Search results for: hospital selection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1270

Search results for: hospital selection

430 Knowledge and Attitude of Palliative Care Towards Work Performance of Nurses in Indonesia Private Hospital

Authors: Novita Verayanti Manalu, Alvin Salim, Esti Yunitasari

Abstract:

Background: Palliative care is caring holistically for patients and families to improve their quality of life. The approach by a multidisciplinary team requires integrated collaboration based on sufficient knowledge of the principles of palliative care as a whole, especially for nurses. Therefore, this study wants to find out the level of knowledge about palliative care of the nurses along the relationship with attitude and performance. Method: This study applies cross-sectional survey design and allows the respondents to fill two questionnaires to determine the level of knowledge and attitude toward palliative care, while one questionnaire is filled by the head nurse to evaluate nurses’ performance. The relationship was analyzed by Spearman rho’s correlation in alpha < 0.05 by SPSS. Results: The majority of respondents were females, age above 25 years old, and married. Most of the nurses are staff nurses and the ratio of education level is not significantly different. The knowledge level is poor, while the attitude and performance are in adequate level. Knowledge may affect attitude, but it does not happen toward performance. Conclusion: There is a need for increased knowledge about palliative care to improve attitude and work performance. Future researchers might use this finding as reference to conduct further study in improving knowledge of palliative care.

Keywords: Knowledge, attitude, work performance, palliative care.

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429 Researches on Attractive Flowered Natural Woody Plants of Bursa Flora in Terms of Landscape Design

Authors: Elvan Ender, Murat Zencirkıran

Abstract:

One of the most important criteria that increase the success of design in landscape architecture is the visual effect. The characteristics that affect visual appearance in plant design vary depending on the phenological periods of the plants. In plants, although different effects are observed in different periods of the year, this effect is felt most prominently in flowering periods. For this reason, knowing the flowering time, duration and flower characteristics should be considered as a factor increasing the success of plant design. In this study, flower characteristics of natural woody plants with attractive flowers have been examined. Because of the variability of these characteristics of plants in the region, consideration of these criteria in the planting design processes in the region may increase the success of the design. At the same time, when species selection is made considering the obtained data, visuality and sustainability of natural species can be possible in Bursa city with planting design.

Keywords: Bursa, flower characteristics, natural plants, planting design.

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428 User Intention Generation with Large Language Models Using Chain-of-Thought Prompting

Authors: Gangmin Li, Fan Yang

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Personalized recommendation is crucial for any recommendation system. One of the techniques for personalized recommendation is to identify the intention. Traditional user intention identification uses the user’s selection when facing multiple items. This modeling relies primarily on historical behavior data resulting in challenges such as the cold start, unintended choice, and failure to capture intention when items are new. Motivated by recent advancements in Large Language Models (LLMs) like ChatGPT, we present an approach for user intention identification by embracing LLMs with Chain-of-Thought (CoT) prompting. We use the initial user profile as input to LLMs and design a collection of prompts to align the LLM's response through various recommendation tasks encompassing rating prediction, search and browse history, user clarification, etc. Our tests on real-world datasets demonstrate the improvements in recommendation by explicit user intention identification and, with that intention, merged into a user model.

Keywords: Personalized recommendation, generative user modeling, user intention identification, large language models, chain-of-thought prompting.

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427 Selection of Pichia kudriavzevii Strain for the Production of Single-Cell Protein from Cassava Processing Waste

Authors: Phakamas Rachamontree, Theerawut Phusantisampan, Natthakorn Woravutthikul, Peerapong Pornwongthong, Malinee Sriariyanun

Abstract:

A total of 115 yeast strains isolated from local cassava processing wastes were measured for crude protein content. Among these strains, the strain MSY-2 possessed the highest protein concentration (>3.5 mg protein/mL). By using molecular identification tools, it was identified to be a strain of Pichia kudriavzevii based on similarity of D1/D2 domain of 26S rDNA region. In this study, to optimize the protein production by MSY-2 strain, Response Surface Methodology (RSM) was applied. The tested parameters were the carbon content, nitrogen content, and incubation time. Here, the value of regression coefficient (R2) = 0.7194 could be explained by the model which is high to support the significance of the model. Under the optimal condition, the protein content was produced up to 3.77 g per L of the culture and MSY-2 strain contains 66.8 g protein per 100 g of cell dry weight. These results revealed the plausibility of applying the novel strain of yeast in single-cell protein production.

Keywords: Single cell protein, response surface methodology, yeast, cassava processing waste.

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426 Knowledge and Organisational Success: Developing a Scale of Knowledge Framework

Authors: Mohammed Almohammedali, Peter Duncan, David Edgar

Abstract:

The aim of this exploratory research is to understand further how organisations can evaluate their activities, which generate knowledge creation, to meet changing stakeholder expectations. A Scale of Knowledge (SoK) Framework is proposed which links knowledge management and organisational activities to changing stakeholder expectations. The framework was informed by the knowledge management literature, as well as empirical work conducted via a single case study of a multi-site hospital organisation in Saudi Arabia. Eight in-depth semi-structured interviews were conducted with managers from across the organisation regarding current and future stakeholder expectations, organisational strategy/activities and knowledge management. Data were analysed using thematic analysis and a hierarchical value map technique to identify activities that can produce further knowledge and consequently impact on how stakeholder expectations are met. The SoK Framework developed may be useful to practitioners as an analytical aid to determine if current organisational activities produce organisational knowledge which helps them meet (increasingly higher levels of) stakeholder expectations. The limitations of the research and avenues for future development of the proposed framework are discussed.

Keywords: Knowledge creation, knowledge management, organisational knowledge, scale of knowledge, knowledge impact.

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425 Selecting Stealth Aircraft Using Determinate Fuzzy Preference Programming in Multiple Criteria Decision Making

Authors: C. Ardil

Abstract:

This paper investigates the application of the determinate fuzzy preference programming method for a more nuanced and comprehensive evaluation of stealth aircraft. Traditional methods often struggle to incorporate subjective factors and uncertainties inherent in complex systems like stealth aircraft. Determinate fuzzy preference programming addresses this limitation by leveraging the strengths of determinate fuzzy sets. The proposed novel multiple criteria decision-making algorithm integrates these concepts to consider aspects and criteria influencing aircraft performance. This approach aims to provide a more holistic assessment by enabling decision-makers to observe positive and negative outranking flows simultaneously. By demonstrating the validity and effectiveness of this approach through a practical example of selecting a stealth aircraft, this paper aims to establish the determinate fuzzy preference programming method as a valuable tool for informed decision-making in this critical domain.

Keywords: Determinate fuzzy set, stealth aircraft selection, distance function, decision making, uncertainty, preference programming. MCDM

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424 Children and Advertising: Issues in Consumer Socialization Process

Authors: Laimona Sliburyte

Abstract:

Today advertising is actively penetrating into many spheres of our lives. We cannot imagine the existence of a lot of economic activities without advertising. That mostly concerns trade and services. Everyone of us should look better into the everyday communication and carefully consider the amount and the quality of the information we receive as well as its influence on our behaviour. Special attention should be paid to the young generation. Theoretical and practical research has proved the ever growing influence of information (especially the one contained in advertising) on a society; on its economics, culture, religion, politics and even people-s private lives and behaviour. Children have plenty of free time and, therefore, see a lot of different advertising. Though education of children is in the hands of parents and schools, advertising makers and customers should think with responsibility about the selection of time and transmission channels of child targeted advertising. The purpose of the present paper is to investigate the influence of advertising upon consumer views and behaviour of children in different age groups. The present investigation has clarified the influence of advertising as a means of information on a certain group of society, which in the modern information society is the most vulnerable – children. In this paper we assess children-s perception and their understanding of advertising.

Keywords: Advertising, children, children targeted advertising, consumer socialization process.

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423 A Comparative Study of Malware Detection Techniques Using Machine Learning Methods

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

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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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422 Developing an Advanced Algorithm Capable of Classifying News, Articles and Other Textual Documents Using Text Mining Techniques

Authors: R. B. Knudsen, O. T. Rasmussen, R. A. Alphinas

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The reason for conducting this research is to develop an algorithm that is capable of classifying news articles from the automobile industry, according to the competitive actions that they entail, with the use of Text Mining (TM) methods. It is needed to test how to properly preprocess the data for this research by preparing pipelines which fits each algorithm the best. The pipelines are tested along with nine different classification algorithms in the realm of regression, support vector machines, and neural networks. Preliminary testing for identifying the optimal pipelines and algorithms resulted in the selection of two algorithms with two different pipelines. The two algorithms are Logistic Regression (LR) and Artificial Neural Network (ANN). These algorithms are optimized further, where several parameters of each algorithm are tested. The best result is achieved with the ANN. The final model yields an accuracy of 0.79, a precision of 0.80, a recall of 0.78, and an F1 score of 0.76. By removing three of the classes that created noise, the final algorithm is capable of reaching an accuracy of 94%.

Keywords: Artificial neural network, competitive dynamics, logistic regression, text classification, text mining.

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421 Evaluating of Bearing Capacity of Two Adjacent Strip Foundations Located around a Soil Slip

Authors: M. Meftahi, M. Hoseinzadeh, S. A. Naeini

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Selection of soil bearing capacity is an important issue that should be investigated under different conditions. The bearing capacity of foundation around of soil slope is based on the active and passive forces. On the other hand, due to extension of urban structures, it is inevitable to put the foundations together. Concerning the two cases mentioned above, investigating the behavior of adjacent foundations which are constructed besides soil slope is essential. It should be noted that, according to the conditions, the bearing capacity of adjacent foundations can be less or more than mat foundations. Also, soil reinforcement increases the bearing capacity of adjacent foundations, and the amount of its increase depends on the distance between foundations. In this research, based on numerical studies, a method is presented for evaluating ultimate bearing capacity of adjacent foundations at different intervals. In the present study, the effect of foundation width, the center to center distance of adjacent foundations and reinforced soil has been investigated on the bearing capacity of adjacent foundations beside soil slope. The results indicate that, due to interference of failure surfaces created under foundation, it depends on their intervals and the ultimate bearing capacity of foundation varies.

Keywords: Adjacent foundation, bearing capacity, reinforcements, settlement, numerical analysis.

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420 A Chaotic Study on Tremor Behavior of Parkinsonian Patients under Deep Brain Stimulation

Authors: M. Sadeghi, A.H. Jafari, S.M.P. Firoozabadi

Abstract:

Deep Brain Stimulation or DBS is a surgical treatment for Parkinson-s Disease with three stimulation parameters: frequency, pulse width, and voltage. The parameters should be selected appropriately to achieve effective treatment. This selection now, performs clinically. The aim of this research is to study chaotic behavior of recorded tremor of patients under DBS in order to present a computational method to recognize stimulation optimum voltage. We obtained some chaotic features of tremor signal, and discovered embedding space of it has an attractor, and its largest Lyapunov exponent is positive, which show tremor signal has chaotic behavior, also we found out, in optimal voltage, entropy and embedding space variance of tremor signal have minimum values in comparison with other voltages. These differences can help neurologists recognize optimal voltage numerically, which leads to reduce patients' role and discomfort in optimizing stimulation parameters and to do treatment with high accuracy.

Keywords: Chaos, Deep Brain Stimulation, Parkinson's Disease, Stimulation Parameters, tremor.

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419 UDCA: An Energy Efficient Clustering Algorithm for Wireless Sensor Network

Authors: Boregowda S.B., Hemanth Kumar A.R. Babu N.V, Puttamadappa C., And H.S Mruthyunjaya

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In the past few years, the use of wireless sensor networks (WSNs) potentially increased in applications such as intrusion detection, forest fire detection, disaster management and battle field. Sensor nodes are generally battery operated low cost devices. The key challenge in the design and operation of WSNs is to prolong the network life time by reducing the energy consumption among sensor nodes. Node clustering is one of the most promising techniques for energy conservation. This paper presents a novel clustering algorithm which maximizes the network lifetime by reducing the number of communication among sensor nodes. This approach also includes new distributed cluster formation technique that enables self-organization of large number of nodes, algorithm for maintaining constant number of clusters by prior selection of cluster head and rotating the role of cluster head to evenly distribute the energy load among all sensor nodes.

Keywords: Clustering algorithms, Cluster head, Energy consumption, Sensor nodes, and Wireless sensor networks.

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418 Resource Leveling in Construction Projects using Re- Modified Minimum Moment Approach

Authors: Abhay Tawalare, Rajesh Lalwani

Abstract:

An attempt in this paper proposes a re-modification to the minimum moment approach of resource leveling which is a modified minimum moment approach to the traditional method by Harris. The method is based on critical path method. The new approach suggests the difference between the methods in the selection criteria of activity which needs to be shifted for leveling resource histogram. In traditional method, the improvement factor found first to select the activity for each possible day of shifting. In modified method maximum value of the product of Resources Rate and Free Float was found first and improvement factor is then calculated for that activity which needs to be shifted. In the proposed method the activity to be selected first for shifting is based on the largest value of resource rate. The process is repeated for all the remaining activities for possible shifting to get updated histogram. The proposed method significantly reduces the number of iterations and is easier for manual computations.

Keywords: Re-Modified, Resource Leveling, Resources Rate, Free Float, Resource Histogram

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417 Use of Fuzzy Edge Image in Block Truncation Coding for Image Compression

Authors: Amarunnishad T.M., Govindan V.K., Abraham T. Mathew

Abstract:

An image compression method has been developed using fuzzy edge image utilizing the basic Block Truncation Coding (BTC) algorithm. The fuzzy edge image has been validated with classical edge detectors on the basis of the results of the well-known Canny edge detector prior to applying to the proposed method. The bit plane generated by the conventional BTC method is replaced with the fuzzy bit plane generated by the logical OR operation between the fuzzy edge image and the corresponding conventional BTC bit plane. The input image is encoded with the block mean and standard deviation and the fuzzy bit plane. The proposed method has been tested with test images of 8 bits/pixel and size 512×512 and found to be superior with better Peak Signal to Noise Ratio (PSNR) when compared to the conventional BTC, and adaptive bit plane selection BTC (ABTC) methods. The raggedness and jagged appearance, and the ringing artifacts at sharp edges are greatly reduced in reconstructed images by the proposed method with the fuzzy bit plane.

Keywords: Image compression, Edge detection, Ground truth image, Peak signal to noise ratio

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416 Optimization of Supersonic Ejector via Sequence-Adapted Micro-Genetic Algorithm

Authors: Kolar Jan, Dvorak Vaclav

Abstract:

In this study, an optimization of supersonic air-to-air ejector is carried out by a recently developed single-objective genetic algorithm based on adaption of sequence of individuals. Adaptation of sequence is based on Shape-based distance of individuals and embedded micro-genetic algorithm. The optimal sequence found defines the succession of CFD-aimed objective calculation within each generation of regular micro-genetic algorithm. A spring-based deformation mutates the computational grid starting the initial individualvia adapted population in the optimized sequence. Selection of a generation initial individual is knowledge-based. A direct comparison of the newly defined and standard micro-genetic algorithm is carried out for supersonic air-to-air ejector. The only objective is to minimize the loose of total stagnation pressure in the ejector. The result is that sequence-adopted micro-genetic algorithm can provide comparative results to standard algorithm but in significantly lower number of overall CFD iteration steps.

Keywords: Grid deformation, Micro-genetic algorithm, shapebased sequence, supersonic ejector.

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415 Development of All-male Fingerlings by Heat Treatment and the Genetic Mechanism of Heat Induced Sex Determination in Nile Tilapia(Oreochromis niloticus L.)

Authors: P. O. Angienda, B. O. Aketch, E. N. Waindi

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Juvenile Nile tilapia subjected to heat treatment at temperatures ranging from 260C to 370C showed positive correlation (P<0.01) between treatment temperatures and resultant sex ratios, while, survival rate of the fry showed a negative correlation against temperature (P<0.01). The optimal temperature for both sex shift towards males and survival rates was 36±0.5°C, producing male percentage of 86.31 and a fry survival of 65.25. To determine the genetic basis of temperature sex-determination in Nile tilapia, we employed three microsatellite markers (Abur36, Abur100 and UNH846). Abur36 predicted the sex of 95% of the heat induced individuals, suggesting that the locus influence sex ratio and its interaction with temperature result in male biased sex ratio. This locus could turn out to be the major sex determining gene operating in Nile tilapia. These markers could be used in marker-assisted selection to select genotypes that give a higher percentage of males for commercial production.

Keywords: Heat treatment, Microsatellite, Nile tilapia, sex-determination.

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414 Dynamic Time Warping in Gait Classificationof Motion Capture Data

Authors: Adam Świtoński, Agnieszka Michalczuk, Henryk Josiński, Andrzej Polański, KonradWojciechowski

Abstract:

The method of gait identification based on the nearest neighbor classification technique with motion similarity assessment by the dynamic time warping is proposed. The model based kinematic motion data, represented by the joints rotations coded by Euler angles and unit quaternions is used. The different pose distance functions in Euler angles and quaternion spaces are considered. To evaluate individual features of the subsequent joints movements during gait cycle, joint selection is carried out. To examine proposed approach database containing 353 gaits of 25 humans collected in motion capture laboratory is used. The obtained results are promising. The classifications, which takes into consideration all joints has accuracy over 91%. Only analysis of movements of hip joints allows to correctly identify gaits with almost 80% precision.

Keywords: Biometrics, dynamic time warping, gait identification, motion capture, time series classification, quaternion distance functions, attribute ranking.

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413 Voice Driven Applications in Non-stationary and Chaotic Environment

Authors: C. Kwan, X. Li, D. Lao, Y. Deng, Z. Ren, B. Raj, R. Singh, R. Stern

Abstract:

Automated operations based on voice commands will become more and more important in many applications, including robotics, maintenance operations, etc. However, voice command recognition rates drop quite a lot under non-stationary and chaotic noise environments. In this paper, we tried to significantly improve the speech recognition rates under non-stationary noise environments. First, 298 Navy acronyms have been selected for automatic speech recognition. Data sets were collected under 4 types of noisy environments: factory, buccaneer jet, babble noise in a canteen, and destroyer. Within each noisy environment, 4 levels (5 dB, 15 dB, 25 dB, and clean) of Signal-to-Noise Ratio (SNR) were introduced to corrupt the speech. Second, a new algorithm to estimate speech or no speech regions has been developed, implemented, and evaluated. Third, extensive simulations were carried out. It was found that the combination of the new algorithm, the proper selection of language model and a customized training of the speech recognizer based on clean speech yielded very high recognition rates, which are between 80% and 90% for the four different noisy conditions. Fourth, extensive comparative studies have also been carried out.

Keywords: Non-stationary, speech recognition, voice commands.

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412 Passenger Seat Vibration Comparison Using ANFIS Control in Active Quarter Car Model

Authors: Devdutt

Abstract:

In this paper, vibration control response of passenger seat in quarter car model having three degrees of freedom is studied. Three different control strategies are taken into account using Adaptive Neuro Fuzzy Inference System (ANFIS) controller. In first case, ANFIS controller is applied in main suspension of active quarter car model. In second case, passenger seat suspension is assembled with ANFIS controller. Finally, both main and passenger seat suspensions are integrated with ANFIS controller. Simulation work under random road excitations is performed using passive and controlled quarter car models for performance comparison of passenger ride comfort. Ride comfort analysis is also compared as per ISO 2631-1 criterion. The obtained simulation responses are compared taking passenger seat acceleration and displacement response in time and frequency domain for the selection of best control strategy in designed quarter car model.

Keywords: Active suspension system, ANFIS controller, passenger ride comfort, quarter car model.

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411 OCR for Script Identification of Hindi (Devnagari) Numerals using Feature Sub Selection by Means of End-Point with Neuro-Memetic Model

Authors: Banashree N. P., R. Vasanta

Abstract:

Recognition of Indian languages scripts is challenging problems. In Optical Character Recognition [OCR], a character or symbol to be recognized can be machine printed or handwritten characters/numerals. There are several approaches that deal with problem of recognition of numerals/character depending on the type of feature extracted and different way of extracting them. This paper proposes a recognition scheme for handwritten Hindi (devnagiri) numerals; most admired one in Indian subcontinent. Our work focused on a technique in feature extraction i.e. global based approach using end-points information, which is extracted from images of isolated numerals. These feature vectors are fed to neuro-memetic model [18] that has been trained to recognize a Hindi numeral. The archetype of system has been tested on varieties of image of numerals. . In proposed scheme data sets are fed to neuro-memetic algorithm, which identifies the rule with highest fitness value of nearly 100 % & template associates with this rule is nothing but identified numerals. Experimentation result shows that recognition rate is 92-97 % compared to other models.

Keywords: OCR, Global Feature, End-Points, Neuro-Memetic model.

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410 A Semi-Fragile Watermarking Scheme for Color Image Authentication

Authors: M. Hamad Hassan, S.A.M. Gilani

Abstract:

In this paper, a semi-fragile watermarking scheme is proposed for color image authentication. In this particular scheme, the color image is first transformed from RGB to YST color space, suitable for watermarking the color media. Each channel is divided into 4×4 non-overlapping blocks and its each 2×2 sub-block is selected. The embedding space is created by setting the two LSBs of selected sub-block to zero, which will hold the authentication and recovery information. For verification of work authentication and parity bits denoted by 'a' & 'p' are computed for each 2×2 subblock. For recovery, intensity mean of each 2×2 sub-block is computed and encoded upto six to eight bits depending upon the channel selection. The size of sub-block is important for correct localization and fast computation. For watermark distribution 2DTorus Automorphism is implemented using a private key to have a secure mapping of blocks. The perceptibility of watermarked image is quite reasonable both subjectively and objectively. Our scheme is oblivious, correctly localizes the tampering and able to recovery the original work with probability of near one.

Keywords: Image Authentication, YST Color Space, Intensity Mean, LSBs, PSNR.

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409 Design and Analysis of 1.4 MW Hybrid Saps System for Rural Electrification in Off-Grid Applications

Authors: Arpan Dwivedi, Yogesh Pahariya

Abstract:

In this paper, optimal design of hybrid standalone power supply system (SAPS) is done for off grid applications in remote areas where transmission of power is difficult. The hybrid SAPS system uses two primary energy sources, wind and solar, and in addition to these diesel generator is also connected to meet the load demand in case of failure of wind and solar system. This paper presents mathematical modeling of 1.4 MW hybrid SAPS system for rural electrification. This paper firstly focuses on mathematical modeling of PV module connected in a string, secondly focuses on modeling of permanent magnet wind turbine generator (PMWTG). The hybrid controller is also designed for selection of power from the source available as per the load demand. The power output of hybrid SAPS system is analyzed for meeting load demands at urban as well as for rural areas.

Keywords: SAPS, DG, PMWTG, rural area, off grid, PV module.

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408 Investigation on Some Ergonomics and Psychological Strains of Common Militarism Protective Clothing

Authors: A. Ashjaran, A. Rashidi, R. Ghazi-Saeidi

Abstract:

Protective clothing limits heat transfer and hampers task performance due to the increased weight. Militarism protective clothing enables humans to operate in adverse environments. In the selection and evaluation of militarism protective clothing attention should be given to heat strain, ergonomic and fit issues next to the actual protection it offers. Fifty Male healthy subjects participated in the study. The subjects were dressed in shorts, T-shirts, socks, sneakers and four deferent kinds of militarism protective clothing such as CS, CSB, CS with NBC protection and CS with NBC- protection added. Ergonomically and psychological strains of every four cloths were investigated on subjects by walking on a treadmill (7km/hour) with a 19.7 kg backpack. As a result of these tests were showed that, the highest heart rate was found wearing the NBC-protection added outfit, the highest temperatures were observed wearing NBCprotection added, followed by respectively CS with NBC protection, CSB and CS and the highest value for thermal comfort (implying worst thermal comfort) was observed wearing NBC-protection added.

Keywords: Militarist protective clothing, Ergonomic, Heat strain, Thermal comfort

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407 An Improved Quality Adaptive Rate Filtering Technique Based on the Level Crossing Sampling

Authors: Saeed Mian Qaisar, Laurent Fesquet, Marc Renaudin

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Mostly the systems are dealing with time varying signals. The Power efficiency can be achieved by adapting the system activity according to the input signal variations. In this context an adaptive rate filtering technique, based on the level crossing sampling is devised. It adapts the sampling frequency and the filter order by following the input signal local variations. Thus, it correlates the processing activity with the signal variations. Interpolation is required in the proposed technique. A drastic reduction in the interpolation error is achieved by employing the symmetry during the interpolation process. Processing error of the proposed technique is calculated. The computational complexity of the proposed filtering technique is deduced and compared to the classical one. Results promise a significant gain of the computational efficiency and hence of the power consumption.

Keywords: Level Crossing Sampling, Activity Selection, Rate Filtering, Computational Complexity, Interpolation Error.

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406 Exploiting Global Self Similarity for Head-Shoulder Detection

Authors: Lae-Jeong Park, Jung-Ho Moon

Abstract:

People detection from images has a variety of applications such as video surveillance and driver assistance system, but is still a challenging task and more difficult in crowded environments such as shopping malls in which occlusion of lower parts of human body often occurs. Lack of the full-body information requires more effective features than common features such as HOG. In this paper, new features are introduced that exploits global self-symmetry (GSS) characteristic in head-shoulder patterns. The features encode the similarity or difference of color histograms and oriented gradient histograms between two vertically symmetric blocks. The domain-specific features are rapid to compute from the integral images in Viola-Jones cascade-of-rejecters framework. The proposed features are evaluated with our own head-shoulder dataset that, in part, consists of a well-known INRIA pedestrian dataset. Experimental results show that the GSS features are effective in reduction of false alarmsmarginally and the gradient GSS features are preferred more often than the color GSS ones in the feature selection.

Keywords: Pedestrian detection, cascade of rejecters, feature extraction, self-symmetry, HOG.

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405 AINA: Disney Animation Information as Educational Resources

Authors: Piedad Garrido, Fernando Repulles, Andy Bloor, Julio A. Sanguesa, Jesus Gallardo, Vicente Torres, Jesus Tramullas

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With the emergence and development of Information and Communications Technologies (ICTs), Higher Education is experiencing rapid changes, not only in its teaching strategies but also in student’s learning skills. However, we have noticed that students often have difficulty when seeking innovative, useful, and interesting learning resources for their work. This is due to the lack of supervision in the selection of good query tools. This paper presents AINA, an Information Retrieval (IR) computer system aimed at providing motivating and stimulating content to both students and teachers working on different areas and at different educational levels. In particular, our proposal consists of an open virtual resource environment oriented to the vast universe of Disney comics and cartoons. Our test suite includes Disney’s long and shorts films, and we have performed some activities based on the Just In Time Teaching (JiTT) methodology. More specifically, it has been tested by groups of university and secondary school students.

Keywords: Information retrieval, animation, educational resources, JiTT.

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404 Solving Bus Terminal Location Problem Using Genetic Algorithm

Authors: S. Babaie-Kafaki, R. Ghanbari, S.H. Nasseri, E. Ardil

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Bus networks design is an important problem in public transportation. The main step to this design, is determining the number of required terminals and their locations. This is an especial type of facility location problem, a large scale combinatorial optimization problem that requires a long time to be solved. The genetic algorithm (GA) is a search and optimization technique which works based on evolutionary principle of natural chromosomes. Specifically, the evolution of chromosomes due to the action of crossover, mutation and natural selection of chromosomes based on Darwin's survival-of-the-fittest principle, are all artificially simulated to constitute a robust search and optimization procedure. In this paper, we first state the problem as a mixed integer programming (MIP) problem. Then we design a new crossover and mutation for bus terminal location problem (BTLP). We tested the different parameters of genetic algorithm (for a sample problem) and obtained the optimal parameters for solving BTLP with numerical try and error.

Keywords: Bus networks, Genetic algorithm (GA), Locationproblem, Mixed integer programming (MIP).

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403 Robust Camera Calibration using Discrete Optimization

Authors: Stephan Rupp, Matthias Elter, Michael Breitung, Walter Zink, Christian Küblbeck

Abstract:

Camera calibration is an indispensable step for augmented reality or image guided applications where quantitative information should be derived from the images. Usually, a camera calibration is obtained by taking images of a special calibration object and extracting the image coordinates of projected calibration marks enabling the calculation of the projection from the 3d world coordinates to the 2d image coordinates. Thus such a procedure exhibits typical steps, including feature point localization in the acquired images, camera model fitting, correction of distortion introduced by the optics and finally an optimization of the model-s parameters. In this paper we propose to extend this list by further step concerning the identification of the optimal subset of images yielding the smallest overall calibration error. For this, we present a Monte Carlo based algorithm along with a deterministic extension that automatically determines the images yielding an optimal calibration. Finally, we present results proving that the calibration can be significantly improved by automated image selection.

Keywords: Camera Calibration, Discrete Optimization, Monte Carlo Method.

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402 A Study of Current Maintenance Strategies and the Reliability of Critical Medical Equipment in Hospitals in Relation to Patient Outcomes

Authors: Khelood A. Mkalaf, Peter Gibson, John Flanagan

Abstract:

This study investigates the relationship between the reliability of critical medical equipment (CME) and the effectiveness of CME maintenance management strategies in relation to patient outcomes in 84 public hospitals of a top 20 OECD country. The work has examined the effectiveness of CME maintenance management strategies used by the public hospital system of a large state run health organization. The conceptual framework was designed to examine the significance of the relationship between six variables: (1) types of maintenance management strategies, (2) maintenance services, (3) maintenance practice, (4) medical equipment reliability, (5) maintenance costs and (6) patient outcomes. The results provide interesting insights into the effectiveness of the maintenance strategies used. For example, there appears to be about a 1 in 10 000 probability of failure of anesthesia equipment, but these seem to be confined to specific maintenance situations. There are also some findings in relation to outsourcing of maintenance. For each of the variables listed, results are reported in relation to the various types of maintenance strategies and services. Decision-makers may use these results to evaluate more effective maintenance strategies for their CME and generate more effective patient outcomes.

Keywords: Critical medical equipment, maintenance strategy, patient outcomes, reliability.

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401 Multidimensional Compromise Programming Evaluation of Digital Commerce Websites

Authors: C. Ardil

Abstract:

Multidimensional compromise programming evaluation of digital commerce websites is essential not only to have recommendations for improvement, but also to make comparisons with global business competitors. This research provides a multidimensional decision making model that prioritizes the objective criteria weights of various commerce websites using multidimensional compromise solution. Evaluation of digital commerce website quality can be considered as a complex information system structure including qualitative and quantitative factors for a multicriteria decision making problem. The proposed multicriteria decision making approach mainly consists of three sequential steps for the selection problem. In the first step, three major different evaluation criteria are characterized for website ranking problem. In the second step, identified critical criteria are weighted using the standard deviation procedure. In the third step, the multidimensional compromise programming is applied to rank the digital commerce websites.

Keywords: Standard deviation, commerce website, website evaluation, multicriteria decision making, multicriteria compromise programming, website quality, multidimensional decision analysis.

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