Search results for: heritage tree

Authors: Wan-Yu Liu

Abstract:

The Taiwan government has started to promote the “Plain Landscape Afforestation and Greening Program" since 2002. A key task of the program was the payment for environmental services (PES), entitled the “Plain Landscape Afforestation Policy" (PLAP), which was certificated by the Executive Yuan on August 31, 2001 and enacted on January 1, 2002. According to the policy, it is estimated that the total area of afforestation will be 25,100 hectares by December 31, 2007. Until the end of 2007, the policy had been enacted for six years in total and the actual area of afforestation was 8,919.18 hectares. Among them, Taiwan Sugar Corporation (TSC) was accounted for 7,960 hectares (with 2,450.83 hectares as public service area) which occupied 86.22% of the total afforestation area; the private farmland promoted by local governments was accounted for 869.18 hectares which occupied 9.75% of the total afforestation area. Based on the above, we observe that most of the afforestation area in this policy is executed by TSC, and the achievement ratio by TSC is better than by others. It implies that the success of the PLAP is seriously related to the execution of TSC. The objective of this study is to analyze the relevant policy planning of TSC's participation in the PLAP, suggest complementary measures, and draw up effective adjustment mechanisms, so as to improve the effectiveness of executing the policy. Our main conclusions and suggestions are summarized as follows: 1. The main reason for TSC’s participation in the PLAP is based on their passive cooperation with the central government or company policy. Prior to TSC’s participation in the PLAP, their lands were mainly used for growing sugarcane. 2. The main factors of TSC's consideration on the selection of tree species are based on the suitability of land and species. The largest proportion of tree species is allocated to economic forests, and the lack of technical instruction was the main problem during afforestation. Moreover, the method of improving TSC’s future development in leisure agriculture and landscape business becomes a key topic. 3. TSC has developed short and long-term plans on participating in the PLAP for the future. However, there is no great willingness or incentive on budgeting for such detailed planning. 4. Most people from TSC interviewed consider the requirements on PLAP unreasonable. Among them, an unreasonable requirement on the number of trees accounted for the greatest proportion; furthermore, most interviewees suggested that the government should continue to provide incentives even after 20 years. 5. Since the government shares the same goals as TSC, there should be sufficient cooperation and communication that support the technical instruction and reduction of afforestation cost, which will also help to improve effectiveness of the policy.

Keywords: Payment for environmental services, afforestation subsidy, Taiwan sugar corporation.

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Authors: C. R. Ríos-Soberanis, V. M. Moo-Huchin, R. J. Estrada-Leon, E. Perez-Pacheco

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Polymers from renewable resources have attracted an increasing amount of attention over the last two decades, predominantly due to two major reasons: firstly environmental concerns, and secondly the realization that our petroleum resources are finite. Finding new uses for agricultural commodities is also an important area of research. Therefore, it is crucial to get new sources of natural materials that can be used in different applications. Ramon tree (Brosimum alicastrum) is a tropical plant that grows freely in Yucatan countryside. This paper focuses on the seeds recollection, processing and starch extraction and characterization in order to find out about its suitability as biomaterial. Results demonstrated that it has a high content of qualities to be used not only as comestible but also as an important component in polymeric blends.

Keywords: Biomaterials, biopolymer, starch, characterization techniques.

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Authors: Bharatendra Rai

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Cutting tools are widely used in manufacturing processes and drilling is the most commonly used machining process. Although drill-bits used in drilling may not be expensive, their breakage can cause damage to expensive work piece being drilled and at the same time has major impact on productivity. Predicting drill-bit breakage, therefore, is important in reducing cost and improving productivity. This study uses twenty features extracted from two degradation signals viz., thrust force and torque. The methodology used involves developing and comparing decision tree, random forest, and multinomial logistic regression models for classifying and predicting drill-bit breakage using degradation signals.

Keywords: Degradation signal, drill-bit breakage, random forest, multinomial logistic regression.

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Authors: Patricia Diogo

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As teachers and researchers, we often find ourselves grappling with a central question about what it truly means to teach project in architecture in Portugal in the 21st century. It is a question that transcends the simple transmission of technical knowledge or even the sharing of our personal experiences. Rather, it is about developing a teaching pedagogy that responds to and reflects the profound social, environmental, and technological shifts we are currently navigating. Teaching architecture in Portugal today is not a mere continuation of tradition; it is, in essence, a living laboratory of innovation. Each new generation of students enters our classrooms with a hunger not just for design techniques, but for meaning—seeking to understand the role they can play in reshaping our physical and cultural environments. They are not passive recipients of knowledge, but active participants in the creation of a more sustainable, ethical, and thoughtful architecture.

Keywords: Architecture, heritage, memories, project studio, teaching.

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Authors: Phanu Waraporn

Abstract:

This paper discusses the designing of knowledge integration of clinical information extracted from distributed medical ontologies in order to ameliorate a machine learning-based multilabel coding assignment system. The proposed approach is implemented using a decision tree technique of the machine learning on the university hospital data for patients with Coronary Heart Disease (CHD). The preliminary results obtained show a satisfactory finding that the use of medical ontologies improves the overall system performance.

Keywords: Medical Ontology, Knowledge Integration, Machine Learning, Medical Coding, Text Assignment.

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Authors: Dipeng Chen, Qi Li

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Image fusion aims to enhance the perception of a scene by combining important information captured by different sensors. Dual-Tree Complex Wavelet (DT-CWT) has been thouroughly investigated for image fusion, since it takes advantages of approximate shift invariance and direction selectivity. But it can only handle limited direction information. To allow a more flexible directional expansion for images, we propose a novel fusion scheme, referred to as complex contourlet transform (CCT). It successfully incorporates directional filter banks (DFB) into DT-CWT. As a result it efficiently deal with images containing contours and textures, whereas it retains the property of shift invariance. Experimental results demonstrated that the method features high quality fusion performance and can facilitate many image processing applications.

Keywords: Complex contourlet transform, Complex wavelettransform, Fusion.

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Authors: Norashikin Ahmad, Damminda Alahakoon

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Self-organizing map (SOM) provides both clustering and visualization capabilities in mining data. Dynamic self-organizing maps such as Growing Self-organizing Map (GSOM) has been developed to overcome the problem of fixed structure in SOM to enable better representation of the discovered patterns. However, in mining large datasets or historical data the hierarchical structure of the data is also useful to view the cluster formation at different levels of abstraction. In this paper, we present a technique to generate concept trees from the GSOM. The formation of tree from different spread factor values of GSOM is also investigated and the quality of the trees analyzed. The results show that concept trees can be generated from GSOM, thus, eliminating the need for re-clustering of the data from scratch to obtain a hierarchical view of the data under study.

Keywords: dynamic self-organizing map, concept formation, clustering.

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Authors: Hanieh Alipour, Alireza Nemaney Pour

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One of the most important applications of wireless sensor networks is data collection. This paper proposes as efficient approach for data collection in wireless sensor networks by introducing Member Forward List. This list includes the nodes with highest priority for forwarding the data. When a node fails or dies, this list is used to select the next node with higher priority. The benefit of this node is that it prevents the algorithm from repeating when a node fails or dies. The results show that Member Forward List decreases power consumption and latency in wireless sensor networks.

Keywords: Data Collection, Wireless Sensor Network, SensorNode, Tree-Based

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Authors: Priyadarsini P.L.K, Hemalatha T.

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In the Top Right Access point Minimum Length Corridor (TRA-MLC) problem [1], a rectangular boundary partitioned into rectilinear polygons is given and the problem is to find a corridor of least total length and it must include the top right corner of the outer rectangular boundary. A corridor is a tree containing a set of line segments lying along the outer rectangular boundary and/or on the boundary of the rectilinear polygons. The corridor must contain at least one point from the boundaries of the outer rectangle and also the rectilinear polygons. Gutierrez and Gonzalez [1] proved that the MLC problem, along with some of its restricted versions and variants, are NP-complete. In this paper, we give a shorter proof of NP-Completeness of TRA-MLC by findig the reduction in the following way.

Keywords: NP-complete, 2-connected planar graph, Grid embedding of a plane graph.

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Authors: Praveen Boinee, Alessandro De Angelis, Gian Luca Foresti

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Leo Breimans Random Forests (RF) is a recent development in tree based classifiers and quickly proven to be one of the most important algorithms in the machine learning literature. It has shown robust and improved results of classifications on standard data sets. Ensemble learning algorithms such as AdaBoost and Bagging have been in active research and shown improvements in classification results for several benchmarking data sets with mainly decision trees as their base classifiers. In this paper we experiment to apply these Meta learning techniques to the random forests. We experiment the working of the ensembles of random forests on the standard data sets available in UCI data sets. We compare the original random forest algorithm with their ensemble counterparts and discuss the results.

Keywords: Random Forests [RF], ensembles, UCI.

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Authors: A.R. Aswatha, T. Basavaraju, S. Sandeep Kumar

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Timing driven physical design, synthesis, and optimization tools need efficient closed-form delay models for estimating the delay associated with each net in an integrated circuit (IC) design. The total number of nets in a modern IC design has increased dramatically and exceeded millions. Therefore efficient modeling of interconnection is needed for high speed IC-s. This paper presents closed–form expressions for RC and RLC interconnection trees in current mode signaling, which can be implemented in VLSI design tool. These analytical model expressions can be used for accurate calculation of delay after the design clock tree has been laid out and the design is fully routed. Evaluation of these analytical models is several orders of magnitude faster than simulation using SPICE.

Keywords: IC design, RC/RLC Interconnection, VLSI Systems.

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Authors: Gameel Abdelmageed

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Arabs have a rhetorical heritage which has greatly contributed to the monitoring and analyzing of the rhetoric of the Holy Quran, Hadith, and Arabic texts on poetry and oratory. But Arab scholars - as far as the researcher knows – have not contributed to monitoring and analyzing the rhetoric of digital Arabic discourse although it has prominence, particularly in social media and has strong effectiveness in the political and social life of Arab society. This discourse has made its impact by using very new rhetorical techniques in language, voice, image, painting and video clips which are known as “Multimedia” and belong to “Digital Rhetoric”. This study suggests that it is time to draw the attention of Arab scholars and invite them to monitor and analyze the rhetoric of digital Arabic discourse.

Keywords: Digital discourse, digital rhetoric, social media, Facebook.

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Authors: Eduard Kuriščák, Jiří Chludil

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We created the tool, which combines the powerful GENESIS (GEneral NEural SImulation System) simulation language with the up-to-date visualisation and internet techniques. Our solution resides in the connection between the simulation output from GENESIS, which is converted to the data-structure suitable for WWW browsers and VRML (Virtual Reality Modelling Language) viewers. The selected GENESIS simulations are once exported into the VRML code, and stored in our neurovisualisation portal (webserver). There, the loaded models, demonstrating mainly the spread of electrical signal (action potentials, postsynaptic potentials) along the neuronal membrane (axon, dendritic tree, neuron) could be displayed in the client-s VRML viewer, without interacting with original GENESIS environment. This enables the visualisation of basic neurophysiological phenomena designed for GENESIS simulator on the independent OS (operation system).

Keywords: GENESIS, neurosimulation, VRML, Java3D.

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Authors: Kamrul Hasan Talukder, Koichi Harada

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The scientific community has invested a great deal of effort in the fields of discrete wavelet transform in the last few decades. Discrete wavelet transform (DWT) associated with the vector quantization has been proved to be a very useful tool for the compression of image. However, the DWT is very computationally intensive process requiring innovative and computationally efficient method to obtain the image compression. The concurrent transformation of the image can be an important solution to this problem. This paper proposes a model of concurrent DWT for image compression. Additionally, the formal verification of the model has also been performed. Here the Symbolic Model Verifier (SMV) has been used as the formal verification tool. The system has been modeled in SMV and some properties have been verified formally.

Keywords: Computation Tree Logic, Discrete WaveletTransform, Formal Verification, Image Compression, Symbolic Model Verifier.

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Authors: Kyoung-jae Kim, Hyunchul Ahn, Sangwon Jeong

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This study proposes a novel recommender system to provide the advertisements of context-aware services. Our proposed model is designed to apply a modified collaborative filtering (CF) algorithm with regard to the several dimensions for the personalization of mobile devices – location, time and the user-s needs type. In particular, we employ a classification rule to understand user-s needs type using a decision tree algorithm. In addition, we collect primary data from the mobile phone users and apply them to the proposed model to validate its effectiveness. Experimental results show that the proposed system makes more accurate and satisfactory advertisements than comparative systems.

Keywords: Location-based advertisement, Recommender system, Collaborative filtering, User needs type, Mobile user.

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Authors: Manas Ranjan Kabat, Rajib Mall, Chita Ranjan Tripathy

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A scalable QoS aware multicast deployment in DiffServ networks has become an important research dimension in recent years. Although multicasting and differentiated services are two complementary technologies, the integration of the two technologies is a non-trivial task due to architectural conflicts between them. A popular solution proposed is to extend the functionality of the DiffServ components to support multicasting. In this paper, we propose an algorithm to construct an efficient QoSdriven multicast tree, taking into account the available bandwidth per service class. We also present an efficient way to provision the limited available bandwidth for supporting heterogeneous users. The proposed mechanism is evaluated using simulated tests. The simulated result reveals that our algorithm can effectively minimize the bandwidth use and transmission cost

Keywords: Differentiated Services, multicasting, QoSheterogeneity, DSCP

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Authors: Rafik Djemili, Mouldi Bedda, Hocine Bourouba

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This paper proposes a novel approach that combines statistical models and support vector machines. A hybrid scheme which appropriately incorporates the advantages of both the generative and discriminant model paradigms is described and evaluated. Support vector machines (SVMs) are trained to divide the whole speakers' space into small subsets of speakers within a hierarchical tree structure. During testing a speech token is assigned to its corresponding group and evaluation using gaussian mixture models (GMMs) is then processed. Experimental results show that the proposed method can significantly improve the performance of text independent speaker identification task. We report improvements of up to 50% reduction in identification error rate compared to the baseline statistical model.

Keywords: Speaker identification, Gaussian mixture model (GMM), support vector machine (SVM), hybrid GMM/SVM.

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Authors: G. Saitova, A. Mashurova, F. Mashurova

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In the national and professional music of oral tradition of many people in the East there is the metric formula called “ussuli", that is to say rhythmic constructions of different character and a composition. Ussuli in translation from Arabic means the law. The cultural contacts of the ancient and medieval inhabitants of the Central Asia, India, China, East Turkestan, Iraq, Afghanistan, Turkey, and Iran have played a certain role in formation of both musical and dancing heritage of each of these people. During theatrical shows many dances were performed under the accompaniment of percussion instruments as nagra, dayulpaz, doll. The abovementioned tools are used as the obligatory accompanying tool in an orchestra and at support of dancing acts as the solo tool. Dynamics of development of a dancing composition, at times execution of technique of movement depends on various combinations of ussuli and their receptions of execution.

Keywords: Dancing, plastic, rhythm, ussuli.

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Authors: Ibidapo O. Akinyemi, Ezekiel F. Adebiyi, Harrison O. D. Longe

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The major goal in defining and examining game scenarios is to find good strategies as solutions to the game. A plausible solution is a recommendation to the players on how to play the game, which is represented as strategies guided by the various choices available to the players. These choices invariably compel the players (decision makers) to execute an action following some conscious tactics. In this paper, we proposed a refinement-based heuristic as a machine learning technique for human-like decision making in playing Ayo game. The result showed that our machine learning technique is more adaptable and more responsive in making decision than human intelligence. The technique has the advantage that a search is astutely conducted in a shallow horizon game tree. Our simulation was tested against Awale shareware and an appealing result was obtained.

Keywords: Decision making, Machine learning, Strategy, Ayo game.

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Authors: Fateme Ashari-Ghomi, Najme Khorasani, Abbas Nowzari-Dalini

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In this paper, we present two new ranking and unranking algorithms for k-ary trees represented by x-sequences in Gray code order. These algorithms are based on a gray code generation algorithm developed by Ahrabian et al.. In mentioned paper, a recursive backtracking generation algorithm for x-sequences corresponding to k-ary trees in Gray code was presented. This generation algorithm is based on Vajnovszki-s algorithm for generating binary trees in Gray code ordering. Up to our knowledge no ranking and unranking algorithms were given for x-sequences in this ordering. we present ranking and unranking algorithms with O(kn2) time complexity for x-sequences in this Gray code ordering

Keywords: k-ary Tree Generation, Ranking, Unranking, Gray Code.

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Authors: Seyed Abolhasan Naeini, Hamidreza Rahmani

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Laboratory consolidated undrained triaxial (CU) tests were carried out to study the strength behavior of silty soil reinforced with randomly plastic waste bottle chips. Specimens mixed with plastic waste chips in triaxial compression tests with 0.25, 0.50, 0.75, 1.0, and 1.25% by dry weight of soil and tree different length including 4, 8, and 12 mm. In all of the samples, the width and thickness of plastic chips were kept constant. According to the results, the amount and size of plastic waste bottle chips played an important role in the increasing of the strength parameters of reinforced silt compared to the pure soil. Because of good results, the suggested method of soil improvement can be used in many engineering problems such as increasing the bearing capacity and settlement reduction in foundations.

Keywords: Soil improvement, waste bottle chips, reinforcement, silt, Triaxial test.

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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: Langa Hendrick Musawenkosi, Twala Bhekisipho

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The success or failure of students is a concern for every academic institution, college, university, governments and students themselves. Several approaches have been researched to address this concern. In this paper, a view is held that when a student enters a university or college or an academic institution, he or she enters an academic environment. The academic environment is unique concept used to develop the solution for making predictions effectively. This paper presents a model to determine the propensity of a student to succeed or fail in the French South African Schneider Electric Education Center (FSASEC) at the Vaal University of Technology (VUT). The Decision Tree algorithm is used to implement the model at FSASEC.

Keywords: Academic environment model, decision trees, FSASEC, K-nearest neighbor, machine learning, popularity index, support vector machine.

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Authors: Shamim Ahmed Koichi Nishigaki

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Genome profiling (GP), a genotype based technology, which exploits random PCR and temperature gradient gel electrophoresis, has been successful in identification/classification of organisms. In this technology, spiddos (Species identification dots) and PaSS (Pattern similarity score) were employed for measuring the closeness (or distance) between genomes. Based on the closeness (PaSS), we can buildup phylogenetic trees of the organisms. We noticed that the topology of the tree is rather robust against the experimental fluctuation conveyed by spiddos. This fact was confirmed quantitatively in this study by computer-simulation, providing the limit of the reliability of this highly powerful methodology. As a result, we could demonstrate the effectiveness of the GP approach for identification/classification of organisms.

Keywords: Fluctuation, Genome profiling (GP), Pattern similarity score (PaSS), Robustness, Spiddos-shift.

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Authors: Wann-Ming Wey, Yi-Chih Huang

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Proper maintenance and preservation of significant cultural heritages or historic buildings is necessary. It can not only enhance environmental benefits and a sense of community, but also preserve a city's history and people’s memory. It allows the next generation to be able to get a glimpse of our past, and achieve the goal of sustainable preserved cultural assets. However, the management of maintenance work has not been appropriate for many designated heritages or historic buildings so far. The planning and implementation of the reuse has yet to have a breakthrough specification. It leads the heritages to a mere formality of being “reserved”, instead of the real meaning of “conservation”. For the restoration and preservation of cultural heritages study issues, it is very important due to the consideration of historical significance, symbolism, and economic benefits effects. However, the decision makers such as the officials from public sector they often encounter which heritage should be prioritized to be restored first under the available limited budgets. Only very few techniques are available today to determine the appropriately restoration priorities for the diverse historical heritages, perhaps because of a lack of systematized decision-making aids been proposed before. In the past, the discussions of management and maintenance towards cultural assets were limited to the selection of reuse alternatives instead of the allocation of resources. In view of this, this research will adopt some integrated research methods to solve the existing problems that decision-makers might encounter when allocating resources in the management and maintenance of heritages and historic buildings.

The purpose of this study is to develop a sustainable decision making model for local governments to resolve these problems. We propose an alternative decision support model to prioritize restoration needs within the limited budgets. The model is constructed based on fuzzy Delphi, fuzzy analysis network process (FANP) and goal programming (GP) methods. In order to avoid misallocate resources; this research proposes a precise procedure that can take multi-stakeholders views, limited costs and resources into consideration. Also, the combination of many factors and goals has been taken into account to find the highest priority and feasible solution results. To illustrate the approach we propose in this research, seven cultural heritages in Taipei city as one example has been used as an empirical study, and the results are in depth analyzed to explain the application of our proposed approach.

Keywords: Cultural Heritage, Historic Buildings, Priority Evaluation, Multi-Criteria Decision Making, Goal Programming, Fuzzy Analytic Network Process, Resource Allocation.

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Authors: Lokendra Singh Umrao, Ravi Shankar Singh

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This paper presents an optimal broadcast algorithm for the hypercube networks. The main focus of the paper is the effectiveness of the algorithm in the presence of many node faults. For the optimal solution, our algorithm builds with spanning tree connecting the all nodes of the networks, through which messages are propagated from source node to remaining nodes. At any given time, maximum n − 1 nodes may fail due to crashing. We show that the hypercube networks are strongly fault-tolerant. Simulation results analyze to accomplish algorithm characteristics under many node faults. We have compared our simulation results between our proposed method and the Fu’s method. Fu’s approach cannot tolerate n − 1 faulty nodes in the worst case, but our approach can tolerate n − 1 faulty nodes.

Keywords: Fault tolerance, hypercube, broadcasting, link/node faults, routing.

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Authors: Ubonwan Chaiyo, Savitri Garivait, Kobsak Wanthongchai

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The study site was located in Ratchaburi Province, Thailand. Four experimental plots in dry dipterocarp forest (DDF) and four plots in mixed deciduous forest (MDF) were set up to estimate the above-ground biomass of tree, sapling and bamboo. The allometry equations were used to investigate above-ground biomass of these vegetation. Seedling and other understory were determined using direct harvesting method. Carbon storage in above-ground biomass was calculated based on IPCC 2006. The results showed that the above-ground biomass of DDF at 20-40% slope, <20% slope and MDF at <20% slope were 91.96, 30.95 and 59.44 ton/ha, respectively. Bamboo covers about half of total aboveground biomass in MDF, which is a specific characteristic of this area. The carbon sequestration potential in above-ground biomass of plot slope range 20-40% DDF, <20% DDF and <20% MDF are 43.22, 14.55 and 27.94 ton C/ha, respectively.

Keywords: Carbon storage, aboveground biomass, tropical deciduous forest, dry dipterocarp forest, mixed deciduous forest.

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Authors: Abdelrahman A. Ramzy, Bassel S. Abdallah, Mohamed E. Bahgat, Sarah M. Abdelkader, Sherif H. ElGohary

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Attention-Deficit/Hyperactivity Disorder (ADHD), epilepsy, and autism affect millions of children worldwide, many of which are undiagnosed despite the fact that all of these disorders are detectable in early childhood. Late diagnosis can cause severe problems due to the late treatment and to the misconceptions and lack of awareness as a whole towards these disorders. Moreover, electroencephalography (EEG) has played a vital role in the assessment of neural function in children. Therefore, quantitative EEG measurement will be utilized as a tool for use in the evaluation of patients who may have ADHD, epilepsy, and autism. We propose a screening tool that uses EEG signals and machine learning algorithms to detect these disorders at an early age in an automated manner. The proposed classifiers used with epilepsy as a step taken for the work done so far, provided an accuracy of approximately 97% using SVM, Naïve Bayes and Decision tree, while 98% using KNN, which gives hope for the work yet to be conducted.

Keywords: ADHD, autism, epilepsy, EEG, SVM.

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Authors: M. T. Artese, G. Ciocca, I. Gagliardi

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Food is a social and cultural aspect of every individual. Food products, processing, and traditions have been identified as cultural objects carrying history and identity of social groups. Traditional recipes are passed down from one generation to the other, often to strengthen the link with the territory. The paper presents CookIT, a web portal developed to collect Italian traditional recipes related to regional cuisine, with the purpose to disseminate the knowledge of typical Italian recipes and the Mediterranean diet which is a significant part of Italian cuisine. The system designed is completed with multimodal means of browsing and data retrieval. Stored recipes can be retrieved integrating and combining a number of different methods and keys, while the results are displayed using classical styles, such as list and mosaic, and also using maps and graphs, with which users can play using available keys for interaction.

Keywords: Collaborative portal, Italian cuisine, intangible cultural heritage, traditional recipes, searching and browsing.

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Authors: Guilherme Ribeiro, Alexandre Oliveira, Antonio Ferreira, Shyam Visweswaran, Gregory Cooper

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Patient-specific models are instance-based learning algorithms that take advantage of the particular features of the patient case at hand to predict an outcome. We introduce two patient-specific algorithms based on decision tree paradigm that use AUC as a metric to select an attribute. We apply the patient specific algorithms to predict outcomes in several datasets, including medical datasets. Compared to the patient-specific decision path (PSDP) entropy-based and CART methods, the AUC-based patient-specific decision path models performed equivalently on area under the ROC curve (AUC). Our results provide support for patient-specific methods being a promising approach for making clinical predictions.

Keywords: Approach instance-based, area Under the ROC Curve, Patient-specific Decision Path, clinical predictions.

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