Search results for: Equality of P and NP Complexity Classes.

Authors: Hycham Aboutaleb, Bruno Monsuez

Abstract:

Current systems complexity has reached a degree that requires addressing conception and design issues while taking into account environmental, operational, social, legal and financial aspects. Therefore, one of the main challenges is the way complex systems are specified and designed. The exponential growing effort, cost and time investment of complex systems in modeling phase emphasize the need for a paradigm, a framework and an environment to handle the system model complexity. For that, it is necessary to understand the expectations of the human user of the model and his limits. This paper presents a generic framework for designing complex systems, highlights the requirements a system model needs to fulfill to meet human user expectations, and suggests a graphbased formalism for modeling complex systems. Finally, a set of transformations are defined to handle the model complexity.

Keywords: Higraph-based, formalism, system engineering paradigm, modeling requirements, graph-based transformations.

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Authors: Asha Rani, Christian Micheloni, Gian Luca Foresti

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In this paper, a neural tree (NT) classifier having a simple perceptron at each node is considered. A new concept for making a balanced tree is applied in the learning algorithm of the tree. At each node, if the perceptron classification is not accurate and unbalanced, then it is replaced by a new perceptron. This separates the training set in such a way that almost the equal number of patterns fall into each of the classes. Moreover, each perceptron is trained only for the classes which are present at respective node and ignore other classes. Splitting nodes are employed into the neural tree architecture to divide the training set when the current perceptron node repeats the same classification of the parent node. A new error function based on the depth of the tree is introduced to reduce the computational time for the training of a perceptron. Experiments are performed to check the efficiency and encouraging results are obtained in terms of accuracy and computational costs.

Keywords: Neural Tree, Pattern Classification, Perceptron, Splitting Nodes.

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Authors: Amit Kumar Jakhar, Kumar Rajnish

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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.

Keywords: Software metrics, object-oriented, complexity, cognitive weight, understandability, basic control structures.

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Authors: Hayedeh Ahrabian, Comfar Badamchi, Abbass Nowzari-Dalini

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In this paper, two versions of an iterative loopless algorithm for the classical towers of Hanoi problem with O(1) storage complexity and O(2n) time complexity are presented. Based on this algorithm the number of different moves in each of pegs with its direction is formulated.

Keywords: Loopless algorithm, Binary tree, Towers of Hanoi.

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Authors: Li Hongwei

Abstract:

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.

Keywords: Predator-prey system, delay, habitat complexity, HOPF bifurcation.

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Authors: Swapnil Gupta, C. Pandu Rangan

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A uniquely restricted matching is defined to be a matching M whose matched vertices induces a sub-graph which has only one perfect matching. In this paper, we make progress on the open question of the status of this problem on interval graphs (graphs obtained as the intersection graph of intervals on a line). We give an algorithm to compute maximum cardinality uniquely restricted matchings on certain sub-classes of interval graphs. We consider two sub-classes of interval graphs, the former contained in the latter, and give O(|E|^2) time algorithms for both of them. It is to be noted that both sub-classes are incomparable to proper interval graphs (graphs obtained as the intersection graph of intervals in which no interval completely contains another interval), on which the problem can be solved in polynomial time.

Keywords: Uniquely restricted matching, interval graph, design and analysis of algorithms, matching, induced matching, witness counting.

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Authors: Erten Gokce

Abstract:

This study was carried out in Ankara, the capital city of Turkey, in order to determine how people living in the slums of Ankara benefit from educational equality. Within the scope of the research, interviews were made with 64 families whose children have been getting education from the primary schools of these parts and the data of the study was collected by the researcher. The results of the research demonstrate that the children getting education in the slums of Ankara can not experience educational equality and justice. The results of this study show that the opportunities of the schools in the slums of Ankara are very limited, so the individuals in these districts can not equally benefit from the education. The families are aware of the problem they are faced with. KeywordsDiscrimination, inequality, primary education, slums of Turkey.

Keywords: Discrimination, inequality, primary education, slums of Turkey.

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Authors: María-Dolores Cubiles-de-la-Vega, Rafael Pino-Mejías, Esther-Lydia Silva-Ramírez

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A dissimilarity measure between the empiric characteristic functions of the subsamples associated to the different classes in a multivariate data set is proposed. This measure can be efficiently computed, and it depends on all the cases of each class. It may be used to find groups of similar classes, which could be joined for further analysis, or it could be employed to perform an agglomerative hierarchical cluster analysis of the set of classes. The final tree can serve to build a family of binary classification models, offering an alternative approach to the multi-class SVM problem. We have tested this dendrogram based SVM approach with the oneagainst- one SVM approach over four publicly available data sets, three of them being microarray data. Both performances have been found equivalent, but the first solution requires a smaller number of binary SVM models.

Keywords: Cluster Analysis, Empiric Characteristic Function, Multi-class SVM, R.

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Authors: Azam Beg, P. W. Chandana Prasad, S.M.N.A Senenayake

Abstract:

When binary decision diagrams are formed from uniformly distributed Monte Carlo data for a large number of variables, the complexity of the decision diagrams exhibits a predictable relationship to the number of variables and minterms. In the present work, a neural network model has been used to analyze the pattern of shortest path length for larger number of Monte Carlo data points. The neural model shows a strong descriptive power for the ISCAS benchmark data with an RMS error of 0.102 for the shortest path length complexity. Therefore, the model can be considered as a method of predicting path length complexities; this is expected to lead to minimum time complexity of very large-scale integrated circuitries and related computer-aided design tools that use binary decision diagrams.

Keywords: Monte Carlo circuit simulation data, binary decision diagrams, neural network modeling, shortest path length estimation

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Authors: R. Ebrahimpour, M. Abbasnezhad Arabi, H. Babamiri Moghaddam

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Combining classifiers is a useful method for solving complex problems in machine learning. The ECOC (Error Correcting Output Codes) method has been widely used for designing combining classifiers with an emphasis on the diversity of classifiers. In this paper, in contrast to the standard ECOC approach in which individual classifiers are chosen homogeneously, classifiers are selected according to the complexity of the corresponding binary problem. We use SATIMAGE database (containing 6 classes) for our experiments. The recognition error rate in our proposed method is %10.37 which indicates a considerable improvement in comparison with the conventional ECOC and stack generalization methods.

Keywords: Error correcting output code, combining classifiers, neural networks.

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Authors: L. Horňák

Abstract:

The aim of the paper is to analyze a longstanding problem in Slovakia – the effective education of Roma students coming from socially disadvantaged backgrounds. Although it is a relatively small country, there are over 630 communities in the Slovak Republic. The efficiency of the projects was verified by interviews with participants; questionnaires; and direct observations. Evaluation reports which summarized and evaluated the outcomes of the projects only confirmed their success. Slovakia realizes that appropriate social inclusion of marginalized citizens coming from the Roma ethnic group can only be achieved through education based on equality of all students and acceptance of diversity.

Keywords: Inclusive education, marginalized communities, Roma student, equality in education, socially disadvantaged backgrounds, social inclusion.

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Authors: P. C. Saxena, D. K. Tayal

Abstract:

The join dependency provides the basis for obtaining lossless join decomposition in a classical relational schema. The existence of Join dependency shows that that the tables always represent the correct data after being joined. Since the classical relational databases cannot handle imprecise data, they were extended to fuzzy relational databases so that uncertain, ambiguous, imprecise and partially known information can also be stored in databases in a formal way. However like classical databases, the fuzzy relational databases also undergoes decomposition during normalization, the issue of joining the decomposed fuzzy relations remains intact. Our effort in the present paper is to emphasize on this issue. In this paper we define fuzzy join dependency in the framework of type-1 fuzzy relational databases & type-2 fuzzy relational databases using the concept of fuzzy equality which is defined using fuzzy functions. We use the fuzzy equi-join operator for computing the fuzzy equality of two attribute values. We also discuss the dependency preservation property on execution of this fuzzy equi- join and derive the necessary condition for the fuzzy functional dependencies to be preserved on joining the decomposed fuzzy relations. We also derive the conditions for fuzzy join dependency to exist in context of both type-1 and type-2 fuzzy relational databases. We find that unlike the classical relational databases even the existence of a trivial join dependency does not ensure lossless join decomposition in type-2 fuzzy relational databases. Finally we derive the conditions for the fuzzy equality to be non zero and the qualification of an attribute for fuzzy key.

Keywords: Fuzzy - equi join, fuzzy functions, fuzzy join dependency, type-1 fuzzy relational database, type-2 fuzzy relational database.

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Authors: Fathi Taibi

Abstract:

The abnormal increase in the number of applications available for download in Android markets is a good indication that they are being reused. However, little is known about their real reusability potential. A considerable amount of these applications is reported as having a poor quality or being malicious. Hence, in this paper, an approach to measure the reusability potential of classes in Android applications is proposed. The approach is not meant specifically for this particular type of applications. Rather, it is intended for Object-Oriented (OO) software systems in general and aims also to provide means to discard the classes of low quality and defect prone applications from being reused directly through inheritance and instantiation. An empirical investigation is conducted to measure and rank the reusability potential of the classes of randomly selected Android applications. The results obtained are thoroughly analyzed in order to understand the extent of this potential and the factors influencing it.

Keywords: Reusability, Software Quality Factors, Software Metrics, Empirical Investigation, Object-Oriented Software, Android Applications.

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Authors: Maythapolnun Athimethphat, Boontarika Lerteerawong

Abstract:

There are several approaches for handling multiclass classification. Aside from one-against-one (OAO) and one-against-all (OAA), hierarchical classification technique is also commonly used. A binary classification tree is a hierarchical classification structure that breaks down a k-class problem into binary sub-problems, each solved by a binary classifier. In each node, a set of classes is divided into two subsets. A good class partition should be able to group similar classes together. Many algorithms measure similarity in term of distance between class centroids. Classes are grouped together by a clustering algorithm when distances between their centroids are small. In this paper, we present a binary classification tree with tuned observation-based clustering (BCT-TOB) that finds a class partition by performing clustering on observations instead of class centroids. A merging step is introduced to merge any insignificant class split. The experiment shows that performance of BCT-TOB is comparable to other algorithms.

Keywords: multiclass classification, hierarchical classification, binary classification tree, clustering, observation-based clustering

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Authors: Andrey V. Timofeev

Abstract:

This paper introduces an original method for guaranteed estimation of the accuracy for an ensemble of Lipschitz classifiers. The solution was obtained as a finite closed set of alternative hypotheses, which contains an object of classification with probability of not less than the specified value. Thus, the classification is represented by a set of hypothetical classes. In this case, the smaller the cardinality of the discrete set of hypothetical classes is, the higher is the classification accuracy. Experiments have shown that if cardinality of the classifiers ensemble is increased then the cardinality of this set of hypothetical classes is reduced. The problem of the guaranteed estimation of the accuracy for an ensemble of Lipschitz classifiers is relevant in multichannel classification of target events in C-OTDR monitoring systems. Results of suggested approach practical usage to accuracy control in C-OTDR monitoring systems are present.

Keywords: Lipschitz classifiers, confidence set, C-OTDR monitoring, classifiers accuracy, classifiers ensemble.

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Authors: Mehran Garmehi, Yasser Mansouri

Abstract:

There are two paradigms proposed to provide QoS for Internet applications: Integrated service (IntServ) and Differentiated service (DiffServ).Intserv is not appropriate for large network like Internet. Because is very complex. Therefore, to reduce the complexity of QoS management, DiffServ was introduced to provide QoS within a domain using aggregation of flow and per- class service. In theses networks QoS between classes is constant and it allows low priority traffic to be effected from high priority traffic, which is not suitable. In this paper, we proposed a fuzzy controller, which reduced the effect of low priority class on higher priority ones. Our simulations shows that, our approach reduces the latency dependency of low priority class on higher priority ones, in an effective manner.

Keywords: QoS, Differentiated Service (DiffServ), FuzzyController, Delay.

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Authors: Jeffrey L. Duffany

Abstract:

Graph coloring is an important problem in computer science and many algorithms are known for obtaining reasonably good solutions in polynomial time. One method of comparing different algorithms is to test them on a set of standard graphs where the optimal solution is already known. This investigation analyzes a set of 50 well known graph coloring instances according to a set of complexity measures. These instances come from a variety of sources some representing actual applications of graph coloring (register allocation) and others (mycieleski and leighton graphs) that are theoretically designed to be difficult to solve. The size of the graphs ranged from ranged from a low of 11 variables to a high of 864 variables. The method used to solve the coloring problem was the square of the adjacency (i.e., correlation) matrix. The results show that the most difficult graphs to solve were the leighton and the queen graphs. Complexity measures such as density, mobility, deviation from uniform color class size and number of block diagonal zeros are calculated for each graph. The results showed that the most difficult problems have low mobility (in the range of .2-.5) and relatively little deviation from uniform color class size.

Keywords: graph coloring, complexity, algorithm.

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Authors: S. Rawashdi, D. Bshouty

Abstract:

This paper aimed at discussing how to urge middle and high school Arab students in Israel to be aware of the importance of and investing in learning mathematics. In the first phase of the study, three questionnaires were passed to two nine-grade classes, one on Awareness, one on Awakeness and one on Learning. One of the two classes was an outstanding class from a public school (PUBS) of 31 students, and the other a heterogeneous class from a private school (PRIS) with 31 students. The Learning questionnaire which was administrated to the Awareness and Awareness topics was passed to PRIS and the Awareness and Awareness Questionnaires were passed to the PUBS class After two months we passed the post-questionnaire to both classes to validate the long-term impact of the study. The findings of the study show that awakeness and awareness processes have an effect on the math learning process, on its context in students' daily lives and their growing interest in learning math.

Keywords: Awakeness, awareness, learning mathematics, pupils.

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Authors: Jiří Barta, Oldřich Svoboda, Jiří. F. Urbánek

Abstract:

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.

Keywords: Leadership, Controlling, Complexity, DYVELOP, Scenarios.

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Authors: M. Kargar, F.Fartash, T. Saderi, M. Ebrahimi Dishabi

Abstract:

In this paper optimization of routing in ad-hoc networks is surveyed and a new method for reducing the complexity of routing algorithms is suggested. Using binary matrices for each node in the network and updating it once the routing is done, helps nodes to stop repeating the routing protocols in each data transfer. The algorithm suggested can reduce the complexity of routing to the least amount possible.

Keywords: Ad-hoc Networks, Algorithm, Protocol, RoutingTrain.

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Authors: Caio Fialho

Abstract:

The automobile incentive policy in Brazil since the 1950s creates several problems in its cities, more visible in large centers such as São Paulo or Rio de Janeiro, but also strongly present in smaller cities, resulting in an increase in social and spatial inequality, together with a drop in the quality of life. The analyzed city, Campo Mourão, reflects these policies, a city that is initially planned to be compact and walkable, took other directions and currently suffers from urban mobility and social inequality in this urban environment, despite being a medium-sized city in Brazil. The research aims to understand and diagnose how these policies shaped the city and what are the results in Brazilian`s inland cities. Based on historical, bibliographical and field research in the city, the result is a diagnosis of the problem faced and how it can be reversed, in search of social equality and better quality of life.

Keywords: Urban mobility, quality of life, social equality, substantiable.

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Authors: Abubakar Idris, Nabade Abdullahi Muhammad

Abstract:

The work presents a development of EN338 strength classes for Strombosia pustulata, Pterygotama crocarpa, Nauclea diderrichii and Entandrophragma cyclindricum Nigerian timber species. The specimens for experimental measurements were obtained from the timber-shed at the famous Panteka market in Kaduna in the northern part of Nigeria. Laboratory experiments were conducted to determine the physical and mechanical properties of the selected timber species in accordance with EN 13183-1 and ASTM D193. The mechanical properties were determined using three point bending test. The generated properties were used to obtain the characteristic values of the material properties in accordance with EN384. The selected timber species were then classified according to EN 338. Strombosia pustulata, Pterygotama crocarpa, Nauclea diderrichii and Entandrophragma cyclindricum were assigned to strength classes D40, C14, D40 and D24 respectively. Other properties such as tensile and compressive strengths parallel and perpendicular to grains, shear strength as well as shear modulus were obtained in accordance with EN 338. 

Keywords: Mechanical properties, Nigerian timber, strength classes, three-point bending test.

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Authors: Chouvalit Khancome, Veera Boonjing

Abstract:

This paper proposes a new solution to string matching problem. This solution constructs an inverted list representing a  string pattern to be searched for. It then uses a new algorithm to process an input string in a single pass. The preprocessing phase  takes 1) time complexity O(m) 2) space complexity O(1) where m is  the length of pattern. The searching phase time complexity takes 1)  O(m+α ) in average case 2) O(n/m) in the best case and 3) O(n) in  the worst case, where α is the number of comparing leading to  mismatch and n is the length of input text.

Keywords: String matching, inverted list, inverted index, pattern, algorithm.

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Authors: Mohammad Akbarpour Sekeh, Mohd. Aizaini Maarof, Mohd. Foad Rohani, Malihe Motiei

Abstract:

Duplicated region detection is a technical method to expose copy-paste forgeries on digital images. Copy-paste is one of the common types of forgeries to clone portion of an image in order to conceal or duplicate special object. In this type of forgery detection, extracting robust block feature and also high time complexity of matching step are two main open problems. This paper concentrates on computational time and proposes a local block matching algorithm based on block clustering to enhance time complexity. Time complexity of the proposed algorithm is formulated and effects of two parameter, block size and number of cluster, on efficiency of this algorithm are considered. The experimental results and mathematical analysis demonstrate this algorithm is more costeffective than lexicographically algorithms in time complexity issue when the image is complex.

Keywords: Copy-paste forgery detection, Duplicated region, Timecomplexity, Local block matching, Sequential block clustering.

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Authors: A. Faro, D. Giordano, F. Maiorana

Abstract:

Data mining uses a variety of techniques each of which is useful for some particular task. It is important to have a deep understanding of each technique and be able to perform sophisticated analysis. In this article we describe a tool built to simulate a variation of the Kohonen network to perform unsupervised clustering and support the entire data mining process up to results visualization. A graphical representation helps the user to find out a strategy to optmize classification by adding, moving or delete a neuron in order to change the number of classes. The tool is also able to automatically suggest a strategy for number of classes optimization.The tool is used to classify macroeconomic data that report the most developed countries? import and export. It is possible to classify the countries based on their economic behaviour and use an ad hoc tool to characterize the commercial behaviour of a country in a selected class from the analysis of positive and negative features that contribute to classes formation.

Keywords: Unsupervised classification, Kohonen networks, macroeconomics, Visual data mining, cluster interpretation.

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Authors: Abhijit Mitra

Abstract:

An effective approach for extracting document images from a noisy background is introduced. The entire scheme is divided into three sub- stechniques – the initial preprocessing operations for noise cluster tightening, introduction of a new thresholding method by maximizing the ratio of stan- dard deviations of the combined effect on the image to the sum of weighted classes and finally the image restoration phase by image binarization utiliz- ing the proposed optimum threshold level. The proposed method is found to be efficient compared to the existing schemes in terms of computational complexity as well as speed with better noise rejection.

Keywords: Document image extraction, Preprocessing, Ratio of stan-dard deviations, Bi-level adaptive thresholding.

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Authors: Nonlapun Meenil, Pisitpong Intarapong, Thitima Wongsheree, Pranchalee Samanpiboon

Abstract:

In Thailand, once pineapples are harvested, they must be classified into two classes based on their sweetness: sweet and unsweet. This paper has studied and developed the assessment of internal quality of pineapples using a low-cost compact spectroscopy sensor according to the spectroscopy approach and Neural Network (NN). During the experiments, Batavia pineapples were utilized, generating 100 samples. The extracted pineapple juice of each sample was used to determine the Soluble Solid Content (SSC) labeling into sweet and unsweet classes. In terms of experimental equipment, the sensor cover was specifically designed to install the sensor and light source to read the reflectance at a five mm depth from pineapple flesh. By using a spectroscopy sensor, data on visible and near-infrared reflectance (Vis-NIR) were collected. The NN was used to classify the pineapple classes. Before the classification step, the preprocessing methods, which are class balancing, data shuffling, and standardization, were applied. The 510 nm and 900 nm reflectance values of the middle parts of pineapples were used as features of the NN. With the sequential model and ReLU activation function, 100% accuracy of the training set and 76.67% accuracy of the test set were achieved. According to the abovementioned information, using a low-cost compact spectroscopy sensor has achieved favorable results in classifying the sweetness of the two classes of pineapples.

Keywords: Spectroscopy, soluble solid content, pineapple, neural network.

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Authors: Jeffrey L. Duffany

Abstract:

The equivalence class subset algorithm is a powerful tool for solving a wide variety of constraint satisfaction problems and is based on the use of a decision function which has a very high but not perfect accuracy. Perfect accuracy is not required in the decision function as even a suboptimal solution contains valuable information that can be used to help find an optimal solution. In the hardest problems, the decision function can break down leading to a suboptimal solution where there are more equivalence classes than are necessary and which can be viewed as a mixture of good decision and bad decisions. By choosing a subset of the decisions made in reaching a suboptimal solution an iterative technique can lead to an optimal solution, using series of steadily improved suboptimal solutions. The goal is to reach an optimal solution as quickly as possible. Various techniques for choosing the decision subset are evaluated.

Keywords: np-complete, complexity, algorithm.

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Authors: Jae-Jeong Kim, Ki-Ro Kim, Hyoung-Kyu Song

Abstract:

In this paper, we propose an efficient signal detector that switches M parameter of QRD-M detection scheme is proposed for MIMO-OFDM system. The proposed detection scheme calculates the threshold by 1-norm condition number and then switches M parameter of QRD-M detection scheme according to channel information. If channel condition is bad, the parameter M is set to high value to increase the accuracy of detection. If channel condition is good, the parameter M is set to low value to reduce complexity of detection. Therefore, the proposed detection scheme has better tradeoff between BER performance and complexity than the conventional detection scheme. The simulation result shows that the complexity of proposed detection scheme is lower than QRD-M detection scheme with similar BER performance.

Keywords: MIMO-OFDM, QRD-M, Channel condition.

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Authors: Maziyar Nouraee

Abstract:

Electronic markets in recent decades contribute remarkably in business transactions. Many organizations consider traditional ways of trade non-economical and therefore they do trade only through electronic markets. There are different categorizations of electronic markets functions. In one classification, functions of electronic markets are categorized into classes as information, transactions, and value added. In the present paper, effects of the three classes on the two major elements of the supply chain management are measured. The two elements are decrease in the product unit cost and reduction in response time to the customer. The results of the current research show that among nine minor elements related to the three classes of electronic markets functions, six factors and three factors influence on reduction of the product unit cost and reduction of response time to the customer, respectively.

Keywords: Electronic Commerce, Electronic Market, B2B Trade, Supply Chain Management.

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