Selection of Coffee Shop Business Locations Using the Analytical Hierarchy Process Method

The Coffee Shop business is one of the trending businesses in Indonesia, so competition in this business field can be said to be increasing rapidly. In order to get a strategic business location, the majority of decision makers are wrong in choosing the location of their business, this is due to the lack of analysis and to the data from the location survey and the lack of decision-making limitations in analyzing the survey data. For this reason, it is necessary to create a system, where this system uses the Analytical Hierarchy Process (AHP) method to assist in processing survey data. The application of the Analytical Hierarchy Process (AHP) method in determining the location of the Coffee Shop business is determined using 7 (criteria) criteria including rental prices, buildings, clean water, accessibility, distance to offices, internet connections and electricity sources. The final result of the process using the AHP method is ranking of several alternative locations that have been set, and several alternative locations get the highest global weight, it becomes recommendations for the development of this coffee shop business

Challenges and Their Practices in Adoption of Hybrid Cloud Computing: An Analytical Hierarchy Approach

Cloud computing adoption provides various advantages for companies. In particular, hybrid cloud shares the advantages of both the public and private cloud technologies because it combines the private in-house cloud with the public on-demand cloud. In order to obtain benefits from the opportunities provided by the hybrid cloud, organizations want to adopt or develop novel capabilities. Maturity models have proved to be an exceptional and easily available method for evaluating and improving capabilities. However, there is a dire need for a robust framework that helps client organizations in the adoption and assessment of hybrid cloud. Therefore, this research paper aims to present a taxonomy of the challenging factors faced by client organizations in the adoption of hybrid cloud. Typically, such a taxonomy is presented on the basis of obtained results from the empirical analysis with the execution of analytical hierarchy process (AHP) method. From the review of literature and empirical study, in total 13 challenging factors are recognized and plotted into four groups: “Lack of Inclination,” “Lack of Readiness,” “Lack of Adoption,” and “Lack of Satisfaction.” The AHP technique is executed to prioritize the identified factors and their groups. By this way, we found that “Lack of Adoption” and “Lack of Satisfaction” are the most significant groups from the identified challenging factors. Findings from AHP also show that “public cloud security concern” and “achieving QoS” are the upper ranking factors confronted in the adoption of hybrid cloud mechanism by client organizations because their global weight (0.201) is greater than those of all the other reported challenging factors. We also found out 46 practices to address the identified challenges. The taxonomy developed in this study offers a comprehensive structure for dealing with hybrid cloud computing issues, which is essential for the success and advancement of client and vendor organizations in hybrid cloud computing relationships.

Slugging Fatigue Assessment for Steel Lazy Wave Risers

The objective of this paper is to introduce a new analysis methodology for assessment of riser fatigue due to slugging. Under certain flow regimes, a multiphase (oil-gas-water) flow can result in slug flow, in which a sequence of relatively high density slugs and relatively low density bubbles propagate along the flowline and the riser. The variation of slug and bubble density at a location with time is random, and slug characteristics can also change significantly along the riser length. Due to local and global weight variations, the riser undergoes cycles of bending which cause fatigue. By explicitly modeling full spatial and temporal variability and randomness of slugs, the new analysis method is significantly more accurate than other methods and it captures physics of riser's slugging response. The slugging fatigue of a steel lazy wave riser was analyzed in Orcaflex software by modeling a repeating pair of slug and bubble with constant slug and bubble densities and associated lengths over the 3-hour simulation time. A separate slug train was propagated in five sub-segments of the riser. To model a more accurate and realistic representation of slugging behavior, the time series of density was extracted at each node from the multiphase flow simulator Olga. Statistical and spectral analysis of the Olga output showed that assumptions of constant slug-bubble density, and of slug behavior being uniform over long segments of riser are too simplistic. Therefore, full time series of density at each node was input into the riser analysis using the existing capabilities of Orcaflex software. As the Orcaflex slug form approach was computationally expensive, we also developed an extrenal slug loader, which provides same level of accuracy while being computationally fast and full automated. The new method shows that the cyclic riser response at the touchdown point (TDP) is composed of two parts. One is the relatively short period (~20-60 seconds) fluctuations that occur because of local weight variations as a slug-bubble passes a riser node. The other is the relatively long period (~10-30 minutes) fluctuations that occur due to global weight variations, which are due to spatial integration of density time series over the lower catenary. These long period fluctuations drive the TDP fatigue. Preliminary field measurements with an ROV, while inducing temporary slugging in the riser, confirmed analytical predictions of long period and high amplitude motions at hog bend. This paper presents a new and significantly more accurate method for analyzing riser fatigue due to slugging. Previously unknown behavior of very long period and high amplitude riser motions is identified and explained. SLWR response to slugging can be an important contributor to the overall fatigue design budget especially at the TDP. This work reflects ExxonMobil's on-going efforts to ensure that we maintain safe designs as we adopt systems new to us in new and challenging environments.

An Improved Term Weighting Method Based on Relevance Frequency for Text Classification

As a vital step of text classification (TC) task, the assignment of term weight has a great influence on the performance of TC. Currently, masses of term weighting schemes can be utilized, such as term frequency-inverse documents frequency (TF-IDF) and term frequency-relevance frequency (TF-RF), and they are all consisted of local part (TF) and global part (e.g., IDF, RF). However, most of these schemes adopt the logarithmic processing on their respective global parts, and it is natural to consider whether the logarithmic processing apply to all these schemes or not. Actually, for a specific term weighting scheme, due to its different ratio of local weight and global weight resulting from logarithmic processing, it usually shows diverse text clasification results on different text sets, which presents poor robustness. To explore the influence of logarithmic processing imposed on the global weight on the classification result of term weighting schemes, TF-RF is selected as the representative because it can achieve a better performance among these schemes adopting logarithmic processing. Then, two propositions along with corresponding methods about the relation between TF part and RF part are proposed based on TF-RF. In addition, two groups of experiments are conducted on the two methods. The first group of experiments proves that one method (denoted as TF-ERF) is more helpful to the improvement than the other one (denoted as ETF-RF). The second group of experiments shows that TF-ERF not only ourperforms TF-RF but also obtains better performance than other existing term weighting schemes.

A Study on the Strategic Decision Making Used in the Revitalization of Fishing Village Tourism: Using A’WOT Analysis

As society has developed, fishing villages that have relied solely on traditional fishing have found themselves on the verge of extinction. Therefore, efforts are being made to transform fishing villages into areas with various functions including recreation, tourism, and education. In this regard, the main purpose of this study is to analyze the relative importance and priorities of the multi-criteria decision-making (MCDM) process used in the revitalization of fishing village tourism. To this end, the A’WOT (AHP/SWOT) hybrid approach, developed in combination with the SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis and the AHP (Analytic Hierarchy Process) method, was used to determine the significant factors. The results of the study demonstrated that the ‘opportunities’ and ‘strengths’ areas are relatively important when it comes to the priority of sustainable development. We also identified the high importance in terms of global weight of both ‘Increased demand for leisure, rest and ecotourism’ and ‘Possession of natural resources of diverse and distinctive fishing villages by sea and region’ as sustainable ways to revitalize fishing communities. This study demonstrates that with appropriate data and an applicable systematic process, the A’WOT approach can adequately show where intervention is most needed. The study shows that the application of tourism in the current context has the potential to approach the issue of fishing village tourism. Furthermore, this study is meaningful in that it quantifies the importance of fishing village tourism attributes by using a systematic approach, and it concludes with suggesting where the emphasis should be placed on policy and strategy.

Sustainable Quality of Life Criteria for Ledang National Park Community: Fuzzy Approach

Recently, there is a rising concern among researchers regarding the issue of sustainable criteria for quality of life (QoL). As it gains more interest, the issue becomes highly debated worldwide especially with regards to the national park community area. The aim of this study is to assess the identified sustainable criteria for QoL, particularly for the surrounding community of Ledang National Park (LNP) using the fuzzy Analytical Network Process (ANP). The fuzzy ANP was employed based on graded mean integration of representation and canonical representation of multiple operations to derive both local and global weights. To show the feasibility of the proposed method, three decision makers (DMs) were identified from the relevant agencies to assess three main criteria using linguistic evaluation via pairwise comparison process. In addition, nine sub-criteria were also investigated and analysed thoroughly using six steps of the fuzzy ANP towards achieving the sustainable criteria for QoL assessment. Based on the numerical analysis, it was found that the sub-criterion health(c32) has the highest global weight with a score of 0.184, which indicates that this sub-criterion is the biggest contributor to achieve the sustainability of QoL. The results also revealed the overall total score of 73.14%, thus placing LNP in the ‘moderately sustainable’ category. In the future, the entire investigated sub-criteria are suggested to be maintained and used to measure the sustainability of QoL. The findings from this study can be used to guide and assist the relevant authorities for future development planning in studied areas.

PERFORMANCE STUDY OF GLOBAL WEIGHT WINDOW GENERATOR BASED ON PARTICLE DENSITY UNIFORMITY

The variance reduction techniques are necessary for Monte Carlo calculations in which obtaining a detailed calculation result for a large and complex model is required. The GVR method named as global weight window generator (GWWG) was proposed by the FDS team. In this paper, two typical calculation examples, ISPRA-Fe benchmark in SINBAD (Shielding Integral Benchmark Archive Database) and TF Coils (Toroidal Field coils) of European HCPB DEMO (Helium Cooled Pebble Bed demonstration fusion plant), are used to study the performance of GWWG method. It can be seen from the calculation results that the GWWG method has a significant effect in accelerating the Monte Carlo calculation. Especially when the global convergence calculation results are needed, the acceleration effect (FOMG) can reach 105 or more. It proves that the GWWG method is an effective tool for deep-penetration simulations using Monte Carlo method.

APPLICATION OF SUPERMC3.2 TO PRELIMINARY NEUTRONICS ANALYSIS FOR EUROPEAN HCPB DEMO

In the D-T fueled tokamak, the neutrons not only carry the approximately 80% energy released in the per fusion reaction, but also are the source of radioactivity in the fusion system. Therefore, high-fidelity neutronics simulation is required to support such reactor design and safety analysis. In the present work, taking European HCPB DEMO (Helium Cooled Pebble Bed demonstration fusion plant) developed by KIT (Karlsruhe Institute of Technology) as an example, the preliminary neutronics analysis covering the assessments of NWL (neutron wall loading), TBR (tritium breeding ratio), nuclear power generation, radiation loads on PFCs (plasma-facing components) and TFCs (toroidal field coils) has been carried out by using SuperMC in the case of both unbiased and biased simulations. The preliminary results indicate that the blanket scheme could satisfy the design requirements in terms of TBR and shielding of inboard blankets. Specially, a speed-up by ~164 times in the calculation for thick shielding region (TFC region) is achieved by using global weight windows generated via GWWG in SuperMC. In addition, compared to MCNP, SuperMC shows advantages in accurate and efficient modeling of complex system, efficient calculation and 3D interactive visualization.