Boolean Method Research Articles

공유경제 비즈니스 모델의 가치 요인 분석

On account of multiple causes, including prolonged global economic crisis, addressing environmental pollution and the advent of hyper-connected society, a new paradigm called 'sharing economy' has rapidly emerged. Many startups have attempted to build promising business model based on the sharing economy concept. Nevertheless, successful cases are still very rare in the global level, except for Uber and Airbnb cases. Therefore, this study analyzes necessary causes and sufficient causes for successful settlements in the market through a comparative case analysis on digital matching firms in the sharing economy businesses. For the case study, we compare five successful cases (Uber, Airbnb, Kickstarter, TaskRabbit and DogVacay), three failure cases (Homejoy, Ridejoy and Tuterspree) and a platform cooperativism case (Juno) in accordance with six value attributes of business model including value proposition, market segment, value chain, cost structure and profit potential, value network and competitive strategy. We apply Boolean method to support controlled comparison and eliminate unnecessary attributes. The Boolean analysis result shows that value proposition, cost structure and profit potential, value network and competitive strategy are the essential attributes. Furthermore, the result indicates that each attribute is a necessary condition, where all four conditions should be met simultaneously in order to be successful. With this result, we discuss essential consideration for those who are planning startup based on the sharing economy business model.

IMPLICIT THREE-DIMENSIONAL GEO-MODELLING BASED ON HRBF SURFACE

Abstract. Three-dimensional (3D) geological models are important representations of the results of regional geological surveys. However, the process of constructing 3D geological models from two-dimensional (2D) geological elements remains difficult and time-consuming. This paper proposes a method of migrating from 2D elements to 3D models. First, the geological interfaces were constructed using the Hermite Radial Basis Function (HRBF) to interpolate the boundaries and attitude data. Then, the subsurface geological bodies were extracted from the spatial map area using the Boolean method between the HRBF surface and the fundamental body. Finally, the top surfaces of the geological bodies were constructed by coupling the geological boundaries to digital elevation models. Based on this workflow, a prototype system was developed, and typical geological structures (e.g., folds, faults, and strata) were simulated. Geological modes were constructed through this workflow based on realistic regional geological survey data. For extended applications in 3D modelling of other kinds of geo-objects, mining ore body models and urban geotechnical engineering stratum models were constructed by this method from drill-hole data. The model construction process was rapid, and the resulting models accorded with the constraints of the original data.

Piecewise linear approximations to model the dynamics of adaptation to osmotic stress by food-borne pathogens

Addition of salt to food is one of the most ancient and most common methods of food preservation. However, little is known of how bacterial cells adapt to such conditions. We propose to use piecewise linear approximations to model the regulatory adaptation of Escherichiacoli to osmotic stress. We apply the method to eight selected genes representing the functions known to be at play during osmotic adaptation. The network is centred on the general stress response factor, sigma S, and also includes a module representing the catabolic repressor CRP-cAMP. Glutamate, potassium and supercoiling are combined to represent the intracellular regulatory signal during osmotic stress induced by salt. The output is a module where growth is represented by the concentration of stable RNAs and the transcription of the osmotic gene osmY. The time course of gene expression of transport of osmoprotectant represented by the symporter proP and of the osmY is successfully reproduced by the network. The behaviour of the rpoS mutant predicted by the model is in agreement with experimental data. We discuss the application of the model to food-borne pathogens such as Salmonella; although the genes considered have orthologs, it seems that supercoiling is not regulated in the same way. The model is limited to a few selected genes, but the regulatory interactions are numerous and span different time scales. In addition, they seem to be condition specific: the links that are important during the transition from exponential to stationary phase are not all needed during osmotic stress. This model is one of the first steps towards modelling adaptation to stress in food safety and has scope to be extended to other genes and pathways, other stresses relevant to the food industry, and food-borne pathogens. The method offers a good compromise between systems of ordinary differential equations, which would be unmanageable because of the size of the system and for which insufficient data are available, and the more abstract Boolean methods.

Majority-Inverter Graph: A New Paradigm for Logic Optimization

In this paper, we propose a paradigm shift in representing and optimizing logic by using only majority (MAJ) and inversion (INV) functions as basic operations. We represent logic functions by majority-inverter graph (MIG): a directed acyclic graph consisting of three-input majority nodes and regular/complemented edges. We optimize MIGs via a new Boolean algebra, based exclusively on majority and inversion operations, that we formally axiomatize in this paper. As a complement to MIG algebraic optimization, we develop powerful Boolean methods exploiting global properties of MIGs, such as bit-error masking. MIG algebraic and Boolean methods together attain very high optimization quality. Considering the set of IWLS'05 benchmarks, our MIG optimizer (MIGhty) enables a 7% depth reduction in LUT-6 circuits mapped by ABC while also reducing size and power activity, with respect to similar and-inverter graph (AIG) optimization. Focusing on arithmetic intensive benchmarks instead, MIGhty enables a 16% depth reduction in LUT-6 circuits mapped by ABC, again with respect to similar AIG optimization. Employed as front-end to a delay-critical 22-nm application-specified integrated circuit flow (logic synthesis + physical design) MIGhty reduces the average delay/area/power by 13%/4%/3%, respectively, over 31 academic and industrial benchmarks. We also demonstrate delay/area/power improvements by 10%/10%/5% for a commercial FPGA flow.

Landfill site selection for municipal solid wastes in mountainous areas with landslide susceptibility.

Several cities across the world are located in mountainous and landslide prone areas. Any landfill siting without considering landslide susceptibility in such regions may impose additional environmental adversity. This study was aimed to propose a practical method for selecting waste disposal site that accounts for landslide exposure. The proposed method was applied to a city which is highly proneness to landslide due to its geology, morphology, and climatic conditions. First, information on the previously occurred landslides of the region was collected. Based on this information, proper landslide causative factors were selected and their thematic maps were prepared. Factors' classes were then standardized in 0-1 domain, and thematic layers were weighted by using analytical hierarchy process (AHP). The landslide susceptibility map was prepared afterwards. Unsuitable areas for landfill location were masked in GIS environment by Boolean method, retaining sufficient areas for further evaluation. Nine remaining alternatives were selected through comprehensive field visits and were ranked by using AHP. Consequently, 17 factors in three environmental, economical, and social perspectives were employed. Sensitivity analyses were performed to assess the stability of the alternatives ranking with respect to variations in criterion weights. Based on the obtained landslide susceptible map, nearly 36% of the entire region is proneness to landslide. The prepared Boolean map indicates that potential areas for landfill construction cover 11% of the whole region. The results further indicated that if landslide susceptible areas are not considered in landfill site selection, the potential landfill sites would become more than twice. It can be concluded that if any of these landslide prone sites are selected for landfilling, further environmental disaster would be terminated in the future. It can be further concluded that the proposed method could reasonably well be adjusted to consider landslide exposure when siting a solid waste landfill.

Towards Automatic and Topologically Consistent 3D Regional Geological Modeling from Boundaries and Attitudes

Three-dimensional (3D) geological models are important representations of the results of regional geological surveys. However, the process of constructing 3D geological models from two-dimensional (2D) geological elements remains difficult and is not necessarily robust. This paper proposes a method of migrating from 2D elements to 3D models. First, the geological interfaces were constructed using the Hermite Radial Basis Function (HRBF) to interpolate the boundaries and attitude data. Then, the subsurface geological bodies were extracted from the spatial map area using the Boolean method between the HRBF surface and the fundamental body. Finally, the top surfaces of the geological bodies were constructed by coupling the geological boundaries to digital elevation models. Based on this workflow, a prototype system was developed, and typical geological structures (e.g., folds, faults, and strata) were simulated. Geological modes were constructed through this workflow based on realistic regional geological survey data. The model construction process was rapid, and the resulting models accorded with the constraints of the original data. This method could also be used in other fields of study, including mining geology and urban geotechnical investigations.

The Use of AHP within GIS in Selecting Potential Sites for Water Harvesting Sites in the Azraq Basin—Jordan

The identification of potential sites for water harvesting is an important step towards maximizing water availability and land productivity in the arid and semi-arid areas. This research aimed to select the optimum sites for water harvesting in the Azraq basin of Jordan through the use of GIS techniques. The Azraq basin is characterized by flash floods that involve large quantities of runoff. The selection criteria in this research were based on six parameters identified based on an extensive literature review. Five experts were then asked to evaluate the importance of each criterion. The consistency ratio between the experts opinions was evaluated using the pairwise comparison method and a final weight was computed for each criterion. A water harvesting suitability map was then generated following the weighted linear combination (WLC) method. The sites that are not suitable for water harvesting within the study area were identified and eliminated following the Boolean method, and final water harvesting suitability map was generated. Finally, the findings of this research can be used to assist in the efficient planning of the water resources management to ensure a sustainable development of the water in Jordan and in other areas suffering from water shortages.

Reliability Measures for Tele-Communication System with Redundant Transferring Machine by Using Algebraic Method

There are so many existing methods to obtain system reliability like re-generating point function technique, supplementary variables technique etc., but all these techniques are full of complicated calculations. Keeping above these facts in mind, the authors in this paper have evaluated some reliability parameters for tele-communication system by using Boolean functions technique and algebraic method. Reliability of considered tele-communication system has been evaluated by considering the fact that failures follow arbitrary time distribution. In particular, the reliability expression has also been calculated for Exponential and Weibull distributions. Further, an important reliability parameter namely M.T.T.F. (mean time to failure) has also been calculated. A numerical example with graphical illustrations has been appended at the end to highlight the important results and practical utility of the model.

Procedure of Assessing Usefulness of the Land in the Process of Optimal Investment Location for Multi-family Housing Function

Spatial planning as a typical example of decision-making, resulting in the term land use is a complex and lengthy process. The procedure for assessing the usefulness of the land is associated with the determination of the possibilities and limitations for different types and forms of land use. In the process of determining the optimal use of land, the evaluation of the area usefulness with the use of geo-information was taking account. The purpose of this analysis is to make a choice of the optimal location of the investment, taking into account various criteria with a significant impact on the assessment of the usefulness of the land. The paper presents the possibility of applying procedures for assessing the usefulness of the land as a support tool in the process of planning decision. The procedure and criteria for selecting the optimal investment location for multi-family housing function is presented. The aim is also to present the parameters characterizing them and the possibilities of using geo-information that identify the restrictions and potential uses of the land. The dummy (0,1) maps of usefulness area was developed with the use of Boolean methods for all adopted criteria. The maps are indicating a set of locations that fulfil all the criteria of usefulness. The proposed procedure is also extended through the methods of significance and elimination of superfluous criteria analysis.

The regularity theory of mechanistic constitution and a methodology for constitutive inference

This paper discusses a Boolean method for establishing constitutive regularity statements which, according to the regularity theory of mechanistic constitution, form the core of any mechanistic explanation in neuroscience. After presenting the regularity definition for the constitution relation, the paper develops a set of inference rules allowing one to establish constitutive hypotheses in light of certain kinds of empirical evidence. The general methodology consisting of these rules is characterized as having formed the basis of many successful explanatory projects in neuroscience.

Parking Lot Site Selection: An Opening Gate Towards Sustainable GIS-based Urban Traffic Management

Mismatch between urban development and public parking lots have caused problems in transportation systems and urban traffic so that occupied passages by on-street stopping disrupt smoothing traffic flow. This makes it inevitable to increase the capacity of passages and to devote more space to off-street parking spots. The present study aims at finding the most suitable sites for public parking lots in one of the most crowded cities of western Iran. Before the site selection process is getting started, the area required for construction of new parking lots was estimated using Parking Generation Method. Afterwards, site selection criteria including “distance from travel absorber centers”, “distance from passages”, “the cost of real estate”, and “suitable land uses for parking lots” were determined while “unsuitable land uses for public parking spaces” such as historical monuments were recognized as a constraint factor and excluded from being further analyzed. The selected criteria were then weighted using pair wise comparisons. The map layers were finally overlaid once by Boolean Method. Since the selected spots on the output map had not adequate distribution throughout the study area, the overlaying was done once again by fuzzy Ordered Weighted Average (OWA) by which a total number of four spots were recognized suitable for public parking lots in the city.

Map of potential areas of groundwater by the multi-criteria analysis for the needs for water of the Bayas catchment basin (East of Cte dIvoire)

The watershed located Baya is facing difficulties of drinking water supply. The objective of this study is to develop a model for preferential zone mapping to the implementation of water points. To achieve this objective, a combined approach of Geographic Information System and Multicriteria Analysis has been adopted for the mapping of these preferential. Multi-criteria analysis methods including Boolean method and the linear combination of weights based on pairwise comparisons were used. Two types of indicators were used: The productivity indicator which combines the accessibility, exploitability and availability of groundwater and control indicator, which is represented by the vulnerability to pollution in groundwater. It appears that the preferential zone of future water points implantation covers 84% of the catchment area. When making water productivity map, the calculation of uncertainties parameters show that the most sensitive parameters are: The slope, recharge, induced permeability and total depth. However, the topography, vadose zone and hydraulic conductivity are the most sensitive to the development of the map of vulnerability to pollution. The errors determined on different maps are respectively 12, 20 and 12% for productive zone, vulnerability and preferential zone. Preferential areas cover almost all of the study area and are influenced by the topography, vadose zone and hydraulic conductivity; the margin of error is low. Key words: Geographic information system, multi-criteria analysis, groundwater, vulnerability, catchment of Baya.

Profiling of genetic switches using boolean implications in expression data.

Correlation analysis assuming coexpression of the genes is a widely used method for gene expression analysis in molecular biology. Yet growing extent, quality and dimensionality of the molecular biological data permits emerging, more sophisticated approaches like Boolean implications. We present an approach which is a combination of the SOM (self organizing maps) machine learning method and Boolean implication analysis to identify relations between genes, metagenes and similarly behaving metagene groups (spots). Our method provides a way to assign Boolean states to genes/metagenes/spots and offers a functional view over significantly variant elements of gene expression data on these three different levels. While being able to cover relations between weakly correlated entities Boolean implication method also decomposes these relations into six implication classes. Our method allows one to validate or identify potential relationships between genes and functional modules of interest and to assess their switching behaviour. Furthermore the output of the method renders it possible to construct and study the network of genes. By providing logical implications as updating rules for the network it can also serve to aid modelling approaches.

Process modeling of end mill groove machining based on Boolean method

Helical groove is one of the key structures of end mills. Its grinding process is the hardest and most time-consuming in end mill machining. According to the practical groove-grinding process, a Boolean method to simulate the groove-grinding process is proposed in this paper. The groove model is obtained with the known wheel geometry by a sequence of Boolean operations. Accordingly, the wheel used to machine a desired groove is deduced with the similar method. Based on the Boolean operation results and principles of differential geometry, contact lines of the wheel and groove are illustrated and calculated to optimize the groove-grinding process. Wheel positions relative to the blank are described by a sequence of mathematical coordinates. Wheel profile expressions are built with the corresponding transformation matrixes including groove geometry transformation matrix, cutter tip transformation matrix, and start processing position transformation matrix. Some simulated examples are included to illustrate the presented method.

On spline-based differential quadrature

In the paper Barrera et al. (2014), a boolean sum differential quadrature method (DQM) was proposed by combining a spline interpolation operator having a fundamental function with minimal compact support and a spline quasi-interpolation operator reproducing the polynomials in the spline space. It is a general framework that provides results that differ from the ones obtained by defining specific schemes with structures which depend on the degree of the B-spline to be considered. The main drawback of these boolean sum DQMs is that the number of evaluation points increases quickly with the degree of the B-spline due to the use of a quasi-interpolation operator. We propose a different construction avoiding this problem and derive explicit results for low degree B-splines.

Prediction of Cutter-Workpiece Engagement for Five-Axis Ball-End Milling

Five-axis ball-end milling technology is widely used in many industries such as aerospace, automotive and die-mold for complex surface machining. Despite recent advances in machining technology, productivity in five-axis ball-end milling is still limited due to the high cutting forces and stability. Moreover, cutting forces in machining is determined by extracting the cutter workpiece engagement (CWE) from the in-process workpiece. A discrete boundary representation method is developed. Cutter is firstly divided into disk elements along the tool axis. And in each disk element, boundary representation based exact Boolean method is introduced for extracting complex cutter-workpiece engagements at every cutter location due to its efficiency and speed over other discrete methods. Developed engagement model is proved to calculate complex engagement regions between tool and workpiece efficiently and accurately.

English

The different parameters such as water, soil and climate have an important effect in the decision making and performance of pressurized irrigation systems. The underground and surface water resources in per region have no unique quality and quantity. The Kerman Plain, which has about 7500 km2, is located in the Kerman Province. The irrigation of this plain is done with using the underground water resources which are facing drop in the water level, due to over exploitation. Accordingly, the pressurized irrigation is suggested in order to the prevention of drop the loss trend and increasing irrigation efficiency. The aim of this research is to identify suitable lands for performance of pressurized irrigation system, with the help of remote sensing techniques and geography information system (GIS), in Kerman plain of southeast of Iran. In this research, 2 methods of site selection: logical overlay method –Boolean method- and Arithmetic overlay - proportion percent method are compared and evaluated. On the basis of Boolean site selection model 5% of desert lands for performance of sprinkle irrigation and 25% of lands for drip irrigation and on the basis of arithmetic overlay 15% of lands for performance of sprinkle irrigation and 20% of them for performance of drip irrigation reasonably were recognized. The comparison of these 2 methods with considering the condition of regions showed that arithmetic overlay site selection model is more suitable for recognizing the suitable zones for performance of pressurized irrigation systems.   Key words: Pressurized irrigation, geography information system (GIS), boolean model, proportion percent model, site selection.

Parsimony and Causality

This paper takes issue with the current tendency in the literature on Qualitative Comparative Analysis (QCA) to settle for so-called intermediate solution formulas, in which parsimony is not maximized. I show that there is a tight conceptual connection between parsimony and causality: only maximally parsimonious solution formulas reflect causal structures. However, in order to maximize parsimony, QCA—due to its reliance on Quine-McCluskey optimization (Q-M)—is often forced to introduce untenable simplifying assumptions. The paper ends by demonstrating that there is an alternative Boolean method for causal data analysis, viz. Coincidence Analysis (CNA), that replaces Q-M by a different optimization algorithm and, thereby, succeeds in consistently maximizing parsimony without reliance on untenable assumptions.

Profiling of Genetic Switches using Boolean Implications in Expression Data

Summary Correlation analysis assuming coexpression of the genes is a widely used method for gene expression analysis in molecular biology. Yet growing extent, quality and dimensionality of the molecular biological data permits emerging, more sophisticated approaches like Boolean implications. We present an approach which is a combination of the SOM (self organizing maps) machine learning method and Boolean implication analysis to identify relations between genes, metagenes and similarly behaving metagene groups (spots). Our method provides a way to assign Boolean states to genes/metagenes/spots and offers a functional view over significantly variant elements of gene expression data on these three different levels. While being able to cover relations between weakly correlated entities Boolean implication method also decomposes these relations into six implication classes. Our method allows one to validate or identify potential relationships between genes and functional modules of interest and to assess their switching behaviour. Furthermore the output of the method renders it possible to construct and study the network of genes. By providing logical implications as updating rules for the network it can also serve to aid modelling approaches.

Minimal Realizations of Logic Functions Using Truth Table Method with Distributed Simplification

ABSTRACTIn the conventional method, a truth table (TT) is prepared from the specified logic function. Then it is expressed as the sum of min terms corresponding to the rows in which 1 appears. Finally, this function is further reduced using the Boolean identities. Thus, all the simplifications are concentrated at one place after the TT. This procedure does not always lead to the minimal realization. This paper deals with the minimal realization of logic function using TT in which TT is reduced successively by one variable at a time till all the variables are exhausted. The simplification is carried out, instead at the end of the truth table, at the end of each step of TT reduction. The method is shown to be systematic, and definitely leads to the minimal function. It is simpler in operation than that based on only Boolean identities, Karnaugh map and Quine-McClusky methods, and can handle any number of variables. It is explained with several examples. It is worth introducing as an improvement over the classical TT method in class room teaching.