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Purpose: Banyuwangi Regency is intensively optimizing the tourism sector that has enormous natural and cultural potential. The tourism sector has a broad impact (multiplier effect) felt by all layers of businesses, including businesses in the entertainment industry, hospitality and restaurants. These three business sectors will directly affect income through the tourism sector's local tax. The purpose of this study is determine the relationship of the tourist visitation number to the entertainment tax of Banyuwangi Regency, to find out the relationship of the tourist visitation number to the hotel tax of Banyuwangi Regency, to determine the relationship of the tourist visitation number to the restaurant tax of Banyuwangi Regency. Research methods: The analytical method used in this study is Product Moment Correlation Analysis. Results and discussions: The results of this study indicate that the relationship of the Tourist visitation Number (X1) to the Entertainment Tax (Y1) obtained by Pearson product moment value is 0.938 (Very Strong). The relationship of the Tourist visitation Number (X1) to the Hotel Tax (Y2) obtained by Pearson product moment value is 0.955 (Very Strong). The relationship of the Tourist visitation Number (X1) to Restaurant Tax (Y3) obtained by Pearson product moment value from the Correlation Coefficient is 0.889 (Very Strong). Conclusion: The Three tourism taxes had positive correlations with the Tourist visitation

Background Despite documented benefits of contraceptives, uptake among young people aged 20–24 years is high compared to adolescents aged 15–19 years in Malawi. As the world’s population of 15–19-year-olds continues to grow the need to meet the increasing demand for contraceptive services and information that address adolescent-specific needs cannot be underestimated. To inform Sexual and Reproductive health services for the youth, we explored strategies for optimizing uptake of contraceptives among this age group. Methods An exploratory qualitative cross-sectional study was conducted at Nsanje District Hospital and Nyamadzere Community Day Secondary School guided by Social-Ecological Framework to understand strategies that may optimize the uptake of contraceptives among adolescents aged 15–19. Nsanje district was purposively selected based on the reason that it is the second district in Malawi with the highest rate of adolescent childbearing of girls aged 15–19 years. We conducted a Focus Group Discussion (FGD) with 9 traditional leaders, 11 Key Informant Interviews (KIIs) with health workers, 20 In-depth Interviews (IDIs) with 12 adolescents, 4 teachers, and 4 parents. All data were digitally recorded, transcribed verbatim into English. The data was analyzed and managed using deductive thematic analysis guided by Social-Ecological Framework. Results Adolescents suggested accessing contraceptives from local drug stores, pharmacies and hospitals at a health system level and through Youth Centres, clubs, and corners at a Community level. There is a need to ensure a continuous supply of various kinds of contraceptives and the presence of youth-friendly health care workers in the specified areas. Conclusion There is no one way of delivering contraceptives to adolescents. Multiple avenues existent at the health facility and community could be leveraged to optimize delivery and uptake of contraceptives in a manner that is not intimidating to an adolescent while involving key stakeholders.

The aim of this paper is to theoretically evaluate the process of machining metallic materials and at the same time evaluate the cost reduction defined by the evaluation criteria. When cutting conditions and tool durability optimizing, it is necessary to apply certain optimizing criterion within certain restraining conditions. [12] The restrictions are given by technical parameters of a machine, tool, machined material, required quality of machined surface etc. The essential economic criterion is the amount of production cost. The notion of “machinability of materials” is a complex of characteristics of the machined material which is monitored in the view of its fitness for the production in a certain way of machining.

Quick responses in managing peatfire disasters in Indonesia are one key success in mitigating and controlling the risk of peatfire disasters. The aim of this study was to simulate and identify the optimum numbers and locations of fire brigade posts for improving their response times in mitigating peatfire events in Bengkalis Island, Riau, Indonesia. Network analyses were applied in the case of peatfire events on this island. The results of this study may assist local governments and fire brigade teams in developing a strategy to manage peatfires systematically. Hence, the results may contribute to the body of knowledge as a reference in systematically controlling peatfire disasters elsewhere in the world. This study proposed five steps in the identification of appropriate locations of fire brigade posts and performs two main steps to achieve this objective: (i) evaluating existing fire brigade posts’ service coverages; and (ii) developing three scenarios for simulating additions of one, two, and three posts. The results of this study improve fire brigade dispatch time performances as well as expand their service coverage areas from 40.7% to 62.4% within 60 minutes of dispatch time.

Introduction: In addition to its protective role, dressings not only prevent infection, but also accelerate wound healing process. In this study, the influence of optimizing the properties of the calendered needle-punched nonwoven fabrics using the finishing materials of Honey, Aloe Vera, Chitosan and Nano Argentum Nitrate for the end-usage as dressing has been investigated. Methods: The prepared samples of the needle-punched nonwoven fabrics were firstly calendered and then, tested for the fundamental expected physical characteristics in the dressing purpose, i.e. crease recovery magnitude, air permeability, etc. in order to distinct initial optimized sample. In the following, the antimicrobial finishing process was carried out on the primary sample by the four studied finishing materials. The finished samples were finally analyzed simultaneously from the antimicrobial aspect and also, for the same physical properties of the dressing, as tested before, to distinguish the ultimate optimized sample. The bacteria of Staphylococcus aureus and Escherichia coli (E.coli) were also employed for antimicrobial tests. Results: The results demonstrated that combination of four finishing materials of Nano Silver 1%, Aloe-Vera 20%, Honey 7% and Chitosan 1% improved desired properties for wound dressing application in comparison to the other samples from one side and, showed no cellular toxicity and allergy from the other side. The FTIR’s results also implied stretching bonding of hydroxyl group in 3200-3400 wavenumber. Conclusion: The needle-punched nonwoven fabric finished by the recommended antimicrobial materials can be considered as wound dressing, regarding to sufficient physical properties and hygienic condition.

The Slovak automotive industry consists of various companies and suppliers, with different positions in the supply chain for automotive manufacturers. The accuracy of component deliveries and their quality affect the ultimate competitiveness of the entire automotive industry. The creation of strategic partnerships and stable supplier–customer relationships is currently a necessity. The aim of the article is to design the model for optimizing the ratio of the company suppliers in the Slovak automotive industry. The basis for designing the model was the results of our own research focused on the quality and timeliness of component deliveries from various suppliers. Supply chain members work with multiple subcontractors, using multiple subcontractors to supply the same components. We analyzed the overall quality of delivered components at a certain stage of the supply chain. The quality of the supplied components was the sum of all items from all suppliers. The aim of the proposed model is to determine the optimal percentage of individual suppliers of a particular part so as to minimize the overall risk associated with the supply and inventory of a particular part for the customer. Research methodology was focused on identification of the key performance indicators and key risk indicators of components deliveries by different suppliers. Those indicators provide a basis for the effective results of further research. We designed and used an algorithm for preparing and evaluating the model for optimizing the ratio of the company suppliers in the Slovak automotive industry. This research used modeling methods, simulations, and optimization models. The proposed model was verified in the specific conditions of the automotive supply chain. Deliveries from two subcontractors were simulated. Based on the results of the simulations, the optimal supply ratio of the two subcontractors was determined for a specific component of a member of the supply chain at a higher level. The results of the research can be useful for different suppliers in the Slovak automotive industry. By partially modifying the model and adapting it for different conditions in other industries, the model of optimizing the distribution of supply from individual suppliers can be used for other supply chains.

Background Positron emission tomography (PET) imaging with 68Gallium labeled somatostatin analogues (68Ga-DOTA-SSA) plays a key role in neuroendocrine tumor management. The impact of patient size on PET image quality is not well known for PET imaging with 68Ga-DOTA-SSA. The aim of this study is to propose a dose regimen based on patient size that optimizes image quality and yields sufficient image quality for diagnosis. Methods Twenty-one patients (12 males, 9 females) were prospectively included for 68Gallium-DOTA-Tyr3-Octreotate (68Ga-DOTA-TATE) PET/CT, which was acquired in whole body list mode using 6 min per bed position (mbp). The list-mode events were randomly sampled to obtain 1 to 6 mbp PET reconstructions. For semi-quantitative assessment of image quality, the signal-to-noise ratio (SNR) was measured in the liver. The SNR normalized (SNRnorm) for administered activity and mbp was correlated with body mass, length, body mass index, body mass/length, and lean body mass. Three experienced nuclear medicine physicians visually graded image quality using a 4-point scale, and categorically scored the number of somatostatin-receptor positive lesions for each reconstruction. To investigate the impact of image quality on lesion quantification, the mean, maximum, and peak standardized uptake values (SUVs) of one abdominal lesion were measured in the 1 to 6 mbp PET reconstructions. Results Of all patient-dependent parameters, body mass showed the strongest correlation (R2 = 0.6) with SNRnorm. Lesion detectability analysis showed no significant difference for 3-5 mbp compared with the complete 6 mbp PET reconstruction. The SUV measurements showed no significant (p > 0.05) differences across the reconstructions. Visual assessment revealed that an SNR of 6.2 results in PET scans with moderate to good image quality. A non-linear expression was derived to calculate the required (dose × acquisition time) product (DTP) for the chosen SNR level of 6.2 that would yield a more constant image quality. Conclusion Body mass can be used to predict 68Ga-DOTA-TATE PET image quality. The proposed non-linear dose regimen based on body mass standardizes the image quality while maintaining sufficient image quality for diagnosis.

Nowadays, learning-based modeling system is adopted to establish an accurate prediction model for renewable energy resources. Computational Intelligence (CI) methods have become significant tools in production and optimization of renewable energies. The complexity of this type of energy lies in its coverage of large volumes of data and variables which have to be analyzed carefully. The present study discusses different types of Deep Learning (DL) algorithms applied in the field of solar and wind energy resources and evaluates their performance through a novel taxonomy. It also presents a comprehensive state-of-the-art of the literature leading to an assessment and performance evaluation of DL techniques as well as a discussion about major challenges and opportunities for comprehensive research. Based on results, differences on accuracy, robustness, precision values as well as the generalization ability are the most common challenges for the employment of DL techniques. In case of big dataset, the performance of DL techniques is significantly higher than that for other CI techniques. However, using and developing hybrid DL techniques with other optimization techniques in order to improve and optimize the structure of the techniques is preferably emphasized. In all cases, hybrid networks have better performance compared with single networks, because hybrid techniques take the advantages of two or more methods for preparing an accurate prediction. It is recommended to use hybrid methods in DL techniques. Open Access, This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see http://creativecommons.org/licenses/by/4.0/

Smart grid (SG) has been recognized as a promising solution to manage and distribute electricity in the next generation power systems. The large number of devices in power systems make the wired communication a non feasible solution, thus wireless transmission becomes necessary. However this demands a huge portion of radio spectrum. In this work, we aim to provide the secure and reliable SG communication through an efficient spectrum sharing mechanism. Specifically, we consider an underlay transmission and seek to minimize the interference under complete spectrum reuse while guaranteeing the required secrecy rate as well as end to end delay. A mathematical optimization problem is formulated and convex optimization techniques are exploited to find the near optimal solution. Further a suboptimal solution is also proposed to reduce the computational complexity. Simulation results are presented to verify the effectiveness of the proposed schemes.

Everything that science has discovered in technological, medical, functional, video-IT and methodological fields has been given to football professionals in order to make the road to progress smoother. The present research tries to demonstrate that physical training can be optimized using adapted specific tests as means of training in high performance football. From the point of view of physical effort, football falls into the category of mixed sports. More specifically, the energy needed for sustaining effort in competition is provided by all the three energetic systems in different proportions.

This article describes design of algorithm for finding maximum possible speed. Maximum speed of robot's endpoint is 4.4 meters per second, but this speed is achieved rarely by the robot. Robot name is MELFA RV-2DB. Robot has integrated development environment with name RT-Toolbox2. Robot maximum speed is under 1 meter per second in motions, where the trajectory is important. Algorithm analyzes and designs speed optimizing motions on high accuracy motions. Circular motions and motions on straight line require high accuracy of trajectory. In these types of motion trajectory is important. I also describe results and analyses of proposed algorithm in this paper.

In order to make the Economic Production Quantity (EPQ) model more applicable to real-world production and inventory control problems, in this paper we expand this model by assuming that some imperfect items of different product types being produced such as reworks are allowed. In addition, we may have more than one product and supplier along with warehouse space and budget limitation. We show that the model of the problem is a constrained non-linear integer program and propose a genetic algorithm to solve it. Moreover, a design of experiments is employed to calibrate the parameters of the algorithm for different problem sizes. In the end, a numerical example is presented to demonstrate the application of the proposed methodology.

We tested whether principles that describe the allocation of overt behavior, as in choice experiments, also describe the allocation of cognition, as in attention experiments. Our procedure is a cognitive version of the “two-armed bandit choice procedure.” The two-armed bandit procedure has been of interest to psychologists and economists because it tends to support patterns of responding that are suboptimal. Each of two alternatives provides rewards according to fixed probabilities. The optimal solution is to choose the alternative with the higher probability of reward on each trial. However, subjects often allocate responses so that the probability of a response approximates its probability of reward. Although it is this result which has attracted most interest, probability matching is not always observed. As a function of monetary incentives, practice, and individual differences, subjects tend to deviate from probability matching toward exclusive preference, as predicted by maximizing. In our version of the two-armed bandit procedure, the monitor briefly displayed two, small adjacent stimuli that predicted correct responses according to fixed probabilities, as in a two-armed bandit procedure. We show that in this setting, a simple linear equation describes the relationship between attention and correct responses, and that the equation’s solution is the allocation of attention between the two stimuli. The calculations showed that attention allocation varied as a function of the degree to which the stimuli predicted correct responses. Linear regression revealed a strong correlation (r ¬= 0.99) between the predictiveness of a stimulus and the probability of attending to it. Nevertheless there were deviations from probability matching, and although small, they were systematic and statistically significant. As in choice studies, attention allocation deviated toward maximizing as a function of practice, feedback, and incentives. Our approach also predicts the frequency of correct guesses and the relationship between attention allocation and response latencies. The results were consistent with these two predictions, the assumptions of the equations used to calculate attention allocation, and recent studies which show that predictiveness and reward are important determinants of attention.

A new level‐by‐level methodology for flowsheet synthesis presented. In the first level, an initial superstructure is constructed to form a master model. Optimization of the master gives an initial optimal flowsheet, which indicates major structural features. In the second level this initial flowsheet is analyzed using exergy analysis to identify relevent modification options. The Promising options are used to update the intial superstructure, which is optimized to obtain an improved design. The results from the above design process determine the flowsheet of overall system and provide targets for design of subsystems. Design of subsystems forms the third design level. The predetermined of subsystems. Design of subsystems froms the third design level due to use of simplistic models in the previous design levels. The master model is updated and then Optimized again. The overall design process terminates when designs for subsystems can meet the design targets determined by the master model.

Highly efficient Cu(In,Ga)(S,Se)2 photovoltaic thin film solar cells often have a compositional variation of Ga to In in the absorber layer, here described as a Ga-profile. In this work we have studied the role of Ga-profiles in four different models, based on input data from electrical and optical characterizations of an in-house state-of-the-art Cu(In,Ga)Se2 (CIGS) solar cell with power conversion efficiency above 19 %. A simple defect model with mid-gap defects in the absorber layer was compared with models with Ga-dependent defect concentrations and amphoteric defects. In these models optimized single-graded Ga-profiles have been compared with optimized double-graded Ga-profiles. It was found that the defect concentration for effective Shockley-Read-Hall recombination is low for high efficiency CIGS devices and that the doping concentration of the absorber layer, chosen according to the defect model, is paramount when optimizing Ga-profiles. For optimized single-graded Ga-profiles the simulated power conversion efficiency, depending on the model, is 20.5-20.8 %, and the equivalent double-graded Ga-profiles yield 20.6-21.4 %, indicating that the bandgap engineering of the CIGS device structure can lead to improvements in efficiency. Apart from the effects of increased doping in the complex defect models, the results are similar when comparing the complex defect models to the simple defect models.

this paper proposes a radio access network (RAN) selection algorithm for the next generation of wireless networks. The proposed algorithm uses mobile terminal measurements from different radio access technologies to obtain information for multi-criteria decision making between different RANs available to the mobile user. The proposed system uses a novel algorithm designed for decision-making under service parameters, Quality of Service (QoS), and service costs for the mobile user. The algorithm has been implemented within both client and server terminals. Also, an analysis of the results obtained using the new algorithm in 3G and wireless local area networks (WLANs), has been performed.

In business analysis, models are sometimes oversimplified. We pragmatically approach many problems with a single financial objective and include monetary values for non-monetary variables. We enforce constraints which may not be as strict in reality. Based on a case in distributed energy production, we illustrate how we can avoid simplification by modeling multiple objectives, solving it with an NSGA-II algorithm with a novel comparison operator. Advantages include a strengthened focus on the trade-off relation between financial and non-monetary objectives. We conclude that this approach is very applicable in a business analysis setting. © 2010 IEEE.

Resource allocation in bandwidth-sharing networks is inherently complex: the distributed nature of resource allocation management prohibits global coordination for efficiency, i.e., aiming at full resource usage at all times. In addition, it is well recognized that resource efficiency may conflict with other critical performance measures, such as flow delay. Without a notion of optimal (or "near-optimal") behavior, the performance of resource allocation schemes cannot be assessed properly. In previous work, we showed that optimal workload-based (or queue-length based) strategies have certain structural properties (they are characterized by so-called switching curves), but are too complex, in general, to be determined exactly. In addition, numerically determining the optimal strategy often requires excessive computational effort. This raises the need for simpler strategies with "near-optimal" behavior, that can serve as a sensible bench-mark to test resource allocation strategies. We focus on flows traversing the network, sharing the resources on their common path with (independently generated) cross-traffic. Assuming exponentially distributed flow sizes, we show that in many scenarios optimizing under a fluid scaling gives a simple linear switching strategy, that accurately approximates the optimal strategy. When two nodes on the flow path are equally congested, however, fluid scaling is not appropriate, and the corresponding strategy may not even ensure stability. In such cases, we show that the appropriate scaling for efficient workload-based allocations follows a square-root law. Armed with these, we then assess the potential gain that any sophisticated strategy can achieve over standard α-fair strategies, which are representations of common distributed allocation schemes, and confirm that α-fair strategies perform excellently among non-anticipating policies. In particular, we can approximate the optimal policy with a weighted α-fair strategy. © 2008 Elsevier B.V. All rights reserved.

Purpose: To study the feasibility of measuring volumetric changes in the primary tumor on megavoltage-computed tomography (MVCT) during chemoradiation and to examine the correlation with local response. Patients and methods: Fifteen consecutive patients with stage III, inoperable, locally advanced non-small cell lung cancer (NSCLC) were treated in a prospective dose escalation study protocol of concurrent chemoradiation. They were monitored for acute toxicity and evaluated with daily MVCT imaging. The volumetric changes were fitted to a negative exponential resulting in a regression coefficient (RC). Local response evaluation was done with positron emission tomography using the radio-labeled glucose analogue F18 fluorodeoxyglucose (FDG-PET). Results: The mean volume decrease (+/- standard deviation) was 73% (+/- 18%). With a mean treatment time of 42 days this treatment schedule resulted in a mean decrease of 1.74%/day. Of the 13 evaluable patients seven developed a metabolic complete remission (MCR). The mean RC of the patients with MCR is 0.050 versus a mean RC of 0.023 in non-responders (p=0.0074). Using a proposed cut-off value for the RC of 0.0380% of the non-responders will be detected correctly while misclassifying 16.4% of patients who will eventually achieve an MCR. The total cumulative percentage of esophageal grade 3 or more toxicity was 46.7%. Conclusion: The RC derived from volumetric analysis of daily MVCT is prognostic and predictive for local response in patients treated with chemoradiation for a locally advanced NSCLC. Because this treatment schedule is toxic in nearly half of the patient population, MVCT is a tool in the implementation of patient-individualized treatment strategies. (C) 2009 Elsevier Ireland Ltd. All rights reserved. Radiotherapy and Oncology 91 (2009) 438-442

The Simulation/Optimization MOdeling System (SOMOS) has modules adapted for a range of international water resource management needs. The SOMOA module is best for field groundwater and conjunctive water management situations. It employs several analytical simulation models and several optimization methods to give appropriate optimal guidance for situations having sparse data. SOMOA requires understanding of the limitations of common analytical equations. It does not require experience in finite difference or element numerical modeling. SOMOS also has modules ideal for situations in which there is sufficient data for numerical modeling or aquifer and stream -aquifer systems. Emphasized here are SOMOA and its applications for common field-level water management problems. Sample situations include optimizing: minimizing required surface reservoir size for a period of low surface flows in a stream -aquifer system; conjunctive use for blending irrigation waters of different qualities; and artificial injection.

Three well configurations were compared in terms of short-term ground-water contaminant plume containment. These include parallel, octagonal and combination systems. Each system had three extraction wells upgradient and three injection wells downgradient of the contaminant plume. For each system, optimal pumping values and resulting potentiometric surface smoothness were computed for a hypothetical plume. Tested models utilized linear programming optimization and simulation via the response matrix method. The octagonal well configuration required less pumping for a pumping period of 8 days, than did the parallel or combination systems. The octagonal configuration resulted in the smoothest potentiometric surface, in terms of difference in final head at observation wells compared with those at the contaminant source.