Search results for: k-ary Tree Generation

Authors: J. Miranda, D. Chavarría-Barrientos, M. Ramírez-Cadena, M. E. Macías, P. Ponce, J. Noguez, R. Pérez-Rodríguez, P. K. Wright, A. Molina

Abstract:

Higher education methods need to evolve because the new generations of students are learning in different ways. One way is by adopting emergent technologies, new learning methods and promoting the maker movement. As a result, Tecnologico de Monterrey is developing Open Innovation Laboratories as an immediate response to educational challenges of the world. This paper presents an Open Innovation Laboratory for Rapid Realization of Sensing, Smart and Sustainable Products (S³ Products). The Open Innovation Laboratory is composed of a set of specific resources where students and teachers use them to provide solutions to current problems of priority sectors through the development of a new generation of products. This new generation of products considers the concepts Sensing, Smart, and Sustainable. The Open Innovation Laboratory has been implemented in different courses in the context of New Product Development (NPD) and Integrated Manufacturing Systems (IMS) at Tecnologico de Monterrey. The implementation consists of adapting this Open Innovation Laboratory within the course’s syllabus in combination with the implementation of specific methodologies for product development, learning methods (Active Learning and Blended Learning using Massive Open Online Courses MOOCs) and rapid product realization platforms. Using the concepts proposed it is possible to demonstrate that students can propose innovative and sustainable products, and demonstrate how the learning process could be improved using technological resources applied in the higher educational sector. Finally, examples of innovative S³ products developed at Tecnologico de Monterrey are presented.

Keywords: Active learning, blended learning, maker movement, new product development, open innovation laboratory.

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Authors: Jia-Hong Lee, Mei-Yi Wu, Hsien-Tsung Kuo

Abstract:

Texture is an important characteristic in real and synthetic scenes. Texture analysis plays a critical role in inspecting surfaces and provides important techniques in a variety of applications. Although several descriptors have been presented to extract texture features, the development of object recognition is still a difficult task due to the complex aspects of texture. Recently, many robust and scaling-invariant image features such as SIFT, SURF and ORB have been successfully used in image retrieval and object recognition. In this paper, we have tried to compare the performance for texture classification using these feature descriptors with k-means clustering. Different classifiers including K-NN, Naive Bayes, Back Propagation Neural Network , Decision Tree and Kstar were applied in three texture image sets － UIUCTex, KTH-TIPS and Brodatz, respectively. Experimental results reveal SIFTS as the best average accuracy rate holder in UIUCTex, KTH-TIPS and SURF is advantaged in Brodatz texture set. BP neuro network works best in the test set classification among all used classifiers.

Keywords: Texture classification, texture descriptor, SIFT, SURF, ORB.

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Authors: K. Sivasubramanian, K. B. Jayanthi

Abstract:

Floorplanning plays a vital role in the physical design process of Very Large Scale Integrated (VLSI) chips. It is an essential design step to estimate the chip area prior to the optimized placement of digital blocks and their interconnections. Since VLSI floorplanning is an NP-hard problem, many optimization techniques were adopted in the literature. In this work, a music-inspired Harmony Search (HS) algorithm is used for the fixed die outline constrained floorplanning, with the aim of reducing the total chip area. HS draws inspiration from the musical improvisation process of searching for a perfect state of harmony. Initially, B*-tree is used to generate the primary floorplan for the given rectangular hard modules and then HS algorithm is applied to obtain an optimal solution for the efficient floorplan. The experimental results of the HS algorithm are obtained for the MCNC benchmark circuits.

Keywords: Floor planning, harmony search, non-slicing floorplan, very large scale integrated circuits.

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Authors: Yang Zhang, Jian He

Abstract:

Heart disease is one of the leading causes of death in the world, and coronary heart disease (CHD) is one of the major heart diseases. Electrocardiogram (ECG) is widely used in the detection of heart diseases, but the traditional manual method for CHD prediction by analyzing ECG requires lots of professional knowledge for doctors. This paper presents sliding window and continuous wavelet transform (CWT) to transform ECG signals into images, and then ResNet and Bi-LSTM are introduced to build the ECG feature extraction network (namely ECGNet). At last, an auxiliary system for CHD prediction was developed based on modified ResNet18 and Bi-LSTM, and the public ECG dataset of CHD from MIMIC-3 was used to train and test the system. The experimental results show that the accuracy of the method is 83%, and the F1-score is 83%. Compared with the available methods for CHD prediction based on ECG, such as kNN, decision tree, VGGNet, etc., this method not only improves the prediction accuracy but also could avoid the degradation phenomenon of the deep learning network.

Keywords: Bi-LSTM, CHD, coronary heart disease, ECG, electrocardiogram, ResNet, sliding window.

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Authors: Jin-Hong Kim, Joon Sung Park, Jun-Hyuk Choi, In-Soung Jung

Abstract:

With a development of Hybrid Electric Vehicle(HEV), A photovoltaic(PV) generation system is used for charging batteries in many cases. A dc/dc converter using PV power for a battery charger requires a high efficiency. In this paper, A ZVS boost converter using the renewable energies for HEV charger is proposed. Through the theoretical analysis and experimental result, operation modes and characteristics of the proposed topology are verified.

Keywords: HEV, EV, charger, resonant

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Authors: Marco Actis Grande, Somlak Wannarumon

Abstract:

This paper proposes the numerical simulation of the investment casting of gold jewelry. It aims to study the behavior of fluid flow during mould filling and solidification and to optimize the process parameters, which lead to predict and control casting defects such as gas porosity and shrinkage porosity. A finite difference method, computer simulation software FLOW-3D was used to simulate the jewelry casting process. The simplified model was designed for both numerical simulation and real casting production. A set of sensor acquisitions were allocated on the different positions of the wax tree of the model to detect filling times, while a set of thermocouples were allocated to detect the temperature during casting and cooling. Those detected data were applied to validate the results of the numerical simulation to the results of the real casting. The resulting comparisons signify that the numerical simulation can be used as an effective tool in investment-casting-process optimization and casting-defect prediction.

Keywords: Computer fluid dynamic, Investment casting, Jewelry, Mould filling, Simulation.

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Authors: Hyun-Woo Cho

Abstract:

The early diagnostic decision making in industrial processes is absolutely necessary to produce high quality final products. It helps to provide early warning for a special event in a process, and finding its assignable cause can be obtained. This work presents a hybrid diagnostic schmes for batch processes. Nonlinear representation of raw process data is combined with classification tree techniques. The nonlinear kernel-based dimension reduction is executed for nonlinear classification decision boundaries for fault classes. In order to enhance diagnosis performance for batch processes, filtering of the data is performed to get rid of the irrelevant information of the process data. For the diagnosis performance of several representation, filtering, and future observation estimation methods, four diagnostic schemes are evaluated. In this work, the performance of the presented diagnosis schemes is demonstrated using batch process data.

Keywords: Diagnostics, batch process, nonlinear representation, data filtering, multivariate statistical approach

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Authors: Farrukh Shahzad

Abstract:

The rich Islamic resources related to religious text, Islamic sciences, and history are widely available in print and in electronic format online. However, most of these works are only available in Arabic language. In this research, an attempt is made to utilize these resources to create interactive web applications in Arabic, English and other languages. The system utilizes the Pattern Recognition, Knowledge Management, Data Mining, Information Retrieval and Management, Indexing, storage and data-analysis techniques to parse, store, convert and manage the information from authentic Arabic resources. These interactive web Apps provide smart multi-lingual search, tree based search, on-demand information matching and linking. In this paper, we provide details of application architecture, design, implementation and technologies employed. We also presented the summary of web applications already developed. We have also included some screen shots from the corresponding web sites. These web applications provide an Innovative On-line Learning Systems (eLearning and computer based education).

Keywords: Islamic resources, Muslim scholars, hadith, narrators, history, fiqh.

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Authors: Wisam H. Benamer, Ehab A. Elfallah, Mohamed A. Elshaari, Farag A. Elshaari

Abstract:

A challenge for laboratories is to provide bacterial identification and antibiotic sensitivity results within a short time. Hence, advancement in the required technology is desirable to improve timing, accuracy and quality. Even with the current advances in methods used for both phenotypic and genotypic identification of bacteria the need is there to develop method(s) that enhance the outcome of bacteriology laboratories in accuracy and time. The hypothesis introduced here is based on the assumption that the chromosome of any bacteria contains unique sequences that can be used for its identification and typing. The outcome of a pilot study designed to test this hypothesis is reported in this manuscript. Methods: The complete chromosome sequences of several bacterial species were downloaded to use as search targets for unique sequences. Visual basic and SQL server (2014) were used to generate a complete set of 18-base long primers, a process started with reverse translation of randomly chosen 6 amino acids to limit the number of the generated primers. In addition, the software used to scan the downloaded chromosomes using the generated primers for similarities was designed, and the resulting hits were classified according to the number of similar chromosomal sequences, i.e., unique or otherwise. Results: All primers that had identical/similar sequences in the selected genome sequence(s) were classified according to the number of hits in the chromosomes search. Those that were identical to a single site on a single bacterial chromosome were referred to as unique. On the other hand, most generated primers sequences were identical to multiple sites on a single or multiple chromosomes. Following scanning, the generated primers were classified based on ability to differentiate between medically important bacterial and the initial results looks promising. Conclusion: A simple strategy that started by generating primers was introduced; the primers were used to screen bacterial genomes for match. Primer(s) that were uniquely identical to specific DNA sequence on a specific bacterial chromosome were selected. The identified unique sequence can be used in different molecular diagnostic techniques, possibly to identify bacteria. In addition, a single primer that can identify multiple sites in a single chromosome can be exploited for region or genome identification. Although genomes sequences draft of isolates of organism DNA enable high throughput primer design using alignment strategy, and this enhances diagnostic performance in comparison to traditional molecular assays. In this method the generated primers can be used to identify an organism before the draft sequence is completed. In addition, the generated primers can be used to build a bank for easy access of the primers that can be used to identify bacteria.

Keywords: Bacteria chromosome, bacterial identification, sequence, primer generation.

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Authors: Insaf Mehani, Bachir Bouchekima

Abstract:

The fight against climate change and the replacement of fossil energies nearing exhaustion gradually emerge as major societal and economic challenges. It is possible to develop common dates of low commercial value, and put on the local and international market a new generation of products with high added values such as bio ethanol. Besides its use in chemical synthesis, bio ethanol can be blended with gasoline to produce a clean fuel while improving the octane.

Keywords: Bio energy, waste dates, bio ethanol.

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Authors: Cristina Vatamanu, Doina Cosovan, Dragoş Gavriluţ, Henri Luchian

Abstract:

In the past few years, the amount of malicious software increased exponentially and, therefore, machine learning algorithms became instrumental in identifying clean and malware files through (semi)-automated classification. When working with very large datasets, the major challenge is to reach both a very high malware detection rate and a very low false positive rate. Another challenge is to minimize the time needed for the machine learning algorithm to do so. This paper presents a comparative study between different machine learning techniques such as linear classifiers, ensembles, decision trees or various hybrids thereof. The training dataset consists of approximately 2 million clean files and 200.000 infected files, which is a realistic quantitative mixture. The paper investigates the above mentioned methods with respect to both their performance (detection rate and false positive rate) and their practicability.

Keywords: Detection Rate, False Positives, Perceptron, One Side Class, Ensembles, Decision Tree, Hybrid methods, Feature Selection.

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Authors: Ehsan Amid, Sina Rezaei Aghdam, Hamidreza Amindavar

Abstract:

Steel surface defect detection is essentially one of pattern recognition problems. Support Vector Machines (SVMs) are known as one of the most proper classifiers in this application. In this paper, we introduce a more accurate classification method by using SVMs as our final classifier of the inspection system. In this scheme, multiclass classification task is performed based on the "one-againstone" method and different kernels are utilized for each pair of the classes in multiclass classification of the different defects. In the proposed system, a decision tree is employed in the first stage for two-class classification of the steel surfaces to "defect" and "non-defect", in order to decrease the time complexity. Based on the experimental results, generated from over one thousand images, the proposed multiclass classification scheme is more accurate than the conventional methods and the overall system yields a sufficient performance which can meet the requirements in steel manufacturing.

Keywords: Steel Surface Defect Detection, Support Vector Machines, Kernel Methods.

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Authors: Kevin Fong-Rey Liu, Jia-Shen Chen, Han-Hsi Liang, Cheng-Wu Chen, Yung-Shuen Shen

Abstract:

The purpose of determining impact significance is to place value on impacts. Environmental impact assessment review is a process that judges whether impact significance is acceptable or not in accordance with the scientific facts regarding environmental, ecological and socio-economical impacts described in environmental impact statements (EIS) or environmental impact assessment reports (EIAR). The first aim of this paper is to summarize the criteria of significance evaluation from the past review results and accordingly utilize fuzzy logic to incorporate these criteria into scientific facts. The second aim is to employ data mining technique to construct an EIS or EIAR prediction model for reviewing results which can assist developers to prepare and revise better environmental management plans in advance. The validity of the previous prediction model proposed by authors in 2009 is 92.7%. The enhanced validity in this study can attain 100.0%.

Keywords: Environmental impact assessment review, impactsignificance, fuzzy logic, data mining, classification tree.

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Authors: Insah Bhurtah, P. Clarel Catherine, K. M. Sunjiv Soyjaudah

Abstract:

When using modern Code Division Multiple Access (CDMA) in mobile communications, the user must be able to vary the transmission rate of users to allocate bandwidth efficiently. In this work, Orthogonal Variable Spreading Factor (OVSF) codes are used with the same principles applied in a low-rate superorthogonal turbo code due to their variable-length properties. The introduced system is the Variable Rate Superorthogonal Turbo Code (VRSTC) where puncturing is not performed on the encoder’s final output but rather before selecting the output to achieve higher rates. Due to bandwidth expansion, the codes outperform an ordinary turbo code in the AWGN channel. Simulations results show decreased performance compared to those obtained with the employment of Walsh-Hadamard codes. However, with OVSF codes, the VRSTC system keeps the orthogonality of codewords whilst producing variable rate codes contrary to Walsh-Hadamard codes where puncturing is usually performed on the final output.

Keywords: CDMA, MAP Decoding, OVSF, Superorthogonal Turbo Code.

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Authors: Panchalee Sukjit, Herwig Unger

Abstract:

IT infrastructures are becoming more and more difficult. Therefore, in the first industrial IT systems, the P2P paradigm has replaced the traditional client server and methods of self-organization are gaining more and more importance. From the past it is known that especially regular structures like grids may significantly improve the system behavior and performance. This contribution introduces a new algorithm based on a biologic analogue, which may provide the growth of several regular structures on top of anarchic grown P2P- or social network structures.

Keywords: P2P, Pattern generation, Grid, Social network, Inheritance, Reproduction

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Authors: Denise Levy, Helen J. Khoury

Abstract:

Nuclear technology is a controversial issue among a great share of the Brazilian population. Misinformation and common wrong beliefs confuse public’s perceptions and the scientific community is expected to offer a wider perspective on the benefits and risks resulting from ionizing radiation in everyday life. Attentive to the need of new approaches between science and society, the Nuclear Energy Museum, in northeast Brazil, is an initiative created to communicate the growing impact of the beneficial applications of nuclear technology in medicine, industry, agriculture and electric power generation. Providing accessible scientific information, the museum offers a rich learning environment, making use of different educational strategies, such as films, interactive panels and multimedia learning tools, which not only increase the enjoyment of visitors, but also maximize their learning potential. Developed according to modern active learning instructional strategies, multimedia materials are designed to present the increasingly role of nuclear science in modern life, transforming science education into a meaningful learning experience. In year 2016, nine different interactive computer-based activities were developed, presenting curiosities about ionizing radiation in different landmarks around the world, such as radiocarbon dating works in Egypt, nuclear power generation in France and X-radiography of famous paintings in Italy. Feedback surveys have reported a high level of visitors’ satisfaction, proving the high quality experience in learning nuclear science at the museum. The Nuclear Energy Museum is the first and, up to the present time, the only permanent museum in Brazil devoted entirely to nuclear science.

Keywords: Nuclear technology, multimedia learning tools, science museum, society and education.

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Authors: Snezhana G. Gocheva-Ilieva, Maya P. Stoimenova

Abstract:

Ambient air pollution with fine particulate matter (PM10) is a systematic permanent problem in many countries around the world. The accumulation of a large number of measurements of both the PM10 concentrations and the accompanying atmospheric factors allow for their statistical modeling to detect dependencies and forecast future pollution. This study applies the classification and regression trees (CART) method for building and analyzing PM10 models. In the empirical study, average daily air data for the city of Pleven, Bulgaria for a period of 5 years are used. Predictors in the models are seven meteorological variables, time variables, as well as lagged PM10 variables and some lagged meteorological variables, delayed by 1 or 2 days with respect to the initial time series, respectively. The degree of influence of the predictors in the models is determined. The selected best CART models are used to forecast future PM10 concentrations for two days ahead after the last date in the modeling procedure and show very accurate results.

Keywords: Cross-validation, decision tree, lagged variables, short-term forecasting.

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Authors: Ivaylo I. Atanasov, Evelina N.Pencheva

Abstract:

This paper presents a mark-up approach to service creation in Next Generation Networks. The approach allows deriving added value from network functions exposed by Parlay/OSA (Open Service Access) interfaces. With OSA interfaces service logic scripts might be executed both on callrelated and call-unrelated events. To illustrate the approach XMLbased language constructions for data and method definitions, flow control, time measuring and supervision and database access are given and an example of OSA application is considered.

Keywords: Service creation, mark-up approach.

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Authors: Vesile Evrim, Aliyu Awwal

Abstract:

By the evolvement in technology, the way of expressing opinions switched direction to the digital world. The domain of politics, as one of the hottest topics of opinion mining research, merged together with the behavior analysis for affiliation determination in texts, which constitutes the subject of this paper. This study aims to classify the text in news/blogs either as Republican or Democrat with the minimum number of features. As an initial set, 68 features which 64 were constituted by Linguistic Inquiry and Word Count (LIWC) features were tested against 14 benchmark classification algorithms. In the later experiments, the dimensions of the feature vector reduced based on the 7 feature selection algorithms. The results show that the “Decision Tree”, “Rule Induction” and “M5 Rule” classifiers when used with “SVM” and “IGR” feature selection algorithms performed the best up to 82.5% accuracy on a given dataset. Further tests on a single feature and the linguistic based feature sets showed the similar results. The feature “Function”, as an aggregate feature of the linguistic category, was found as the most differentiating feature among the 68 features with the accuracy of 81% in classifying articles either as Republican or Democrat.

Keywords: Politics, machine learning, feature selection, LIWC.

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Authors: M. Stewart, Ameer Al-Khaykan, J. M. Counsell

Abstract:

Emissions are a consequence of electricity generation. A major option for low carbon generation, local energy systems featuring Combined Heat and Power with solar PV (CHPV) has significant potential to increase energy performance, increase resilience, and offer greater control of local energy prices while complementing the UK’s emissions standards and targets. Recent advances in dynamic modelling and simulation of buildings and clusters of buildings using the IDEAS framework have successfully validated a novel multi-vector (simultaneous control of both heat and electricity) approach to integrating the wide range of primary and secondary plant typical of local energy systems designs including CHP, solar PV, gas boilers, absorption chillers and thermal energy storage, and associated electrical and hot water networks, all operating under a single unified control strategy. Results from this work indicate through simulation that integrated control of thermal storage can have a pivotal role in optimizing system performance well beyond the present expectations. Environmental impact analysis and reporting of all energy systems including CHPV LES presently employ a static annual average carbon emissions intensity for grid supplied electricity. This paper focuses on establishing and validating CHPV environmental performance against conventional emissions values and assessment benchmarks to analyze emissions performance without and with an active thermal store in a notional group of non-domestic buildings. Results of this analysis are presented and discussed in context of performance validation and quantifying the reduced environmental impact of CHPV systems with active energy storage in comparison with conventional LES designs.

Keywords: CHPV, thermal storage, control, dynamic simulation.

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Authors: Govindaraju.M, Ganeshkumar.R.S, Suganthi.P, Muthukumaran.V.R, Visvanathan.P

Abstract:

The present study was conducted to investigate the response of plants exposed to lignite-based thermal power plant emission. For this purpose, five plant species were collected from 1.0 km distance (polluted site) and control plants were collected from 20.0 km distance (control site) to thermal power plant. The common tree species Cassia siamea Lamk., Polyalthia longifolia. Sonn, Acacia longifolia (Andrews) Wild., Azadirachta indica A.Juss, Ficus religiosa L. were selected as test plants. Photosynthetic pigments changes (chlorophyll a, chlorophyll b and carotenoids) and rubisco enzyme modifications were studied. Reduction was observed in the photosynthetic pigments of plants growing in polluted site and also large sub unit of the rubisco enzyme was degraded in Azadirachta indica A. Juss collected from polluted site.

Keywords: Air pollution, Lignite-based thermal power plant, Photosynthetic pigments, Rubisco enzyme.

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Authors: Rade M. Ciric, Nikola Lj.Rajakovic

Abstract:

Since the 80s huge efforts have been made to utilize renewable energy sources to generate electric power. This paper reports some aspects of integration of the distributed generators into the low voltage distribution networks. An assessment of impact of the distributed generators on the reliability indices of low voltage network is performed. Results obtained from case study using low voltage network, are presented and discussed.

Keywords: low voltage network, distributed generation, reliability indices

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Authors: M. Mehani, N. Salhi, T. Valeria, S. Ladjel

Abstract:

Red River Gum (Eucalyptus camaldulensis) is a tree of the genus Eucalyptus widely distributed in Algeria and in the world. The value of its aromatic secondary metabolites offers new perspectives in the pharmaceutical industry. This strategy can contribute to the sustainable development of our country. Preliminary tests performed on the essential oil of Eucalyptus camendulensis showed that this oil has antibacterial activity vis-à-vis the bacterial strains (Enterococcus feacalis, Enterobacter cloaceai, Proteus microsilis, Escherichia coli, Klebsiella pneumonia, and Pseudomonas aeruginosa) and antifungic (Fusarium sporotrichioide and Fusarium graminearum). The culture medium used was nutrient broth Muller Hinton. The interaction between the bacteria and the essential oil is expressed by a zone of inhibition with diameters of MIC indirectly expression of. And we used the PDA medium to determine the fungal activity. The extraction of the aromatic fraction (essentially oilhydrolat) of the fresh aerian part of the Eucalyptus camendulensis was performed by hydrodistillation. The average essential oil yield is 0.99%. The antimicrobial and fungal study of the essential oil and hydrosol showed a high inhibitory effect on the growth of pathogens.

Keywords: Essential oil, Eucalyptus camendulensis, bacteria and Fungi.

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Authors: Tessy Badriyah, Jim S. Briggs, Dave R. Prytherch

Abstract:

It is well known that Logistic Regression is the gold standard method for predicting clinical outcome, especially predicting risk of mortality. In this paper, the Decision Tree method has been proposed to solve specific problems that commonly use Logistic Regression as a solution. The Biochemistry and Haematology Outcome Model (BHOM) dataset obtained from Portsmouth NHS Hospital from 1 January to 31 December 2001 was divided into four subsets. One subset of training data was used to generate a model, and the model obtained was then applied to three testing datasets. The performance of each model from both methods was then compared using calibration (the χ2 test or chi-test) and discrimination (area under ROC curve or c-index). The experiment presented that both methods have reasonable results in the case of the c-index. However, in some cases the calibration value (χ2) obtained quite a high result. After conducting experiments and investigating the advantages and disadvantages of each method, we can conclude that Decision Trees can be seen as a worthy alternative to Logistic Regression in the area of Data Mining.

Keywords: Decision Trees, Logistic Regression, clinical outcome, risk of mortality.

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Authors: I. Turk Cakir, B. Hacisahinoglu, S. Kartal, A. Yilmaz, A. Yilmaz, Z. Uysal, O. Cakir

Abstract:

In the search for new physics beyond the Standard Model, Flavour Changing Neutral Current (FCNC) is a good research field in terms of the observability at future colliders. Increased Higgs production with higher energy and luminosity in colliders is essential for verification or falsification of our knowledge of physics and predictions, and the search for new physics. Prospective electron-proton collider constituent of the Future Circular Collider project is FCC-eh. It offers great sensitivity due to its high luminosity and low interference. In this work, thq FCNC interaction vertex with off-shell top quark decay at electron-proton colliders is studied. By using MadGraph5_aMC@NLO multi-purpose event generator, observability of tuh and tch couplings are obtained with equal coupling scenario. Upper limit on branching ratio of tree level top quark FCNC decay is determined as 0.012% at FCC-eh with 1 ab ^−1 luminosity.

Keywords: FCC, FCNC, Higgs Boson, Top Quark.

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Authors: Yasser M. Saad, Amr A. El Hanafy, Saleh A. Alkarim, Hussein A. Almehdar, Elrashdy M. Redwan

Abstract:

Camels are substantial providers of transport, milk, sport, meat, shelter, security and capital in many countries, particularly in Saudi Arabia. Inter simple sequence repeat technique was used to detect the genetic variations among some camel breeds (Majaheim, Safra, Wadah, and Hamara). Actual number of alleles, effective number of alleles, gene diversity, Shannon’s information index and polymorphic bands were calculated for each evaluated camel breed. Neighbor-joining tree that re-constructed for evaluated these camel breeds showed that, Hamara breed is distantly related from the other evaluated camels. In addition, the polymorphic sites, haplotypes and nucleotide diversity were identified for some camelidae cox1 gene sequences (obtained from NCBI). The distance value between C. bactrianus and C. dromedarius (0.072) was relatively low. Analysis of genetic diversity is an important way for conserving Camelus dromedarius genetic resources.

Keywords: Camel, genetics, ISSR, cox1, neighbor-joining.

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Authors: T. C. Manjunath, C. Ardil

Abstract:

This paper presents an efficient method of obtaining a straight-line motion in the tool configuration space using an articulated robot between two specified points. The simulation results & the implementation results show the effectiveness of the method.

Keywords: Bounded deviation algorithm, Straight line motion, Tool configuration space, Joint space, TCV.

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Authors: Gideon J. Bonthuys, Marco van Dijk, Jay N. Bhagwan

Abstract:

Small scale hydropower used to play a very important role in the provision of energy to urban and rural areas of South Africa. The national electricity grid, however, expanded and offered cheap, coal generated electricity and a large number of hydropower systems were decommissioned. Unfortunately, large numbers of households and communities will not be connected to the national electricity grid for the foreseeable future due to high cost of transmission and distribution systems to remote communities due to the relatively low electricity demand within rural communities and the allocation of current expenditure on upgrading and constructing of new coal fired power stations. This necessitates the development of feasible alternative power generation technologies. A feasibility and implementation model was developed to assist in designing and financially evaluating small-scale hydropower (SSHP) plants. Several sites were identified using the model. The SSHP plants were designed for the selected sites and the designs for the different selected sites were priced using pricing models (civil, mechanical and electrical aspects). Following feasibility studies done on the designed and priced SSHP plants, a feasibility analysis was done and a design chart developed for future similar potential SSHP plant projects. The methodology followed in conducting the feasibility analysis for other potential sites consisted of developing cost and income/saving formulae, developing net present value (NPV) formulae, Capital Cost Comparison Ratio (CCCR) and levelised cost formulae for SSHP projects for the different types of plant installations. It included setting up a model for the development of a design chart for a SSHP, calculating the NPV, CCCR and levelised cost for the different scenarios within the model by varying different parameters within the developed formulae, setting up the design chart for the different scenarios within the model and analyzing and interpreting results. From the interpretation of the develop design charts for feasible SSHP in can be seen that turbine and distribution line cost are the major influences on the cost and feasibility of SSHP. High head, short transmission line and islanded mini-grid SSHP installations are the most feasible and that the levelised cost of SSHP is high for low power generation sites. The main conclusion from the study is that the levelised cost of SSHP projects indicate that the cost of SSHP for low energy generation is high compared to the levelised cost of grid connected electricity supply; however, the remoteness of SSHP for rural electrification and the cost of infrastructure to connect remote rural communities to the local or national electricity grid provides a low CCCR and renders SSHP for rural electrification feasible on this basis.

Keywords: Feasibility, cost, rural electrification, small-scale hydropower.

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Authors: Ploysai Ohama, Nattida Tumpat

Abstract:

Natural dye extracted from Caesalpinia sappan Linn. was applied to a cotton fabric and silk yarn by dyeing process. The dyestuff component of Caesalpinia sappan Linn. was extracted using water and ethanol. Analytical studies such as UV–VIS spectrophotometry and gravimetric analysis were performed on the extracts. Brazilein, the major dyestuff component of Caesalpinia sappan Linn. was confirmed in both aqueous and ethanolic extracts by UV–VIS spectrum. The color of each dyed material was investigated in terms of the CIELAB (L*, a* and b*) and K/S values. Cotton fabric dyed without mordant had a shade of reddish-brown, while those post-mordanted with aluminum potassium sulfate, ferrous sulfate and copper sulfate produced a variety of wine red to dark purple color shades. Cotton fabric and silk yarn dyeing was studied using aluminum potassium sulfate as a mordant. The observed color strength was enhanced with increase in mordant concentration.

Keywords: Natural dyes, Plant materials, Dyeing, Mordant.

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Authors: S. Rokhsari, M. Delavar, A. Sadeghi-Niaraki, A. Abed-Elmdoust, B. Moshiri

Abstract:

Traffic incident has bad effect on all parts of society so controlling road networks with enough traffic devices could help to decrease number of accidents, so using the best method for optimum site selection of these devices could help to implement good monitoring system. This paper has considered here important criteria for optimum site selection of traffic camera based on aggregation methods such as Bagging and Dempster-Shafer concepts. In the first step, important criteria such as annual traffic flow, distance from critical places such as parks that need more traffic controlling were identified for selection of important road links for traffic camera installation, Then classification methods such as Artificial neural network and Decision tree algorithms were employed for classification of road links based on their importance for camera installation. Then for improving the result of classifiers aggregation methods such as Bagging and Dempster-Shafer theories were used.

Keywords: Aggregation, Bagging theory, Dempster-Shafer theory, Site selection

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