Search results for: extraction of logical rules

Authors: Diana M.L. Wong

Abstract:

This paper presents an integrated case based and rule based reasoning method for car faulty diagnosis. The reasoning method is done through extracting the past cases from the Proton Service Center while comparing with the preset rules to deduce a diagnosis/solution to a car service case. New cases will be stored to the knowledge base. The test cases examples illustrate the effectiveness of the proposed integrated reasoning. It has proven accuracy of similar reasoning if carried out by a service advisor from the service center.

Keywords: component; case based reasoning (CBR), rule basedreasoning (RBR), decision support systems, diagnosis tool.

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Authors: Dharell B. Siano, Wendy C. Mateo, Victorino T. Taylan, Francisco D. Cuaresma

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Biofuel is one of the renewable energy sources adapted by the Philippine government in order to lessen the dependency on foreign fuel and to reduce carbon dioxide emissions. Rain tree pods were seen to be a promising source of bioethanol since it contains significant amount of fermentable sugars. The study was conducted to establish the complete procedure in processing rain tree pods for village level hydrous bioethanol production. Production processes were done for village level hydrous bioethanol production from collection, drying, storage, shredding, dilution, extraction, fermentation, and distillation. The feedstock was sundried, and moisture content was determined at a range of 20% to 26% prior to storage. Dilution ratio was 1:1.25 (1 kg of pods = 1.25 L of water) and after extraction process yielded a sugar concentration of 22 ⁰Bx to 24 ⁰Bx. The dilution period was three hours. After three hours of diluting the samples, the juice was extracted using extractor with a capacity of 64.10 L/hour. 150 L of rain tree pods juice was extracted and subjected to fermentation process using a village level anaerobic bioreactor. Fermentation with yeast (Saccharomyces cerevisiae) can fasten up the process, thus producing more ethanol at a shorter period of time; however, without yeast fermentation, it also produces ethanol at lower volume with slower fermentation process. Distillation of 150 L of fermented broth was done for six hours at 85 °C to 95 °C temperature (feedstock) and 74 °C to 95 °C temperature of the column head (vapor state of ethanol). The highest volume of ethanol recovered was established at with yeast fermentation at five-day duration with a value of 14.89 L and lowest actual ethanol content was found at without yeast fermentation at three-day duration having a value of 11.63 L. In general, the results suggested that rain tree pods had a very good potential as feedstock for bioethanol production. Fermentation of rain tree pods juice can be done with yeast and without yeast.

Keywords: Fermentation, hydrous bioethanol, rain tree pods, village level.

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Authors: Susannah G. Fleming Lionel Tarassenko

Abstract:

The photoplethysmogram (PPG) is the pulsatile waveform produced by the pulse oximeter, which is widely used for monitoring arterial oxygen saturation in patients. Various methods for extracting the breathing rate from the PPG waveform have been compared using a consistent data set, and a novel technique using autoregressive modelling is presented. This novel technique is shown to outperform the existing techniques, with a mean error in breathing rate of 0.04 breaths per minute.

Keywords: Autoregressive modelling, breathing rate, photoplethysmogram, pulse oximetry.

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Authors: Su Myat Marlar Soe, May Paing Paing Zaw

Abstract:

It has been defined that the “network is the system". This implies providing levels of service, reliability, predictability and availability that are commensurate with or better than those that individual computers provide today. To provide this requires integrated network management for interconnected networks of heterogeneous devices covering both the local campus. In this paper we are addressing a framework to effectively deal with this issue. It consists of components and interactions between them which are required to perform the service fault management. A real-world scenario is used to derive the requirements which have been applied to the component identification. An analysis of existing frameworks and approaches with respect to their applicability to the framework is also carried out.

Keywords: To diagnose the possible network faults by using thepredetermined rules.

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Authors: Anu Paul, Varghese Paul

Abstract:

The focal aspire of e-Government (eGovt) is to offer citizen-centered service delivery. Accordingly, the citizenry consumes services from multiple government agencies through national portal. Thus, eGovt is an enterprise with the primary business motive of transparent, efficient and effective public services to its citizenry and its logical structure is the eGovernment Enterprise Architecture (eGEA). Since eGovt is IT oriented multifaceted service-centric system, EA doesn’t do much on an automated enterprise other than the business artifacts. Service-Oriented Architecture (SOA) manifestation led some governments to pertain this in their eGovts, but it limits the source of business artifacts. The concurrent use of EA and SOA in eGovt executes interoperability and integration and leads to Service-Oriented e-Government Enterprise (SOeGE). Consequently, agile eGovt system becomes a reality. As an IT perspective eGovt comprises of centralized public service artifacts with the existing application logics belong to various departments at central, state and local level. The eGovt is renovating to SOeGE by apply the Service-Orientation (SO) principles in the entire system. This paper explores IT perspective of SOeGE in India which encompasses the public service models and illustrated with a case study the Passport service of India.

Keywords: Enterprise Architecture, Service-Oriented e-Government Enterprise, Service Interface Layer, Service Model.

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Authors: Debashree Guha, Debjani Chakraborty

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The aim of this paper is to adopt a compromise ratio (CR) methodology for fuzzy multi-attribute single-expert decision making proble. In this paper, the rating of each alternative has been described by linguistic terms, which can be expressed as triangular fuzzy numbers. The compromise ratio method for fuzzy multi-attribute single expert decision making has been considered here by taking the ranking index based on the concept that the chosen alternative should be as close as possible to the ideal solution and as far away as possible from the negative-ideal solution simultaneously. From logical point of view, the distance between two triangular fuzzy numbers also is a fuzzy number, not a crisp value. Therefore a fuzzy distance measure, which is itself a fuzzy number, has been used here to calculate the difference between two triangular fuzzy numbers. Now in this paper, with the help of this fuzzy distance measure, it has been shown that the compromise ratio is a fuzzy number and this eases the problem of the decision maker to take the decision. The computation principle and the procedure of the compromise ratio method have been described in detail in this paper. A comparative analysis of the compromise ratio method previously proposed [1] and the newly adopted method have been illustrated with two numerical examples.

Keywords: Compromise ratio method, Fuzzy multi-attributesingle-expert decision making, Fuzzy number, Linguistic variable

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Authors: E. Movahednejad, F. Ommi

Abstract:

Droplet size distributions in the cold spray of a fuel are important in observed combustion behavior. Specification of droplet size and velocity distributions in the immediate downstream of injectors is also essential as boundary conditions for advanced computational fluid dynamics (CFD) and two-phase spray transport calculations. This paper describes the development of a new model to be incorporated into maximum entropy principle (MEP) formalism for prediction of droplet size distribution in droplet formation region. The MEP approach can predict the most likely droplet size and velocity distributions under a set of constraints expressing the available information related to the distribution. In this article, by considering the mechanisms of turbulence generation inside the nozzle and wave growth on jet surface, it is attempted to provide a logical framework coupling the flow inside the nozzle to the resulting atomization process. The purpose of this paper is to describe the formulation of this new model and to incorporate it into the maximum entropy principle (MEP) by coupling sub-models together using source terms of momentum and energy. Comparison between the model prediction and experimental data for a gas turbine swirling nozzle and an annular spray indicate good agreement between model and experiment.

Keywords: Droplet, instability, Size Distribution, Turbulence, Maximum Entropy

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Authors: M. Gomaa Abdoelatef, Robert M. Field, Lee, Yong-Kwan

Abstract:

Growing human population has placed increased demands on water supplies and spurred a heightened interest in desalination infrastructure. Key elements of the economics of desalination projects are thermal and electrical inputs. With growing concerns over use of fossil fuels to (indirectly) supply these inputs, coupling of desalination with nuclear power production represents a significant opportunity. Individually, nuclear and desalination technologies have a long history and are relatively mature. For desalination, Reverse Osmosis (RO) has the lowest energy inputs. However, the economically driven output quality of the water produced using RO, which uses only electrical inputs, is lower than the output water quality from thermal desalination plants. Therefore, modern desalination projects consider that RO should be coupled with thermal desalination technologies (MSF, MED, or MED-TVC) with attendant steam inputs to permit blending to produce various qualities of water. A large nuclear facility is well positioned to dispatch large quantities of both electrical and thermal power. This paper considers the supply of thermal energy to a large desalination facility to examine heat balance impact on the nuclear steam cycle. The APR1400 nuclear plant is selected as prototypical from both a capacity and turbine cycle heat balance perspective to examine steam supply and the impact on electrical output. Extraction points and quantities of steam are considered parametrically along with various types of thermal desalination technologies to form the basis for further evaluations of economically optimal approaches to the interface of nuclear power production with desalination projects. In our study, the thermodynamic evaluation will be executed by DE-TOP, an IAEA sponsored program. DE-TOP has capabilities to analyze power generation systems coupled to desalination plants through various steam extraction positions, taking into consideration the isolation loop between the nuclear and the thermal desalination facilities (i.e., for radiological isolation).

Keywords: APR1400, Cogeneration, Desalination, DE-TOP, IAEA, MED, MED-TVC, MSF, RO.

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Authors: Takashi Mitsuishi, Koji Saigusa

Abstract:

This paper presents circular polar coordinates transformation of periodic fuzzy membership function. The purpose is identification of domain of periodic membership functions in consequent part of IF-THEN rules. Proposed methods in this paper remove complicatedness concerning domain of periodic membership function from defuzzification in fuzzy approximate reasoning. Defuzzification on circular polar coordinates is also proposed.

Keywords: Defuzzification, periodic membership function, polar coordinates transformation.

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Authors: Satoshi Shimizu, Kazuaki Yamaguchi, Toshiki Saitoh, Sumio Masuda

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Some fast exact algorithms for the maximum weight clique problem have been proposed. Östergard’s algorithm is one of them. Kumlander says his algorithm is faster than it. But we confirmed that the straightforwardly implemented Kumlander’s algorithm is slower than O¨ sterga˚rd’s algorithm. We propose some improvements on Kumlander’s algorithm.

Keywords: Maximum weight clique, exact algorithm, branch-andbound, NP-hard.

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Authors: J. Chumee, D. Seeburin

Abstract:

The cellulose was extracted from pomelo peel and an etherification reaction used for converting cellulose to carboxymethyl cellulose (CMC). The pomelo peel was refluxed with 0.5 M HCl and 1 M NaOH solution at 90°C for 1 h and 2 h, respectively. The cellulose was bleached with calcium hypochlorite and used as precursor. The precursor was soaked in mixed solution between isopropyl alcohol and 40%w/v NaOH for 12 h. After that, chloroacetic acid was added and reacted at 55°C for 6 h. The optimum condition was 5 g of cellulose: 0.25 mole of NaOH : 0.07 mole of ClCH2COOH with 78.00% of yield. Moreover, the product had 0.54 of degree of substitution (DS).

Keywords: Pomelo peel, Carboxymethyl cellulose, Cellulose.

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Authors: Sung Ho Ha, Seong Hyeon Joo

Abstract:

Data mining techniques have been used in medical research for many years and have been known to be effective. In order to solve such problems as long-waiting time, congestion, and delayed patient care, faced by emergency departments, this study concentrates on building a hybrid methodology, combining data mining techniques such as association rules and classification trees. The methodology is applied to real-world emergency data collected from a hospital and is evaluated by comparing with other techniques. The methodology is expected to help physicians to make a faster and more accurate classification of chest pain diseases.

Keywords: Data mining, medical decisions, medical domainknowledge, chest pain.

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Authors: Fazl Ullah, Rahmat Ullah

Abstract:

This paper shows a comprehensive learning focused on the optimization of gas production in shale gas reservoirs through hydraulic fracturing. Shale gas has emerged as an important unconventional vigor resource, necessitating innovative techniques to enhance its extraction. The key objective of this study is to examine the influence of fracture parameters on reservoir productivity and formulate strategies for production optimization. A sophisticated model integrating gas flow dynamics and real stress considerations is developed for hydraulic fracturing in multi-stage shale gas reservoirs. This model encompasses distinct zones: a single-porosity medium region, a dual-porosity average region, and a hydraulic fracture region. The apparent permeability of the matrix and fracture system is modeled using principles like effective stress mechanics, porous elastic medium theory, fractal dimension evolution, and fluid transport apparatuses. The developed model is then validated using field data from the Barnett and Marcellus formations, enhancing its reliability and accuracy. By solving the partial differential equation by means of COMSOL software, the research yields valuable insights into optimal fracture parameters. The findings reveal the influence of fracture length, diversion capacity, and width on gas production. For reservoirs with higher permeability, extending hydraulic fracture lengths proves beneficial, while complex fracture geometries offer potential for low-permeability reservoirs. Overall, this study contributes to a deeper understanding of hydraulic cracking dynamics in shale gas reservoirs and provides essential guidance for optimizing gas production. The research findings are instrumental for energy industry professionals, researchers, and policymakers alike, shaping the future of sustainable energy extraction from unconventional resources.

Keywords: Fluid-solid coupling, apparent permeability, shale gas reservoir, fracture property, numerical simulation.

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Authors: Rein Kuusik, Grete Lind

Abstract:

Generator of hypotheses is a new method for data mining. It makes possible to classify the source data automatically and produces a particular enumeration of patterns. Pattern is an expression (in a certain language) describing facts in a subset of facts. The goal is to describe the source data via patterns and/or IF...THEN rules. Used evaluation criteria are deterministic (not probabilistic). The search results are trees - form that is easy to comprehend and interpret. Generator of hypotheses uses very effective algorithm based on the theory of monotone systems (MS) named MONSA (MONotone System Algorithm).

Keywords: data mining, monotone systems, pattern, rule.

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Authors: Weng Ian Ho, Seng Fat Wong

Abstract:

In recent years, Radio Frequency Identification (RFID) is followed with interest by many researches, especially for the purpose of indoor positioning as the innate properties of RFID are profitable for achieving it. A lot of algorithms or schemes are proposed to be used in the RFID-based positioning system, but most of them are lack of environmental consideration and it induces inaccuracy of application. In this research, a lot of algorithms and schemes of RFID indoor positioning are discussed to see whether effective or not on application, and some rules are summarized for achieving accurate positioning. On the other hand, a new term “Noise Factor" is involved to describe the signal loss between the target and the obstacle. As a result, experimental data can be obtained but not only simulation; and the performance of the positioning system can be expressed substantially.

Keywords: Indoor positioning, LANDMARC, noise factors, RFID.

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Authors: Monika Chuchro, Maciej Dwornik

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The extraction of meaningful information from image could be an alternative method for time series analysis. In this paper, we propose a graphical analysis of time series grouped into table with adjusted colour scale for numerical values. The advantages of this method are also discussed. The proposed method is easy to understand and is flexible to implement the standard methods of pattern recognition and verification, especially for noisy environmental data.

Keywords: graphical analysis, time series, seasonality, noisy environmental data

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Authors: Ahmad T. Al-Taani

Abstract:

Car failure detection is a complicated process and requires high level of expertise. Any attempt of developing an expert system dealing with car failure detection has to overcome various difficulties. This paper describes a proposed knowledge-based system for car failure detection. The paper explains the need for an expert system and the some issues on developing knowledge-based systems, the car failure detection process and the difficulties involved in developing the system. The system structure and its components and their functions are described. The system has about 150 rules for different types of failures and causes. It can detect over 100 types of failures. The system has been tested and gave promising results.

Keywords: Expert system, car failure diagnosis, knowledgebasedsystem, CLIPS.

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Authors: Rui Qiu, Giles Hardy, Dong Qu, Robert Trengove, Manjree Agarwal, YongLin Ren

Abstract:

Phytophthora cinnamomi (P. c) is a plant pathogenic oomycete that is capable of damaging plants in commercial production systems and natural ecosystems worldwide. The most common methods for the detection and diagnosis of P. c infection are expensive, elaborate and time consuming. This study was carried out to examine whether species specific and life cycle specific volatile organic compounds (VOCs) can be absorbed by solid-phase microextraction fibers and detected by gas chromatography that are produced by P. c and another oomycete Pythium dissotocum. A headspace solid-phase microextraction (HS-SPME) together with gas chromatography (GC) method was developed and optimized for the identification of the VOCs released by P. c. The optimized parameters included type of fiber, exposure time, desorption temperature and desorption time. Optimization was achieved with the analytes of P. c+V8A and V8A alone. To perform the HS-SPME, six types of fiber were assayed and compared: 7μm Polydimethylsiloxane (PDMS), 100μm Polydimethylsiloxane (PDMS), 50/30μm Divinylbenzene/CarboxenTM/Polydimethylsiloxane DVB/CAR/PDMS), 65μm Polydimethylsiloxane/Divinylbenzene (PDMS/DVB), 85μm Polyacrylate (PA) fibre and 85μm CarboxenTM/ Polydimethylsiloxane (Carboxen™/PDMS). In a comparison of the efficacy of the fibers, the bipolar fiber DVB/CAR/PDMS had a higher extraction efficiency than the other fibers. An exposure time of 16h with DVB/CAR/PDMS fiber in the sample headspace was enough to reach the maximum extraction efficiency. A desorption time of 3min in the GC injector with the desorption temperature of 250°C was enough for the fiber to desorb the compounds of interest. The chromatograms and morphology study confirmed that the VOCs from P. c+V8A had distinct differences from V8A alone, as did different life cycle stages of P. c and different taxa such as Pythium dissotocum. The study proved that P. c has species and life cycle specific VOCs, which in turn demonstrated the feasibility of this method as means of

Keywords: Gas chromatography, headspace solid-phase microextraction, optimization, volatile compounds.

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Authors: Victoria A. Bakhtina

Abstract:

At a time of growing market turbulence and a strong shifts towards increasingly complex risk models and more stringent audit requirements, it is more critical than ever to maintain the highest quality of financial and credit information. IFC implemented an approach that helps increase data integrity and quality significantly. This approach is called “Screening". Screening is based on linking information from different sources to identify potential inconsistencies in key financial and credit data. That, in turn, can help to ease the trials of portfolio supervision, and improve overall company global reporting and assessment systems. IFC experience showed that when used regularly, Screening led to improved information.

Keywords: Information Integrity, Information Quality, Business Rules, Portfolio Management

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Authors: Alexander Denzler, Marcel Wehrle, Andreas Meier

Abstract:

A knowledge base stores facts and rules about the world that applications can use for the purpose of reasoning. By applying the concept of granular computing to a knowledge base, several advantages emerge. These can be harnessed by applications to improve their capabilities and performance. In this paper, the concept behind such a construct, called a granular knowledge cube, is defined, and its intended use as an instrument that manages to cope with different data types and detect knowledge domains is elaborated. Furthermore, the underlying architecture, consisting of the three layers of the storing, representing, and structuring of knowledge, is described. Finally, benefits as well as challenges of deploying it are listed alongside application types that could profit from having such an enhanced knowledge base.

Keywords: Granular computing, granular knowledge, hierarchical structuring, knowledge bases.

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Authors: Ali Shojaei-Fard

Abstract:

In this paper we consider quantum motion integrals depended on the algebraic reconstruction of BPHZ method for perturbative renormalization in two different procedures. Then based on Bogoliubov character and Baker-Campbell-Hausdorff (BCH) formula, we show that how motion integral condition on components of Birkhoff factorization of a Feynman rules character on Connes- Kreimer Hopf algebra of rooted trees can determine a family of fixed point equations.

Keywords: Birkhoff Factorization, Connes-Kreimer Hopf Algebra of Rooted Trees, Integral Renormalization, Lax Pair Equation, Rota- Baxter Algebras.

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Authors: Federico Cabitza, Bernardo Dal Seno

Abstract:

In this paper DJess is presented, a novel distributed production system that provides an infrastructure for factual and procedural knowledge sharing. DJess is a Java package that provides programmers with a lightweight middleware by which inference systems implemented in Jess and running on different nodes of a network can communicate. Communication and coordination among inference systems (agents) is achieved through the ability of each agent to transparently and asynchronously reason on inferred knowledge (facts) that might be collected and asserted by other agents on the basis of inference code (rules) that might be either local or transmitted by any node to any other node.

Keywords: Knowledge-Based Systems, Expert Systems, Distributed Inference Systems, Parallel Production Systems, Ambient Intelligence, Mobile Agents.

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Authors: Ε. Giovanis

Abstract:

In this paper we present, propose and examine additional membership functions for the Smoothing Transition Autoregressive (STAR) models. More specifically, we present the tangent hyperbolic, Gaussian and Generalized bell functions. Because Smoothing Transition Autoregressive (STAR) models follow fuzzy logic approach, more fuzzy membership functions should be tested. Furthermore, fuzzy rules can be incorporated or other training or computational methods can be applied as the error backpropagation or genetic algorithm instead to nonlinear squares. We examine two macroeconomic variables of US economy, the inflation rate and the 6-monthly treasury bills interest rates.

Keywords: Forecast , Fuzzy membership functions, Smoothingtransition, Time-series

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Authors: Ε. Giovanis

Abstract:

In this paper we propose and examine an Adaptive Neuro-Fuzzy Inference System (ANFIS) in Smoothing Transition Autoregressive (STAR) modeling. Because STAR models follow fuzzy logic approach, in the non-linear part fuzzy rules can be incorporated or other training or computational methods can be applied as the error backpropagation algorithm instead to nonlinear squares. Furthermore, additional fuzzy membership functions can be examined, beside the logistic and exponential, like the triangle, Gaussian and Generalized Bell functions among others. We examine two macroeconomic variables of US economy, the inflation rate and the 6-monthly treasury bills interest rates.

Keywords: Forecasting, Neuro-Fuzzy, Smoothing transition, Time-series

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Authors: Kunyanuth Kularbphettong, Phanu Waraporn, Cholticha Tongsiri

Abstract:

This research aims to create a model for analysis of student motivation behavior on e-Learning based on association rule mining techniques in case of the Information Technology for Communication and Learning Course at Suan Sunandha Rajabhat University. The model was created under association rules, one of the data mining techniques with minimum confidence. The results showed that the student motivation behavior model by using association rule technique can indicate the important variables that influence the student motivation behavior on e-Learning.

Keywords: Motivation behavior, e-learning, moodle log, association rule mining.

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Authors: S. A. Naeini, M. M. Shojaedin

Abstract:

Oil leakage from the pipelines and the tanks carrying them, or during oil extraction, could lead to the changes in the characteristics and properties of the soil. In this paper, conducting a series of experimental cyclic triaxial tests, the effects of oil contamination on the liquefaction potential of sandy soils is investigated. The studied specimens are prepared by mixing the Firoozkuh sand with crude oil in 4, 8 and 12 percent by soil dry weight. The results show that the oil contamination up to 8% causes an increase in the soil liquefaction resistance and then with increase in the contamination, the liquefaction resistance decreases.

Keywords: Cyclic triaxial test, Liquefaction resistance, Oil contamination, Sandy soil.

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Authors: Helene Le Cadre

Abstract:

Three service providers in competition, try to optimize their quality of service / content level and their service access price. But, they have to deal with uncertainty on the consumers- preferences. To reduce their uncertainty, they have the opportunity to buy information and to build alliances. We determine the Shapley value which is a fair way to allocate the grand coalition-s revenue between the service providers. Then, we identify the values of β (consumers- sensitivity coefficient to the quality of service / contents) for which allocating the grand coalition-s revenue using the Shapley value guarantees the system stability. For other values of β, we prove that it is possible for the regulator to impose a per-period interest rate maximizing the market coverage under equal allocation rules.

Keywords: Alliance, Shapley value, Stability, Repeated game, Interest rate.

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Authors: Abdulrahim Shamayleh

Abstract:

In this work, the surgical theater of a local hospital in KSA was analyzed using simulation. The focus was on attempting to answer questions related to how many Operating Rooms (ORs) to open and to analyze the performance of the surgical theater in general and mainly the Post Anesthesia Care Unit (PACU) to assist making decisions regarding PACU staffing. The surgical theater consists of ten operating rooms and the PACU unit which has a maximum capacity of fifteen beds. Different sequencing rules to sequence the surgical cases were tested and the Longest Case First (LCF) were superior to others. The results of the different alternatives developed and tested can be used by the manager as a tool to plan and manage the OR and PACU

Keywords: Operating room, post anesthesia care unit, PACUstaffing, sequencing, healthcare

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Authors: Swetha Kurup, Sridhar G., Sridhar V.

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In this paper we present a novel technique for data hiding in binary document images. We use the concept of entropy in order to identify document specific least distortive areas throughout the binary document image. The document image is treated as any other image and the proposed method utilizes the standard document characteristics for the embedding process. Proposed method minimizes perceptual distortion due to embedding and allows watermark extraction without the requirement of any side information at the decoder end.

Keywords: Entropy, Steganography, Watermarking.

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Authors: Luciano Nieddu, Giuseppe Manfredi

Abstract:

In this paper a Pattern Recognition algorithm based on a constrained version of the k-means clustering algorithm will be presented. The proposed algorithm is a non parametric supervised statistical pattern recognition algorithm, i.e. it works under very mild assumptions on the dataset. The performance of the algorithm will be tested, togheter with a feature extraction technique that captures the information on the closed two-dimensional contour of an image, on images of industrial mineral ores.

Keywords: K-means, Industrial ores classification, Invariant Features, Supervised Classification.

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