Order scheduling in dedicated and flexible machine environments

Order scheduling models are relatively new in the field of scheduling. Consider a facility with m parallel machines that can process k different products (job types). Each machine can process a given subset of different product types. There are n orders from n different clients. Each order requests specific quantities of the various different products that can be produced concurrently on their given subsets of machines; it may have a release date, a weight and a due date. Preemptions may be allowed. An order can not be shipped until the processing of all the products for the order has been completed. Thus, the finish time of an order is the time when the last job of the order has been completed. Even though the idea is somewhat new that order scheduling measures the overall completion time of a set of jobs (i.e., an order requesting different product types) instead of the individual completion time of each product type for any given order, many applications require that decision-makers consider orders rather than the individual product types in orders. Research into order scheduling models is motivated by their various real-life applications in manufacturing systems, equipment maintenance, computing systems, and other industrial contexts, where the components of each order can be processed concurrently on the parallel machines. In this research, two cases of order scheduling models are studied, namely, the fully dedicated environment in which each machine can produce one and only one product type, and the fully flexible machine environment in which each machine can produce all product types. With different side constraints and objective functions, the two cases include a lot of problems that are of interest. Special interest is focused on the minimization of the total weighted completion time, the number of late orders, the maximum lateness, and so on. On the one hand, polynomial time algorithms are proposed for some problems. One the other hand, for problems that are NP-hard, complexity proofs are shown and heuristics with their worst-case performance and empirical analyses are also presented

Financial fraud detection by using grammar-based multiobjective genetic programming with ensemble learning

Financial fraud is a criminal act, which violates the law, rules or policy to gain unauthorized financial benefit. As an increasingly serious problem, it has attracted a lot of concerns. The major consequences are loss of billions of dollars each year, investor confidence and corporate reputation. Therefore, a study area called Financial Fraud Detection (FFD) is obligatory, in order to prevent the destructive results caused by financial fraud. In general, traditional modeling approaches are applied and based on pre-defined hypothesis testing of causes and effects for FFD problems. In addition, the evaluation criteria are often based on variable significance level or Goodness-of-fit only. FFD has many common features like other data mining problems. It has accumulated vast amounts of data records of different forms (e.g. financial statements or annual reports) over a period of time. It is very difficult to observe the interesting information just by relying on traditional statistical methods. However, data mining techniques can be used to extract implicit, previously unknown and potentially useful patterns, rules or relations from massive data repositories. Such discovered patterns are appropriate to executive leadership, stakeholders and related regulatory agencies to reduce or avoid the losses. As real-life problems, it is not sufficient for FFD to consider only a single criterion (e.g. Goodness-of-fit or accuracy). Instead, FFD can also seek multiple objectives (e.g. accuracy versus interestingness). It is not easy to consider multiple objectives at the same time unless applying combination methods (e.g. linear combination) by assigning different weights to present the importance for each criterion by using data mining techniques with a single evaluation criterion. For example, accuracy is more important than interestingness with weights of 0.9:0.1. But it is still difficult to decide the appropriate or exact values for weights. There-fore, multi-objective data-mining techniques are required to tackle FFD problems. In this study, FFD is targeted, and comprehensively evaluated by a number of methods. The proposed method is based on Grammar-Based Genetic Programming (GBGP), which has been proven to be a powerful data mining technique to generate compact and straightforward results. The major contributions are three improvements of GBGP for FFD problems. First, multi-criteria are considered by integrating the concept of multi-objectives into GBGP. Second, minority prediction is applied to demonstrate the class prediction with unmatched rows in their rules. Lastly, a new meta-heuristic approach is introduced for ensemble learning in order to help users to select patterns from a pool of models to facilitate final decision-making. The experimental results showed the effectiveness of the new approach in four FFD problems including two real-life problems. The major implications and significances of the study can concretely generalize for three points. First, it suggests a new ensemble learning technique with GBGP. Second, it demonstrates the usability of classification rules generated by the proposed method. Third, it provides an efficient multi-objective method for solving FFD problems

Sequence and Structural Analysis of the Chitinase Insertion Domain Reveals Two Conserved Motifs Involved in Chitin-Binding

Chitinases are prevalent in life and are found in species including archaea, bacteria, fungi, plants, and animals. They break down chitin, which is the second most abundant carbohydrate in nature after cellulose. Hence, they are important for maintaining a balance between carbon and nitrogen trapped as insoluble chitin in biomass. Chitinases are classified into two families, 18 and 19 glycoside hydrolases. In addition to a catalytic domain, which is a triosephosphate isomerase barrel, many family 18 chitinases contain another module, i.e., chitinase insertion domain. While numerous studies focus on the biological role of the catalytic domain in chitinase activity, the function of the chitinase insertion domain is not completely understood. Bioinformatics offers an important avenue in which to facilitate understanding the role of residues within the chitinase insertion domain in chitinase function.Twenty-seven chitinase insertion domain sequences, which include four experimentally determined structures and span five kingdoms, were aligned and analyzed using a modified sequence entropy parameter. Thirty-two positions with conserved residues were identified. The role of these conserved residues was explored by conducting a structural analysis of a number of holo-enzymes. Hydrogen bonding and van der Waals calculations revealed a distinct subset of four conserved residues constituting two sequence motifs that interact with oligosaccharides. The other conserved residues may be key to the structure, folding, and stability of this domain.Sequence and structural studies of the chitinase insertion domains conducted within the framework of evolution identified four conserved residues which clearly interact with the substrates. Furthermore, evolutionary studies propose a link between the appearance of the chitinase insertion domain and the function of family 18 chitinases in the subfamily A

Soft Sediment Deformation Structures Triggered by the Earthquakes: Response to the High Frequent Tectonic Events during the Main Tectonic Movements

Typical cases of the soft-sediment deformation structures (SSDSs), triggered by the modern earthquakes to the oldest of paleo-earthquakes in the Mesoproterozoic, have been observed in China. These deformation structures have various geometry morphology, different interior structural architectures and sediment compositions, in centimetre to metre-scales. They are intercalated with the undeformed layers, which are composed of similar sediments of lithology and sedimentary environments. SSDSs are formed during sediments deposited but incompletely consolidated. And they exist in different periods and are closely related to the active or paleo-active faults. They occur nearby the faults and usually have the characteristics nearer to the faults and more. And they distribute parallel to the trending of the active faults and have the characters of the vertical duplication. They have responded to the high-frequency activity of different faults in tectonic movement and are the perfect records of the paleo-active faults

A study of the distobuccal root canal orifice of the maxillary second molars in Chinese individuals evaluated by cone-beam computed tomography

As is commonly understood, the root canal morphology of the maxillary molars is usually complex and variable. It is sometimes difficult to detect the distobuccal root canal orifice of a maxillary second molar with root canal treatment. No literature related to the distobuccal root canals of the maxillary second molars has been published. Objective: To investigate the position of the distobuccal root canal orifice of the maxillary second molars in a Chinese population using cone-beam computed tomography (CBCT). Material and methods: In total, 816 maxillary second molars from 408 patients were selected from a Chinese population and scanned using CBCT. The following information was recorded: (1) the number of root canals per tooth, (2) the distance between the mesiobuccal and distobuccal root canal orifice (DM), (3) the distance between the palatal and distobuccal root canal orifice (DP), (4) the angle formed by the mesiobuccal, distobuccal and palatal root canal orifices (∠PDM). DM, DP and ∠PDM of the teeth with three or four root canals were analyzed and evaluated. Results: In total, 763 (93.51%) of 816 maxillary second molars had three or four root canals. The distance between the mesiobuccal and distobuccal orifice was 0.7 to 4.8 mm. 621 (81.39%) of 763 teeth were distributed within 1.5-3.0 mm. The distance between the palatal and distobuccal orifice ranged from 0.8 mm to 6.7 mm; 585 (76.67%) and were distributed within 3.0-5.0 mm. The angle (∠PDM) ranged from 69. 4º to 174.7º in 708 samples (92.80%), the angle ranged from 90º to 140º. Conclusions: The position of the distobuccal root canal orifice of the maxillary second molars with 3 or 4 root canals in a Chinese population was complex and variable. Clinicians should have a thorough knowledge of the anatomy of the maxillary second molars

Disclosure Analysis for Two-Way Contingency Tables

Ministry of Education, Singapore under its Academic Research Funding Tier 1; SMU Research Offic

Clinical observation of different dosages of dexmedetomidine combined with a target-controlled infusion of propofol in hysteroscopic submucosal myomectomy

ObjectiveThis study aimed to explore the clinical effects of different dosages of dexmedetomidine (Dex) combined with a target-controlled infusion of propofol in hysteroscopic submucosal myomectomy.MethodsNinety patients who underwent hysteroscopic submucosal myomectomy between September 2021 and March 2022 were enrolled and randomly divided into three groups, with 30 patients in each group. Patients in Groups A, B, and C received injections of 0.25, 0.5, or 0.75 µg/kg of Dex, respectively, by intravenous pump over 10 min. After this time, a maintenance dosage of 0.5 µg/kg/h was administered by intravenous infusion until the end of the surgery. Anesthesia was induced using 1.5 mg/kg of propofol and 0.3 µg/kg of sufentanil that were introduced through a laryngeal mask. The plasma concentration of propofol was maintained at 3 µg/ml by target-controlled infusion until the end of the surgery. The mean arterial pressure (MAP), heart rate (HR), and electroencephalographic bispectral index (BIS) were observed when the patient entered the operating room (T0), after catheter indwelling for anesthesia (T1), at the time of cervical dilation (T2), at the time of hysteroscopic surgery (T3), and at the end of the surgery (T4) in all three groups. The total dosage of propofol for induction and maintenance, anesthesia awakening time, orientation recovery time, Visual Analog Scale (VAS) score of the post-awakening uterine contraction pain, and adverse reactions were recorded.ResultsThe intraoperative reductions of MAP and HR in patients were significant in Group C when compared with those in Groups A and B (P < 0.05), and BIS was significantly lower in Group C at T2 and T3 when compared with the baseline measurement at T0 (P < 0.05). The dosage of propofol was significantly higher for Group A than for Groups B and C (P < 0.05). The anesthesia awakening time and orientation recovery time were significantly longer for patients in Group C when compared with patients in Groups A and B (P < 0.05). Within 5–30 min after awakening, the VAS scores in Groups B and C were significantly lower than those for Group A (P < 0.05). The incidence of adverse reactions in Group B was significantly less than that for Groups A and C (P < 0.05).ConclusionThe continuous pumping of 0.5 µg/kg of Dex combined with a target-controlled infusion of propofol in hysteroscopic submucosal myomectomy resulted in positive anesthetic and analgesia effects and fewer adverse reactions. It therefore has high clinical significance