Application of STEEP and Interpretive Structural Modeling in the Design Imagery of Taiwan Public Ceramic Relief Murals

Ceramic relief mural is a contemporary landscape art that is carefully designed based on human nature,culture,and architectural wall space,combined with social customs,visual sensibility,and art.It may also become the main axis of ceramic art in the future.Taiwan public ceramic relief murals(PCRM)are most distinctive with the PCRM pioneered by Pan-Hsiung Chu of Meinong Kiln in 1987.In addition to breaking through the limitations of traditional public ceramic murals,Chu leveraged local culture and sensibility.The theme of art gives PCRM its unique style and innovative value throughout the Taiwan region.This study mainly analyzes and understands the design image of public ceramic murals,taking Taiwan PCRM’s design and creation as the scope,and applies STEEP analysis,that is,the social,technological,economic,ecological,and political-legal environments are analyzed as core factors;eight main important factors in the artistic design image of ceramic murals are evaluated.Then,interpretive structural modeling(ISM)is used to establish five levels,analyze the four main problems in the main core factor area and the four main target results in the affected factor area;and analyze the problem points and target points as well as their causal relationships.It is expected to sort out the relationship between these factors,obtain the hierarchical relationship of each factor,and provide a reference basis and research methods.

Analysis of Ecosystem Degradation Factors in Yuanmou Arid-Hot Valleys Based on Interpretative Structural Model

For ecological restoration and reconstruction of the degraded area, it is an important premise to correctly understand the degradation factors of the ecosystem in the arid-hot valleys. The factors including vegetation degradation, land degradation, arid climate, policy failure, forest fire, rapid population growth, excessive deforestation, overgrazing, steep slope reclamation, economic poverty, engineering construction, lithology, slope, low cultural level, geological hazards, biological disaster, soil properties etc, were selected to study the Yuanmou arid-hot valleys. Based on the interpretative structural model （ISM）, it has found out that the degradation factors of the Yuanmou arid-hot valleys were not at the same level but in a multilevel hierarchical system with internal relations, which pointed out that the degradation mode of the arid-hot valleys was ＂straight （appearance）-penetrating-background＂. Such researches have important directive significance for the restoration and reconstruction of the arid-hot valleys ecosystem.

An Auto-Grading Oriented Approach for Off-Line Handwritten Organic Cyclic Compound Structure Formulas Recognition

Auto-grading,as an instruction tool,could reduce teachers’workload,provide students with instant feedback and support highly personalized learning.Therefore,this topic attracts considerable attentions from researchers recently.To realize the automatic grading of handwritten chemistry assignments,the problem of chemical notations recognition should be solved first.The recent handwritten chemical notations recognition solutions belonging to the end-to-end trainable category suffered fromthe problem of lacking the accurate alignment information between the input and output.They serve the aim of reading notations into electrical devices to better prepare relevant edocuments instead of auto-grading handwritten assignments.To tackle this limitation to enable the auto-grading of handwritten chemistry assignments at a fine-grained level.In this work,we propose a component-detectionbased approach for recognizing off-line handwritten Organic Cyclic Compound Structure Formulas(OCCSFs).Specifically,we define different components of OCCSFs as objects(including graphical objects and text objects),and adopt the deep learning detector to detect them.Then,regarding the detected text objects,we introduce an improved attention-based encoder-decoder model for text recognition.Finally,with these detection results and the geometric relationships of detected objects,this article designs a holistic algorithm for interpreting the spatial structure of handwritten OCCSFs.The proposedmethod is evaluated on a self-collected data set consisting of 3000 samples and achieves promising results.

Is Ziarat a Potential Site for Conventional or Unconventional Energy Resources?

A structural interpretation of the Ziarat block in the Balochistan region （a part of the Suleiman Fold and Thrust Belt） has been carried out using seismic and seismological data. Seismic data consists of nine 2.5D pre-stack migrated seismic lines, whereas the seismological data covers the Fault Plane Solution and source parameters. Structural interpretation describes two broad fault sets of fore and back thrusts in the study area that have resulted in the development of pop-up structures, accountable for the structural traps and seismicity pattern in terms of seismic hazard. Seismic interpretation includes time and depth contour maps of the Dungan Formation and Ranikot group, while seismological interpretation includes Fault Plane Solution, that is correlated with a geological and structural map of the area for the interpretation of the nature of the subsurface faults. Principal stresses are also estimated for the Ranikot group and Dungan Formation. In order to calculate anisotropic elastic properties, the parameters of the rock strength of the formations are first determined from seismic data, along with the dominant stresses （vertical, minimum horizontal, and maximum horizontal）. The differential ratio of the maximum and minimum horizontal stresses is obtained to indicate optimal zones for hydraulic fracturing, and to assess the potential for geothermal energy reservoir prospect generation. The stress maps indicate high values towards the deeper part of the horizon, and low towards the shallower part, attributed to the lithological and structural variation in the area. Outcomes of structural interpretation indicate a good correlation of structure and tectonics from both seismological and seismic methods.

Hydrocarbon Play Assessment of “Oswil” Field, Onshore Niger Delta Region

Hydrocarbon play assessment of any field involves the evaluation of the production capacity of hydrocarbon reservoir unit in the field.This involves detail study of the reservoir petrophysical properties and geological interpretation of structures suitable for hydrocarbon accumulation in the field as observed from seismic reflection images.This study details the assessment of hydrocarbon play in OSWIL field onshore in Niger Delta,with the intent of appraising its productivity using a combination of seismic,well logs,petrophysical parameters and volumetric estimation using proven techniques which involves an integrated methodology.Two reservoir windows“R1”and“R2”were defined from five wells OSWIL-02,04,06,07 and 12.The top and base of each reservoir window was delineated from the wells.Structural interpretation for inline 6975 revealed two horizons(X and Y)and eight faults labelled(F1,F2,F6,F8,F10,F16,F17 and F18).Five faults(F1,F6,F10,F17 and F18)were identified as synthetic faults and dip basin wards while three faults(F2,F8 and F16)were identified as antithetic faults and dips landwards.Time-depth structural map at top of reservoirs R1 and R2 revealed structural highs and closures.These observations are characteristics of growth structures(faults)which depicts the tectonic style of the Niger Delta.Results of petrophysical evaluation for reservoirs“R1”and“R2”across the five wells were analysed.For reservoir“R1”effective porosity values of 27%,26%,23%,20%and 22%were obtained for wells OSWIL-04,12,07,06 and 02 respectively with an average of 23.6%,while for reservoir“R2”effective porosity values of 26%,22%,21%,24%and 23%for wells OSWIL-04,12,07,06 and 02 were obtained respectively with an average of 23.2%.This porosity values correspond with the already established porosity range of 28-32%within the Agbada formation of the Niger Delta.Permeability index of the order(K>100mD)were obtained for both reservoirs across the five wells and is rated very good.Hydrocarbon saturation(Shc)across the five wells averages at 61.6%for reservoir“R1”and 67.4%for reservoir“R2”.Result of petrophysical model for porosity,permeability and water saturation reveal that the reservoir system in R1 and R2 is fault assisted and fluid flow within both reservoirs is aided by presence of effective porosity and faulting.Volumetric estimation for both reservoirs showed that reservoir R1 contains an estimate of 455×106 STB of hydrocarbon in place,while reservoir R2 contains an estimate of 683×106 STB of hydrocarbon in place.These findings impact positively on hydrocarbon production in the field and affirm that the two reservoirs R1 and R2 are highly prospective.

Correction of seismic attribute-based smallstructure prediction errors using GPR data-a case study of the Shuguang Coal Mine,Shanxi

Small structures in coal mine working face is one of the main hidden dangers of safe and effi cient production in coal mine.Currently,seismic exploration is often used as the main method for detecting such structures.However,limited by the accuracy of seismic data processing and interpretation,the interpreted location of small structures is often deviated.Ground-penetrating radar(GPR)can detect small structures accurately,but the exploration depth is shallow.The combination of the two methods can improve the exploration accuracy of small structures in coal mine.Aiming at the 1226#working face of Shuguang coal mine,we propose a method of seismic-attributes based small-structure prediction error correction using GPR data.First,we extract the coherence,curvature,and dip attributes from seismic data,that are sensitive to small structures,then by considering factors such as the eff ective detection range of GPR and detection environment,we select two structures from the prediction results of seismic attributes for GPR detection.Finally,based on the relationship between the positions of small structures predicted by the two methods,we use statistical methods to determine the overall off set distance and azimuth of the small structures in the entire study area and use the results as a standard for correcting each structure position.The results show that the GPR data can be used to correct the horizontal position errors of small structures predicted by seismic attribute analysis.The accuracy of the prediction results is greatly improved,with the error controlled within 5 m and reduced by more than 80%.Therefore,the feasibility of the method proposed in this study is verified.

ISM-based Correlation Analysis of Development Constraints of Forest Resource-exhausted Cities

Forest resource-exhausted cities have to face with various constraints in the acceleration of its urbanization.This paper analyzed major development constraints of these cities,such as unitary economic structure,weakened forest ecological functions,and geographical barriers,and applied ISM method(Interpretive Structural Modeling) to analyze the correlation among the constraints,and gave suggestions for promoting the development of forest resource-exhausted cities.

Analysis on the Structure of Influencing Factors of Sustainable Supply Chain Implementation of Water Diversion Project

The systematic analysis of the hierarchical relationship among the factors affecting the sustainable supply chain implementation of water diversion projects has theoretical value and practical significance for the sustainable development of large-scale water diversion projects. Through the investigation of relevant literature, books, web pages, materials, and discussions with relevant experts and scholars, a total of 23 factors influencing the sustainable supply chain implementation of water diversion projects were identified. Then using ISM (Interpretative Structural Modeling Method) to analyze the causality of each factor, a multi-level hierarchical structure model was obtained. The results showed that: 1) The surface-level influencing factors of the sustainable supply chain implementation of the water diversion project mainly included 8 factors such as water-saving awareness and water-saving intensity in the diversion area, water quality, water pollution and other disasters, effective incentive mechanisms, etc., and surface-level influencing factors were directly related to the sustainable supply chain implementation of water diversion projects. 2) The indirect influencing factors of the sustainable supply chain of water diversion projects included 12 factors such as the water quality and quantity guarantee rate of the supply chain, the government’s enforcement of laws and regulations, water distribution, ecological compensation, and compensation mechanisms for residents in the water source area. Indirect influencing factor scan acts directly on the direct influencing factors, and intervening in the factors that can be controlled by humans is one of the important ways to improve the sustainable operation of water diversion projects. 3) The fundamental influencing factors for the sustainable supply chain implementation of water diversion projects included three factors: Resettlement policy, government financial support, and sound laws and regulations. Deep influencing factors had multi-channel influence and controllability, and intervening in them was the main means to improve the sustainable operation of water diversion projects.

Knowledge-Based Multifaceted Modeling Methodology for Open Complex Giant Systems

In this paper, the structure characteristics of open complex giant systems are concretely analysed in depth, thus the view and its significance to support the meta synthesis engineering with manifold knowledge models are clarified. Furthermore, the knowledge based multifaceted modeling methodology for open complex giant systems is emphatically studied. The major points are as follows: (1) nonlinear mechanism and general information partition law; (2) from the symmetry and similarity to the acquisition of construction knowledge; (3) structures for hierarchical and nonhierarchical organizations; (4) the integration of manifold knowledge models; (5) the methodology of knowledge based multifaceted modeling.

COMPLEXITY OF SYSTEM MAINTAINABILITY ANALYSIS BASED ON THE INTERPRETIVE STRUCTURAL MODELING METHODOLOGY： TRANSDISCIPLINARY APPROACH

This paper outlines a diagnostic approach to quantify the maintainability of a Commercial off-the-Shelf （COTS）-based system by analyzing the complexity of the deployment of the system components. Interpretive Structural Modeling （ISM） is used to demonstrate how ISM supports in identifying and understanding interdependencies among COTS components and how they affect the complexity of the maintenance of the COTS Based System （CBS）. Through ISM analysis we have determined which components in the CBS contribute most significantly to the complexity of the system. With the ISM, architects, system integrators, and system maintainers can isolate the COTS products that cause the most complexity, and therefore cause the most effort to maintain, and take precautions to only change those products when necessary or during major maintenance efforts. The analysis also clearly shows the components that can be easily replaced or upgraded with very little impact on the rest of the system.

Toward equation structural modeling:an integration of interpretive structural modeling and structural equation modeling

Interpretive structural modeling(ISM)is an interactive process in which a malformed(bad structured)problem is structured into a comprehensive systematic model.Yet,despite many advantages that ISM provides,this method has some shortcomings,the most important one of which is its reliance on participants’intuition and judgment.This problem undermines the validity of ISM.To solve this problem and further enhance the ISM method,the present study proposes a method called equation structural modeling(ESM),which draws on the capacities of structural equation modeling(SEM).As such,ESM provides a statistically verifiable framework and provides a graphical,hierarchical and intuitive model.

Barriers to big data analytics (BDA) implementation in manufacturing supply chains

Big data analysis(BDA)can increase the capability of supply chain analysis of manufacturing companies.Therefore,many manufacturing companies want to use BDA,but it has been seen that BDA implementation is difficult,especially in developing countries due to the existence of various barriers related to finance,government regulations,etc.This paper aims to investigate the barriers to BDA implementation in Iranian companies.In literature,limited work has been done on identifying barriers to implementing BDA in developing countries.In this regard,34 barriers were identified to BDA adoption in Iran by employing a literature review and feedback received from experts.Then,the most important barriers(14)were analyzed using integrated Interpretive Structural Modeling and MICMAC approach.Results show that two barriers;namely,lack of sufficient knowledge of senior managers and weakness of governance policies,are the most significant.Finally,crucial policy measures and recommendations are proposed to assist managers and government bodies.

Post-evaluation of a water pollution control plan： methodology and case study

China has developed more than 20 water pollution control plans for river basins （RBWPs） since 1996. However, the implementation has generally lagged. This paper proposes a three-step, post-evaluation methodology to analyze the implementation result of a RBWP and its influential factors. First, a multi-attribute evaluation method based on an index system is established to score the enforcement results of a RBWP. Indicators measure how well a RBWP has achieved its objectives, which include water quality compliance, pollution load control, project construction, financial inputs, and related management requirements. Second, an interpretive structural model is used to detect the significant factors that affect RBWP implementation. This model can effectively analyze the cause-effect chain and hierarchical relationship among variables. Five groups of factors were identified, namely, plan preparation, water resource endowment, policy, institution, and management. Both qualitative and quantitative methods are employed in the third step to evaluate the extent to which these factors have influenced the execution result of a RBWP, including pre-post contrast, scenario analysis, and correlation analysis. This research then post-evaluated the implementation of the Huai River Basin water pollution control plans （H-RBWPs） over a period of 10 years as a case study. Results showed that the implementation of the H-RBWPs was unsatisfactory during 2001–2005, although it improved during 2006–2010. The poor execution of these plans was partially caused by the underestimation of regional economic development in combination with ineffective industrial structure adjustment policies. Therefore, this case study demonstrates the feasibility and flexibility of the proposed post-evaluation methodology.

Evaluation of liquefaction-induced lateral displacement using Bayesian belief networks

Liquefaction-induced lateral displacement is responsible for considerable damage to engineered structures during major earthquakes.Therefore,an accurate estimation of lateral displacement in liquefaction-prone regions is an essential task for geotechnical experts for sustainable development.This paper presents a novel probabilistic framework for evaluating liquefaction-induced lateral displacement using the Bayesian belief network(BBN)approach based on an interpretive structural modeling technique.The BBN models are trained and tested using a wide-range casehistory records database.The two BBN models are proposed to predict lateral displacements for free-face and sloping ground conditions.The predictive performance results of the proposed BBN models are compared with those of frequently used multiple linear regression and genetic programming models.The results reveal that the BBN models are able to learn complex relationships between lateral displacement and its influencing factors as cause-effect relationships,with reasonable precision.This study also presents a sensitivity analysis to evaluate the impacts of input factors on the lateral displacement.