Multiprocessor task scheduling in multistage hyrid flowshops: a genetic algorithm approach

This paper considers multiprocessor task scheduling in a multistage hybrid flow-shop environment. The objective is to minimize the make-span, that is, the completion time of all the tasks in the last stage. This problem is of practical interest in the textile and process industries. A genetic algorithm (GA) is developed to solve the problem. The GA is tested against a lower bound from the literature as well as against heuristic rules on a test bed comprising 400 problems with up to 100 jobs, 10 stages, and with up to five processors on each stage. For small problems, solutions found by the GA are compared to optimal solutions, which are obtained by total enumeration. For larger problems, optimum solutions are estimated by a statistical prediction technique. Computational results show that the GA is both effective and efficient for the current problem. Test problems are provided in a web site at www.benchmark.ibu.edu.tr/mpt-h; fsp

Algorithms for within-cluster searches using inverted files

Information retrieval over clustered document collections has two successive stages: first identifying the best-clusters and then the best-documents in these clusters that are most similar to the user query. In this paper, we assume that an inverted file over the entire document collection is used for the latter stage. We propose and evaluate algorithms for within-cluster searches, i.e., to integrate the best-clusters with the best-documents to obtain the final output including the highest ranked documents only from the best-clusters. Our experiments on a TREC collection including 210,158 documents with several query sets show that an appropriately selected integration algorithm based on the query length and system resources can significantly improve the query evaluation efficiency. © Springer-Verlag Berlin Heidelberg 2006

Efficient processing of category-restricted queries for web directories

We show that a cluster-skipping inverted index (CS-IIS) is a practical and efficient file structure to support category-restricted queries for searching Web directories. The query processing strategy with CS-IIS improves CPU time efficiency without imposing any limitations on the directory size. © 2008 Springer-Verlag Berlin Heidelberg

Nearest-Neighbor based Metric Functions for indoor scene recognition

Indoor scene recognition is a challenging problem in the classical scene recognition domain due to the severe intra-class variations and inter-class similarities of man-made indoor structures. State-of-the-art scene recognition techniques such as capturing holistic representations of an image demonstrate low performance on indoor scenes. Other methods that introduce intermediate steps such as identifying objects and associating them with scenes have the handicap of successfully localizing and recognizing the objects in a highly cluttered and sophisticated environment. We propose a classification method that can handle such difficulties of the problem domain by employing a metric function based on the Nearest-Neighbor classification procedure using the bag-of-visual words scheme, the so-called codebooks. Considering the codebook construction as a Voronoi tessellation of the feature space, we have observed that, given an image, a learned weighted distance of the extracted feature vectors to the center of the Voronoi cells gives a strong indication of the image's category. Our method outperforms state-of-the-art approaches on an indoor scene recognition benchmark and achieves competitive results on a general scene dataset, using a single type of descriptor. © 2011 Elsevier Inc. All rights reserved

Dialectical Behavior Therapy for Adult Attention Deficit Hyperactivity Disorder: A Narrative Review

Due to the multifaceted psychosocial problems of adults with ADHD and the low level of functionality in different areas such as education, work and family life, the search for psychotherapeutic treatment other than pharmacological approaches has increased in the last decade. This study aims to evaluate the clinical contributions of Dialectical Behavioral Therapy (DBT)-based interventions and the controlled studies in which DBT were tested. This study is a qualitative narrative review. This review included the controlled studies reached by searching the DDT and Adult ADHD as keywords in Medline, Pubmed, Science Direct and EBSCO Psychology & Behavioral Sciences Collection databases until 2021. A total of 12 research articles and 1 short report were identified, but only 9 studies met the inclusion criteria and controlled study conditions. In all studies, it was seen that the skills training mode of DBT was used or adapted. Although the results of the studies reviewed in this review are not consistent, DBT Skills Training shows promise in controlling ADHD symptoms and increasing other psychosocial skills of adults. However, there is a need for more controlled studies on the effectiveness of DBT Skills Training in different experimental research designs

Site-based dynamic pruning for query processing in search engines

Web search engines typically index and retrieve at the page level. In this study, we investigate a dynamic pruning strategy that allows the query processor to first determine the most promising websites and then proceed with the similarity computations for those pages only within these sites

Mobile multi-view object image search

High user interaction capability of mobile devices can help improve the accuracy of mobile visual search systems. At query time, it is possible to capture multiple views of an object from different viewing angles and at different scales with the mobile device camera to obtain richer information about the object compared to a single view and hence return more accurate results. Motivated by this, we propose a new multi-view visual query model on multi-view object image databases for mobile visual search. Multi-view images of objects acquired by the mobile clients are processed and local features are sent to a server, which combines the query image representations with early/late fusion methods and returns the query results. We performed a comprehensive analysis of early and late fusion approaches using various similarity functions, on an existing single view and a new multi-view object image database. The experimental results show that multi-view search provides significantly better retrieval accuracy compared to traditional single view search. © 2016, Springer Science+Business Media New York

Incremental cluster-based retrieval using compressed cluster-skipping inverted files

We propose a unique cluster-based retrieval (CBR) strategy using a new cluster-skipping inverted file for improving query processing efficiency. The new inverted file incorporates cluster membership and centroid information along with the usual document information into a single structure. In our incremental-CBR strategy, during query evaluation, both best(-matching) clusters and the best(-matching) documents of such clusters are computed together with a single posting-list access per query term. As we switch from term to term, the best clusters are recomputed and can dynamically change. During query-document matching, only relevant portions of the posting lists corresponding to the best clusters are considered and the rest are skipped. The proposed approach is essentially tailored for environments where inverted files are compressed, and provides substantial efficiency improvement while yielding comparable, or sometimes better, effectiveness figures. Our experiments with various collections show that the incremental-CBR strategy using a compressed cluster-skipping inverted file significantly improves CPU time efficiency, regardless of query length. The new compressed inverted file imposes an acceptable storage overhead in comparison to a typical inverted file. We also show that our approach scales well with the collection size. © 2008 ACM

Large-scale cluster-based retrieval experiments on Turkish texts

We present cluster-based retrieval (CBR) experiments on the largest available Turkish document collection. Our experiments evaluate retrieval effectiveness and efficiency on both an automatically generated clustering structure and a manual classification of documents. In particular, we compare CBR effectiveness with full-text search (FS) and evaluate several implementation alternatives for CBR. Our findings reveal that CBR yields comparable effectiveness figures with FS. Furthermore, by using a specifically tailored cluster-skipping inverted index we significantly improve in-memory query processing efficiency of CBR in comparison to other traditional CBR techniques and even FS

Effects of stock density on texture-colour quality and chemical composition of rainbow trout (Oncorhynchus mykiss)

This study describes the effects of different stocking densities on texture/colour characteristics, protein content/amino acid and lipid content/fatty acid composition of rainbow trout fillet. Stocking density was selected 5 (Group A), 15 (Group B), 25 (Group C) kg fish m^−3. Tukey’s Multiple Comparison Test showed insignificant differences between measured size/weight measurement and condition factors. No significant differences were found between A and C groups for colour analysis (L* and a* value) and texture profile analysis (hardness, adhesiveness, cohesiveness and gumminess values) of rainbow trout fillets. The proximate composition analysis showed rainbow trout fillets from the A and C groups to exhibit higher values of moisture than the B group. Fish from the A and B groups had a lower of ash and protein in comparison to C group samples. The highest fat values of rainbow trout were measured in B group samples. The content essential amino acid and non-essential amino acid was lower in A and B groups than in C groups. Fish from the C group had higher content of polyunsaturated fatty acids, especially n-3, docosahexanoic acid (DHA) and eicosapentaenoic acid (EPA) in comparison to A and C group. As a result, 25 kg fish m^−3 is recommended stock density in terms of product texture/color and composition quality