Convolutional Neural Networks Used to Date Photographs

Nowadays, the information provided by digital photographs is very complete and very relevant in different professional fields, such as scientific or forensic photography. Taking this into account, it is possible to determine the date when they were taken, as well as the type of device that they were taken with, and thus be able to locate the photograph in a specific context. This is not the case with analog photographs, which lack any information regarding the date they were taken. Extracting this information is a complicated task, so classifying each photograph according to the date it was taken is a laborious task for a human expert. Artificial intelligence techniques make it possible to determine the characteristics and classify the images automatically. Within the field of artificial intelligence, convolutional neural networks are one of the most widely used methods today. This article describes the application of convolutional neural networks to automatically classify photographs according to the year they were taken. To do this, only the photograph is used, without any additional information. The proposed method divides each photograph into several segments that are presented to the network so that it can estimate a year for each segment. Once all the segments of a photograph have been processed, a general year for the photograph is calculated from the values generated by the network for each of its segments. In this study, images taken between 1960 and 1999 were analyzed and classified using different architectures of a convolutional neural network. The computational results obtained indicate that 44% of the images were classified with an error of less than 5 years, 20.25% with a marginal error between 5 and 10 years, and 35.75% with a higher marginal error of more than 10 years. Due to the complexity of the problem, the results obtained are considered good since 64.25% of the photographs were classified with an error of less than 10 years. Another important result of the study carried out is that it was found that the color is a very important characteristic when classifying photographs by date. The results obtained show that the approach given in this study is an important starting point for this type of task and that it allows placing a photograph in a specific temporal context, thus facilitating the work of experts dedicated to scientific and forensic photography.

Is [ReCl4(CN)2]2− a good Building Block for Single Molecule Magnets? A Theoretical Investigation.

Building blocks containing $5d$ spin centres are promising for constructing single molecule magnets due to their large spin-orbit interaction, but experimental and computational results obtained so far indicate that this might not be the case for Re$^\textrm{IV}$ centres in an octahedral environment. Density functional results obtained in this work for [ReCl$_4$(CN)$_2$]$^{2-}$ and trinuclear complexes formed by attaching Mn$^\textrm{II}$ centres to the cyano ligands indicate that zero field splitting in such complexes exhibits large rhombicity (which leads to fast relaxation of the magnetisation) even if there are only small distortions from an ideal geometry with a four-fold symmetry axis. This is already apparent if second-order spin-orbit perturbation theory is applied but even more pronounced if higher-order spin-orbit effects are included as well, as demonstrated by wavefunction based calculations. Computational results are cast into a ligand field model and these simulations show that especially a distortion which is not along the $C_4/C_2$ axeshas a large effect on the rhombicity. Quantum simulations on these complexes are difficult because the zero field splitting strongly depends on the energetic position of the low-lying doublets from the $t_{2g}^3$ configuration.

Selective skeletal editing of polycyclic arenes using organophotoredox dearomative functionalization

Reactions that lead to destruction of aromatic ring systems often require harsh conditions and, thus, take place with poor selectivities. Selective partial dearomatization of fused arenes is even more challenging but it can be a strategic approach to creating versatile, complex polycyclic frameworks. Herein we describe a general organophotoredox approach for the chemo- and regioselective dearomatization of structurally diverse polycyclic aromatics, including quinolines, isoquinolines, quinoxalines, naphthalenes, anthracenes and phenanthrenes. The success of the new method for chemoselective oxidative rupture of aromatic moieties relies on precise manipulation of the electronic nature of the fused polycyclic arenes. Experimental and computational results show that the key to overcoming the intrinsic thermodynamic and kinetic unfavorability of the dearomatization process is an ultimate hydrogen atom transfer (HAT) step, which enables dearomatization to predominate over the otherwise favorable aromatization pathway. We show that this strategy can be applied to rapid synthesis of biologically valued targets and late-stage skeletal remodeling en route to complex structures.

GRASP-Tabu Search Algorithms for the Route Planning Problem in Spatial Crowdsourcing

With the speedy progress of mobile devices, a lot of commercial enterprises have exploited crowdsourcing as a useful approach to gather information to develop their services. Thus, spatial crowdsourcing has appeared as a new platform in e-commerce and which implies procedures of requesters and workers. A requester submits spatial tasks request to the workers who choose and achieve them during a limited time. Thereafter, the requester pays only the worker for the well accomplished the task. In spatial crowdsourcing, each worker is required to physically move to the place to accomplish the spatial task and each task is linked with location and time. The objective of this article is to find an optimal route to the worker through maximizing her rewards with respecting some constraint, using an approach based on GRASP with Tabu. The proposed algorithm is used in the literature for benchmark instances. Computational results indicate that the proposed and the developed algorithm is competitive with other solution approaches.

Combining Fix and Relax Heuristic and LP-Metric Method to Solve the Multi-Objective Integrated Production-Routing Problem

Production routing problem is one of the problems of the integrated planning that interests in optimizing simultaneously production, inventory, and distribution planning. This chapter has the purpose of developing two mono-objective models for the production-routing problem: one of them minimizes the total costs which is the classical objective while the other one minimizes the energy consumed by the production system. A bi-objective model is then proposed to combine the two objectives mentioned previously using LP-metric method. To solve big instances of the problem in reasonable time, an approximate approach is proposed using the rolling horizon-based fix and relax heuristic. Finally, computational results are presented to compare the solutions obtained by both approaches.

Variable fixing method by weighted average for the continuous quadratic knapsack problem

<p style='text-indent:20px;'>We analyze the method of solving the separable convex continuous quadratic knapsack problem by weighted average from the viewpoint of variable fixing. It is shown that this method, considered as a variant of the variable fixing algorithms, and Kiwiel's variable fixing method generate the same iterates. We further improve the algorithm based on the analysis regarding the semismooth Newton method. Computational results are given and comparisons are made among the state-of-the-art algorithms. Experiments show that our algorithm has significantly good performance; it behaves very much like an <inline-formula><tex-math id="M1">\begin{document}$ O(n) $\end{document}</tex-math></inline-formula> algorithm with a very small constant.</p>

EXPERIMENTAL ANALYSIS OF DOUBLE BOX WING UAV.

In an attempt to reduce the induced drag on a wing, Prandtl found that induced drag reduced significantly by highly increasing the number of vertically offset wings. The same result could be obtained by joining the wingtips of two vertically offset wings. This helped increase payload capacity and also reduced fuel consumption and emissions. Such a wing configuration came to be known as Prandtl’s box wing. In this work, the design and analysis of a box wing aircraft model has been carried out. The preliminary analysis is performed using XFLR5, and the computational analysis is done with the help of ANSYS 18.2. The values of experiments are computed with the help of MATLab R2017. The box wing model has shown a nearly 53.74% reduction in drag as compared with conventional wing models. The computational results of drag have been compared and validated with the results of analytical and the experimental results from the wind tunnel and found to be within 10% of the computational result. Since the drag of the box wing is significantly lesser than the conventional wings the box wing is a feasible configuration which can be used to design various aircrafts including Unmanned Aerial Vehicles and Commercial Planes.

An exact algorithm for constrained k-cardinality unbalanced assignment problem

An assignment problem (AP) usually deals with how a set of persons/tasks can be assigned to a set of tasks/persons on a one-to-one basis in an optimal manner. It has been observed that balancing among the persons and jobs in several real-world situations is very hard, thus such scenarios can be seen as unbalanced assignment models (UAP) being a lack of workforce. The solution techniques presented in the literature for solving UAP’s depend on the assumption to allocate some of the tasks to fictitious persons; those tasks assigned to dummy persons are ignored at the end. However, some situations in which it is inevitable to assign more tasks to a single person. This paper addresses a practical variant of UAP called k-cardinality unbalanced assignment problem (k-UAP), in which only of persons are asked to perform jobs and all the persons should perform at least one and at most jobs. The k-UAP aims to determine the optimal assignment between persons and jobs. To tackle this problem optimally, an enumerative Lexi-search algorithm (LSA) is proposed. A comparative study is carried out to measure the efficiency of the proposed algorithm. The computational results indicate that the suggested LSA is having the great capability of solving the smaller and moderate instances optimally.

AHP–TOPSIS Methodology for Stock Portfolio Investments

This paper presents a methodology for making decisions in the stock market using the AHP-TOPSIS multi-criteria technique. The problem is related to the stock market’s investment process considering the criteria of liquidity, risk, and profitability. The proposed methodology includes integrating economic and financial theories of investment in equity portfolios with the AHP-TOPSIS multi-criteria technique, which allows for evaluating a finite number of alternatives hierarchically under qualitative and quantitative criteria. The methodology has been tested in a real case of selecting a portfolio of high and medium marketability stocks for the Colombian market from April 2012 to April 2017. The computational results show the importance and efficiency of successfully integrating traditional equity portfolio investment criteria and multi-criteria methodologies to find an appropriate balance between profitability and risk in the investment decision-making process in shares in the Colombian stock market. The proposed methodology could be applied to other emerging markets, similar to Colombia.