Earticle

In this paper, an iterative learning control topic for a kind of singular distributed parameter system with forgetting with time-delay which initial value can vary in a little space has been discussed. And a high level algorithm is extended and proven, using Green formula and Gronwall inequality, that it is suitable for the given system. Convergence of the proposed approach is analyzed and the uniform boundedness of tracking error is obtained in this paper. Numerical simulation is presented for a parabolic partial differential equations solved using ILC based on Eular difference format. At present, the application research of ILC method to the singular distributed parameter system with forgetting factor with time-delay is less. So this paper expands the scope of research for singular system and iterative learning control. Numerical example is given to illustrate the effectiveness of the proposed method.

With the advancements in technology, there is a paradigm shift in the outlook, usage, provision, and access of e-services. This has led to increased availability of services through electronic media as e-services, e-government services, e-businesses, e-commerce, and many more. It is imperative to ascertain the quality of such services regularly against internationally accepted guidelines, standards, and tools to verify whether it is satisfying, increasing user expectations and technological advancements. This research investigates the current status of the quality of e-services in Oman by considering key quality dimensions that affect the services in the country using web diagnostic tools. The study not only benchmarks against international standards but also gives an insight into any meager aspects of quality of e-service in Oman. The study concluded that selected e-services in Oman performed at adequate or superior levels in some metrics; however, they fell short in a few metrics.

Forecasting quality of complex products is a major concern for quality engineers and enterprises' decision-makers. But only a few researchers have investigated how multiple linear regression analysis can improve forecasts. This article presents a predictive control model for personalized forecasting system of complex product quality using multiple linear regression analysis. First, this paper compares the performance of personalized forecasting system for product quality which leads to a better understanding of the applicability of the forecasting model. Second, this paper identifies the effect of predictive control model of multiple linear regression analysis on forecasting accuracy. Then, an example shows the feasibility of using predictive control model in complex product quality personalized forecasting. Finally, it makes a conclusion that the approved prediction system embraces superiority over the prediction of the quality factors and manufacturing resources.

In recent years, China's wind power industry has developed rapidly, however, factor of economic operation of the wind power project is complex, it is necessary to define the influence degree of factors and correlation. To improve the analysis and management of economic operation of the wind power project, the DEMATEL - ISM method for wind power projects in various factors for identification and analysis, identification of the factors that affect wind projects economic operation model was constructed, according to the multilevel hierarchical structure model is established for analysis. Results show that the influence factors of wind energy resources is the deepest level, in the actual wind power economy should focus on it for analysis; Five economic factors such as profitability for chain type influencing factors, two factors restricting influence each other, in the actual wind power project should be focused on it. This article can provide the basis for enterprise managers at all levels of management decision-making and reference.

Impulse buying as an unplanned purchasing decision is influenced by several factors. This study explores the relationship between store atmosphere and impulse buying behavior (IBB). It also examines how demographic variables such as age, gender, and education affect the relationship between store atmosphere and IBB. Mall intercept technique was used to collect data from over seven hundred shoppers from eighteen mega stores in Pakistan using self administered questioners. In order to analyze the data and test the Hypothesis, Structure Equation Modeling (SEM) technique was used. The results suggest that store atmosphere has positive relationship and significant influence on IBB. Additionally, it reveals that only one demographic variable i.e. age has substantial influence on IBB while other variables such as gender and education bear insignificant relationship with IBB. Age moderates the relationship between store atmosphere and IBB. This study is a valuable addition in the existing literature and the findings of the study would be helpful in making different selling and retailing decisions. From a managerial perspective, it is recommended that marketers and the retail managers can considerably enrich the IBB through improving the store environments. In contrast to the common studies that research the impact of store atmospheres on IBB, this research mainly takes into account the demographic variables as moderators.

For the dynamic of the number of rescue nodes, the number of person at the rescue node, the number and location of rescue boats, the uncertainty of rescue time (travel time of boats and rescue time of workers), the paper established a dynamic fuzzy rescue time Location-Allocation Problem (LRP) model. To ensure that the decision makers could make new decisions in a very short period of time according to the dynamic data update. A matching hybrid genetic algorithm containing heuristic rule was introduced according the characteristics above. The algorithm used three-stage real-code that represents the search order of boats. The search order and the heuristic rule determined the rescue completed moment of each rescue nodes. The simulated test analysis shows the validity and the correctness of the model and algorithm.

The financially reputed, global financial powerhouses, such as the United Kingdom, Germany, China, etc, have invested more than $3,000 million in fintech worldwide. Fin-tech, so called ‘financial tech,’ is a portmanteau of ‘finance’ and ‘technology,’ referring to the financial service where various techniques have been introduced, such as bank transfer, personal finance asset management, crowdfunding, and mobile payments. A global financial hub, the United Kingdom, is emerging as a center of fin-tech start-ups, where investments are concentrated. Recently, approximately $800 million of investments have been intensively made in fin-tech start-ups of the UK and Ireland, showing more than 600% in a growth rate. Cash transactions account for nearly 85% worldwide, so the credit card fee market seems yet to be a highly potential market. Given the credit card industry has earned about $48 billion of fees last year, it is predicted that enterprises’ desire for the fee market innovation will much change. For fin-tech, security is a prerequisite. It is because if security is not guaranteed, no one knows what security threat will occur. Fin-tech is just like a double-edged sword it’s easy access but security must be guaranteed for users at the same time. Thus, it is necessary to blend convenience and security. The reality is that changes in the financial environment are made clearly. In addition, with the specialization and diversification of financial needs, it will be required to devise the thing that will meet the needs for new financial services from a number of customers and prosumers.

For solving the picture misappropriation problem in e-commerce, this paper proposes a content-based copyright detection method. In the method, a picture is smoothed by bilateral filter to ensure the integrity of its key points, and the shape feature and texture feature are extracted by Hu moment and Gabor filter respectively. Finally copyright-infringing pictures are detected by calculating the Euclidean distance and we use fuzzy heuristics to measure similarity between the query and the database images. The test dataset is crawled from the largest e-commerce website (Taobao.com). The copyright-infringing pictures can be detected by the method and the average accuracy reaches 91%, achieved the desired effect.

Due to the normal forecasting methods for subgrade settlement using observation data have different applicabilities, and the predicting results has bigger volatility and lower accuracy. In view of the above problems, based on the twin support vector regression tool, the settlement prediction model is established by combining with the measured roadbed settlement data; The related parameters of the prediction model are given and compared with the standard support vector regression machine, the comparison tests show that the twins support vector regression is a new method to predict the settlement of the roadbed, and is superior in forecasting accuracy to the standard support vector regression.

With the development of information technology, electronic commerce is closely related to People's Daily lives. To improve the efficiency of electric information management has become the key to the development of electronic commerce. Ecological theory and information science as new areas of cross, based on the basic theory of information ecology to build e-commerce system, formulate the related policy, by analyzing the feasibility of the system has better.

This paper proposes a new technique based on reversible watermarking to improve information embedding capacity and security level in medical images. This technique uses two methods namely Image compression and image partitioning techniques. Original image is converted into R-S Vector interms of ones and zeros and it is compressed to provide space for embedding more information. Hash value is calculated from original image to analyze security level. Image partitioning technique divides the image into two parts then secret information is embedded into LSB bits. This image compression and partitioning technique improves the information embedding capacity level and hash output confirms the image integrity level.

BDM-NBI algorithm is proposed in this paper. It focuses on the analysis of a personalized recommendation algorithm that utilizes a weighted bipartite graph suitable for processing big data. To improve the performance of this recommendation algorithm through parallel processing techniques, a sparse matrix partitioning algorithm is then developed that uses the bipartite graph as input. Our algorithm adopts bipartite graph partitioning using a vertex separator method that partitions a high-dimensional sparse matrix into a pseudo-block based diagonal matrix. Then, the recommendation algorithm analyzes all weighted sub-matrices in parallel. We produce the global recommendation weighted matrix by merging all of the sub-matrices in parallel. Experiments with Hadoop show that our algorithm has good approximation for small matrices and excellent scalability.

Understanding the value that customers perceive in an offer, creating value for them, and managing it over time have long been recognized as essential elements of a firm’s business strategy. Identifying what an individual customer seeks from a service also helps a firm with formulating its value proposition. The purpose of this paper is to extend this line of research to consider user satisfaction, brand trust, as mediating variables in the context of using mobile phone that relate customers perceived value and brand loyalty. It is also to investigate the roles of product knowledge and self-efficacy on the constructs. Thus, this study investigates the importance of sub-dimensions of perceived value and brand loyalty. The main findings show that the positive linkage between satisfaction, brand trust, and brand loyalty in the mobile phone users is substantiated.

The user interest model is the key technology for us to efficiently obtain personalized high quality resources in huge amounts of data. On the basis of traditional user interest model, combining with the concept of ontology, this paper comes up with a construction method based on ontology semantic tree and space vector method, and its eigenvalue is changing by using forgetting curve. The model describes a theme by using semantic concept tree, and it not only simply to describe the semantic relations between concepts, but also can reflect the user interest drift character. It is more accurate in characterization of user interest, and better reflects the change of user interest, and efficiently improves the quality of network document resource personalized services. Finally the experiment describes the update process of the proposed model by using an example, and illustrates that the proposed model is simple and practical.

The traditional collaborative plotting system is a single user plot in which users are independent of each other, and the data can’t be shared among them. It can’t meet the requirements of multi-users to collaborative plot in the modern society. In this paper, we proposed multi-agent technology applying into the collaborative plotting system, and designed a collaborative plotting system based on web and multi-agent, which can solve the problem of real-time collaborative plotting for multi-users. At the same time, it provides the map editing interactive interface and realizes the dynamic exchange of the plotting information. Also, it supports a wide range of collecting effective plotting data, and realizes a new way of information acquisition. Experiments show that the system based on multi-agent can achieve fast and real-time cooperation under the Web environment, and its response time is short and the system performance is stable.

Fuzzy Neural Networks (FNNs) techniques have been effectively used in applications that range from medical to mechanical engineering, to business and economics. Despite of attracting researchers in recent years and outperforming other fuzzy systems, Adaptive Neuro-Fuzzy Inference System (ANFIS) still needs effective parameter training and rule-base optimization methods to perform efficiently when the number of inputs increase. Moreover, the standard gradient based learning via two pass learning algorithm is prone slow and prone to get stuck in local minima. Therefore many researchers have trained ANFIS parameters using metaheuristic algorithms however very few have considered optimizing the ANFIS rule-base. Mostly Particle Swarm Optimization (PSO) and its variants have been applied for training approaches used. Other than that, Genetic Algorithm (GA), Firefly Algorithm (FA), Ant Bee Colony (ABC) optimization methods have been employed for effective training of ANFIS networks when solving various problems in the field of business and finance.

Considering the imbalance of the economic development, ecological and social resources in the management of economic development, in this study, a general equilibrium is designed to find out the general relationship among those three resources. This research is based on the historical data of Henan Province. And the result will show how social demographics and ecological resources restrain the adjustment of industrial structure reversely. With the view of macroeconomics in general equilibrium theory, this research will dig out the regular existing in variables and draw the diagram explaining how they link with and restrict to each other. In the sample area, the research will give some personal suggestions for economic development management, including, perfecting the planting structure in primary industry, strengthening the resource utilization of the secondary industry, and taking appropriate mitigation measures to the development of the tertiary industry. The results of this study can provide some characteristic thoughts for sustaining economic development.

Cloud computing has the advantages of low cost, large scale, general and scalable. In all areas of the social life and the economic life, the cloud computing is widely used. And the emergence of the cloud computing is another revolution in the information society. With the rapid development of e-commerce, the combination of e-commerce and cloud computing has been proved to be a win-win combination. But, there still are many problems of the e-commerce in the cloud computing environment, especially in logistics. In this paper, we establish the e-commerce logistics evaluation system in the cloud computing. And we use the e-commerce logistics evaluation method to evaluate the logistics in the cloud computing based on the improved entropy method. Finally, the experiments show that the proposed method can be effectively applied to the evaluation of e-commerce logistics in the cloud environment and the evaluation results are objective and effective.

The extraction of similar features based on quality is called pattern discovery to the huge number of terms, phrases and noise. Identifying the better pattern discovery is the major problem to extract the accurate information from the text documents because of the noise and unwanted data present in the text documents. In this paper, pattern discovery is used to find the frequent item sets and reducing the noise from text documents and implement the advanced pattern discovery approach. In this paper, for implementation we use .txt files with unstructured data to find the efficient patterns.

With the continuous rapid growth of national economy and the prominent improvement of people’s income level, people’s consumption concepts and habits have been significantly changed. People also have higher and higher requirements for the quality of life and environment. In recent years, as the safety problems of foods and life products are frequently exposed, the quality safety problem of products also has become a focus. How to eat and use safely becomes the topic that people are most concerned about. So people all cast their eyes to gradually certified pollution-free and green sustainable products. The sustainable product is not just a fashion concept of brand consumption but also of importance significance in solving product quality safety, improving product value, protecting environment and enhancing the international competitiveness of products. In the paper, we first make a survey on consumers’ sustainable product preference by the questionnaire. The paper analyzed the problems existent in consumer sustainable product preference in the form of questionnaire , discussed the mutual relation between corporate green logistics supply and sustainable product production, and put forward beneficial suggestions for corporate green supply chain management.

The application of simulation-optimization technique is merged with viable reality for computation of the scheduling process in a cloud environment. The optical systems are needed to be scheduled for requirement satisfaction of IOT (Internet of Things) services and demand services of QoS. Normally in the rule based scheduling algorithm are widely used to schedule the sequence process efficiently. The significance of environmental factors is simulated with meta-heuristics scheduling and processed under an accurate hypothesis of stochastic processing. In order to overcome the issues of scheduling a heuristic approach is proposed with the function to obtain a feasible high quality scheduling solution. The proposed heuristic algorithm, named INSMG, is performed and analyzed with the other heuristic algorithm. The analysis result shows the proposed algorithm efficiency and possible alternative for solving scheduling issues. This paper aims to provide a more possibilities of sequences, minimize makespan and solutions to solve the scheduling problems. Moreover the scheduling process is evaluated by the improved meta-heuristic GA for better schedules to prove the efficiency and better performances than the existing system.

The optimal scheduling of crude-oil operation in refineries has been researched by various groups during the past decade. Different mixed integer linear programming or mixed nonlinear programming formulations are derived. This paper proposes a novel MINLP formulation with multiple charging tanks charging a distiller overlapingly and oil residency time constraint that is based on multi-operation sequencing with synchronized start time (MOS-SST). It is different from previous formulations because of its consideration for oil residency time constraint and multiple charging tanks charging a distiller overlapingly. A branch and bound algorithm combined with the Lagrangian Relaxation Subgradient Optimization algorithm is proposed to solve this model, resulting in a satisfactory optimal result.

Supply chain integration is widely used by both practitioners and researchers because of its essential role in enhancing the competitive advantage of the supply chain. Organizational competences such as relational competence and information technology (IT) competence have been recognized as factors influencing the promotion of supply chain integration to obtain supply chain performance. This paper extends the stream of research on supply chain management by systematically identifying the antecedents and consequences of supply chain integration between supply chain partners. The results indicate that relational competence and IT competence in the supply chain were positively related to supply chain integration. Information exchange was directly related to supply chain performance. In addition, it had a positive impact on the relationship between organizational competences and supply chain performance through its positive effect on supply chain integration. The results provide strong support for the notion that information exchange and supply chain integration enhance supply chain performance and have important theoretical and practical implications.

Considered the integrate of forward and reverse logistics, the separability of recycle products, the timeliness of recycle products, the paper established a location-routing-inventory control optimization model with batch transportation of recycle products. A matching hybrid genetic algorithm containing heuristic rule was introduced according the characteristics above. The algorithm used three-stage real-code that represents the transport order of vehicles. And the quantity of new products and recycle products will be determined too. The unreasonable solution will be eliminated in the iterative process of genetic algorithm. The simulated test analysis shows the validity and the correctness of the model and algorithm.

Recently, the web users are able to access to web pages in various access environments through various media. However, use of ActiveX and inconformity to the web standards prevent web pages from providing the web users the same functions and designs in various web browsers. In this study, the current status of ActiveX utilization and conformity to the web standards were investigated with the online shopping mall sites and governmental institutions which often employ ActiveX. The result showed that web pages of a number of shopping malls and governmental institutions still use ActiveX and are vulnerable to cross-browsing for not conforming to the web standards

Supply chain has been one of the most popular and efficient ways of exploring more benefits across businesses from the perspective of particular enterprise, with the objective of improving the long-term performance of individual companies. With the rapid development of social media platforms, such as Twitter, Facebook, LinkedIn, etc., social media has become one of the most valuable businesses due to largest user coverage, widest influential dissemination and highest commercial value. From the perspective of enterprises, leveraging social media for e-commerce are gradually being taken seriously. Indeed, social media helps compress the supply chain by eliminating unnecessary intermediate links. In this paper, we consider the roles in Twitter users (i.e., brands and audiences) as the nodes in supply chain, and simulate the social interactions between them as the collaboration decisions among supply chain members. Specifically, we consider social interactions as transactions, and sentiments as trust information. In this way, we tailor the traditional game model for modeling relationships among supply chain members in the context of Twitter, and propose a long-term game model based on trust.

The supplier is an important member in the supply chain. The work of supplier evaluation is also an essential effect for the good operation of the manufacturing supply chain. However, supply chain has some characteristics. They are dynamic composition, the complicated management and the high risk. These characteristics determine that supplier evaluation is complex and difficult. Therefore, in this paper, we study the supplier evaluation and put forward the assessment framework of supply chain evaluation. This assessment framework with new hesitant fuzzy sets can better express the decision maker's preference more accurately and can be applied in more multiple decision making problems. Finally, we apply this method to evaluate the supplier and get the evaluated results. The experiments show that this method can express better the decision maker’s preference more accurately.

Colors are recognized by human vision or visual organ. In particular, many studies show that these colors have been proved to give great influences on cognitive development and emotional formation of children. The subconsciousness of children is detectable by colors and through this, their inner emotions and subconsciousness can be revealed. Children have higher interaction of emotion and feelings with colors than adults. Moreover, children tend to express their subconsciousness through colors. However, children are defenselessly exposed to colors coming from the IT devices due to the broad diffusion of these appliances. Different types of media materials give impact on the emotions and cognitive development of children. Likewise, the colors represented by media materials considerably exert influence on the emotions and cognitive development of children. With this in mind, this study proposes design game graphics through analysis of colors, composition, nature and character of these colors preferred by children.

This paper the regular patterns of chip flow, chip curler radius and thickness under different cutting parameters when processing PE WPC with different wood flour contents under the condition of up milling and down milling. Compared with up milling, down milling has greater impact on chip flow direction and cutting speed. However, there are more dust-shaped chips in the up milling. In the down milling, chip curler has less change with cutting parameters. Only when the feed speed is 14m/min or the cutting speed is 1800m/min, the chip curl radius is larger. The chip thickness increases when the feed speed or the cutting width increases and decreases when the cutting speed increases.