Search results for: Tourist’s decision making process
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 20144

Search results for: Tourist’s decision making process

13424 The Importance of Anthropometric Indices for Assessing the Physical Development and Physical Fitness of Young Athletes

Authors: Akbarova Gulnozakhon

Abstract:

Relevance. Physical exercises can prolong the function of the growth zones of long tubular bones, delay the fusion of the epiphyses and diaphyses of bones and, thus, increase the growth of the body. At the same time, intensive strength exercises can accelerate the process of ossification of bone growth zones and slow down their growth in length. The influence of physical exercises on the process of biological maturation is noted. Gymnastics, which requires intense speed and strength loads, delays puberty. On the other hand, it is indicated that the relatively slow puberty of gymnasts is associated with the selection of girls with a special somatotype in this sport. It was found that the later onset of menstruation in female athletes does not have a negative effect on the maturation process and fertility (the ability to procreate). Observations are made about the normalizing influence of sports on the puberty of girls. The purpose of the study. Our goal is to study physical activity of varying intensity on the formation of secondary sexual characteristics and hormonal status of girls in adolescence. Each biological process peculiar to a given organism is not in a stationary state, but fluctuates with a certain frequency. According to the duration, there are, for example, circadian cycles, and infradian cycles, a typical example of which is the menstrual cycle. Materials and methods, results. Violations of menstrual function in athletes were detected by applying a questionnaire survey that contains several paragraphs and sub-paragraphs where passport data, anthropometric indicators, taking into account anthropometric indices, information about the menstrual cycle are indicated. Of 135 female athletes aged 1-3 to 16 years engaged in various sports - gymnasts, menstrual function disorders were noted in 86.7% (primary or secondary amenorrhea, irregular MC), in swimming-in 57.1%. The general condition also changes during the menstrual cycle. In a large percentage of cases, athletes indicate an increase in irritability in the premenstrual (45%) and menstrual (36%) phases. During these phases, girls note an increase in fatigue of 46.5% and 58% (respectively). In girls, secondary sexual characteristics continue to form during puberty and the clearest indicator of the onset of puberty is the age of the onset of the first menstruation - menarche. Conclusions. 1. Physical exercise has a positive effect on all major systems of the body and thus promotes health.2. Along with a beneficial effect on human health, physical exercise, if the requirements of sports are not observed, can be harmful.

Keywords: girls health, anthropometric, physical development, reproductive health

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13423 Hybrid Fuzzy Weighted K-Nearest Neighbor to Predict Hospital Readmission for Diabetic Patients

Authors: Soha A. Bahanshal, Byung G. Kim

Abstract:

Identification of patients at high risk for hospital readmission is of crucial importance for quality health care and cost reduction. Predicting hospital readmissions among diabetic patients has been of great interest to many researchers and health decision makers. We build a prediction model to predict hospital readmission for diabetic patients within 30 days of discharge. The core of the prediction model is a modified k Nearest Neighbor called Hybrid Fuzzy Weighted k Nearest Neighbor algorithm. The prediction is performed on a patient dataset which consists of more than 70,000 patients with 50 attributes. We applied data preprocessing using different techniques in order to handle data imbalance and to fuzzify the data to suit the prediction algorithm. The model so far achieved classification accuracy of 80% compared to other models that only use k Nearest Neighbor.

Keywords: machine learning, prediction, classification, hybrid fuzzy weighted k-nearest neighbor, diabetic hospital readmission

Procedia PDF Downloads 174
13422 Fengqiao: An Ongoing Experiment with 'UrbanMemory' Theory in an Ancient Town and ItsDesign Experience

Authors: Yibei Ye, Lei Xu, Zhenyu Cao

Abstract:

Ancient town is a unique carrier of urban culture, maintaining the core culture of a region and continuing the urban context. Fengqiao, a nearly 2000-year-old town was on the brink of dilapidation in the past few decades. The town faced such problems as poor construction quality, environmental degeneration, inadequate open space, cultural characteristics and industry vitality. Therefore, the research upholds the principle of ‘organic renewal’ and puts forward three practical updated strategies which are ‘Repair Old as Ever,' ‘Activate Function’ and ‘Fill in with The New’. Also as a participant in updating the design, the author aims to ‘keep the memory of the history and see the development of the present’ as the goal of updating the design and regards the process of town renewal as the experimental venue for realizing this purpose. The research will sum up innovations on the designing process and the engineering progress in the past two years, and find out the innovation experiment and the effect of its implementation on the methodological level of the organic renewal design in Fengqiao ancient town. From here, we can also enjoy the very characteristic development trend presented by China in the design practice of the organic renewal in the ancient town.

Keywords: characteristic town, Fengqiao, organic renewal, urban memory

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13421 Flocculation on the Treatment of Olive Oil Mill Wastewater: Pre-Treatment

Authors: G. Hodaifa, J. A. Páez, C. Agabo, E. Ramos, J. C. Gutiérrez, A. Rosal

Abstract:

Currently, the continuous two-phase decanter process used for olive oil production is the more internationally widespread. The wastewaters generated from this industry (OMW) is a real environmental problem because of its high organic load. Among proposed treatments for these wastewaters, the advanced oxidation technologies (Fenton process, ozone, photoFenton, etc.) are the most favourable. The direct application of these processes is somewhat expensive. Therefore, the application of a previous stage based on a flocculation-sedimentation operation is of high importance. In this research five commercial flocculants (three cationic, and two anionic) have been used to achieve the separation of phases (liquid clarified-sludge). For each flocculant, different concentrations (0-1000 mg/L) have been studied. In these experiments, sludge volume formed over time and the final water quality were determined. The final removal percentages of total phenols (11.3-25.1%), COD (5.6-20.4%), total carbon (2.3-26.5%), total organic carbon (1.50-23.8%), total nitrogen (1.45-24.8%), and turbidity (27.9-61.4%) were obtained. Also, the variation on the electric conductivity reduction percentage (1-8%) was determined. Finally, the best flocculants with highest removal percentages have been determined (QG2001 and Flocudex CS49).

Keywords: flocculants, flocculation, olive oil mill wastewater, water quality

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13420 Historical Development of Negative Emotive Intensifiers in Hungarian

Authors: Martina Katalin Szabó, Bernadett Lipóczi, Csenge Guba, István Uveges

Abstract:

In this study, an exhaustive analysis was carried out about the historical development of negative emotive intensifiers in the Hungarian language via NLP methods. Intensifiers are linguistic elements which modify or reinforce a variable character in the lexical unit they apply to. Therefore, intensifiers appear with other lexical items, such as adverbs, adjectives, verbs, infrequently with nouns. Due to the complexity of this phenomenon (set of sociolinguistic, semantic, and historical aspects), there are many lexical items which can operate as intensifiers. The group of intensifiers are admittedly one of the most rapidly changing elements in the language. From a linguistic point of view, particularly interesting are a special group of intensifiers, the so-called negative emotive intensifiers, that, on their own, without context, have semantic content that can be associated with negative emotion, but in particular cases, they may function as intensifiers (e.g.borzasztóanjó ’awfully good’, which means ’excellent’). Despite their special semantic features, negative emotive intensifiers are scarcely examined in literature based on large Historical corpora via NLP methods. In order to become better acquainted with trends over time concerning the intensifiers, The exhaustively analysed a specific historical corpus, namely the Magyar TörténetiSzövegtár (Hungarian Historical Corpus). This corpus (containing 3 millions text words) is a collection of texts of various genres and styles, produced between 1772 and 2010. Since the corpus consists of raw texts and does not contain any additional information about the language features of the data (such as stemming or morphological analysis), a large amount of manual work was required to process the data. Thus, based on a lexicon of negative emotive intensifiers compiled in a previous phase of the research, every occurrence of each intensifier was queried, and the results were stored in a separate data frame. Then, basic linguistic processing (POS-tagging, lemmatization etc.) was carried out automatically with the ‘magyarlanc’ NLP-toolkit. Finally, the frequency and collocation features of all the negative emotive words were automatically analyzed in the corpus. Outcomes of the research revealed in detail how these words have proceeded through grammaticalization over time, i.e., they change from lexical elements to grammatical ones, and they slowly go through a delexicalization process (their negative content diminishes over time). What is more, it was also pointed out which negative emotive intensifiers are at the same stage in this process in the same time period. Giving a closer look to the different domains of the analysed corpus, it also became certain that during this process, the pragmatic role’s importance increases: the newer use expresses the speaker's subjective, evaluative opinion at a certain level.

Keywords: historical corpus analysis, historical linguistics, negative emotive intensifiers, semantic changes over time

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13419 Analysing Modern City Heritage through Modernization Transformation: A Case of Wuhan, China

Authors: Ziwei Guo, Liangping Hong, Zhiguo Ye

Abstract:

The exogenous modernization process in China and other late-coming countries, is not resulted from a gradual growth of their own modernity features, but a conscious response to external challenges. Under this context, it had been equally important for Chinese cities to make themselves ‘Chinese’ as well as ‘modern’. Wuhan was the first opened inland treaty port in late Qing Dynasty. In the following one hundred years, Wuhan transferred from a feudal town to a modern industrial city. It is a good example to illustrate the urban construction and cultural heritage through the process and impact of social transformation. An overall perspective on transformation will contribute to develop the city`s uniqueness and enhance its inclusive development. The study chooses the history of Wuhan from 1861 to 1957 as the study period. The whole transformation process will be divided into four typical periods based on key historical events, and the paper analyzes the changes on urban structure and constructions activities in each period. Then, a lot of examples are used to compare the features of Wuhan modern city heritage in the four periods. In this way, three characteristics of Wuhan modern city heritage are summarized. The paper finds that globalization and localization worked together to shape the urban physical space environment. For Wuhan, social transformation has a profound and comprehensive impact on urban construction, which can be analyzed in the aspects of main construction, architecture style, location and actors. Moreover, the three towns of Wuhan have a disparate cityscape that is reflected by the varied heritages and architecture features over different transformation periods. Lastly, the protection regulations and conservation planning of heritage in Wuhan are discussed, and suggestions about the conservation of Wuhan modern heritage are tried to be drawn. The implications of the study are providing a new perspective on modern city heritage for cities like Wuhan, and the future local planning system and heritage conservation policies can take into consideration the ‘Modern Cultural Transformation Route’ in this paper.

Keywords: modern city heritage, transformation, identity, Wuhan

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13418 Treatment of Low-Grade Iron Ore Using Two Stage Wet High-Intensity Magnetic Separation Technique

Authors: Moses C. Siame, Kazutoshi Haga, Atsushi Shibayama

Abstract:

This study investigates the removal of silica, alumina and phosphorus as impurities from Sanje iron ore using wet high-intensity magnetic separation (WHIMS). Sanje iron ore contains low-grade hematite ore found in Nampundwe area of Zambia from which iron is to be used as the feed in the steelmaking process. The chemical composition analysis using X-ray Florence spectrometer showed that Sanje low-grade ore contains 48.90 mass% of hematite (Fe2O3) with 34.18 mass% as an iron grade. The ore also contains silica (SiO2) and alumina (Al2O3) of 31.10 mass% and 7.65 mass% respectively. The mineralogical analysis using X-ray diffraction spectrometer showed hematite and silica as the major mineral components of the ore while magnetite and alumina exist as minor mineral components. Mineral particle distribution analysis was done using scanning electron microscope with an X-ray energy dispersion spectrometry (SEM-EDS) and images showed that the average mineral size distribution of alumina-silicate gangue particles is in order of 100 μm and exists as iron-bearing interlocked particles. Magnetic separation was done using series L model 4 Magnetic Separator. The effect of various magnetic separation parameters such as magnetic flux density, particle size, and pulp density of the feed was studied during magnetic separation experiments. The ore with average particle size of 25 µm and pulp density of 2.5% was concentrated using pulp flow of 7 L/min. The results showed that 10 T was optimal magnetic flux density which enhanced the recovery of 93.08% of iron with 53.22 mass% grade. The gangue mineral particles containing 12 mass% silica and 3.94 mass% alumna remained in the concentrate, therefore the concentrate was further treated in the second stage WHIMS using the same parameters from the first stage. The second stage process recovered 83.41% of iron with 67.07 mass% grade. Silica was reduced to 2.14 mass% and alumina to 1.30 mass%. Accordingly, phosphorus was also reduced to 0.02 mass%. Therefore, the two stage magnetic separation process was established using these results.

Keywords: Sanje iron ore, magnetic separation, silica, alumina, recovery

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13417 Improving the Aqueous Solubility of Taxol through Altering XLOGP3

Authors: Arianna Zhu, Thomas Bakupog

Abstract:

Taxol (generic name paclitaxel) is an antineoplastic drug used to treat breast, lung, and ovarian cancer. It performs exceptionally well against a wide variety of tumors, including B16 melanoma, L1210 and P388 leukemias, MX-1 mammary tumors, and CX-1 colon tumor xenografts. However, despite taxol’s efficacy in antitumor activity, its aqueous solubility is extremely poor, decreasing its bioavailability and making it difficult for the body to absorb. The objective of this study is to improve the solubility of taxol, thus increasing the bioavailability of the drug in preventing cancer. By modifying the structure of taxol, four novel taxol derivatives were created with improved solubilities. Two of the derivatives were given an additional hydrogen donor and acceptor and thus showed a pronounced positive change in solubility. The results of this work solve the issue of taxol’s inadequate solubility and show potential in increasing the absorption of the drug.

Keywords: Taxol, Solubility, improving bioavailability, logP

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13416 Evaluating Classification with Efficacy Metrics

Authors: Guofan Shao, Lina Tang, Hao Zhang

Abstract:

The values of image classification accuracy are affected by class size distributions and classification schemes, making it difficult to compare the performance of classification algorithms across different remote sensing data sources and classification systems. Based on the term efficacy from medicine and pharmacology, we have developed the metrics of image classification efficacy at the map and class levels. The novelty of this approach is that a baseline classification is involved in computing image classification efficacies so that the effects of class statistics are reduced. Furthermore, the image classification efficacies are interpretable and comparable, and thus, strengthen the assessment of image data classification methods. We use real-world and hypothetical examples to explain the use of image classification efficacies. The metrics of image classification efficacy meet the critical need to rectify the strategy for the assessment of image classification performance as image classification methods are becoming more diversified.

Keywords: accuracy assessment, efficacy, image classification, machine learning, uncertainty

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13415 Urban Big Data: An Experimental Approach to Building-Value Estimation Using Web-Based Data

Authors: Sun-Young Jang, Sung-Ah Kim, Dongyoun Shin

Abstract:

Current real-estate value estimation, difficult for laymen, usually is performed by specialists. This paper presents an automated estimation process based on big data and machine-learning technology that calculates influences of building conditions on real-estate price measurement. The present study analyzed actual building sales sample data for Nonhyeon-dong, Gangnam-gu, Seoul, Korea, measuring the major influencing factors among the various building conditions. Further to that analysis, a prediction model was established and applied using RapidMiner Studio, a graphical user interface (GUI)-based tool for derivation of machine-learning prototypes. The prediction model is formulated by reference to previous examples. When new examples are applied, it analyses and predicts accordingly. The analysis process discerns the crucial factors effecting price increases by calculation of weighted values. The model was verified, and its accuracy determined, by comparing its predicted values with actual price increases.

Keywords: apartment complex, big data, life-cycle building value analysis, machine learning

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13414 Energy Efficient Recycling of In-Plant Fines

Authors: H. Ahmed, A. Persson, L. Sundqvist, B. Biorkman

Abstract:

Numerous amounts of metallurgical dusts and sludge containing iron as well as some other valuable elements such as Zn, Pb and C are annually produced in the steelmaking industry. These alternative iron ore resources (fines) with unsatisfying physical and metallurgical properties are difficult to recycle. However, agglomerating these fines to be further used as a feed stock for existing iron and steel making processes is practiced successfully at several plants but for limited extent. In the present study, briquettes of integrated steelmaking industry waste materials (namely, BF-dust and sludge, BOF-dust and sludge) were used as feed stock to produce direct reduced iron (DRI). Physical and metallurgical properties of produced briquettes were investigated by means of TGA/DTA/QMS in combination with XRD. Swelling, softening and melting behavior were also studied using heating microscope.

Keywords: iron and steel wastes, recycling, self-reducing briquettes, thermogravimetry

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13413 Design an Development of an Agorithm for Prioritizing the Test Cases Using Neural Network as Classifier

Authors: Amit Verma, Simranjeet Kaur, Sandeep Kaur

Abstract:

Test Case Prioritization (TCP) has gained wide spread acceptance as it often results in good quality software free from defects. Due to the increase in rate of faults in software traditional techniques for prioritization results in increased cost and time. Main challenge in TCP is difficulty in manually validate the priorities of different test cases due to large size of test suites and no more emphasis are made to make the TCP process automate. The objective of this paper is to detect the priorities of different test cases using an artificial neural network which helps to predict the correct priorities with the help of back propagation algorithm. In our proposed work one such method is implemented in which priorities are assigned to different test cases based on their frequency. After assigning the priorities ANN predicts whether correct priority is assigned to every test case or not otherwise it generates the interrupt when wrong priority is assigned. In order to classify the different priority test cases classifiers are used. Proposed algorithm is very effective as it reduces the complexity with robust efficiency and makes the process automated to prioritize the test cases.

Keywords: test case prioritization, classification, artificial neural networks, TF-IDF

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13412 Multi-Sensor Target Tracking Using Ensemble Learning

Authors: Bhekisipho Twala, Mantepu Masetshaba, Ramapulana Nkoana

Abstract:

Multiple classifier systems combine several individual classifiers to deliver a final classification decision. However, an increasingly controversial question is whether such systems can outperform the single best classifier, and if so, what form of multiple classifiers system yields the most significant benefit. Also, multi-target tracking detection using multiple sensors is an important research field in mobile techniques and military applications. In this paper, several multiple classifiers systems are evaluated in terms of their ability to predict a system’s failure or success for multi-sensor target tracking tasks. The Bristol Eden project dataset is utilised for this task. Experimental and simulation results show that the human activity identification system can fulfill requirements of target tracking due to improved sensors classification performances with multiple classifier systems constructed using boosting achieving higher accuracy rates.

Keywords: single classifier, ensemble learning, multi-target tracking, multiple classifiers

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13411 A Comparative Study of Malware Detection Techniques Using Machine Learning Methods

Authors: Cristina Vatamanu, Doina Cosovan, Dragos Gavrilut, 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: ensembles, false positives, feature selection, one side class algorithm

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13410 Understanding Team Member Autonomy and Team Collaboration: A Qualitative Study

Authors: Ayşen Bakioğlu, Gökçen Seyra Çakır

Abstract:

This study aims to explore how research assistants who work in project teams experience team member autonomy and how they reconcile team member autonomy with team collaboration. The study utilizes snowball sampling. 20 research assistants who work the faculties of education in Marmara University and Yıldız Technical University have been interviewed. The analysis of data involves a content analysis MAXQDAPlus 11 which is a qualitative data analysis software is used as the data analysis tool. According to the findings of this study, emerging themes include team norm formation, team coordination management, the role of individual tasks in team collaboration, leadership distribution. According to the findings, interviewees experience team norm formation process in terms of processes, which pertain to task fulfillment, and processes, which pertain to the regulation of team dynamics. Team norm formation process instills a sense of responsibility amongst individual team members. Apart from that, the interviewees’ responses indicate that the realization of the obligation to work in a team contributes to the team norm formation process. The participants indicate that individual expectations are taken into consideration during the coordination of the team. The supervisor of the project team also has a crucial role in maintaining team collaboration. Coordination problems arise when an individual team member does not relate his/her academic field with the research topic of the project team. The findings indicate that the leadership distribution in the project teams involves two leadership processes: leadership distribution which is based on the processes that focus on individual team members and leadership distribution which is based on the processes that focus on team interaction. Apart from that, individual tasks serve as a facilitator of collaboration amongst team members. Interviewees also indicate that individual tasks also facilitate the expression of individuality.

Keywords: project teams in higher education, research assistant teams, team collaboration, team member autonomy

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13409 The Asymptotic Hole Shape in Long Pulse Laser Drilling: The Influence of Multiple Reflections

Authors: Torsten Hermanns, You Wang, Stefan Janssen, Markus Niessen, Christoph Schoeler, Ulrich Thombansen, Wolfgang Schulz

Abstract:

In long pulse laser drilling of metals, it can be demonstrated that the ablation shape approaches a so-called asymptotic shape such that it changes only slightly or not at all with further irradiation. These findings are already known from ultra short pulse (USP) ablation of dielectric and semiconducting materials. The explanation for the occurrence of an asymptotic shape in long pulse drilling of metals is identified, a model for the description of the asymptotic hole shape numerically implemented, tested and clearly confirmed by comparison with experimental data. The model assumes a robust process in that way that the characteristics of the melt flow inside the arising melt film does not change qualitatively by changing the laser or processing parameters. Only robust processes are technically controllable and thus of industrial interest. The condition for a robust process is identified by a threshold for the mass flow density of the assist gas at the hole entrance which has to be exceeded. Within a robust process regime the melt flow characteristics can be captured by only one model parameter, namely the intensity threshold. In analogy to USP ablation (where it is already known for a long time that the resulting hole shape results from a threshold for the absorbed laser fluency) it is demonstrated that in the case of robust long pulse ablation the asymptotic shape forms in that way that along the whole contour the absorbed heat flux density is equal to the intensity threshold. The intensity threshold depends on the special material and radiation properties and has to be calibrated be one reference experiment. The model is implemented in a numerical simulation which is called AsymptoticDrill and requires such a few amount of resources that it can run on common desktop PCs, laptops or even smart devices. Resulting hole shapes can be calculated within seconds what depicts a clear advantage over other simulations presented in literature in the context of industrial every day usage. Against this background the software additionally is equipped with a user-friendly GUI which allows an intuitive usage. Individual parameters can be adjusted using sliders while the simulation result appears immediately in an adjacent window. A platform independent development allow a flexible usage: the operator can use the tool to adjust the process in a very convenient manner on a tablet during the developer can execute the tool in his office in order to design new processes. Furthermore, at the best knowledge of the authors AsymptoticDrill is the first simulation which allows the import of measured real beam distributions and thus calculates the asymptotic hole shape on the basis of the real state of the specific manufacturing system. In this paper the emphasis is placed on the investigation of the effect of multiple reflections on the asymptotic hole shape which gain in importance when drilling holes with large aspect ratios.

Keywords: asymptotic hole shape, intensity threshold, long pulse laser drilling, robust process

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13408 Early Recognition and Grading of Cataract Using a Combined Log Gabor/Discrete Wavelet Transform with ANN and SVM

Authors: Hadeer R. M. Tawfik, Rania A. K. Birry, Amani A. Saad

Abstract:

Eyes are considered to be the most sensitive and important organ for human being. Thus, any eye disorder will affect the patient in all aspects of life. Cataract is one of those eye disorders that lead to blindness if not treated correctly and quickly. This paper demonstrates a model for automatic detection, classification, and grading of cataracts based on image processing techniques and artificial intelligence. The proposed system is developed to ease the cataract diagnosis process for both ophthalmologists and patients. The wavelet transform combined with 2D Log Gabor Wavelet transform was used as feature extraction techniques for a dataset of 120 eye images followed by a classification process that classified the image set into three classes; normal, early, and advanced stage. A comparison between the two used classifiers, the support vector machine SVM and the artificial neural network ANN were done for the same dataset of 120 eye images. It was concluded that SVM gave better results than ANN. SVM success rate result was 96.8% accuracy where ANN success rate result was 92.3% accuracy.

Keywords: cataract, classification, detection, feature extraction, grading, log-gabor, neural networks, support vector machines, wavelet

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13407 The Effects of High Technology on Communicative Translation: A Case Study of Yoruba Language

Authors: Modupe Beatrice Adeyinka

Abstract:

European Languages are languages of literature, science and technology. Whereas, African languages are of literature, both written and oral, making it difficult for Yoruba, the African language of Kwa linguistic classification, to neatly and accurately translate European scientific and technological words, expressions and technologies. Unless a pragmatic and communicative approach is adopted, equivalence of European technical and scientific texts might be a mission impossible for Yoruba scholars. In view of the aforementioned difficult task, this paper tends to highlight the need for a thorough study and evaluation of English or French words, expressions, idiomatic expressions, technical and scientific terminologies then, trying to find ways of adopting them to Yoruba environment through interpretative translation.

Keywords: communication, high technology, translation, Yoruba language

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13406 Mango (Mangifera indica L.) Lyophilization Using Vacuum-Induced Freezing

Authors: Natalia A. Salazar, Erika K. Méndez, Catalina Álvarez, Carlos E. Orrego

Abstract:

Lyophilization, also called freeze-drying, is an important dehydration technique mainly used for pharmaceuticals. Food industry also uses lyophilization when it is important to retain most of the nutritional quality, taste, shape and size of dried products and to extend their shelf life. Vacuum-Induced during freezing cycle (VI) has been used in order to control ice nucleation and, consequently, to reduce the time of primary drying cycle of pharmaceuticals preserving quality properties of the final product. This procedure has not been applied in freeze drying of foods. The present work aims to investigate the effect of VI on the lyophilization drying time, final moisture content, density and reconstitutional properties of mango (Mangifera indica L.) slices (MS) and mango pulp-maltodextrin dispersions (MPM) (30% concentration of total solids). Control samples were run at each freezing rate without using induced vacuum. The lyophilization endpoint was the same for all treatments (constant difference between capacitance and Pirani vacuum gauges). From the experimental results it can be concluded that at the high freezing rate (0.4°C/min) reduced the overall process time up to 30% comparing process time required for the control and VI of the lower freeze rate (0.1°C/min) without affecting the quality characteristics of the dried product, which yields a reduction in costs and energy consumption for MS and MPM freeze drying. Controls and samples treated with VI at freezing rate of 0.4°C/min in MS showed similar results in moisture and density parameters. Furthermore, results from MPM dispersion showed favorable values when VI was applied because dried product with low moisture content and low density was obtained at shorter process time compared with the control. There were not found significant differences between reconstitutional properties (rehydration for MS and solubility for MPM) of freeze dried mango resulting from controls, and VI treatments.

Keywords: drying time, lyophilization, mango, vacuum induced freezing

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13405 Study and Improvement of the Quality of a Production Line

Authors: S. Bouchami, M.N. Lakhoua

Abstract:

The automotive market is a dynamic market that continues to grow. That’s why several companies belonging to this sector adopt a quality improvement approach. Wanting to be competitive and successful in the environment in which they operate, these companies are dedicated to establishing a system of quality management to ensure the achievement of the objective quality, improving the products and process as well as the satisfaction of the customers. In this paper, the management of the quality and the improvement of a production line in an industrial company is presented. In fact, the project is divided into two essential parts: the creation of the technical line documentation and the quality assurance documentation and the resolution of defects at the line, as well as those claimed by the customer. The creation of the documents has required a deep understanding of the manufacturing process. The analysis and problem solving were done through the implementation of PDCA (Plan Do Check Act) and FTA (Fault Tree Analysis). As perspective, in order to better optimize production and improve the efficiency of the production line, a study on the problems associated with the supply of raw materials should be made to solve the problems of stock-outs which cause delays penalizing for the industrial company.

Keywords: quality management, documentary system, Plan Do Check Act (PDCA), fault tree analysis (FTA) method

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13404 Review of Energy Efficiency Routing in Ad Hoc Wireless Networks

Authors: P. R. Dushantha Chaminda, Peng Kai

Abstract:

In this review paper, we enclose the thought of wireless ad hoc networks and particularly mobile ad hoc network (MANET), their field of study, intention, concern, benefit and disadvantages, modifications, with relation of AODV routing protocol. Mobile computing is developing speedily with progression in wireless communications and wireless networking protocols. Making communication easy, we function most wireless network devices and sensor networks, movable, battery-powered, thus control on a highly constrained energy budget. However, progress in battery technology presents that only little improvements in battery volume can be expected in the near future. Moreover, recharging or substitution batteries is costly or unworkable, it is preferable to support energy waste level of devices low.

Keywords: wireless ad hoc network, energy efficient routing protocols, AODV, EOAODV, AODVEA, AODVM, AOMDV, FF-AOMDV, AOMR-LM

Procedia PDF Downloads 199
13403 “Octopub”: Geographical Sentiment Analysis Using Named Entity Recognition from Social Networks for Geo-Targeted Billboard Advertising

Authors: Oussama Hafferssas, Hiba Benyahia, Amina Madani, Nassima Zeriri

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Although data nowadays has multiple forms; from text to images, and from audio to videos, yet text is still the most used one at a public level. At an academical and research level, and unlike other forms, text can be considered as the easiest form to process. Therefore, a brunch of Data Mining researches has been always under its shadow, called "Text Mining". Its concept is just like data mining’s, finding valuable patterns in data, from large collections and tremendous volumes of data, in this case: Text. Named entity recognition (NER) is one of Text Mining’s disciplines, it aims to extract and classify references such as proper names, locations, expressions of time and dates, organizations and more in a given text. Our approach "Octopub" does not aim to find new ways to improve named entity recognition process, rather than that it’s about finding a new, and yet smart way, to use NER in a way that we can extract sentiments of millions of people using Social Networks as a limitless information source, and Marketing for product promotion as the main domain of application.

Keywords: textmining, named entity recognition(NER), sentiment analysis, social media networks (SN, SMN), business intelligence(BI), marketing

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13402 Destination Nollywood: A Newspaper Analysis of the Connections between Film and Tourism in Nigeria, 2012-2022

Authors: E. S. Martens, E. E. Onwuliri

Abstract:

Over the past three decades, Nigeria’s film industry has become a global powerhouse, releasing hundreds of films annually and even monthly. Nollywood, a portmanteau of Nigeria and Hollywood as well as Bollywood that was coined by New York Times journalist Norimitsu Onishi in 2002, came to mark the plenitude of filmmaking happening in Lagos from the early 1990s onwards. Following the success of the 1992 straight-to-VHS film Living in Bondage, the Nigerian film industry experienced a popular home video boom that gained a huge following in Nigeria, across Africa, and among the global African diaspora. In fact, with an estimated worth of $6.4 billion as of 2021, Nollywood is nowadays considered the world’s second-largest film industry and even the largest in terms of output and popularity. Producing about 2,500 films annually and reaching an estimated audience of over 200 million people worldwide, Nollywood has not only seemingly surpassed Hollywood but also Bollywood with regard to production and consumption size. Due to its commercial success and cultural impact from the early 2010s, Nollywood has often been heralded as a potential driver of Africa’s tourism industry. In its 2012 Global Trends Report, the World Travel Market forecasted an increase in GDP in Africa due to tourism in Nollywood filming locations. Additionally, it was expected that the rising popularity of Nollywood would significantly contribute to growth in the leisure sector, drawing both film enthusiasts and business travelers intrigued by the expanding significance of the Nigerian film industry. Still, despite much talk about the potential impact of Nollywood on Nigerian tourism in the past 10 years or so, relatively little is known about Nollywood’s association with film tourism and the existing connections between Nigeria’s film and tourism industries more generally. Already well over a decade ago, it was observed that there is still a lack of research examining the extent to which film tourism related to Nollywood in Africa has been generated – and to date, this is still largely the case. This paper, then, seeks to discuss the reported connections between Nollywood and tourism and to review the efforts and opportunities related to Nollywood film tourism as suggested in Nigeria’s public domain. Based on a content analysis of over 50 newspaper articles and other online available materials, such as websites, blogs and forums, this paper explores the practices and discourses surrounding Nollywood connections with tourism in Nigeria and across Africa over the past ten years. The analysis shows that, despite these high expectations, film tourism related to Nollywood has remained limited. Despite growing government attention and support to Nollywood and its potential for tourism, most state initiatives in this direction have not (yet) materialize – and it very much remains to be seen to what extent ‘Destination Nollywood’ is really able to come to fruition as long as the structural issues underlying the development of Nigerian film (and) tourism are not sufficiently addressed.

Keywords: film tourism, Nigerian cinema, Nollywood, tourist destination

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13401 Exploring Ugliness as an Aesthetic Theme in Contemporary Chinese Literature through Analyzing Five Dragons, Protagonist in Rice by Xianfeng Writer Su Tong

Authors: Ku Yu Yiu

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Writers have included the ugly in their works for centuries, but ugliness has often served merely as a contrast to bring out the beautiful, not having emerged as an independent aesthetic category until recent history. In the 1980s, China was going through a series of changes and transformations; the wounds and scars from the Cultural Revolution, a freer literary atmosphere then, and the introduction of Western thoughts into China gave rise to a trend of penning the ugly and the repulsive among writers. Such trend of utilizing 'Ugliness' as a theme of writing in Chinese literature is especially observed among Xianfeng writers (China’s pioneer writers or avant-garde writers). As a prominent Xianfeng writer, Su Tong (1963-) also incorporates ugliness into his novels: shoddy environment, degenerate and ruthless society, distorted and decadent humanity are part and parcel of his deliberate efforts of exploring and depicting the ugly aspects of the world. His full-length novel Rice, staging the appalling protagonist Five Dragons, is a prime example. In fact, all characters in Rice exhibit Ugliness but Five Dragons’s turning into a figure of ugly spite is the most thorough and complete, making Rice a masterpiece of Su Tong’s art in projecting the Ugliness embedded in society and human nature. Approaching Rice from the angle of the aesthetics of the Ugly and selecting Five Dragons as the subject of close reading and analysis, this paper offers insights into both Su Tong’s distinct style of foregrounding and unfolding Ugliness in his novel and the workings of such text when he deploys the Ugly as a center component of his writing. In addition to citing from the discussion of Rice by literary critics and the author himself, this paper also presents textual evidence and analyzes the imageries/motifs and calculated vocabulary/narration employed by Su Tong to illustrate how Five Dragons' extreme behaviors and psychological states are integral to the plot and ultimately to the manifestation of ugliness as the novel’s theme. This study reveals that although the psyche and doings of Five Dragons and other 'ugly' characters are, as the author once stated, imagined products of the writer Su Tong himself, Rice sheds light onto the ugly aspects of life in China in 1920s-30s. Three aspects of Ugliness are identified and discussed in the paper. Lastly, this paper also suggests some effects of Su Tong’s exploration of Ugliness in Rice, proposing that the portrayal of Ugliness per se is not the ends of Su Tong’s mastery of the aesthetics of the Ugly but rather a means to making his writing transcend from provoking spontaneous moral judgment in readers on the doings of Five Dragons to prompting readers to ponder on philosophical questions such as how humanity can still be possible when an individual confronts the dark sides of a self, a society, and his/her fate.

Keywords: aesthetics, Rice, Su Tong, Ugly

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13400 Biochar as a Strong Adsorbent for Multiple-Metal Removal from Contaminated Water

Authors: Eman H. El-Gamal, Mai E. Khedr, Randa Ghonim, Mohamed Rashad

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In the past few years, biochar - a highly carbon-rich material produced from agro-wastes by pyrolysis process - was used as an effective adsorbent for heavy metals removal from polluted water. In this study, different types of biochar (rice straw 'RSB', corn cob 'CCB', and Jatropha shell 'JSB' were used to evaluate the adsorption capacity of heavy metals removal from multiple-metal solutions (Cu, Mn, Zn, and Cd). Kinetics modeling has been examined to illustrate potential adsorption mechanisms. The results showed that the potential removal of metal is dependent on the metal and biochar types. The adsorption capacity of the biochars followed the order: RSB > JSB > CCB. In general, RSB and JSB biochars presented high potential removal of heavy metals from polluted water, which was higher than 90 and 80% after 2 hrs of contact time for all metals, respectively. According to the kinetics data, the pseudo-second-order model was agreed strongly with Cu, Mn, Zn, and Cd adsorption onto the biochars (R2 ≥ 0.97), indicating the dominance of specific adsorption process, i.e., chemisorption. In conclusion, this study revealed that RSB and JSB biochar have the potential to be a strong adsorbent for multiple-metal removal from wastewater.

Keywords: adsorption, biochar, chemisorption, polluted water

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13399 Geospatial Technologies in Support of Civic Engagement and Cultural Heritage: Lessons Learned from Three Participatory Planning Workshops for Involving Local Communities in the Development of Sustainable Tourism Practices in Latiano, Brindisi

Authors: Mark Opmeer

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The fruitful relationship between cultural heritage and digital technology is evident. Due to the development of user-friendly software, an increasing amount of heritage scholars use ict for their research activities. As a result, the implementation of information technology for heritage planning has become a research objective in itself. During the last decades, we have witnessed a growing debate and literature about the importance of computer technologies for the field of cultural heritage and ecotourism. Indeed, implementing digital technology in support of these domains can be very fruitful for one’s research practice. However, due to the rapid development of new software scholars may find it challenging to use these innovations in an appropriate way. As such, this contribution seeks to explore the interplay between geospatial technologies (geo-ict), civic engagement and cultural heritage and tourism. In this article, we discuss our findings on the use of geo-ict in support of civic participation, cultural heritage and sustainable tourism development in the southern Italian district of Brindisi. In the city of Latiano, three workshops were organized that involved local members of the community to distinguish and discuss interesting points of interests (POI’s) which represent the cultural significance and identity of the area. During the first workshop, a so called mappa della comunità was created on a touch table with collaborative mapping software, that allowed the participators to highlight potential destinations for tourist purposes. Furthermore, two heritage-based itineraries along a selection of identified POI’s was created to make the region attractive for recreants and tourists. These heritage-based itineraries reflect the communities’ ideas about the cultural identity of the region. Both trails were subsequently implemented in a dedicated mobile application (app) and was evaluated using a mixed-method approach with the members of the community during the second workshop. In the final workshop, the findings of the collaboration, the heritage trails and the app was evaluated with all participants. Based on our conclusions, we argue that geospatial technologies have a significant potential for involving local communities in heritage planning and tourism development. The participants of the workshops found it increasingly engaging to share their ideas and knowledge using the digital map of the touch table. Secondly, the use of a mobile application as instrument to test the heritage-based itineraries in the field was broadly considered as fun and beneficial for enhancing community awareness and participation in local heritage. The app furthermore stimulated the communities’ awareness of the added value of geospatial technologies for sustainable tourism development in the area. We conclude this article with a number of recommendations in order to provide a best practice for organizing heritage workshops with similar objectives.

Keywords: civic engagement, geospatial technologies, tourism development, cultural heritage

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13398 Long Short-Time Memory Neural Networks for Human Driving Behavior Modelling

Authors: Lu Zhao, Nadir Farhi, Yeltsin Valero, Zoi Christoforou, Nadia Haddadou

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In this paper, a long short-term memory (LSTM) neural network model is proposed to replicate simultaneously car-following and lane-changing behaviors in road networks. By combining two kinds of LSTM layers and three input designs of the neural network, six variants of the LSTM model have been created. These models were trained and tested on the NGSIM 101 dataset, and the results were evaluated in terms of longitudinal speed and lateral position, respectively. Then, we compared the LSTM model with a classical car-following model (the intelligent driving model (IDM)) in the part of speed decision. In addition, the LSTM model is compared with a model using classical neural networks. After the comparison, the LSTM model demonstrates higher accuracy than the physical model IDM in terms of car-following behavior and displays better performance with regard to both car-following and lane-changing behavior compared to the classical neural network model.

Keywords: traffic modeling, neural networks, LSTM, car-following, lane-change

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13397 From Binary Solutions to Real Bio-Oils: A Multi-Step Extraction Story of Phenolic Compounds with Ionic Liquid

Authors: L. Cesari, L. Canabady-Rochelle, F. Mutelet

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The thermal conversion of lignin produces bio-oils that contain many compounds with high added-value such as phenolic compounds. In order to efficiently extract these compounds, the possible use of choline bis(trifluoromethylsulfonyl)imide [Choline][NTf2] ionic liquid was explored. To this end, a multistep approach was implemented. First, binary (phenolic compound and solvent) and ternary (phenolic compound and solvent and ionic liquid) solutions were investigated. Eight binary systems of phenolic compound and water were investigated at atmospheric pressure. These systems were quantified using the turbidity method and UV-spectroscopy. Ternary systems (phenolic compound and water and [Choline][NTf2]) were investigated at room temperature and atmospheric pressure. After stirring, the solutions were let to settle down, and a sample of each phase was collected. The analysis of the phases was performed using gas chromatography with an internal standard. These results were used to quantify the values of the interaction parameters of thermodynamic models. Then, extractions were performed on synthetic solutions to determine the influence of several operating conditions (temperature, kinetics, amount of [Choline][NTf2]). With this knowledge, it has been possible to design and simulate an extraction process composed of one extraction column and one flash. Finally, the extraction efficiency of [Choline][NTf2] was quantified with real bio-oils from lignin pyrolysis. Qualitative and quantitative analysis were performed using gas chromatographic connected to mass spectroscopy and flame ionization detector. The experimental measurements show that the extraction of phenolic compounds is efficient at room temperature, quick and does not require a high amount of [Choline][NTf2]. Moreover, the simulations of the extraction process demonstrate that [Choline][NTf2] process requires less energy than an organic one. Finally, the efficiency of [Choline][NTf2] was confirmed in real situations with the experiments on lignin pyrolysis bio-oils.

Keywords: bio-oils, extraction, lignin, phenolic compounds

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13396 Humic Acid and Azadirachtin Derivatives for the Management of Crop Pests

Authors: R. S. Giraddi, C. M. Poleshi

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Organic cultivation of crops is gaining importance consumer awareness towards pesticide residue free foodstuffs is increasing globally. This is also because of high costs of synthetic fertilizers and pesticides, making the conventional farming non-remunerative. In India, organic manures (such as vermicompost) are an important input in organic agriculture.  Though vermicompost obtained through earthworm and microbe-mediated processes is known to comprise most of the crop nutrients, but they are in small amounts thus necessitating enrichment of nutrients so that crop nourishment is complete. Another characteristic of organic manures is that the pest infestations are kept under check due to induced resistance put up by the crop plants. In the present investigation, deoiled neem cake containing azadirachtin, copper ore tailings (COT), a source of micro-nutrients and microbial consortia were added for enrichment of vermicompost. Neem cake is a by-product obtained during the process of oil extraction from neem plant seeds. Three enriched vermicompost blends were prepared using vermicompost (at 70, 65 and 60%), deoiled neem cake (25, 30 and 35%), microbial consortia and COTwastes (5%). Enriched vermicompost was thoroughly mixed, moistened (25+5%), packed and incubated for 15 days at room temperature. In the crop response studies, the field trials on chili (Capsicum annum var. longum) and soybean, (Glycine max cv JS 335) were conducted during Kharif 2015 at the Main Agricultural Research Station, UAS, Dharwad-Karnataka, India. The vermicompost blend enriched with neem cake (known to possess higher amounts of nutrients) and vermicompost were applied to the crops and at two dosages and at two intervals of crop cycle (at sowing and 30 days after sowing) as per the treatment plan along with 50% recommended dose of fertilizer (RDF). 10 plants selected randomly in each plot were studied for pest density and plant damage. At maturity, crops were harvested, and the yields were recorded as per the treatments, and the data were analyzed using appropriate statistical tools and procedures. In the crops, chili and soybean, crop nourishment with neem enriched vermicompost reduced insect density and plant damage significantly compared to other treatments. These treatments registered as much yield (16.7 to 19.9 q/ha) as that realized in conventional chemical control (18.2 q/ha) in soybean, while 72 to 77 q/ha of green chili was harvested in the same treatments, being comparable to the chemical control (74 q/ha). The yield superiority of the treatments was of the order neem enriched vermicompost>conventional chemical control>neem cake>vermicompost>untreated control.  The significant features of the result are that it reduces use of inorganic manures by 50% and synthetic chemical insecticides by 100%.

Keywords: humic acid, azadirachtin, vermicompost, insect-pest

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13395 Facebook Spam and Spam Filter Using Artificial Neural Networks

Authors: A. Fahim, Mutahira N. Naseem

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SPAM is any unwanted electronic message or material in any form posted to many people. As the world is growing as global world, social networking sites play an important role in making world global providing people from different parts of the world a platform to meet and express their views. Among different social networking sites facebook become the leading one. With increase in usage different users start abusive use of facebook by posting or creating ways to post spam. This paper highlights the potential spam types nowadays facebook users faces. This paper also provide the reason how user become victim to spam attack. A methodology is proposed in the end discusses how to handle different types of spam.

Keywords: artificial neural networks, facebook spam, social networking sites, spam filter

Procedia PDF Downloads 363