|Commenced in January 1999||Frequency: Monthly||Edition: International||Paper Count: 70|
Mass customization production increases the difficulty of the production line layout planning. The material distribution process for variety of parts is very complex, which greatly increases the cost of material handling and logistics. In response to this problem, this paper presents an approach of production line layout planning based on complexity measurement. Firstly, by analyzing the influencing factors of equipment layout, the complexity model of production line is established by using information entropy theory. Then, the cost of the part logistics is derived considering different variety of parts. Furthermore, the function of optimization including two objectives of the lowest cost, and the least configuration complexity is built. Finally, the validity of the function is verified in a case study. The results show that the proposed approach may find the layout scheme with the lowest logistics cost and the least complexity. Optimized production line layout planning can effectively improve production efficiency and equipment utilization with lowest cost and complexity.
A city is an intertwined texture from the relationship of different components in a whole which is united in a one, so designing the whole complex and its planning is not an easy matter. By considering that a city is a complex system with infinite components and communications, providing flexible layouts that can respond to the unpredictable character of the city, which is a result of its complexity, is inevitable. Parametric design approach as a new approach can produce flexible and transformative layouts in any stage of design. This study aimed to introduce parametric design as a modern approach to respond to complex urban issues by using descriptive and analytical methods. This paper firstly introduces complex systems and then giving a brief characteristic of complex systems. The flexible design and layout flexibility is another matter in response and simulation of complex urban systems that should be considered in design, which is discussed in this study. In this regard, after describing the nature of the parametric approach as a flexible approach, as well as a tool and appropriate way to respond to features such as limited predictability, reciprocating nature, complex communications, and being sensitive to initial conditions and hierarchy, this paper introduces parametric design.
The performance of the tightening equipment will decline with the working process in manufacturing system. The main manifestations are the randomness and discretization degree increasing of the tightening performance. To evaluate the degradation tendency of the tightening performance accurately, a complexity measurement approach based on Kolmogorov entropy is presented. At first, the states of performance index are divided for calibrating the discrete degree. Then the complexity measurement model based on Kolmogorov entropy is built. The model describes the performance degradation tendency of tightening equipment quantitatively. At last, a study case is applied for verifying the efficiency and validity of the approach. The research achievement shows that the presented complexity measurement can effectively evaluate the degradation tendency of the tightening equipment. It can provide theoretical basis for preventive maintenance and life prediction of equipment.
Inherited complexity is one of the difficult tasks in software engineering field. Further, it is said that there is no physical laws or standard guidelines suit for designing different types of software. Hence, to make the software engineering as a matured engineering discipline like others, it is necessary that it has its own theoretical frameworks and laws. Software designing and development is a human effort which takes a lot of time and considers various parameters for successful completion of the software. The cognitive informatics plays an important role for understanding the essential characteristics of the software. The aim of this work is to consider the fundamental characteristics of the source code of Object-Oriented software i.e. complexity and understandability. The complexity of the programs is analyzed with the help of extracted important attributes of the source code, which is further utilized to evaluate the understandability factor. The aforementioned characteristics are analyzed on the basis of 16 C++ programs by distributing them to forty MCA students. They all tried to understand the source code of the given program and mean time is taken as the actual time needed to understand the program. For validation of this work, Briand’s framework is used and the presented metric is also evaluated comparatively with existing metric which proves its robustness.
For the last decade, researchers have started to focus their interest on Multicast Group Key Management Framework. The central research challenge is secure and efficient group key distribution. The present paper is based on the Bit model based Secure Multicast Group key distribution scheme using the most popular absolute encoder output type code named Gray Code. The focus is of two folds. The first fold deals with the reduction of computation complexity which is achieved in our scheme by performing fewer multiplication operations during the key updating process. To optimize the number of multiplication operations, an O(1) time algorithm to multiply two N-bit binary numbers which could be used in an N x N bit-model of reconfigurable mesh is used in this proposed work. The second fold aims at reducing the amount of information stored in the Group Center and group members while performing the update operation in the key content. Comparative analysis to illustrate the performance of various key distribution schemes is shown in this paper and it has been observed that this proposed algorithm reduces the computation and storage complexity significantly. Our proposed algorithm is suitable for high performance computing environment.
In this work we use the Discrete Proper Orthogonal Decomposition transform to characterize the properties of coupled dynamics in thin-walled beams by exploiting numerical simulations obtained from finite element simulations. The outcomes of the will improve our understanding of the linear and nonlinear coupled behavior of thin-walled beams structures. Thin-walled beams have widespread usage in modern engineering application in both large scale structures (aeronautical structures), as well as in nano-structures (nano-tubes). Therefore, detailed knowledge in regard to the properties of coupled vibrations and buckling in these structures are of great interest in the research community. Due to the geometric complexity in the overall structure and in particular in the cross-sections it is necessary to involve computational mechanics to numerically simulate the dynamics. In using numerical computational techniques, it is not necessary to over simplify a model in order to solve the equations of motions. Computational dynamics methods produce databases of controlled resolution in time and space. These numerical databases contain information on the properties of the coupled dynamics. In order to extract the system dynamic properties and strength of coupling among the various fields of the motion, processing techniques are required. Time- Proper Orthogonal Decomposition transform is a powerful tool for processing databases for the dynamics. It will be used to study the coupled dynamics of thin-walled basic structures. These structures are ideal to form a basis for a systematic study of coupled dynamics in structures of complex geometry.
This work proposes a data-driven multiscale based quantitative measures to reveal the underlying complexity of electroencephalogram (EEG), applying to a rodent model of hypoxic-ischemic brain injury and recovery. Motivated by that real EEG recording is nonlinear and non-stationary over different frequencies or scales, there is a need of more suitable approach over the conventional single scale based tools for analyzing the EEG data. Here, we present a new framework of complexity measures considering changing dynamics over multiple oscillatory scales. The proposed multiscale complexity is obtained by calculating entropies of the probability distributions of the intrinsic mode functions extracted by the empirical mode decomposition (EMD) of EEG. To quantify EEG recording of a rat model of hypoxic-ischemic brain injury following cardiac arrest, the multiscale version of Tsallis entropy is examined. To validate the proposed complexity measure, actual EEG recordings from rats (n=9) experiencing 7 min cardiac arrest followed by resuscitation were analyzed. Experimental results demonstrate that the use of the multiscale Tsallis entropy leads to better discrimination of the injury levels and improved correlations with the neurological deficit evaluation after 72 hours after cardiac arrest, thus suggesting an effective metric as a prognostic tool.
The aim of this paper is to understand emerging learning conditions, when a visual analytics is implemented and used in K 12 (education). To date, little attention has been paid to the role visual analytics (digital media and technology that highlight visual data communication in order to support analytical tasks) can play in education, and to the extent to which these tools can process actionable data for young students. This study was conducted in three public K 12 schools, in four social science classes with students aged 10 to 13 years, over a period of two to four weeks at each school. Empirical data were generated using video observations and analyzed with help of metaphors within Actor-network theory (ANT). The learning conditions are found to be distinguished by broad complexity, characterized by four dimensions. These emerge from the actors’ deeply intertwined relations in the activities. The paper argues in relation to the found dimensions that novel approaches to teaching and learning could benefit students’ knowledge building as they work with visual analytics, analyzing visualized data.
Software reusability is an essential characteristic of Component-Based Software (CBS). The component reusability is an important assess for the effective reuse of components in CBS. The attributes of reusability proposed by various researchers are studied and four of them are identified as potential factors affecting reusability. This paper proposes metric for reusability estimation of black-box software component along with metrics for Interface Complexity, Understandability, Customizability and Reliability. An experiment is performed for estimation of reusability through a case study on a sample web application using a real world component.
An effort estimation model is needed for softwareintensive projects that consist of hardware, embedded software or some combination of the two, as well as high level software solutions. This paper first focuses on functional decomposition techniques to measure functional complexity of a computer system and investigates its impact on system development effort. Later, it examines effects of technical difficulty and design team capability factors in order to construct the best effort estimation model. With using traditional regression analysis technique, the study develops a system development effort estimation model which takes functional complexity, technical difficulty and design team capability factors as input parameters. Finally, the assumptions of the model are tested.
Prior literature on innovation diffusion or acceptance has almost exclusively concentrated on consumers’ positive attitudes and behaviors for new products/services. Consumers’ negative attitudes or behaviors to innovations have received relatively little marketing attention, but it happens frequently in practice. This study discusses consumer psychological factors when they try to learn or use new technologies. According to recent research, technological innovation acceptance has been considered as a dynamic or mediated process. This research argues that consumers can experience inertia and emotions in the initial use of new technologies. However, given such consumer psychology, the argument can be made as to whether the inclusion of consumer inertia (routine seeking and cognitive rigidity) and emotions increases the predictive power of new technology acceptance model. As data from the empirical study find, the process is potentially consumer emotion changing (independent of performance benefits) because of technology complexity and consumer inertia, and impact innovative technology use significantly. Finally, the study presents the superior predictability of the hypothesized model, which let managers can better predict and influence the successful diffusion of complex technological innovations.
In this paper, we employ a directed hypergraph model to investigate the extent to which environmental variability influences the set of available biochemical reactions within a living cell. Such an approach avoids the limitations of the usual complex network formalism by allowing for the multilateral relationships (i.e. connections involving more than two nodes) that naturally occur within many biological processes. More specifically, we extend the concept of network reciprocity to complex hyper-networks, thus enabling us to characterise a network in terms of the existence of mutual hyper-connections, which may be considered a proxy for metabolic network complexity. To demonstrate these ideas, we study 115 metabolic hyper-networks of bacteria, each of which can be classified into one of 6 increasingly varied habitats. In particular, we found that reciprocity increases significantly with increased environmental variability, supporting the view that organism adaptability leads to increased complexities in the resultant biochemical networks.
In this paper will be discussed two coin´s sides of crisis scenarios dynamics. On the one's side is negative role of subsidiary scenario branches in its compactness weakening by means unduly chaotic atomizing, having many interactive feedbacks cases, increasing a value of a complexity here. This negative role reflects the complexity of use cases, weakening leader compliancy, which brings something as a ´readiness for controlling capabilities provision´. Leader´s dissatisfaction has zero compliancy, but factual it is a ´crossbar´ (interface in fact) between planning and executing use cases. On the other side of this coin, an advantage of rich scenarios embranchment is possible to see in a support of response awareness, readiness, preparedness, adaptability, creativity and flexibility. Here rich scenarios embranchment contributes to the steadiness and resistance of scenario mission actors. These all will be presented in live power-points ´Blazons´, modelled via DYVELOP (Dynamic Vector Logistics of Processes) on the Conference.
Using the technology acceptance model (TAM), this study examined the external variables of technological complexity (TC) to acquire a better understanding of the factors that influence the acceptance of computer application courses by learners at Active Aging Universities. After the learners in this study had completed a 27-hour Facebook course, 44 learners responded to a modified TAM survey. Data were collected to examine the path relationships among the variables that influence the acceptance of Facebook-mediated community learning. The partial least squares (PLS) method was used to test the measurement and the structural model. The study results demonstrated that attitudes toward Facebook use directly influence behavioral intentions (BI) with respect to Facebook use, evincing a high prediction rate of 58.3%. In addition to the perceived usefulness (PU) and perceived ease of use (PEOU) measures that are proposed in the TAM, other external variables, such as TC, also indirectly influence BI. These four variables can explain 88% of the variance in BI and demonstrate a high level of predictive ability. Finally, limitations of this investigation and implications for further research are discussed.
Measuring the reusability of Object-Oriented (OO) program code is important to ensure a successful and timely adaptation and integration of the reused code in new software projects. It has become even more relevant with the availability of huge amounts of open-source projects. Reuse saves cost, increases the speed of development and improves software reliability. Measuring this reusability is not s straight forward process due to the variety of metrics and qualities linked to software reuse and the lack of comprehensive empirical studies to support the proposed metrics or models. In this paper, a conceptual model is proposed to measure the reusability of OO program code. A comprehensive set of metrics is used to compute the most significant factors of reusability and an empirical investigation is conducted to measure the reusability of the classes of randomly selected open-source Java projects. Additionally, the impact of using inner and anonymous classes on the reusability of their enclosing classes is assessed. The results obtained are thoroughly analyzed to identify the factors behind lack of reusability in open-source OO program code and the impact of nesting on it.
According to investigating impact of complexity of stereoscopic frame pairs on stereoscopic video coding and transmission, a new rate control algorithm is presented. The proposed rate control algorithm is performed on three levels: stereoscopic group of pictures (SGOP) level, stereoscopic frame (SFrame) level and frame level. A temporal-spatial frame complexity model is firstly established, in the bits allocation stage, the frame complexity, position significance and reference property between the left and right frames are taken into account. Meanwhile, the target buffer is set according to the frame complexity. Experimental results show that the proposed method can efficiently control the bitrates, and it outperforms the fixed quantization parameter method from the rate distortion perspective, and average PSNR gain between rate-distortion curves (BDPSNR) is 0.21dB.
In this paper, application of the complexity reduction approach based on half- and quarter-sweep iteration concepts with Jacobi iterative method for solving composite trapezoidal (CT) algebraic equations is discussed. The performances of the methods for CT algebraic equations are comparatively studied by their application in solving linear Fredholm integral equations of the second kind. Furthermore, computational complexity analysis and numerical results for three test problems are also included in order to verify performance of the methods.
In theoretical computer science, the Turing machine has played a number of important roles in understanding and exploiting basic concepts and mechanisms in computing and information processing . It is a simple mathematical model of computers . After that, M.Blum and C.Hewitt first proposed two-dimensional automata as a computational model of two-dimensional pattern processing, and investigated their pattern recognition abilities in 1967 . Since then, a lot of researchers in this field have been investigating many properties about automata on a two- or three-dimensional tape. On the other hand, the question of whether processing fourdimensional digital patterns is much more difficult than two- or threedimensional ones is of great interest from the theoretical and practical standpoints. Thus, the study of four-dimensional automata as a computasional model of four-dimensional pattern processing has been meaningful -,. This paper introduces a cooperating system of four-dimensional finite automata as one model of four-dimensional automata. A cooperating system of four-dimensional finite automata consists of a finite number of four-dimensional finite automata and a four-dimensional input tape where these finite automata work independently (in parallel). Those finite automata whose input heads scan the same cell of the input tape can communicate with each other, that is, every finite automaton is allowed to know the internal states of other finite automata on the same cell it is scanning at the moment. In this paper, we mainly investigate some accepting powers of a cooperating system of eight- or seven-way four-dimensional finite automata. The seven-way four-dimensional finite automaton is an eight-way four-dimensional finite automaton whose input head can move east, west, south, north, up, down, or in the fu-ture, but not in the past on a four-dimensional input tape.
We here propose improved version of elastic graph matching (EGM) as a face detector, called the multi-scale EGM (MS-EGM). In this improvement, Gabor wavelet-based pyramid reduces computational complexity for the feature representation often used in the conventional EGM, but preserving a critical amount of information about an image. The MS-EGM gives us higher detection performance than Viola-Jones object detection algorithm of the AdaBoost Haar-like feature cascade. We also show rapid detection speeds of the MS-EGM, comparable to the Viola-Jones method. We find fruitful benefits in the MS-EGM, in terms of topological feature representation for a face.
In this paper, a predator-prey model with time delay and habitat complexity is investigated. By analyzing the characteristic equations, the local stability of each feasible equilibria of the system is discussed and the existence of a Hopf bifurcation at the coexistence equilibrium is established. By choosing the sum of two delays as a bifurcation parameter, we show that Hopf bifurcations can occur as crosses some critical values. By deriving the equation describing the flow on the center manifold, we can determine the direction of the Hopf bifurcations and the stability of the bifurcating periodic solutions. Numerical simulations are carried out to illustrate the main theoretical results.
We consider linear regression models where both input data (the values of independent variables) and output data (the observations of the dependent variable) are interval-censored. We introduce a possibilistic generalization of the least squares estimator, so called OLS-set for the interval model. This set captures the impact of the loss of information on the OLS estimator caused by interval censoring and provides a tool for quantification of this effect. We study complexity-theoretic properties of the OLS-set. We also deal with restricted versions of the general interval linear regression model, in particular the crisp input – interval output model. We give an argument that natural descriptions of the OLS-set in the crisp input – interval output cannot be computed in polynomial time. Then we derive easily computable approximations for the OLS-set which can be used instead of the exact description. We illustrate the approach by an example.
Sports Sciences has been historically supported by the positivism idea of science, especially by the mechanistic/reductionist and becomes a field that views experimentation and measurement as the mayor research domains. The disposition to simplify nature and the world by parts has fragmented and reduced the idea of bodyathletes as machine. In this paper we intent to re-think this perception lined by Complexity Theory. We come with the idea of athletes as a reflexive and active being (corporeity-body). Therefore, the construction of a training that considers the cultural, biological, psychological elements regarding the experience of the human corporal movements in a circumspect and responsible way could bring better chances of accomplishment. In the end, we hope to help coaches understand the intrinsic complexity of the body they are training, how better deal with it, and, in the field of a deep globalization among the different types of knowledge, to respect and accepted the peculiarities of knowledge that comprise this area.