Scheduling Optimization Modelling: A Case Study of a Woven Label Manufacturing Company

Production scheduling involves all activities of building production schedules, including coordinating and assigning activities to each person, group of people, or machine and arranging work orders in each workplace. Production scheduling must solve all problems such as minimizing customer wait time, storage costs, and production time; and effectively using the enterprise’s human resources. This paper studies the application of flexible job shop modelling on scheduling a woven labelling process. The labelling process includes several steps which are handled in different work-stations. Each workstation is also comprised of several identical parallel machines. In this study, job splitting is allowed so that the power of work stations can be utilized better. The final objective is to minimize the total completion time of all jobs. The results show a significant improvement since the new planning may save more than 60% of lead time compared to the current schedule. The contribution of this research is to propose a flexible job shop model for scheduling a woven labelling process. The proposed approach can also be applied to support complex production scheduling processes under fuzzy environments in different industries. A practical case study demonstrates the effectiveness of the proposed model.     

Noise-adaptive synthetic oversampling technique

Applied Intelligence - In the field of supervised learning, the problem of class imbalance is one of the most difficult problems, and has attracted a great deal of research attention in recent...     

Investigation of long term drift of an intraocular pressure sensor

Microsystem Technologies - “Zero drift” behavior of an optical intraocular pressure sensor is studied using an analytical model based on the deflection of a circular membrane. Results...     

Roll‐to‐roll UV embossing process applied for light bar‐based sub‐wavelength gratings for backlight

This study proposes a roll‐to‐roll process‐based sub‐wavelength grating, which is attached on a light bar to turn the side‐lit red/green/blue (620, 520, and 450 nm) incident rays into a uniformly and normally output white light with high illuminance from the light bar's surface. On the basis of the rigorous coupling wave analysis, the relationship between the first‐order transmission/reflection efficiency and the pitch of the gratings with different shapes was analyzed. The optimal design can effectively reduce the coupling length and enhance the white color balance for display applications.     

ANDES: efficient evaluation of NOT-twig queries in relational databases

Despite a large body of work on XPath query processing in relational environment, systematic study of queries containing not-predicates have received little attention in the literature. Particularly, several xml supports of industrial-strength commercial rdbms fail to efficiently evaluate such queries. In this paper, we present an efficient and novel strategy to evaluate not -twig queries in a tree-unaware relational environment. not -twig queries are XPath queries with ancestor–descendant and parent–child axis and contain one or more not-predicates. We propose a novel Dewey-based encoding scheme called Andes (ANcestor Dewey-based Encoding Scheme), which enables us to efficiently filter out elements satisfying a not-predicate by comparing their ancestor group identifiers. In this approach, a set of elements under the same common ancestor at a specific level in the xml tree is assigned same ancestor group identifier. Based on this scheme, we propose a novel sql translation algorithm for not-twig query evaluation. Experiments carried out confirm that our proposed approach built on top of an off-the-shelf commercial rdbms significantly outperforms state-of-the-art relational and native approaches. We also explore the query plans selected by a commercial relational optimizer to evaluate our translated queries in different input cardinality. Such exploration further validates the performance benefits of Andes.     

CLARO: modeling and processing uncertain data streams

Uncertain data streams, where data are incomplete and imprecise, have been observed in many environments. Feeding such data streams to existing stream systems produces results of unknown quality, which is of paramount concern to monitoring applications. In this paper, we present the claro system that supports stream processing for uncertain data naturally captured using continuous random variables. claro employs a unique data model that is flexible and allows efficient computation. Built on this model, we develop evaluation techniques for relational operators by exploring statistical theory and approximation. We also consider query planning for complex queries given an accuracy requirement. Evaluation results show that our techniques can achieve high performance while satisfying accuracy requirements and outperform state-of-the-art sampling methods.     

A self-learning particle swarm optimizer for global optimization problems

Particle swarm optimization (PSO) has been shown as an effective tool for solving global optimization problems. So far, most PSO algorithms use a single learning pattern for all particles, which means that all particles in a swarm use the same strategy. This monotonic learning pattern may cause the lack of intelligence for a particular particle, which makes it unable to deal with different complex situations. This paper presents a novel algorithm, called self-learning particle swarm optimizer (SLPSO), for global optimization problems. In SLPSO, each particle has a set of four strategies to cope with different situations in the search space. The cooperation of the four strategies is implemented by an adaptive learning framework at the individual level, which can enable a particle to choose the optimal strategy according to its own local fitness landscape. The experimental study on a set of 45 test functions and two real-world problems show that SLPSO has a superior performance in comparison with several other peer algorithms.     

Scalable influence maximization for independent cascade model in large-scale social networks

Influence maximization, defined by Kempe et al. (SIGKDD 2003), is the problem of finding a small set of seed nodes in a social network that maximizes the spread of influence under certain influence cascade models. The scalability of influence maximization is a key factor for enabling prevalent viral marketing in large-scale online social networks. Prior solutions, such as the greedy algorithm of Kempe et al. (SIGKDD 2003) and its improvements are slow and not scalable, while other heuristic algorithms do not provide consistently good performance on influence spreads. In this article, we design a new heuristic algorithm that is easily scalable to millions of nodes and edges in our experiments. Our algorithm has a simple tunable parameter for users to control the balance between the running time and the influence spread of the algorithm. Our results from extensive simulations on several real-world and synthetic networks demonstrate that our algorithm is currently the best scalable solution to the influence maximization problem: (a) our algorithm scales beyond million-sized graphs where the greedy algorithm becomes infeasible, and (b) in all size ranges, our algorithm performs consistently well in influence spread—it is always among the best algorithms, and in most cases it significantly outperforms all other scalable heuristics to as much as 100–260% increase in influence spread.     

Choline Acetyltransferase Induces the Functional Regeneration of the Salivary Gland in Aging SAMP1/Kl -/- Mice

Salivary gland dysfunction induces salivary flow reduction and a dry mouth, and commonly involves oral dysfunction, tooth structure deterioration, and infection through reduced salivation. This study aimed to investigate the impact of aging on the salivary gland by a metabolomics approach in an extensive aging mouse model, SAMP1/Klotho -/- mice. We found that the salivary secretion of SAMP1/Klotho -/- mice was dramatically decreased compared with that of SAMP1/Klotho WT (+/+) mice. Metabolomics profiling analysis showed that the level of acetylcholine was significantly decreased in SAMP1/Klotho -/- mice, although the corresponding levels of acetylcholine precursors, acetyl-CoA and choline, increased. Interestingly, the mRNA and protein expression of choline acetyltransferase (ChAT), which is responsible for catalyzing acetylcholine synthesis, was significantly decreased in SAMP1/Klotho -/- mice. The overexpression of ChAT induced the expression of salivary gland functional markers (α–amylase, ZO-1, and Aqua5) in primary cultured salivary gland cells from SAMP1/Klotho +/+ and -/- mice. In an in vivo study, adeno-associated virus (AAV)-ChAT transduction significantly increased saliva secretion compared with the control in SAMP1/Klotho -/- mice. These results suggest that the dysfunction in acetylcholine biosynthesis induced by ChAT reduction may cause impaired salivary gland function     

Na+ and/or Cl− Toxicities Determine Salt Sensitivity in Soybean (Glycine max (L.) Merr.), Mungbean (Vigna radiata (L.) R. Wilczek), Cowpea (Vigna unguiculata (L.) Walp.), and Common Bean (Phaseolus vulgaris L.)

Grain legumes are important crops, but they are salt sensitive. This research dissected the responses of four (sub)tropical grain legumes to ionic components (Na⁺ and/or Cl⁻) of salt stress. Soybean, mungbean, cowpea, and common bean were subjected to NaCl, Na⁺ salts (without Cl⁻), Cl⁻ salts (without Na⁺), and a “high cation” negative control for 57 days. Growth, leaf gas exchange, and tissue ion concentrations were assessed at different growing stages. For soybean, NaCl and Na⁺ salts impaired seed dry mass (30% of control), more so than Cl⁻ salts (60% of control). All treatments impaired mungbean growth, with NaCl and Cl⁻ salt treatments affecting seed dry mass the most (2% of control). For cowpea, NaCl had the greatest adverse impact on seed dry mass (20% of control), while Na⁺ salts and Cl⁻ salts had similar intermediate effects (~45% of control). For common bean, NaCl had the greatest adverse effect on seed dry mass (4% of control), while Na⁺ salts and Cl⁻ salts impaired seed dry mass to a lesser extent (~45% of control). NaCl and Na⁺ salts (without Cl⁻) affected the photosynthesis (P_n) of soybean more than Cl⁻ salts (without Na⁺) (50% of control), while the reverse was true for mungbean. Na⁺ salts (without Cl⁻), Cl⁻ salts (without Na⁺), and NaCl had similar adverse effects on P_n of cowpea and common bean (~70% of control). In conclusion, salt sensitivity is predominantly determined by Na⁺ toxicity in soybean, Cl⁻ toxicity in mungbean, and both Na⁺ and Cl⁻ toxicity in cowpea and common bean.