Search results for: stereotypical customer types

Authors: Nicanor Garcia Alvarez, Belarmino Adenso-Diaz, Laura Calzada Infante

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In recent years, researchers have shown an interest in modelling maritime traffic as a complex network. In this paper, we propose a bipartite weighted network to model maritime traffic and detect port maritime communities. The bipartite weighted network considers two different types of nodes. The first one represents Spanish ports, while the second one represents the countries with which there is major import/export activity. The flow among both types of nodes is modeled by weighting the volume of product transported. To illustrate the model, the data is segmented by each type of traffic. This will allow fine tuning and the creation of communities for each type of traffic and therefore finding similar ports for a specific type of traffic, which will provide decision-makers with tools to search for alliances or identify their competitors. The traffic with the greatest impact on the Spanish gross domestic product is selected, and the evolution of the communities formed by the most important ports and their differences between 2019 and 2009 will be analyzed. Finally, the set of communities formed by the ports of the Spanish port system will be inspected to determine global similarities between them, analyzing the sum of the membership of the different ports in communities formed for each type of traffic in particular.

Keywords: bipartite networks, competition, infomap, maritime traffic, port communities

Procedia PDF Downloads 148

Authors: S. Oladoyinbo, A. A. Tijani

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Multilevel inverters (MLI) are used at high power application based on their operation. There are 3 main types of multilevel inverters (MLI); diode clamped, flying capacitor and cascaded MLI. A cascaded MLI requires the least number of components to achieve same number of voltage levels when compared to other types of MLI while the flying capacitor has the minimum harmonic distortion. However, maximizing the advantage of cascaded H-bridge MLI and flying capacitor MLI, an improved MLI can be achieved with fewer components and better performance. In this paper an improved MLI is presented by asymmetrically integrating a flying capacitor to a cascaded H-bridge MLI also integrating an auxiliary transformer to the main transformer to decrease the total harmonics distortion (THD) with increased number of output voltage levels. Furthermore, the system is incorporated with a hybrid time and climate based solar panel cleaner and power selector which intelligently manage the input of the MLI and clean the solar panel weekly ensuring the environmental factor effect on the panel is reduced to minimum.

Keywords: multilevel inverter, total harmonics distortion, cascaded h-bridge inverter, flying capacitor

Procedia PDF Downloads 363

Authors: Mao Zhaofang, Xu Yida, Fang Kan, Fu Enyuan, Zhao Zhao

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Nowadays, last-mile distribution plays an increasingly important role in the whole industrial chain delivery link and accounts for a large proportion of the whole distribution process cost. Promoting the upgrading of logistics networks and improving the layout of final distribution points has become one of the trends in the development of modern logistics. Due to the discrete and heterogeneous needs and spatial distribution of customer demand, which will lead to a higher delivery failure rate and lower vehicle utilization, last-mile delivery has become a time-consuming and uncertain process. As a result, courier companies have introduced a range of innovative parcel storage facilities, including pick-up points and lockers. The introduction of pick-up points and lockers has not only improved the users’ experience but has also helped logistics and courier companies achieve large-scale economy. Against the backdrop of the COVID-19 of the previous period, contactless delivery has become a new hotspot, which has also created new opportunities for the development of collection services. Therefore, a key issue for logistics companies is how to design/redesign their last-mile distribution network systems to create integrated logistics and distribution networks that consider pick-up points and lockers. This paper focuses on the introduction of self-pickup facilities in new logistics and distribution scenarios and the heterogeneous demands of customers. In this paper, we consider two types of demand, including ordinary products and refrigerated products, as well as corresponding transportation vehicles. We consider the constraints associated with self-pickup points and lockers and then address the location-routing problem with self-pickup facilities and heterogeneous demands (LRP-PFHD). To solve this challenging problem, we propose a mixed integer linear programming (MILP) model that aims to minimize the total cost, which includes the facility opening cost, the variable transport cost, and the fixed transport cost. Due to the NP-hardness of the problem, we propose a hybrid adaptive large-neighbourhood search algorithm to solve LRP-PFHD. We evaluate the effectiveness and efficiency of the proposed algorithm by using instances generated based on benchmark instances. The results demonstrate that the hybrid adaptive large neighbourhood search algorithm is more efficient than MILP solvers such as Gurobi for LRP-PFHD, especially for large-scale instances. In addition, we made a comprehensive analysis of some important parameters (e.g., facility opening cost and transportation cost) to explore their impacts on the results and suggested helpful managerial insights for courier companies.

Keywords: city logistics, last-mile delivery, location-routing, adaptive large neighborhood search

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Authors: Masoumeh Ghorbania, Falk Liebnerb, Hendrikus W.G. van Herwijnenc, Johannes Konnertha

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Phenol formaldehyde (PF) resins are widely used as wood adhesives for variety of industrial products such as plywood, laminated veneer lumber and others. Lignin as a main constituent of wood has become well-known as a potential substitute for phenol in PF adhesives because of their structural similarity. During the last decades numerous research approaches have been carried out to substitute phenol with pulping-derived lignin, whereby the lower reactivity of resins synthesized with shares of lignin seem to be one of the major challenges. This work reports about a systematic screening of different types of lignin (plant origin and pulping process) for their suitability to replace phenol in phenolic resins. Lignin from different plant sources (softwood, hardwood and grass) were used, as these should differ significantly in their reactivity towards formaldehyde of their reactive phenolic core units. Additionally a possible influence of the pulping process was addressed by using the different types of lignin from soda, kraft, and organosolv process and various lignosulfonates (sodium, ammonium, calcium, magnesium). To determine the influence of lignin on the adhesive performance beside others the rate of viscosity development, bond strength development of varying hot pressing time and other thermal properties were investigated. To evaluate the performance of the cured end product, a few selected properties were studied at the example of solid wood-adhesive bond joints, compact panels and plywood. As main results it was found that lignin significantly accelerates the viscosity development in adhesive synthesis. Bonding strength development during curing of adhesives decelerated for all lignin types, while this trend was least for pine kraft lignin and spruce sodium lignosulfonate. However, the overall performance of the products prepared with the latter adhesives was able to fulfill main standard requirements, even after exposing the products to harsh environmental conditions. Thus, a potential application can be considered for processes where reactivity is less critical but adhesive cost and product performance is essential.

Keywords: phenol formaldehyde resin, lignin phenol formaldehyde resin, ABES, DSC

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Authors: Luyin Liang

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Although sibling relationship has been viewed as one of the most important family relationships that significantly impacted on the quality of life of both adults with Intellectual Disability (AWID) and their brothers/sisters, very few research have been done to investigate this relationship in China. This study investigated Chinese siblings of AWID’s relational motivations in sibling relationship and their determining factors. Quantitative research method has been adopted and 284 samples were recruited in this study. Siblings of AWID’s two types of relational motivations, including obligatory motivations and discretionary motivations were examined. Their emotional closeness, senses of responsibility, experiences of ID stigma, and expectancy of self-reward in sibling relationship were measured by validated scales. Personal, and familial-social demographic characteristics were also investigated. Linear correlation test and standard multiple regression analysis were the major statistical methods that have been used to analyze the data. The findings of this study showed that all the measured factors, including siblings of AWID’s emotional closeness, their senses of responsibility, experiences of ID stigma, and self-reward expectations had significant relationships with their both types of motivations. However, when these factors were grouped together to measure each type of these motivations, the prediction results were varied. The order of factors that best predict siblings of AWID’s obligatory motivations was: their senses of responsibility, emotional closeness, experiences of ID stigma, and their expectancy of self-reward, whereas the order of these factors that best determine siblings of AWID’s discretionary motivations was: their self-reward expectations, experiences of ID stigma, senses of responsibility, and emotional closeness. Among different demographic characteristics, AWID’s disability condition, their siblings’ age, gender, marital status, number of children, both siblings’ living arrangements and family financial status were found to have significant impacts on siblings of AWID’s both types of motivations in sibling relationship. The results of this study could enhance social work practitioners’ understandings about the needs and challenges of siblings of AWID. Suggestions on advocacies for policy changes and services improvements for these siblings were discussed in this study.

Keywords: sibling relationship, intellectual disability, adults, China

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Authors: Nushrat Khan, Mike Thelwall, Kayvan Kousha

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Making research data openly accessible has been mandated by most funders over the last 5 years as it promotes reproducibility in science and reduces duplication of effort to collect the same data. There are evidence that articles that publicly share research data have higher citation rates in biological and social sciences. However, how and whether shared data is being reused is not always intuitive as such information is not easily accessible from the majority of research data repositories. This study aims to understand the practice of data citation and how data is being reused over the years focusing on biodiversity since research data is frequently reused in this field. Metadata of 38,878 datasets including citation counts were collected through the Global Biodiversity Information Facility (GBIF) API for this purpose. GBIF was used as a data source since it provides citation count for datasets, not a commonly available feature for most repositories. Analysis of dataset types, citation counts, creation and update time of datasets suggests that citation rate varies for different types of datasets, where occurrence datasets that have more granular information have higher citation rates than checklist and metadata-only datasets. Another finding is that biodiversity datasets on GBIF are frequently updated, which is unique to this field. Majority of the datasets from the earliest year of 2007 were updated after 11 years, with no dataset that was not updated since creation. For each year between 2007 and 2017, we compared the correlations between update time and citation rate of four different types of datasets. While recent datasets do not show any correlations, 3 to 4 years old datasets show weak correlation where datasets that were updated more recently received high citations. The results are suggestive that it takes several years to cumulate citations for research datasets. However, this investigation found that when searched on Google Scholar or Scopus databases for the same datasets, the number of citations is often not the same as GBIF. Hence future aim is to further explore the citation count system adopted by GBIF to evaluate its reliability and whether it can be applicable to other fields of studies as well.

Keywords: data citation, data reuse, research data sharing, webometrics

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Authors: Niousha Bagheri Khulenjani, Mohammad Saniee Abadeh

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Learning from very big datasets is a significant problem for most present data mining and machine learning algorithms. MicroRNA (miRNA) is one of the important big genomic and non-coding datasets presenting the genome sequences. In this paper, a hybrid method for the classification of the miRNA data is proposed. Due to the variety of cancers and high number of genes, analyzing the miRNA dataset has been a challenging problem for researchers. The number of features corresponding to the number of samples is high and the data suffer from being imbalanced. The feature selection method has been used to select features having more ability to distinguish classes and eliminating obscures features. Afterward, a Convolutional Neural Network (CNN) classifier for classification of cancer types is utilized, which employs a Genetic Algorithm to highlight optimized hyper-parameters of CNN. In order to make the process of classification by CNN faster, Graphics Processing Unit (GPU) is recommended for calculating the mathematic equation in a parallel way. The proposed method is tested on a real-world dataset with 8,129 patients, 29 different types of tumors, and 1,046 miRNA biomarkers, taken from The Cancer Genome Atlas (TCGA) database.

Keywords: cancer classification, feature selection, deep learning, genetic algorithm

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Authors: Sujoy Anirudha Das, Albert Thomas

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Building sector is a major consumer of energy globally, and it has corresponding effects to the environment with respect to the carbon emissions. Given the fact that India is expected to add 40-billion square meter of new buildings till 2050, we need frameworks that help in reducing the overall energy consumption in the building sector. Even though several simulation-based frameworks that help in analyzing the building energy consumption are developed globally, in the Indian context, to the best of our knowledge, there is a lack of a comprehensive, yet user-friendly framework to simulate and optimize the effects of various energy influencing factors, specifically for Indian buildings. Therefore, this study is aimed at developing a simulation-based optimization framework to model the energy interactions in different types of Indian buildings by considering the dynamic nature of various energy influencing factors. This comprehensive framework can be used by various building stakeholders to test the energy effects of different factors such as, but not limited to, the various building materials, the orientation, the weather fluctuations, occupancy changes and the type of the building (e.g., office, residential). The results from the case study involving several building types would help us in gaining insights to build new energy-efficient buildings as well as retrofit the existing structures in a more convenient way to consume less energy, exclusively for an Indian scenario.

Keywords: building energy consumption, building energy simulations, energy efficient buildings, optimization framework

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Authors: Daniel Barros, Carlos Mota, Raul Fangueiro, Pedro Rosa, Gonçalo Domingos, Alfredo Passanha, Norberto Almeida

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The main aim of the work was to compare the ballistic performance of developed composites using different types of fiber woven fabrics [0,90] and different layers orientation (Angle-ply). The ballistic laminate composites were developed using E-glass, S-glass and aramid fabrics impregnated with thermosetting epoxy resin and using different layers orientation (0,0)º and (0,15)º. The idea of the study is to compare the ballistic performance of each laminate produced by studying the velocity loss of the fragment fired into the laminate surface. There are present some mechanical properties for laminates produced using the different types of fiber, where tensile, flexural and impact Charpy properties were studied. Overall, the angle-ply laminates produced using orientations of (0,15)º, despite the slight loss of mechanical properties compared to the (0,0)º orientation, presents better ballistic resistance and dissipation of energy, for lower ballistic impact velocities (under 290 m/s-1). After treatment of ballistic impact results, the S-Glass with (0,15)º laminate presents better ballistic perforce compared to the other combinations studied.

Keywords: ballistic impact, angle-ply, ballistic composite, s-glass fiber, aramid fiber, fabric fiber, energy dissipation, mechanical performance

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Authors: Wanderson Goncalves e Goncalves, José Alberto Silva de Sá

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Human actions are a threat to the balance and conservation of the Amazon forest. Therefore the environmental monitoring services play an important role as the preservation and maintenance of this environment. This study classified forest types using data from a forest inventory provided by the 'Florestal e da Biodiversidade do Estado do Pará' (IDEFLOR-BIO), located between the municipalities of Santarém, Juruti and Aveiro, in the state of Pará, Brazil, covering an area approximately of 600,000 hectares, Bands 3, 4 and 5 of the TM-Landsat satellite image, and Self - Organizing Maps. The information from the satellite images was extracted using QGIS software 2.8.1 Wien and was used as a database for training the neural network. The midpoints of each sample of forest inventory have been linked to images. Later the Digital Numbers of the pixels have been extracted, composing the database that fed the training process and testing of the classifier. The neural network was trained to classify two forest types: Rain Forest of Lowland Emerging Canopy (Dbe) and Rain Forest of Lowland Emerging Canopy plus Open with palm trees (Dbe + Abp) in the Mamuru Arapiuns glebes of Pará State, and the number of examples in the training data set was 400, 200 examples for each class (Dbe and Dbe + Abp), and the size of the test data set was 100, with 50 examples for each class (Dbe and Dbe + Abp). Therefore, total mass of data consisted of 500 examples. The classifier was compiled in Orange Data Mining 2.7 Software and was evaluated in terms of the confusion matrix indicators. The results of the classifier were considered satisfactory, and being obtained values of the global accuracy equal to 89% and Kappa coefficient equal to 78% and F1 score equal to 0,88. It evaluated also the efficiency of the classifier by the ROC plot (receiver operating characteristics), obtaining results close to ideal ratings, showing it to be a very good classifier, and demonstrating the potential of this methodology to provide ecosystem services, particularly in anthropogenic areas in the Amazon.

Keywords: artificial neural network, computational intelligence, pattern recognition, unsupervised learning

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Authors: Darko Prebežac, Josip Mikulić, Maja Šerić, Damir Krešić

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Camping tourism is recognized as a growing segment of the broader tourism industry, currently evolving from an inexpensive, temporary sojourn in a rural environment into a highly fragmented niche tourism sector. The trends among public-managed campgrounds seem to be moving away from rustic campgrounds that provide only a tent pad and a fire ring to more developed facilities that offer a range of different amenities, where campers still search for unique experiences that go above the opportunity to experience nature and social interaction. In addition, while camping styles and options changed significantly over the last years, coastal camping in particular became valorized as is it regarded with a heightened sense of nostalgia. Alongside this growing interest in the camping tourism, a demand for quality servicing infrastructure emerged in order to satisfy the wide variety of needs, wants, and expectations of an increasingly demanding traveling public. However, camping activity in general and quality of camping experience and campers’ satisfaction in particular remain an under-researched area of the tourism and consumption behavior literature. In this line, very few studies addressed the issue of quality product/service provision in satisfying nature based tourists and in driving their future behavior with respect to potential re-visitation and recommendation intention. The present study thus aims to investigate the drivers of positive and negative campsite experience using the case of Croatia. Due to the well-preserved nature and indented coastline, camping tourism has a long tradition in Croatia and represents one of the most important and most developed tourism products. During the last decade the number of tourist overnights in Croatian camps has increased by 26% amounting to 16.5 million in 2014. Moreover, according to Eurostat the market share of campsites in the EU is around 14%, indicating that the market share of Croatian campsites is almost double large compared to the EU average. Currently, there are a total of 250 camps in Croatia with approximately 75.8 thousands accommodation units. It is further noteworthy that Croatian camps have higher average occupancy rates and a higher average length of stay as compared to the national average of all types of accommodation. In order to explore the main drivers of positive and negative campsite experiences, this study uses principal components analysis (PCA) and an impact-asymmetry analysis (IAA). Using the PCA, first the main dimensions of the campsite experience are extracted in an exploratory manner. Using the IAA, the extracted factors are investigated for their potentials to create customer delight and/or frustration. The results provide valuable insight to both researchers and practitioners regarding the understanding of campsite satisfaction.

Keywords: Camping tourism, campsite, impact-asymmetry analysis, satisfaction

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Authors: Mohammed Abbas Al-Jumaili

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There are some studies which have been conducted in resent years to investigate the possibility of producing high performance polymer concrete. However, despite the great important of this subject, very limited amount of literature is available about the strength and performance of this type of concrete in case using in rigid pavement highway. In this study, the possibility of producing high performance polymer concrete by using Styrene Butadiene Rubber (SBR) emulsion with various (SBR) percents of 5,10 ,15, and 20 % by weight of cement has been investigated. The compressive, splitting tensile and flexural strengths and dynamic modulus of elasticity tests were conducted after age of 7 and 28 days for control without polymer and SBR concretes. A total of (30) cubes, (30) cylinders and (30) prisms were prepared using different types of concrete mixes. The AASHTO guide-1993 method was used to determine slab concrete thickness of rigid pavement highway in case of using various SBR polymer concrete mixture types. The research results indicate that the use of 10% SBR by weight of cement leads to produce high performance concrete especially with regard to mechanical properties and structural relative to corresponding control concrete.

Keywords: rigid pavement highway, styrene–butadiene rubber (SBR) latex, compressive test, splitting tensile test, flexural test and dynamic modulus of elasticity test

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Authors: Lien-Fa Lin, Yung-Ming Li, Fu-Shun Hsieh

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With the advancement of information technology and development of group commerce, people have obviously changed in their lifestyle. However, group commerce faces some challenging problems. The products or services provided by vendors do not satisfactorily reflect customers’ opinions, so that the sale and revenue of group commerce gradually become lower. On the other hand, the process for a formed customer group to reach group-purchasing consensus is time-consuming and the final decision is not the best choice for each group members. In this paper, we design a social decision support mechanism, by using group discussion message to recommend suitable options for group members and we consider social influence and personal preference to generate option ranking list. The proposed mechanism can enhance the group purchasing decision making efficiently and effectively and venders can provide group products or services according to the group option ranking list.

Keywords: social network, group decision, text mining, group commerce

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Authors: Panaya Sudta, Wanchalerm Patanacharoenwong, Prachya Bumrungkun

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As With the evolution of smart grids, ensuring the reliability and efficiency of electrical systems in smart cities has become crucial. This paper proposes a distinct approach that combines advanced machine learning techniques to accurately predict electrical failures and address voltage reliability issues. This approach aims to improve the accuracy and efficiency of reliability evaluations in smart cities. The aim of this research is to develop a comprehensive predictive model that accurately predicts electrical failures and voltage reliability in smart cities. This model integrates RFM analysis, K-means clustering, and LSTM networks to achieve this objective. The research utilizes RFM analysis, traditionally used in customer value assessment, to categorize and analyze electrical components based on their failure recency, frequency, and monetary impact. K-means clustering is employed to segment electrical components into distinct groups with similar characteristics and failure patterns. LSTM networks are used to capture the temporal dependencies and patterns in customer data. This integration of RFM, K-means, and LSTM results in a robust predictive tool for electrical failures and voltage reliability. The proposed model has been tested and validated on diverse electrical utility datasets. The results show a significant improvement in prediction accuracy and reliability compared to traditional methods, achieving an accuracy of 92.78% and an F1-score of 0.83. This research contributes to the proactive maintenance and optimization of electrical infrastructures in smart cities. It also enhances overall energy management and sustainability. The integration of advanced machine learning techniques in the predictive model demonstrates the potential for transforming the landscape of electrical system management within smart cities. The research utilizes diverse electrical utility datasets to develop and validate the predictive model. RFM analysis, K-means clustering, and LSTM networks are applied to these datasets to analyze and predict electrical failures and voltage reliability. The research addresses the question of how accurately electrical failures and voltage reliability can be predicted in smart cities. It also investigates the effectiveness of integrating RFM analysis, K-means clustering, and LSTM networks in achieving this goal. The proposed approach presents a distinct, efficient, and effective solution for predicting and mitigating electrical failures and voltage issues in smart cities. It significantly improves prediction accuracy and reliability compared to traditional methods. This advancement contributes to the proactive maintenance and optimization of electrical infrastructures, overall energy management, and sustainability in smart cities.

Keywords: electrical state prediction, smart grids, data-driven method, long short-term memory, RFM, k-means, machine learning

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Authors: Stuti Modi, Aditi Kambli

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This paper addresses the need for intelligent water management and distribution system in smart cities to ensure optimal consumption and distribution of water for drinking and sanitation purposes. Water being a limited resource in cities require an effective system for collection, storage and distribution. In this paper, applications of two mostly widely used particular types of data-driven models, namely artificial neural networks (ANN) and fuzzy logic-based models, to modelling in the water resources management field are considered. The objective of this paper is to review the principles of various types and architectures of neural network and fuzzy adaptive systems and their applications to integrated water resources management. Final goal of the review is to expose and formulate progressive direction of their applicability and further research of the AI-related and data-driven techniques application and to demonstrate applicability of the neural networks, fuzzy systems and other machine learning techniques in the practical issues of the regional water management. Apart from this the paper will deal with water storage, using ANN to find optimum reservoir level and predicting peak daily demands.

Keywords: artificial neural networks, fuzzy systems, peak daily demand prediction, water management and distribution

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Authors: Sihem Benaouda

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English is gaining an international identity as it affects every academic and professional field in the world. Without increasing their cultural understanding, it would obviously be difficult to completely educate learners for communication in a globalised environment. The concept of culture is intricate and needs to be elucidated, especially in an English language teaching (ELT) context. The study focuses on the investigation of the cultural studies integrated into the different types of English for specific purposes (ESP) materials, as opposed to English for general purposes (EGP) textbooks. A qualitative methodology based on a triangulation of techniques was conducted through materials analysis of five textbooks in both advanced EGP and three types of ESP. In addition to a semi-structured interview conducted with Algerian ESP practitioners, data analysis results revealed that culture in ESP textbooks is not overtly isolated into chapters and that cultural studies are predominantly present in business and economics materials, namely English for hotel and catering staff, tourism, and flight attendants. However, implicit cultural instruction is signalled in the social sciences and is negligible in science and technology sources. In terms of content, cultural studies in EGP are more related to generic topics, whereas, in some ESP materials, the topics are rather oriented to the specific field they belong to. Furthermore, the respondents’ answers showed an unawareness of the importance of culture in ESP teaching, besides some disregard for culture teaching per se in ESP contexts.

Keywords: ESP, EGP, cultural studies, textbooks, teaching, materials

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Authors: Barbara Magallona

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Given the observations between students who were active participants in a dialogue with their teacher and students who simply answered the teacher’s questions, the researcher will investigate the relationship between student-teacher dialogue in the classroom and the development of higher level thinking skills with an emphasis on the questioning techniques used by the teacher. The study posits the main question: What is the relationship between teachers’ questioning techniques and the development of students’ higher level thinking skills in a literature class (or in literature classes) in Xavier? The following are the study’s sub-questions: a) What types of questions do literature teachers at Xavier School ask? b) What types of responses do literature students at Xavier School give to teachers' questions? c) To what extent is the development of students' higher level thinking skills shown in teacher-student classroom dialogues in Xavier School's literature classroom? Since questioning techniques and student responses in the literature classroom form the core of this paper and in order to evaluate them, the study uses Andersen and Krathwohl’s revision of Harold Bloom’s Taxonomy of Educational Objectives. Teun van Dijk’s discourse-cognition-society triangle will be used as a theoretical framework to design and to guide the classroom interaction.

Keywords: discourse analysis, literature classroom, questioning techniques, secondary education

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Authors: Sivilai Jayankura

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The objective is to study the behaviors, lifestyles and consumption of the student of Suan Sunandha Rajabhat University. This paper is survey research by using a questionnaire to collect the data with students of Suan Sunandha Rajabhat University for 385 sampling, random coincidence sampling has been provide. Data analysis by descriptive statistics include the distribution, frequency, percentage, average, and standard deviation. The result found that the majority of students are female, and spend their time with their own ideas, like socializing with friends and shopping at the shopping mall, see the movie at the theaters and at the night time will enjoy with their mobile phone and found they long for the quality-price and also brand name regarding the dress. The media and promotion is a key factor impact to the decision to purchase the product and service with mobile phones will be good business to expand business channel also.

Keywords: consumption of teenager, internet, lifestyle behavior, Suan Sunundha Rajabhat University

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Authors: Iftikhar Tayubi, Tabrej Khan, Rayan Alsulmi, Abdulrahman Labban

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Spider produces a special kind of substance. This special kind of substance is called a toxin. The toxin is composed of many types of protein, which differs from species to species. Spider toxin consists of several proteins and non-proteins that include various categories of toxins like myotoxin, neurotoxin, cardiotoxin, dendrotoxin, haemorrhagins, and fibrinolytic enzyme. Protein Sequence information with references of toxins was derived from literature and public databases. From the previous findings, the Spider toxin would be the best choice to treat different types of tumors and cancer. There are many therapeutic regimes, which causes more side effects than treatment hence a different approach must be adopted for the treatment of cancer. The combinations of drugs are being encouraged, and dramatic outcomes are reported. Spider toxin is one of the natural cytotoxic compounds. Hence, it is being used to treat different types of tumors; especially its positive effect on breast cancer is being reported during the last few decades. The efficacy of this database is that it can provide a user-friendly interface for users to retrieve the information about Spiders, toxin and toxin protein of different Spiders species. SPIDTOXD provides a single source information about spider toxins, which will be useful for pharmacologists, neuroscientists, toxicologists, medicinal chemists. The well-ordered and accessible web interface allows users to explore the detail information of Spider and toxin proteins. It includes common name, scientific name, entry id, entry name, protein name and length of the protein sequence. The utility of this database is that it can provide a user-friendly interface for users to retrieve the information about Spider, toxin and toxin protein of different Spider species. The database interfaces will satisfy the demands of the scientific community by providing in-depth knowledge about Spider and its toxin. We have adopted the methodology by using A MySQL and PHP and for designing, we used the Smart Draw. The users can thus navigate from one section to another, depending on the field of interest of the user. This database contains a wealth of information on species, toxins, and clinical data, etc. This database will be useful for the scientific community, basic researchers and those interested in potential pharmaceutical Industry.

Keywords: siptoxd, php, mysql, toxin

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Authors: Mona Rezaei, Habib Honari, Mehrzad Hamidi, Fatemeh Kiani

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Make strong brands has become a priority for many organizations in marketing. Brand is an important indicator of marketing status. Brand Strength is in kept customer, profit, brand development and gain competitive advantage and In fact it is a concept that was created from a consumer perspective. It is assumed that the creation of a strong brand is creating numerous marketing benefits. The purpose of this study was to evaluate the psychometric characteristics of the questionnaire the most strong sports brands in the consumer society. Questionnaire was conducted to a sample of 340 customers of sports brands. Psychometric parameters were determined by using appropriate statistical methods. The results of the factor analysis and Varimax rotation revealed five factors of strong brands. The results confirms that questionnaire structure have acceptable associated to the data and confirmed all indicators of the model. Reliability (859/0) was satisfactory. According to calculated psychometric indices, this questionnaire could be appropriate to assess the most strong sports brands.

Keywords: reliability, strong brand, sport brands, psychometric

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Authors: Oustani Mabrouka, Halilat Md Tahar, Hannachi Slimane

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This study was conducted on representative and contrasting soils of arid regions. It focuses on the compared influence of two organic fertilizers: poultry manure (PM) and bovine manure (BM) on improving the microbial functioning of non-saline (SS) and saline (SSS) soils, in particularly, the process of mineralization of nitrogen and carbon. The microbiological activity was estimated by respirometric test (CO2–C emissions) and the extraction of two forms of mineral nitrogen (NH4+-N and NO3--N). Thus, after 56 days of incubation under controlled conditions (28 degrees and 80 per cent of the field capacity), the two types of manures showed that the mineralization activity varies according to type of soil and the organic substrate itself. However, the highest cumulative quantities of CO2–C, NH4+–N and NO3-–N obtained at the end of incubation were recorded in non-saline (SS) soil treated with poultry manure with 1173.4, 4.26 and 8.40 mg/100 g of dry soil, respectively. The reductions in rates of release of CO2–C and of nitrification under saline conditions were 21 and 36, 78 %, respectively. The influence of organic substratum on the microbial density shows a stimulating effect on all microbial groups studied. The whole results show the usefulness of two types of manures for the improvement of the microbiological functioning of arid soils.

Keywords: Salinity, Organic matter, Microorganisms, Mineralization, Nitrogen, Carbon, Arid regions

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Authors: Subarna Ferdous, Mitsuru Ikeda

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For the shrimp companies to remain relevant to its local and international consumers, they must offer new shrimp product and services. It must work actively not just to create value for the consumer, but to involve the consumer in co-creating value for shrimp product innovation in the market. In this theoretical work, we conceptualize the business concept of value co-creation in the context of shrimp products, and propose a framework of value co-creation for shrimp product innovation in shrimp industries. With guidance on value co-creation in in shrimp industry, and shrimp value chain actors mapped to the co-creation cycle, companies can use the framework to offer new shrimp product to consumer communities. Although customer co-creation is known approach in the world, it is not commonly used by the companies in Bangladesh. This paper makes an original contribution by conceptualizing co-creation and set the examples of best co-creation practices in food sector. The results of the study provide management with guidelines for successful co-creation projects with an innovation- and market-oriented approach. The framework also provides a basis for further research in this area.

Keywords: bangladesh, shrimp industry, value co-creation, shrimp product

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Authors: Hissa Sadiq, Abdullah Abu-Tineh, Fatma Al-Mutawah, Hamda Al-Sulaiti

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The purpose of this quantitative study was to measure the difference in levels of satisfaction of students, teachers, and parents in schools run by licensed school leaders comparing with schools run by unlicensed school leaders. Data was gathered from 108 school performance reports as published by Ministry of Education and Higher Education for the year 2015-2016. School leaders in 58 participating schools obtained the professional licenses while school leaders in 56 participating schools have no professional licenses. Percentages, standard deviations, and t-tests were used to analyze the data. Results showed that no statistical differences were found in students’ satisfaction between the two school types. However, there were statistical differences in parents and teachers’ satisfaction in the two school types attributed to obtaining the professional license. Teachers and parents of students in schools run by licensed school leaders satisfied more than schools run by unlicensed school leaders. Finally, many recommendations and implications were discussed and proposed. This paper was made possible by NPRP grant # (NPRP7-1224-5-178) from the Qatar national research fund (a member of Qatar Foundation) to Abdullah M. Abu-Tineh. The statements made herein are solely the responsibility of the author

Keywords: professional licenses, Qatari schools, licensure system, satisfaction

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Authors: Boussoualim Nacira, Aklouf Youcef

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Software as a Service (SaaS) is a software delivery paradigm in which the product is not installed on-premise, but it is available on Internet and Web. The customers do not pay to possess the software itself but rather to use it. This concept of pay per use is very attractive. Hence, we see increasing number of organizations adopting SaaS. However, each customer is unique, which leads to a very large variation in the requirements off the software. As several suppliers propose SaaS products, the choice of this latter becomes a major issue. When multiple criteria are involved in decision making, we talk about a problem of «Multi-Criteria Decision-Making» (MCDM). Therefore, this paper presents a method to help customers to choose a better SaaS product satisfying most of their conditions and alternatives. Also, we know that a good method of adaptive selection should be based on the correct definition of the different parameters of choice. This is why we started by extraction and analysis the various parameters involved in the process of the selection of a SaaS application.

Keywords: cloud computing, business operation, Multi-Criteria Decision-Making (MCDM), Software as a Service (SaaS)

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Authors: Urvee B. Trivedi, U. D. Dalal

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As wireless communication services grow quickly; the seriousness of spectrum utilization has been on the rise gradually. An emerging technology, cognitive radio has come out to solve today’s spectrum scarcity problem. To support the spectrum reuse functionality, secondary users are required to sense the radio frequency environment, and once the primary users are found to be active, the secondary users are required to vacate the channel within a certain amount of time. Therefore, spectrum sensing is of significant importance. Once sensing is done, different prediction rules apply to classify the traffic pattern of primary user. Primary user follows two types of traffic patterns: periodic and stochastic ON-OFF patterns. A cognitive radio can learn the patterns in different channels over time. Two types of classification methods are discussed in this paper, by considering edge detection and by using autocorrelation function. Edge detection method has a high accuracy but it cannot tolerate sensing errors. Autocorrelation-based classification is applicable in the real environment as it can tolerate some amount of sensing errors.

Keywords: cognitive radio (CR), probability of detection (PD), probability of false alarm (PF), primary user (PU), secondary user (SU), fast Fourier transform (FFT), signal to noise ratio (SNR)

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Authors: Gonca Z. Tuncbilek

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Architectural research tends to define architecture in terms of its permanence. In this study, the term ‘temporality’ and its use in architectural discourse is re-visited. The definition, proposition, and efficacy of the temporality occur both in architecture and in its related knowledge. The temporary architecture not only fulfills the requirement of the architectural programs, but also plays a significant role in generating an environment of architectural discourse. In recent decades, there is a great interest on the temporary architectural practices regarding to the installations, exhibition spaces, pavilions, and expositions; inviting the architects to experience and think about architecture. The temporary architecture has a significant role among the architecture, the architect, and the architectural discourse. Experiencing the contemporary materials, methods and technique; they have proposed the possibilities of the future architecture. These structures give opportunities to the architects to a wide-ranging variety of freedoms to experience the ‘new’ in architecture. In addition to this experimentation, they can be considered as an agent to redefine and reform the boundaries of the architectural discipline itself. Although the definition of architecture is re-analyzed in terms of its temporality rather than its permanence; architecture, in reality, still relies on historically codified types and principles of the formation. The concept of type can be considered for several different sciences, and there is a tendency to organize and understand the world in terms of classification in many different cultures and places. ‘Type’ is used as a classification tool with/without the scope of the critical invention. This study considers theories of type, putting forward epistemological and discursive arguments related to the form of architecture, being related to historical and formal disciplinary knowledge in architecture. This study has been to emphasize the importance of the temporality in architecture as a creative tool to reveal the position within the architectural discourse. The temporary architecture offers ‘new’ opportunities in the architectural field to be analyzed. In brief, temporary structures allow the architect freedoms to the experimentation in architecture. While redefining the architecture in terms of temporality, architecture still relies on historically codified types (pavilions, exhibitions, expositions, and installations). The notion of architectural types and its varying interpretations are analyzed based on the texts of architectural theorists since the Age of Enlightenment. Investigating the classification of type in architecture particularly temporary architecture, it is necessary to return to the discussion of the origin of the knowledge and its classification.

Keywords: classification of architecture, exhibition design, pavilion design, temporary architecture

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Authors: Eric Bang

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Interactions between receptors and ligands are crucial for many essential biological processes, including neurotransmission and metabolism. Ligand-receptor analyses that examine cell behavior and interactions often utilize cell type-specific RNA expressions from single-cell RNA sequencing (scRNA-seq) data. Using CellPhoneDB, a public repository consisting of ligands, receptors, and ligand-receptor interactions, the cell-cell interactions were explored in a specific scRNA-seq dataset from kidney tissue and portrayed the results with dot plots and heat maps. Depending on the type of cell, each ligand-receptor pair was aligned with the interacting cell type and calculated the positori probabilities of these associations, with corresponding P values reflecting average expression values between the triads and their significance. Using single-cell data (sample kidney cell references), genes in the dataset were cross-referenced with ones in the existing CellPhoneDB dataset. For example, a gene such as Pleiotrophin (PTN) present in the single-cell data also needed to be present in the CellPhoneDB dataset. Using the single-cell transcriptomics data via slide-seq and reference data, the CellPhoneDB program defines cell types and plots them in different formats, with the two main ones being dot plots and heat map plots. The dot plot displays derived measures of the cell to cell interaction scores and p values. For the dot plot, each row shows a ligand-receptor pair, and each column shows the two interacting cell types. CellPhoneDB defines interactions and interaction levels from the gene expression level, so since the p-value is on a -log10 scale, the larger dots represent more significant interactions. By performing an interaction analysis, a significant interaction was discovered for myeloid and T-cell ligand-receptor pairs, including those between Secreted Phosphoprotein 1 (SPP1) and Fibronectin 1 (FN1), which is consistent with previous findings. It was proposed that an effective protocol would involve a filtration step where cell types would be filtered out, depending on which ligand-receptor pair is activated in that part of the tissue, as well as the incorporation of the CellPhoneDB data in a streamlined workflow pipeline. The filtration step would be in the form of a Python script that expedites the manual process necessary for dataset filtration. Being in Python allows it to be integrated with the CellPhoneDB dataset for future workflow analysis. The manual process involves filtering cell types based on what ligand/receptor pair is activated in kidney cells. One limitation of this would be the fact that some pairings are activated in multiple cells at a time, so the manual manipulation of the data is reflected prior to analysis. Using the filtration script, accurate sorting is incorporated into the CellPhoneDB database rather than waiting until the output is produced and then subsequently applying spatial data. It was envisioned that this would reveal wherein the cell various ligands and receptors are interacting with different cell types, allowing for easier identification of which cells are being impacted and why, for the purpose of disease treatment. The hope is this new computational method utilizing spatially explicit ligand-receptor association data can be used to uncover previously unknown specific interactions within kidney tissue.

Keywords: bioinformatics, Ligands, kidney tissue, receptors, spatial transcriptome

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Authors: Syed Iftikhar Hussain Shah, Vasilis Peristeras, Ioannis Magnisalis

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Data that is high in volume, velocity, veracity and comes from a variety of sources is usually generated in all sectors including the government sector. Globally public administrations are pursuing (big) data as new technology and trying to adopt a data-centric architecture for hosting and sharing data. Properly executed, big data and data analytics in the government (big) data ecosystem can be led to data-driven government and have a direct impact on the way policymakers work and citizens interact with governments. In this research paper, we conduct a systematic literature review. The main aims of this paper are to highlight essential aspects of the government (big) data ecosystem and to explore the most critical socio-technical factors that contribute to the successful implementation of government (big) data ecosystem. The essential aspects of government (big) data ecosystem include definition, data types, data lifecycle models, and actors and their roles. We also discuss the potential impact of (big) data in public administration and gaps in the government data ecosystems literature. As this is a new topic, we did not find specific articles on government (big) data ecosystem and therefore focused our research on various relevant areas like humanitarian data, open government data, scientific research data, industry data, etc.

Keywords: applications of big data, big data, big data types. big data ecosystem, critical success factors, data-driven government, egovernment, gaps in data ecosystems, government (big) data, literature review, public administration, systematic review

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Authors: Robert Cazar, Nathaly Maza

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Energy drinks and sports drinks are quite popular among young adults and teenagers worldwide. Some concerns regarding their health effects – particularly those of the energy drinks - have been raised based on scientific findings. Differentiating between these two types of drinks by means of their chemical properties seems to be an instructive task. Chemometrics provides the most appropriate strategy to do so. In this study, a discrimination analysis of the energy and sports drinks has been carried out applying chemometric methods. A set of eleven samples of available commercial brands of drinks – seven energy drinks and four sports drinks – were collected. Each sample was characterized by eight chemical variables (carbohydrates, energy, sugar, sodium, pH, degrees Brix, density, and citric acid). The data set was standardized and examined by exploratory chemometric techniques such as clustering and principal component analysis. As a preliminary step, a variable selection was carried out by inspecting the variable correlation matrix. It was detected that some variables are redundant, so they can be safely removed, leaving only five variables that are sufficient for this analysis. They are sugar, sodium, pH, density, and citric acid. Then, a hierarchical clustering `employing the average – linkage criterion and using the Euclidian distance metrics was performed. It perfectly separates the two types of drinks since the resultant dendogram, cut at the 25% similarity level, assorts the samples in two well defined groups, one of them containing the energy drinks and the other one the sports drinks. Further assurance of the complete discrimination is provided by the principal component analysis. The projection of the data set on the first two principal components – which retain the 71% of the data information – permits to visualize the distribution of the samples in the two groups identified in the clustering stage. Since the first principal component is the discriminating one, the inspection of its loadings consents to characterize such groups. The energy drinks group possesses medium to high values of density, citric acid, and sugar. The sports drinks group, on the other hand, exhibits low values of those variables. In conclusion, the application of chemometric methods on a data set that features some chemical properties of a number of energy and sports drinks provides an accurate, dependable way to discriminate between these two types of beverages.

Keywords: chemometrics, clustering, energy drinks, principal component analysis, sports drinks

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Authors: Mohammad Borhani, Afshin Danehkar

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With the increase in population and the upward trend of energy demand, mankind has thought of using suppliers that guarantee a stable supply of energy, unlike fossil fuels, which, in addition to the widespread emission of greenhouse gases that one of the main factors in the destruction of the ozone layer and it will be finished in a short time in the not-so-distant future. In this regard, one of the sustainable ways of energy supply is the use of wind converters. That convert wind energy into electricity. For this reason, this research focused on wind turbines and their installation conditions. The main classification of wind turbines is based on the axis of rotation, which is divided into two groups: horizontal axis and vertical axis; each of these two types, with the advancement of technology in man-made environments such as cities, villages, airports, and other human environments can be installed and operated. The main difference between offshore and onshore wind turbines is their installation and foundation. Which are usually divided into five types; including of Monopile Wind Turbines, Jacket Wind Turbines, Tripile Wind Turbines, Gravity-Based Wind Turbines, and Floating Offshore Wind Turbines. For installation in a wind power plant requires an arrangement that produces electric power, the distance between the turbines is usually between 5 or 7 times the diameter of the rotor and if perpendicular to the wind direction be If they are 3 to 5 times the diameter of the rotor, they will be more efficient.

Keywords: wind farms, Savonius, Darrieus, offshore wind turbine, renewable energy

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