Theory and methodology on the global optimal solution to a General Reverse Logistics Inventory Model for deteriorating items and time-varying rates

In this paper, we present a unified general inventory model for integrated production of new items and remanufacturing of returned items for an infinite planning horizon. Our model considers a production environment that consists of three shops. The first shop is for remanufacturing returned items, the second shop is for manufacturing new items, while the third shop is for collecting returned items to be remanufactured in the first shop. The system is subject to joint production and remanufacturing options, the first one is to produce new items while the second one is to reproduce/recycle the returned items “as-good-as new”. Items deteriorate while they are in storage, and production, remanufacturing, demand, return, and deterioration rates are arbitrary functions of time. A closed form for the total relevant costs as well as a rigorous mathematical proof, which shows the global optimality of the solution to the underlying inventory system are introduced. Illustrative examples, which explain the application of the theoretical results as well as their numerical verifications, are also given.     

The effect of nonhuman’s versus human’s external regulation on children’s speech use, manifested self-regulation, and satisfaction during learning tasks

Because of several analytical and methodological critiques on the findings and contexts of children’s private speech (PS), self-regulation learning (SRL), and thinking aloud (TA), the present study was conducted to shed new light on the effect of the nonhuman’s/computer’s versus human’s/teacher’s intervention (C-Condition versus T-Condition) on young children’s speech use, SRL, and satisfaction during learning tasks. Four developmental measurements with novel criteria were used to measure: (1) speech analysis, (3) SRL as a function of task level selection, (3) SRL as a function of task precision, and (4) a friendly-chat questionnaire to measure children’s satisfaction. Two types of intervention (enacted versus verbal encouragement) were applied through computer-based learning environment and investigated by forty preschool children divided by their teachers between the two conditions equivalently. It was hypothesized that children who acted alone (C-Condition) were more PS productive, manifested higher SRL, task performance, and satisfaction. The results confirmed the hypothesis with no significant differential effect of the gender on performance, showed that the injudicious use of encouragement hindered the children’s regulation behavior, and proved that PS and TA elicitation were fully different. However, the results were not confirmed Vygotsky’s view and simultaneously not fully inline with Piaget’s view of self-regulation development.     

An Efficient Solution for Model Checking Graph Transformation Systems

This paper presents an efficient solution for modeling checking graph transformation systems. The approach transforms AGG specifications into Bogor models and supports both attributed typed graphs and layered transformations. Resulting models are amenable to check interesting properties expressed as combinations of LTL (Linear Temporal Logic) and graph transformation rules. The first experimental results are encouraging and show that in most cases our proposal improves existing approaches, both in terms of performance and expressiveness.     

Direct Coupling of Solar Cell Arrays to Electric Power Networks

Results of the investigation of the performance of solar cells when directly coupled to a conventional three-phase power network are presented. This approach dissociates the electricity production problem from the electric energy storage problem. Extensive studies of the required power inverter are performed. Preliminary simulation results indicate that ac power outputs of better than 90 percent of the optimum cell power output can be easily achieved by means of a suitably controlled inverter, thereby justify     

Intelligent system for visual web content analytics: A new approach and case study

The accuracy of searches for visual data elements, as well as other types of information, depends on the terms used by the user in the input query to retrieve the relevant results and to reduce the irrelevant ones. Most of the results that are returned are relevant to the query terms, but not to their meaning. For example, certain types of web contents hold hidden information that traditional search engines are unable to retrieve. Searching for the mathematical construct of 1/x using Google will not result in the retrieval of the documents that contain the mathematically equivalent expressions (i.e. x^?1). Because conventional search engines fall short of providing math-search capabilities. One of these capabilities is the ability of these search engines to detect the mathematical equivalence between users’ quires and math contents. In addition, users sometimes need to use slang terms, either to retrieve slang-based visual data (e.g. social media content) or because they do not know how to write using classical form. To solve such a problem, this paper proposed an AI-based system for analysing multilingual slang web contents so as to allow a user to retrieve web slang contents that are relevant to the user’s query. The proposed system presents an approach for visual data analytics, and it also enables users to analyse hundreds of potential search results/web pages by starting an informed friendly dialogue and presenting innovative answers.     

Antioxidant properties of various solvent extracts of potato peel,sugar beet pulp and sesame cake

BACKGROUND: Growing interest in the replacement of synthetic food antioxidants by natural ones has fostered research on vegetable sources and screening of raw materials to identify new antioxidants. The food‐processing industry generates substantial quantities of phenolic‐rich by‐products that could be valuable natural sources of antioxidants. In this study the antioxidant properties and total phenolic, flavonoid and flavonol contents of three industrial by‐products, sugar beet pulp, sesame cake and potato peel, extracted with various solvents were examined. Since different antioxidant compounds have different mechanisms of action, several methods were used to assess the antioxidant efficacy of extracts. RESULTS: Among the six solvents tested, methanol gave the highest extract yield of potato peel and sugar beet pulp, while diethyl ether gave the highest extract yield of sesame cake. Methanol exhibited the highest extraction ability for phenolic compounds, with total phenolics amounting to 2.91, 1.79 and 0.81 mg gallic acid equivalent g^?1 dry weight in potato peel, sugar beet pulp and sesame cake extracts respectively, and also showed the strongest antioxidant capacity in the three assays used. All three methods proved that potato peel extract had the highest antioxidant activity owing to its high content of phenolic compounds and flavonoids. CONCLUSION: On the basis of the results obtained, potato peel, sugar beet pulp and sesame cake extracts could serve as natural antioxidants owing to their significant antioxidant activity. Therefore they could be used as preservative ingredients in the food and/or pharmaceutical industries. Copyright © 2009 Society of Chemical Industry     

Face Recognition Based on Gabor Feature Extraction Followed by FastICA and LDA

Over the past few decades, face recognition has become the most effective biometric technique in recognizing people’s identity, as it is widely used in many areas of our daily lives. However, it is a challenging technique since facial images vary in rotations, expressions, and illuminations. To minimize the impact of these challenges, exploiting information from various feature extraction methods is recommended since one of the most critical tasks in face recognition system is the extraction of facial features. Therefore, this paper presents a new approach to face recognition based on the fusion of Gabor-based feature extraction, Fast Independent Component Analysis (FastICA), and Linear Discriminant Analysis (LDA). In the presented method, first, face images are transformed to grayscale and resized to have a uniform size. After that, facial features are extracted from the aligned face image using Gabor, FastICA, and LDA methods. Finally, the nearest distance classifier is utilized to recognize the identity of the individuals. Here, the performance of six distance classifiers, namely Euclidean, Cosine, Bray-Curtis, Mahalanobis, Correlation, and Manhattan, are investigated. Experimental results revealed that the presented method attains a higher rank-one recognition rate compared to the recent approaches in the literature on four benchmarked face datasets: ORL, GT, FEI, and Yale. Moreover, it showed that the proposed method not only helps in better extracting the features but also in improving the overall efficiency of the facial recognition system.     

A multiobjective hybrid ant colony optimization approach applied to the assignment and scheduling problem

The assignment and scheduling problem is inherently multiobjective. It generally involves multiple conflicting objectives and large and highly complex search spaces. The problem allows the determination of an efficient allocation of a set of limited and shared resources to perform tasks, and an efficient arrangement scheme of a set of tasks over time, while fulfilling spatiotemporal constraints. The main objective is to minimize the project makespan as well as the total cost. Finding a good approximation set is the result of trade‐offs between diversity of solutions and convergence toward the Pareto‐optimal front. It is difficult to achieve such a balance with NP‐hard problems. In this respect, and in order to efficiently explore the search space, a hybrid bidirectional ant‐based approach is proposed in this paper, which is an improvement of a bi‐colony ant‐based approach. Its main characteristic is that it combines a solution construction developed for a more complicated problem with a Pareto‐guided local search engine.     

Design and motion analysis of vibration-driven small robot Rizeh

Vibration mechanism is good candidates to be used as actuation system in small robots. However, mini fabrication of small electrical and mechanical drives is a challenging issue. Moreover, no analytical model for motion analysis of vibration driven robots is devised. In this paper, a small robot is developed. To setup a low-cost robot, cell phone vibrators are employed as actuation mechanism. Motion principle of the robot is analytically obtained and appropriate mechanical and electronic derives are designed. Some technical tips are employed to reduce the size of the robot. The obtained model was evaluated by simulations in MSC.ADAMS as well as some standard experiments on a real robot named Rizeh. Moreover, the robot is tested in a line following task, as a typical task for mobile robots.