option early in its life when the project is performing well. We provide implications for practice and IT governance.     

A new stall delay algorithm for predicting the aerodynamics loads on wind turbine blades for axial and yawed conditions

Stall delay is a complicated phenomenon that has gained for many years the attention of industry and academics in the fields of helicopter and wind turbine aerodynamics. Since most of the potential flow theories still rely on the use of 2D aerofoil data for simulating loads on a rotating blade, less degree of accuracy is expected because of 3D rotational effects. In this work, a new model for correcting the 2D steady aerodynamic data for 3D effects is presented. The model can reduce the uncertainty in the blade design process and, subsequently, make wind turbines more cost‐effective. This model combines the stall delay model of Corrigan and Schillings, a modified version of an inviscid stall delay model, a new modification factor to account for the effect of the angle of attack changes and a new tip loss factor. Furthermore, the model applies the use of the separation factor of Du and Selig to evaluate the area on the rotor disc where stall delay is most prominent. The new stall delay model was embedded in a free‐wake vortex model to estimate the aerodynamic loads on the National Renewable Energy Laboratory Phase VI rotor blades consisting of the S809 aerofoil sections. The results in this study confirm the validity of the 3D corrections by the proposed new model under both axial and yawed flow conditions. Copyright © 2017 John Wiley & Sons, Ltd.     

The impact of quality considerations on material flow in two-stage inventory systems

Supply chain management literature calls for coordination between the different members of the chain. Inventory models achieve this coordination along a supply chain by making the lot size at an upstream entity an integer multiplier of the lot size at the adjacent downstream entity. Such models assume that all components produced are of acceptable quality and may cause suppliers to produce larger quantities than what is optimal. In this paper, we formulate and solve two-stage supply chain inventory models in which the proportion of defective products increases with increased production lot sizes. We show that quality considerations can lead to significant reduction in production lot sizes. In addition, the models show that most benefits to the supply chain are attained from the suppliers producing on a just-in-time basis rather than delivering to their customers just-in-time. We derive closed-form expressions for the optimal lot sizes for a two-stage supply chain under deterministic and then stochastic demand and illustrate the models with numerical examples.     

Single-period inventory model with a delayed incentive option for selling excess inventory

The single‐period problem (SPP) is to find the order quantity which maximizes the expected profit in a single period probabilistic demand framework. We extend the SPP to a case where a retailer uses delayed incentives in the form of cash mail‐in rebates to sell remaining inventory that did not sell at the regular price. The advantage of cash mail‐in rebates is that not all consumers will redeem them. We address three cases: (1) rebate value is predetermined and the order quantity is a decision variable; (2) order quantity is a decision variable and rebate value is set to the value needed to sell all excess inventory, and (3) order quantity is a decision variable and the rebate may be used to sell part of or all excess inventory. In the third case, any inventory remaining after the rebate offer is salvaged at reduced price. We provide analytical solutions for uniform and exponential demand distributions. In all cases, rebates can lead to significant increases in expected profit. We first maximize the expected profit. We then maximize the probability of achieving a target profit and show that the use of rebates can lead to a substantial increase in that probability.     

THE INDUSTRIAL ROBOTS SELECTION PROBLEM: LITERATURE REVIEW AND DIRECTIONS FOR FUTURE RESEARCH

Research on the industrial robot selection problem (RSP) has received increased attention in the past decade. In this paper, RSP models are reviewed and classified. The strengths and weaknesses of the different approaches to the RSP are summarized. A tabular framework is used to summarize the reviewed RSP models. For quick and easy reference, the table categorizes the models by application, solution approach, robot attributes considered, and selection criteria. We suggest directions for future research     

Fatty acids, 4‐desmethylsterols,and triterpene alcohols from Tunisian lentisc (Pistacia lentiscus) fruits

A comparative study was performed to determine the fatty acid, 4‐desmethylsterol and triterpenic alcohols compositions of three different Tunisian populations of Pistacia lentiscus fruit Rimel (RM), Korbous (KO), and Tebaba (TB). Fruits are rich in lipids, which varied from 39.37% (KO) to 42.48% (TB) on a dry weight basis. Qualitatively, fatty acid, sterol, mono‐ and dimethylsterol composition is identical for all populations. Oleic acid was the major fatty acid for all samples, accounting from 40.49% in TB population to 50.72% in RM population followed by the palmitic and linoleic acids. Other fatty acids are present at lower levels. Total sterol amount varied from 109.72 mg/100 g of oil (KO) to 434.26 mg/100 g of oil (RM) with an average of 248.74 mg/100 g of oil. The major 4‐desmethylsterol component in all studied Tunisian populations of P. lentiscus oil was ß‐sitosterol followed by campesterol in TB and KO, and by stigmasterol in RM. The amount of total triterpenic alcohols varied from 42.39 mg/100 g of oil in RM population to 70.41 mg/100 g oil in TB population. The quantitative difference in the fatty acids and 4‐desmethylsterols of the different populations studied could be due to the effect of geographic region and soil type.     

Antibacterial activity and chemical composition of 20 Eucalyptus species’ essential oils

The essential oils of twenty Eucalyptus species harvested from Zerniza and Souinet arboreta (North West and North of Tunisia), were screened for their antibacterial activities by the agar disc diffusion method. Eighteen major compounds, identified by GC and GC/MS, have been retained for the study of the chemical and biological activity variability. The main ones were 1,8-cineole followed by α-pinene, p-cymene, borneol, cryptone, spathulenol, viridiflorol and limonene. The chemical principal components analysis identified 10 chemotypes, however that of the inhibition zone diameter (izd) of growth bacteria separated 5 groups of Eucalyptus oils, characterised by their antibacterial inhibition ability. The most sensitive strain was the Gram positive Staphylococcus aureus with that of E. odorata oil (16.0 ± 1.0 mm izd), while the most resistant bacteria was Pseudomonas aeruginosa. Some correlation between the amount of 1,8-cineole, p-cymene, α-pinene, or of cryptone and the antibacterial activity were observed.     

Efficient scheduling discipline for Hierarchical Diff‐EDF

Packet networks are currently enabling the integration of traffic with a wide range of characteristics that extend from video traffic with stringent quality of service (QoS) requirements to the best‐effort traffic requiring no guarantees. QoS guarantees can be provided in conventional packet networks by the use of proper packet‐scheduling algorithms. As a computer revolution, many scheduling algorithms have been proposed to provide different schemes of QoS guarantees, with Earliest Deadline First (EDF) as the most popular one. With EDF scheduling, all flows receive the same miss rate regardless of their traffic characteristics and deadlines. This makes the standard EDF algorithm unsuitable for situations in which the different flows have different miss rate requirements since in order to meet all miss rate requirements it is necessary to limit admissions so as to satisfy the flow with the most stringent miss rate requirements. In this paper, we propose a new priority assignment scheduling algorithm, Hierarchal Diff‐EDF (Differentiate Earliest Deadline First), which can meet the real‐time needs of these applications while continuing to provide best‐effort service to non‐real time traffic. The Hierarchal Diff‐EDF features a feedback control mechanism that detects overload conditions and modifies packet priority assignments accordingly. Copyright © 2007 John Wiley & Sons, Ltd.