Search results for: context based recommendation

Authors: Mansour Tarafdar, Mohammad Saniee Abade

Abstract:

This paper investigates the problem of sampling from transactional data streams. We introduce CFISDS as a content based sampling algorithm that works on a landmark window model of data streams and preserve more informed sample in sample space. This algorithm that work based on closed frequent itemset mining tasks, first initiate a concept lattice using initial data, then update lattice structure using an incremental mechanism.Incremental mechanism insert, update and delete nodes in/from concept lattice in batch manner. Presented algorithm extracts the final samples on demand of user. Experimental results show the accuracy of CFISDS on synthetic and real datasets, despite on CFISDS algorithm is not faster than exist sampling algorithms such as Z and DSS.

Keywords: Sampling, data streams, closed frequent item set mining.

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Authors: Radek Němec

Abstract:

Today's business environment requires that companies have access to highly relevant information in a matter of seconds. Modern Business Intelligence tools rely on data structured mostly in traditional dimensional database schemas, typically represented by star schemas. Dimensional modeling is already recognized as a leading industry standard in the field of data warehousing although several drawbacks and pitfalls were reported. This paper focuses on the analysis of another data warehouse modeling technique - the anchor modeling, and its characteristics in context with the standardized dimensional modeling technique from a query performance perspective. The results of the analysis show information about performance of queries executed on database schemas structured according to principles of each database modeling technique.

Keywords: Data warehousing, anchor modeling, star schema, anchor schema, query performance.

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Authors: Elis N. Herliyana , Kunio Tsunoda, Yusuf S. Hadi, Arinana, Dewi A. Natalia

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This study aims to determine the level of resistance of Hevea brasiliensis and Paraserianthes falcataria (synonym: Falcataria molucana) against wood rot fungi Pleurotus ostreatus based on Indonesian standard SNI 01.7207-2006 and Japanese standard JIS K 1571-2004. The variables measured were visual appearance and weight loss percentage of wood based on longitudinal and cross section fiber directions of rubber wood and sengon wood. Measurement of oven dry weight loss of wood samples performed after 12 weeks incubation. Replication performed was 10 times at each treatment combination. The results based on SNI 01.7207-2006, weight loss value of H. brasiliensis and P. falcataria wood with fiber direction longitudinal were 23,12 and 22,25% respectively and cross section were 20,77 and 18,76% respectively, and all were classified to resistance class IV (no resistance). The results based on JIS K 1571-2004, weight loss value of both woods with fiber direction cross section were 10,95 and 14,20% respectively.

Keywords: H. brasiliensis wood, Natural durability, P. falcataria wood, P. ostreatus.

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Authors: Uttam Vijay, Nitin Gupta

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Due to heavy energy constraints in WSNs clustering is an efficient way to manage the energy in sensors. There are many methods already proposed in the area of clustering and research is still going on to make clustering more energy efficient. In our paper we are proposing a minimum spanning tree based clustering using divide and conquer approach. The MST based clustering was first proposed in 1970’s for large databases. Here we are taking divide and conquer approach and implementing it for wireless sensor networks with the constraints attached to the sensor networks. This Divide and conquer approach is implemented in a way that we don’t have to construct the whole MST before clustering but we just find the edge which will be the part of the MST to a corresponding graph and divide the graph in clusters there itself if that edge from the graph can be removed judging on certain constraints and hence saving lot of computation.

Keywords: Algorithm, Clustering, Edge-Weighted Graph, Weighted-LEACH.

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Authors: Z.F. Fadzil, H.S. Hashim, A.I. Che-Ani, S. Aziz

Abstract:

Campus sustainability is the goal of a university striving for sustainable development. This study found that of 17 popular approaches, two comprehensive campus sustainability assessment frameworks were developed in the context of Sustainability in Higher Education (SHE), and used by many university campuses around the world. Sustainability Tracking Assessment and Rating Systems (STARS) and the Campus Sustainability Assessment Framework (CSAF) approaches are more comprehensive than others. Therefore, the researchers examined aspects and elements used by CSAF and STARS in the approach to develop a campus sustainability assessment framework for Universiti Kebangsaan Malaysia (UKM). Documents analysis found that CSAF and STARS do not focus on physical development, especially the construction industry, as key elements of campus sustainability assessment. This finding is in accordance with the Sustainable UKM Programme which consists of three main components of sustainable community, ecosystem and physical development.

Keywords: Campus sustainability, campus sustainability assessment, sustainability assessment framework, sustainable campus

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Authors: Chizzoniti Domenico, Beggiora Klizia, Cattani Letizia, Moscatelli Monica

Abstract:

This paper concerns the study of sustainable construction materials applied on the "Health Post", a prototype for the primary health care situated in alienated areas of the world. It's suitable for social and climatic Sub-Saharan context; however, it could be moved in other countries of the world with similar urgent needs. The idea is to create a Health Post with local construction materials that have a low environmental impact and promote the local workforce allowing reuse of traditional building techniques lowering production costs and transport. The aim of Primary Health Care Centre is to be a flexible and expandable structure identifying a modular form that can be repeated several times to expand its existing functions. In this way it could be not only a health care centre but also a socio-cultural facility.

Keywords: Low costs building, sustainable construction materials, green construction system, prototype, health care, emergency.

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Authors: Maythapolnun Athimethphat, Boontarika Lerteerawong

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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: Mei-Fang Wu, Shu-Li Wang, Tsung-Yueh Lu, Feng-Tsung Cheng

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Strengthening core competitiveness is the main goal of enterprises in a fierce competitive environment. Accurate cost information is a great help for managers in dealing with operation strategies. This paper establishes a profitability management mechanism that applies the Activity-Based Benefit approach (ABBA) to solve the profitability for each customer from the market. ABBA provides financial and non-financial information for the operation, but also indicates what resources have expired in the operational process. The customer profit management model shows the level of profitability of each customer for the company. The empirical data were gathered from a case company operating in the leather industry in Taiwan. The research findings indicate that 30% of customers create little profit for the company as a result of asking for over 5% of sales discounts. Those customers ask for sales discount because of color differences of leather products. This paper provides a customer’s profitability evaluation mechanism to help enterprises to greatly improve operating effectiveness and promote operational activity efficiency and overall operation profitability.

Keywords: Activity-based benefit approach, customer profit analysis, leather industry, profitability management mechanism.

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Authors: Andhe Dharani, P. S. Satyanarayana, Andhe Pallavi

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Considering payload, reliability, security and operational lifetime as major constraints in transmission of images we put forward in this paper a steganographic technique implemented at the physical layer. We suggest transmission of Halftoned images (payload constraint) in wireless sensor networks to reduce the amount of transmitted data. For low power and interference limited applications Turbo codes provide suitable reliability. Ensuring security is one of the highest priorities in many sensor networks. The Turbo Code structure apart from providing forward error correction can be utilized to provide for encryption. We first consider the Halftoned image and then the method of embedding a block of data (called secret) in this Halftoned image during the turbo encoding process is presented. The small modifications required at the turbo decoder end to extract the embedded data are presented next. The implementation complexity and the degradation of the BER (bit error rate) in the Turbo based stego system are analyzed. Using some of the entropy based crypt analytic techniques we show that the strength of our Turbo based stego system approaches that found in the OTPs (one time pad).

Keywords: Halftoning, Turbo codes, security, operationallifetime, Turbo based stego system.

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Authors: Zuraidasahana Zulkarnain, Mohd Shafry Mohd Rahim, Nor Anita Fairos Ismail, Mohd Azhar M. Arsad

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Handwritten signature is accepted widely as a biometric characteristic for personal authentication. The use of appropriate features plays an important role in determining accuracy of signature verification; therefore, this paper presents a feature based on the geometrical concept. To achieve the aim, triangle attributes are exploited to design a new feature since the triangle possesses orientation, angle and transformation that would improve accuracy. The proposed feature uses triangulation geometric set comprising of sides, angles and perimeter of a triangle which is derived from the center of gravity of a signature image. For classification purpose, Euclidean classifier along with Voting-based classifier is used to verify the tendency of forgery signature. This classification process is experimented using triangular geometric feature and selected global features. Based on an experiment that was validated using Grupo de Senales 960 (GPDS-960) signature database, the proposed triangular geometric feature achieves a lower Average Error Rates (AER) value with a percentage of 34% as compared to 43% of the selected global feature. As a conclusion, the proposed triangular geometric feature proves to be a more reliable feature for accurate signature verification.

Keywords: biometrics, euclidean classifier, feature extraction, offline signature verification, VOTING-based classifier

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Authors: Behrooz Movahedi

Abstract:

Fe-based amorphous feedstock powders are used as the matrix into which various ratios of hard B4C nanoparticles (0, 5, 10, 15, 20 vol.%) as reinforcing agents were prepared using a planetary high-energy mechanical milling. The ball-milled nanocomposite feedstock powders were also sprayed by means of high-velocity oxygen fuel (HVOF) technique. The characteristics of the powder particles and the prepared coating depending on their microstructures and nanohardness were examined in detail using nanoindentation tester. The results showed that the formation of the Fe-based amorphous phase was noticed over the course of high-energy ball milling. It is interesting to note that the nanocomposite coating is divided into two regions, namely, a full amorphous phase region and homogeneous dispersion of B4C nanoparticles with a scale of 10–50 nm in a residual amorphous matrix. As the B4C content increases, the nanohardness of the composite coatings increases, but the fracture toughness begins to decrease at the B4C content higher than 20 vol.%. The optimal mechanical properties are obtained with 15 vol.% B4C due to the suitable content and uniform distribution of nanoparticles. Consequently, the changes in mechanical properties of the coatings were attributed to the changes in the brittle to ductile transition by adding B4C nanoparticles.

Keywords: Fe-based amorphous, B4C nanoparticles, nanocomposite coating, HVOF.

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Authors: Pejman Hosseinioun, Rose Shayeghi, Ghasem Ghorbani Rostam

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Nowadays, obtaining traditional statistics and reports is not adequate for the needs of organizational managers. The managers need to analyze and to transform the raw data into knowledge in the world filled with information. Therefore in this regard various processes have been developed. In the meantime the artificial intelligence-based processes are used and the new topics such as business intelligence and knowledge discovery have emerged. In the current paper it is sought to study the business intelligence and its applications in the organizations.

Keywords: Business intelligence, business intelligence infrastructures, business processes.

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Authors: Melike Şah, Konstantin Y.Degtiarev

Abstract:

This paper proposes a novel improvement of forecasting approach based on using time-invariant fuzzy time series. In contrast to traditional forecasting methods, fuzzy time series can be also applied to problems, in which historical data are linguistic values. It is shown that proposed time-invariant method improves the performance of forecasting process. Further, the effect of using different number of fuzzy sets is tested as well. As with the most of cited papers, historical enrollment of the University of Alabama is used in this study to illustrate the forecasting process. Subsequently, the performance of the proposed method is compared with existing fuzzy time series time-invariant models based on forecasting accuracy. It reveals a certain performance superiority of the proposed method over methods described in the literature.

Keywords: Forecasting, fuzzy time series, linguistic values, student enrollment, time-invariant model.

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Authors: O. Benaziz, A. Dorbane, S. Djeraba

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The objective of this work is to formulate a dry dispersible form of furosemide in the context of pediatric dose adjustment. To achieve this, we have produced a set of formulas that will be tested in process and after compression. The formula with the best results will be improved to optimize the final shape of the product. Furosemide is the most widely used pediatric diuretic because of its low toxicity. The manufacturing process was chosen taking into account all the data relating to the active ingredient and the excipients used and complying with the specifications and requirements of dispersible tablets. The process used to prepare these tablets was wet granulation. Different excipients were used: lactose, maize starch, magnesium stearate and two superdisintegrants. The mode of incorporation of super-disintegrant changes with each formula. The use of super-disintegrant in the formula allowed optimization of the disintegration time. Prepared tablets were evaluated for weight, content uniformity, hardness, disintegration time, friability and in vitro dissolution test. 

Keywords: Formulation, dispersible tablets, wet granulation, superdisintegrants, disintegration.

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Authors: Mohit Tyagi, Pradeep Kumar

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The objective of this research work is to identify and analyze the significant corporate social responsibility (CSR) practices with an aim to improve the supply chain performance of automobile industry located at National Capital Region (NCR) of India. To achieve the objective, 6 CSR practices have been considered and analyzed using expert’s preference rating (EPR) approach. The considered CSR practices are namely, Top management and employee awareness about CSR (P₁), Employee involvement in social and environmental problems (P₂), Protection of human rights (P₃), Waste reduction, energy saving and water conservation (P₄), Proper visibility of CSR guidelines (P₅) and Broad perception towards CSR initiatives (P₆). The outcomes of this research may help mangers in decision making processes and framing polices for SCP implementation under CSR context.

Keywords: Supply chain performance, corporate social responsibility, CSR practices, expert’s preference rating approach.

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Authors: Satish Kumar

Abstract:

The feature extraction method(s) used to recognize hand-printed characters play an important role in ICR applications. In order to achieve high recognition rate for a recognition system, the choice of a feature that suits for the given script is certainly an important task. Even if a new feature required to be designed for a given script, it is essential to know the recognition ability of the existing features for that script. Devanagari script is being used in various Indian languages besides Hindi the mother tongue of majority of Indians. This research examines a variety of feature extraction approaches, which have been used in various ICR/OCR applications, in context to Devanagari hand-printed script. The study is conducted theoretically and experimentally on more that 10 feature extraction methods. The various feature extraction methods have been evaluated on Devanagari hand-printed database comprising more than 25000 characters belonging to 43 alphabets. The recognition ability of the features have been evaluated using three classifiers i.e. k-NN, MLP and SVM.

Keywords: Features, Hand-printed, Devanagari, Classifier, Database

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Authors: Hanadi Mubarak AL-Mubaraki, Michael Busler

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In the context of business incubation (BI) as strategic enablers, this paper critically reviews the literature relating to the strategic benefits of BI in the Middle East. The taxonomy of BI benefits in the strategic elements on 1) type, 2) financial model, 3) services, 4) objectives, 5) number of clients, 6) number of graduates, and 7) jobs creation. Understanding the importance of BI benefits can be significant in the economic development although most incubators lead to diversify the economy. Thus, taxonomies of the benefits of BI are produced from both the academic literature and published case studies. In this way, a classification of strategic benefits elements as they relate to incubators has been developed to provide a greater understanding of the benefits needed to obtain a specific element. The result of this paper is Business incubators is aimed entrepreneurship, jobs creation, research commercialization and profitable enterprises in Middle Eastern countries.

Keywords: Economic Development, Incubators, Middle East, Strategic.

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Authors: Koray U. Erbas

Abstract:

Neural networks are appealing for many applications since they are able to learn complex non-linear relationships between input and output data. As the number of neurons and layers in a neural network increase, it is possible to represent more complex relationships with automatically extracted features. Nowadays Deep Neural Networks (DNNs) are widely used in Computer Vision problems such as; classification, object detection, segmentation image editing etc. In this work, Facial Emotion Recognition task is performed by proposed Convolutional Neural Network (CNN)-based DNN architecture using FER2013 Dataset. Moreover, the effects of different hyperparameters (activation function, kernel size, initializer, batch size and network size) are investigated and ablation study results for Pooling Layer, Dropout and Batch Normalization are presented.

Keywords: Convolutional Neural Network, Deep Learning, Deep Learning Based FER, Facial Emotion Recognition.

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Authors: Ehsan Shahrabian, Ali Soleymani

Abstract:

Several yield-based stress indices have been developed that may be more applicable to work on drought tolerance. In this study, we investigate possibility of using stress susceptibility index (SSI), tolerance index (TOL), yield stability index (YSI), yield index (YI), stress tolerance index (STI), geometric mean productivity (GMP), harmonic mean (HARM), mean productivity (MP) to identify genotypic performance of some maize cultivars under normal and stressed condition. The results indicate that it was possible to identify superior genotypes for drought tolerance based on their stress indices and generally SSI indices which showed the lowest negative correlation with dry matter yield can be used as the best index for maize breeding programs to introduce drought tolerant hybrids. It was found that SC 647 showed the best behavior under drought stress condition based on TOL and SSI. A higher STI, GMP, and HARM values were attained for ko_6. It can be suggested that ko₆ should be cultivated in moderate stressful environment of Iran.

Keywords: Index, productivity, stress, susceptibility tolerance, yield.

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Authors: Husam Kaid, Abdulrahman Al-Ahmari, Zhiwu Li

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This paper develops a robust deadlock control technique for shared and unreliable resources in automated manufacturing systems (AMSs) based on structural analysis and colored Petri nets, which consists of three steps. The first step involves using strict minimal siphon control to create a live (deadlock-free) system that does not consider resource failure. The second step uses an approach based on colored Petri net, in which all monitors designed in the first step are merged into a single monitor. The third step addresses the deadlock control problems caused by resource failures. For all resource failures in the Petri net model a common recovery subnet based on colored petri net is proposed. The common recovery subnet is added to the obtained system at the second step to make the system reliable. The proposed approach is evaluated using an AMS from the literature. The results show that the proposed approach can be applied to an unreliable complex Petri net model, has a simpler structure and less computational complexity, and can obtain one common recovery subnet to model all resource failures.

Keywords: Automated manufacturing system, colored Petri net, deadlock, siphon.

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Authors: Yingying Ding

Abstract:

This study presents a methodology of specialized translation with the objective of helping teachers to improve the strategies in teaching translation. In order to allow students to acquire skills to translate specialized texts, they need to become familiar with the semantic and syntactic features of source texts and target texts. The aim of our study is to use a corpus-based approach in the teaching of specialized translation between Chinese and Italian. This study proposes to construct a specialized Chinese - Italian comparable corpus that consists of 50 economic contracts from the domain of food. With the help of AntConc, we propose to compile a comparable corpus in for translation teaching purposes. This paper attempts to provide insight into how teachers could benefit from comparable corpus in the teaching of specialized translation from Italian into Chinese and through some examples of passive sentences how students could learn to apply different strategies for translating appropriately the voice.

Keywords: Corpus-based approach, translation teaching, specialized translation.

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Authors: Hui Zhang, Ye Tian, Fang Ye, Ziming Guo

Abstract:

Communication signal modulation recognition technology is one of the key technologies in the field of modern information warfare. At present, communication signal automatic modulation recognition methods are mainly divided into two major categories. One is the maximum likelihood hypothesis testing method based on decision theory, the other is a statistical pattern recognition method based on feature extraction. Now, the most commonly used is a statistical pattern recognition method, which includes feature extraction and classifier design. With the increasingly complex electromagnetic environment of communications, how to effectively extract the features of various signals at low signal-to-noise ratio (SNR) is a hot topic for scholars in various countries. To solve this problem, this paper proposes a feature extraction algorithm for the communication signal based on the improved Holder cloud feature. And the extreme learning machine (ELM) is used which aims at the problem of the real-time in the modern warfare to classify the extracted features. The algorithm extracts the digital features of the improved cloud model without deterministic information in a low SNR environment, and uses the improved cloud model to obtain more stable Holder cloud features and the performance of the algorithm is improved. This algorithm addresses the problem that a simple feature extraction algorithm based on Holder coefficient feature is difficult to recognize at low SNR, and it also has a better recognition accuracy. The results of simulations show that the approach in this paper still has a good classification result at low SNR, even when the SNR is -15dB, the recognition accuracy still reaches 76%.

Keywords: Communication signal, feature extraction, holder coefficient, improved cloud model.

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Authors: M. R. Vaezi, R. Ghasemi, A. Akramizadeh

Abstract:

Frequency stability of microgrids under islanded operation attracts particular attention recently. A new cooperative frequency control strategy based on centralized multi-agent system (CMAS) is proposed in this study. Based on this strategy, agents sent data and furthermore each component has its own to center operating decisions (MGCC).After deciding on the information, they are returned. Frequency control strategies include primary and secondary frequency control and disposal of multi-stage load in which this study will also provide a method and algorithm for load shedding. This could also be a big problem for the performance of micro-grid in times of disaster. The simulation results show the promising performance of the proposed structure of the controller based on multi agent systems.

Keywords: Frequency Control, Islanded Micro-grid, Load shedding, Multi-agent System.

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Authors: Yi Chao Ma, Cheng Siong Chin, Wai Lok Woo

Abstract:

Since the last decade, there has been a rapid growth in digital multimedia, such as high-resolution media files and threedimentional movies. Hence, there is a need for large digital storage such as Hard Disk Drive (HDD). As such, users expect to have a quieter HDD in their laptop. In this paper, a jury test has been conducted on a group of 34 people where 17 of them are students who are the potential consumer, and the remaining are engineers who know the HDD. A total 13 HDD sound samples have been selected from over hundred HDD noise recordings. These samples are selected based on an agreed subjective feeling. The samples are played to the participants using head acoustic playback system, which enabled them to experience as similar as possible the same environment as have been recorded. Analysis has been conducted and the obtained results have indicated different group has different perception over the noises. Two neural network-based acoustic annoyance models are established based on back propagation neural network. Four psychoacoustic metrics, loudness, sharpness, roughness and fluctuation strength, are used as the input of the model, and the subjective evaluation results are taken as the output. The developed models are reasonably accurate in simulating both training and test samples.

Keywords: Hard disk drive noise, jury test, neural network model, psychoacoustic annoyance.

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Authors: Rooholah Hasanizadeh, Saadan Zokaei

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In the context of sensor networks, where every few dB saving counts, the novel node cooperation schemes are reviewed where MIMO techniques play a leading role. These methods could be treated as joint approach for designing physical layer of their communication scenarios. Then we analyzed the BER performance of transmission diversity schemes under a general fading channel model and proposed a power allocation strategy to the transmitting sensor nodes. This approach is then compared to an equal-power assignment method and its performance enhancement is verified by the simulation. Another key point of the contribution lies in the combination of optimal power allocation and sensor nodes- cooperation in a transmission diversity regime (MISO). Numerical results are given through figures to demonstrate the optimality and efficiency of proposed combined approach.

Keywords: Optimal power allocation, cooperative MISO scheme, sensor networks, diversity branch.

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Authors: Elizabeth Simão Carvalho, Marcirio Silveira Chaves

Abstract:

The information visualization is still a knowledge field that lacks from a solid theory to support it and there is a myriad of existing methodologies and taxonomies that can be combined and adopted as guidelines. In this context, it is necessary to pre-evaluate as much as possible all the assumptions that are considered for its design and development. We present an exploratory study (n = 123) to detect the graphical preferences of travelers using accommodation portals of Web 2.0 (e.g. tripadvisor.com). We took into account some of the most relevant ground rules applied in the field to map visually data and design end-user interaction. Moreover, the evaluation process was completely data visualization oriented. We found out that people tend to refuse more advanced types of visualization and that a hybrid combination between radial graphs and stacked bars should be explored. In sum, this paper introduces new findings about the visual model and the cognitive response of users of accommodation booking websites.

Keywords: Information visualization, Data visualization, Visualization evaluation, Online reviews, Booking portal, Hotel booking.

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Authors: Hardik Vaghela, Mamta Khosla, Balwindar Raj

Abstract:

In this paper, we present and investigate a double gate PN diode based tunnel field effect transistor (DGPNTFET). The importance of proposed structure is that the formation of different drain doping is not required and ambipolar effect in OFF state is completely removed for this structure. Validation of this structure to behave like a Tunnel Field Effect Transistor (TFET) is carried out through energy band diagrams and transfer characteristics. Simulated result shows point subthreshold slope (SS) of 19.14 mV/decade and ON to OFF current ratio (I_ON / I_OFF) of 2.66 × 10¹⁴ (I_ON at V_GS=1.5V, V_DS=1V and I_OFF at V_GS=0V, V_DS=1V) for gate length of 20nm and HfO₂ as gate oxide at room temperature. Which indicate that the DGPNTFET is a promising candidate for nano-scale, ambipolar free switch.

Keywords: Ambipolar effect, double gate PN diode based tunnel field effect transistor, high-κ dielectric material, subthreshold slope, tunnel field effect transistor.

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Authors: L. M. Stefan, A. M. Pana, M. Silion, M. Balan, G. Bandur, L. M. Rusnac

Abstract:

The field of polymeric biomaterials is very important from the socio-economical viewpoint. Synthetic carbohydrate polymers are being increasingly investigated as biodegradable, biocompatible and biorenewable materials. The aim of this study was to synthesize and characterize some derivatives based on D-mannose. D-mannose was chemically modified to obtain 1-O-allyl-2,3:5,6-di- O-isopropylidene-D-mannofuranose and 1-O-(2-,3--epoxy-propyl)- 2,3:5,6-di-O-isopropylidene-D-mannofuranose. The chemical structure of the resulting compounds was characterized by FT-IR and NMR spectroscopy, and by HPLC-MS.

Keywords: D-mannose, biopolymers , spectroscopy, synthesis.

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Authors: Arpita Soni, Sapna Mittal

Abstract:

Austenite and Martensite indicate the phases of solids undergoing phase transformation which we usually associate with materials and not with living organisms. This article provides an overview of bacterial proteins and structures that are undergoing phase transformation and suggests its probable effect on mechanical behavior. The context is mainly within the role of phase transformations occurring in the flagellum of bacteria. The current knowledge of molecular mechanism leading to phase variation in living organisms is reviewed. Since in bacteria, each flagellum is driven by a separate motor, similarity to a Differential drive in case of four-wheeled vehicles is suggested. It also suggests the application of the mechanism in which bacteria changes its direction of movement to facilitate single point turning of a multi-wheeled vehicle. Finally, examples are presented to illustrate that the motion due to phase transformation of flagella in bacteria can start a whole new research on motion mechanisms.

Keywords: Flagella, Phase Transformation, Nanobots, Differential Drive, Single point turn, Biomimetics

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Authors: Srinath Shetty K., Shivashankar R., Rashmi P. Shetty

Abstract:

Earth reinforcing techniques have become useful and economical to solve problems related to difficult grounds and provide satisfactory foundation performance. In this context, this paper uses radial basis function neural network (RBFNN) for predicting the bearing pressure of strip footing on reinforced granular bed overlying weak soil. The inputs for the neural network models included plate width, thickness of granular bed and number of layers of reinforcements, settlement ratio, water content, dry density, cohesion and angle of friction. The results indicated that RBFNN model exhibited more than 84 % prediction accuracy, thereby demonstrating its application in a geotechnical problem.

Keywords: Bearing pressure, granular bed, radial basis function neural network, strip footing.

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