Search results for: social networks sites (SNSs)

Authors: Ogundele Lasun Tunde, Ayeku Oluwagbemiga Patrick

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Heavy metals are released into the sediments in aquatic environment from both natural and anthropogenic sources and they are considered as worldwide issue due to their deleterious ecological risks and food chain disruption. In this study, sediments samples were collected at three major sites (Awoye, Abereke and Ayetoro) along Ondo coastal area using VanVeen grab sampler. The concentrations of As, Cd, Cr, Cu, Fe, Mn, Ni, Pb, V and Zn were determined by employing Atomic Absorption Spectroscopy (AAS). The combined concentrations data were subjected to Positive Matrix Factorization (PMF) receptor approach for source identification and apportionment. The probable risks that might be posed by heavy metals in the sediment were estimated by potential and integrated ecological risks indices. Among the measured heavy metals, Fe had the average concentrations of 20.38 ± 2.86, 23.56 ± 4.16 and 25.32 ± 4.83 lg/g at Abereke, Awoye and Ayetoro sites, respectively. The PMF resulted in identification of four sources of heavy metals in the sediments. The resolved sources and their percentage contributions were oil exploration (39%), industrial waste/sludge (35%), detrital process (18%) and Mn-sources (8%). Oil exploration activities and industrial wastes are the major sources that contribute heavy metals into the coastal sediments. The major pollutants that posed ecological risks to the local aquatic ecosystem are As, Pb, Cr and Cd (40 B Ei ≤ 80) classifying the sites as moderate risk. The integrate risks values of Awoye, Abereke and Ayetoro are 231.2, 234.0 and 236.4, respectively suggesting that the study areas had a moderate ecological risk. The study showed the suitability of PMF receptor model for source identification of heavy metals in the sediments. Also, the intensive anthropogenic activities and natural sources could largely discharge heavy metals into the study area, which may increase the heavy metal contents of the sediments and further contribute to the associated ecological risk, thus affecting the local aquatic ecosystem.

Keywords: positive matrix factorization, sediments, heavy metals, sources, ecological risks

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Authors: Xiaoqi Jia, Qing Zhu, Hao Zhang, Su Yang

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A gender recognition system is able to tell the gender of the given person through a few of frontal facial images. An effective gender recognition approach enables to improve the performance of many other applications, including security monitoring, human-computer interaction, image or video retrieval and so on. In this paper, we present an effective method for gender classification task in frontal facial images based on deep belief networks (DBNs), which can pre-train model and improve accuracy a little bit. Our experiments have shown that the pre-training method with DBNs for gender classification task is feasible and achieves a little improvement of accuracy on FERET and CAS-PEAL-R1 facial datasets.

Keywords: gender recognition, beep belief net-works, semi-supervised learning, greedy-layer wise RBMs

Procedia PDF Downloads 453

Authors: Osama Amer Mohyeldin Mohamed

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Qubbet el-Hawa North (QHN) is an example of an archaeological site in West-Aswan and It has not opened to the public yet and has been under excavation since its discovery in 2013 as a result of the illegal digging that happened in many sites in Egypt because of the unstable situation and the absence of security. The site has the potential to be one of the most attractive sites in Aswan. Moreover, it deserves to be introduced to the visitors in a good manner appropriate to its great significance. Both interpretation and presentation are crucial inseparable tools that communicate the archaeological site's significance to the public and raise their awareness. Moreover, it helps them to understand the past and appreciate archaeological assets. People will never learn or see anything from ancient remains unless it is explained. They would only look at it as ancient and charming. They expect a story, and more than knowledge, authenticity, or even supporting preservation actions, they want to enjoy and be entertained. On the other hand, a lot of archaeologists believe that planning an archaeological site for entertaining visitors deteriorates it and affects its authenticity. Thus, it represents a challenge to design a model for visitors’ experience that meets their expectations and needs while safeguarding the site’s integrity. The article presents a proposal for an interpretation plan for the site of Qubbet el-Hawa North.

Keywords: heritage interpretation and presentation, archaeological site management, qubbet el-hawa North, local community engagement, accessibility

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Authors: Jamerson Felipe Pereira Lima, Jeane Cecília Bezerra de Melo

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The difficulty and cost related to obtaining of protein tertiary structure information through experimental methods, such as X-ray crystallography or NMR spectroscopy, helped raising the development of computational methods to do so. An approach used in these last is prediction of tridimensional structure based in the residue chain, however, this has been proved an NP-hard problem, due to the complexity of this process, explained by the Levinthal paradox. An alternative solution is the prediction of intermediary structures, such as the secondary structure of the protein. Artificial Intelligence methods, such as Bayesian statistics, artificial neural networks (ANN), support vector machines (SVM), among others, were used to predict protein secondary structure. Due to its good results, artificial neural networks have been used as a standard method to predict protein secondary structure. Recent published methods that use this technique, in general, achieved a Q3 accuracy between 75% and 83%, whereas the theoretical accuracy limit for protein prediction is 88%. Alternatively, to achieve better results, support vector machines prediction methods have been developed. The statistical evaluation of methods that use different AI techniques, such as ANNs and SVMs, for example, is not a trivial problem, since different training sets, validation techniques, as well as other variables can influence the behavior of a prediction method. In this study, we propose a prediction method based on artificial neural networks, which is then compared with a selected SVM method. The chosen SVM protein secondary structure prediction method is the one proposed by Huang in his work Extracting Physico chemical Features to Predict Protein Secondary Structure (2013). The developed ANN method has the same training and testing process that was used by Huang to validate his method, which comprises the use of the CB513 protein data set and three-fold cross-validation, so that the comparative analysis of the results can be made comparing directly the statistical results of each method.

Keywords: artificial neural networks, protein secondary structure, protein structure prediction, support vector machines

Procedia PDF Downloads 621

Authors: Swapnil Singh, Sanjoy Das

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Mobile Ad-Hoc Network (MANET) is infrastructure less networks dynamically formed by autonomous system of mobile nodes that are connected via wireless links. Mobile nodes communicate with each other on the fly. In this network each node also acts as a router. The battery power and the bandwidth are very scarce resources in this network. The network lifetime and connectivity of nodes depends on battery power. Therefore, energy is a valuable constraint which should be efficiently used. In this paper, we survey various energy efficient routing protocol. The energy efficient routing protocols are classified on the basis of approaches they use to minimize the energy consumption. The purpose of this paper is to facilitate the research work and combine the existing solution and to develop a more energy efficient routing mechanism.

Keywords: delaunay triangulation, deployment, energy efficiency, MANET

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Authors: Anh T. P. Tran, Harald Von Korflesch

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Entrepreneurial intention play a major role in entrepreneurship academia and practice. The spectrum ranges from the first model of the so-called Entrepreneurial Event, then the Theory of Planned Behavior, the Theory of Planned Behavior Entrepreneurial Model, and the Social Cognitive Career Theory to some typical empirical studies with more or less diverse results. However, little is known so far about the intentions of entrepreneurs in the social areas of venture creation. It is surprising that, since social entrepreneurship is an emerging field with growing importance. Currently, all around the world, there is a big challenge with a lot of urgent soaring social and environmental problems such as poor households, people with disabilities, HIV/AIDS infected people, the lonely elderly, or neglected children, some of them even actual in the Western countries. In addition, the already existing literature on entrepreneurial intentions demonstrates a high level of theoretical diversity in general, especially the missing link to the social dimension of entrepreneurship. Seeking to fill the mentioned gaps in the social entrepreneurial intentions literature, this paper proposes a conceptual model of social entrepreneurial intentions based on the Social Cognitive Career Theory with two main factors influencing entrepreneurial intentions namely self-efficacy and outcome expectation. Moreover, motives, goals and plans do not arise from empty nothingness, but are shaped by interacting with the environment. Hence, personalities (i.e., agreeableness, conscientiousness, extraversion, neuroticism, openness) as well as contextual factors (e.g., role models, education, and perceived support) are also considered as the antecedents of social entrepreneurship intentions.

Keywords: entrepreneurial intention, social cognitive career theory, social entrepreneurial intention, social entrepreneurship

Procedia PDF Downloads 475

Authors: Matej Komanec, Jan Bohata, Stanislav Zvanovec, Tomas Nemecek, Jan Broucek, Josef Beran

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With the exponential growth of social networks, video streaming and increasing demands on data rates, the number of newly built data centers rises proportionately. The data centers, however, have to adjust to the rapidly increased amount of data that has to be processed. For this purpose, multi-mode (MM) fiber based infrastructures are often employed. It stems from the fact, the connections in data centers are typically realized within a short distance, and the application of MM fibers and components considerably reduces costs. On the other hand, the usage of MM components brings specific requirements for installation service conditions. Moreover, it has to be taken into account that MM fiber components have a higher production tolerance for parameters like core and cladding diameters, eccentricity, etc. Due to the high demands for the reliability of data center components, the determination of properly excited optical field inside the MM fiber core belongs to the key parameters while designing such an MM optical system architecture. Appropriately excited mode field of the MM fiber provides optimal power budget in connections, leads to the decrease of insertion losses (IL) and achieves effective modal bandwidth (EMB). The main parameter, in this case, is the encircled flux (EF), which should be properly defined for variable optical sources and consequent different mode-field distribution. In this paper, we present detailed investigation and measurements of the mode field distribution for short MM links purposed in particular for data centers with the emphasis on reliability and safety. These measurements are essential for large MM network design. The various scenarios, containing different fibers and connectors, were tested in terms of IL and mode-field distribution to reveal potential challenges. Furthermore, we focused on estimation of particular defects and errors, which can realistically occur like eccentricity, connector shifting or dust, were simulated and measured, and their dependence to EF statistics and functionality of data center infrastructure was evaluated. The experimental tests were performed at two wavelengths, commonly used in MM networks, of 850 nm and 1310 nm to verify EF statistics. Finally, we provide recommendations for data center systems and networks, using OM3 and OM4 MM fiber connections.

Keywords: optical fiber, multi-mode, data centers, encircled flux

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Authors: A. M. John-Otumu, M. M. Rahman, O. C. Nwokonkwo, M. C. Onuoha

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Online social media networks have long served as a primary arena for group conversations, gossip, text-based information sharing and distribution. The use of natural language processing techniques for text classification and unbiased decision-making has not been far-fetched. Proper classification of this textual information in a given context has also been very difficult. As a result, we decided to conduct a systematic review of previous literature on sentiment classification and AI-based techniques that have been used in order to gain a better understanding of the process of designing and developing a robust and more accurate sentiment classifier that can correctly classify social media textual information of a given context between hate speech and inverted compliments with a high level of accuracy by assessing different artificial intelligence techniques. We evaluated over 250 articles from digital sources like ScienceDirect, ACM, Google Scholar, and IEEE Xplore and whittled down the number of research to 31. Findings revealed that Deep learning approaches such as CNN, RNN, BERT, and LSTM outperformed various machine learning techniques in terms of performance accuracy. A large dataset is also necessary for developing a robust sentiment classifier and can be obtained from places like Twitter, movie reviews, Kaggle, SST, and SemEval Task4. Hybrid Deep Learning techniques like CNN+LSTM, CNN+GRU, CNN+BERT outperformed single Deep Learning techniques and machine learning techniques. Python programming language outperformed Java programming language in terms of sentiment analyzer development due to its simplicity and AI-based library functionalities. Based on some of the important findings from this study, we made a recommendation for future research.

Keywords: artificial intelligence, natural language processing, sentiment analysis, social network, text

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Authors: Khaled S. Abdallah, Abdel-Aziz M. Mohamed

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Moving industries consume numerous resources and dispose masses of used packaging materials. Proper sorting, recycling and disposing the packaging materials is necessary to avoid a sever pollution disaster. This research paper presents a conceptual model to propose sustainable truck rental operations instead of the regular one. An optimization model was developed to select the locations of truck rental centers, collection sites, maintenance and repair sites, and identify the rental fees to be charged for all routes that maximize the total closed supply chain profits. Fixed costs of vehicle purchasing, costs of constructing collection centers and repair centers, as well as the fixed costs paid to use disposal and recycling centers are considered. Operating costs include the truck maintenance, repair costs as well as the cost of recycling and disposing the packing materials, and the costs of relocating the truck are presented in the model. A mixed integer model is developed followed by a simulation model to examine the factors affecting the operation of the model.

Keywords: modeling, truck rental, supply chains management.

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Authors: Loes Nijskens

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The city of The Hague is coping with several social issues: high unemployment rates, segregation and environmental pollution. The amount of social enterprises in The Hague that want to tackle these issues is increasing, but no clear image exists of the stimulants and obstacles social entrepreneurs encounter. In this qualitative study 20 starting and established social entrepreneurs, investors and stimulators of social entrepreneurship have been interviewed. The findings indicate that the majority of entrepreneurs situated in The Hague focuses on creating jobs (the so called social nurturers) and diminishing food waste. Moreover, the study found smaller groups of social connectors, (who focus on stimulating the social cohesion in the city) and social traders (who create a market for products from developing countries). For the social nurturers, working together with local government to find people with a distance to the labour market is a challenge. The entrepreneurs are missing a governance approach within the local government, wherein space is provided to develop suitable legislation and projects in cooperation with several stakeholders in order to diminish social problems. All entrepreneurs in the sample face(d) the challenge of having a clear purpose of their business in the beginning. Starting social entrepreneurs tend to be idealistic without having defined a business model. Without a defined business model it is difficult to find proper funding for their business. The more advanced enterprises cope with the challenge of measuring social impact. The larger they grow, the more they have to ‘defend’ themselves towards the local government and their customers, of mainly being social. Hence, the more experienced social nurturers still find it difficult to work together with the local government. They tend to settle their business in other municipalities, where they find more effective public-private partnerships. Al this said, the eco-system for social enterprises in The Hague is on the rise. To stimulate the amount and growth of social enterprises the cooperation between entrepreneurs and local government, the developing of social business models and measuring of impact needs more attention.

Keywords: obstacles, social enterprises, stimulants, the Hague

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Authors: Katie Kilgour, Brendan Turner, Carly Catella, Michael Daniele, Stefano Menegatti

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In vivo, the extracellular matrix (ECM) provides biochemical and mechanical properties that are instructional to resident cells to form complex tissues with characteristics to develop and support vascular networks. In vitro, the development of vascular networks can be guided by biochemical patterning of substrates via spatial distribution and display of peptides and growth factors to prompt cell adhesion, differentiation, and proliferation. We have developed a technique utilizing peptide ligands that specifically bind vascular endothelial growth factor (VEGF), erythropoietin (EPO), or angiopoietin-1 (ANG1) to spatiotemporally distribute growth factors to cells. This allows for the controlled release of each growth factor, ultimately enhancing the formation of a vascular network. Our engineered tissue constructs (ETCs) are fabricated out of gelatin methacryloyl (GelMA), which is an ideal substrate for tailored stiffness and bio-functionality, and covalently patterned with growth factor specific peptides. These peptides mimic growth factor receptors, facilitating the non-covalent binding of the growth factors to the ETC, allowing for facile uptake by the cells. We have demonstrated in the absence of cells the binding affinity of VEGF, EPO, and ANG1 to their respective peptides and the ability for each to be patterned onto a GelMA substrate. The ability to organize growth factors on an ETC provides different functionality to develop organized vascular networks. Our results demonstrated a method to incorporate biochemical cues into ETCs that enable spatial and temporal control of growth factors. Future efforts will investigate the cellular response by evaluating gene expression, quantifying angiogenic activity, and measuring the speed of growth factor consumption.

Keywords: growth factor, hydrogel, peptide, angiogenesis, vascular, patterning

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Authors: Ebrahim Alrashed

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Wireless sensor networks are vulnerable to attacks from adversaries attempting to disrupt their operations. Sink-hole attacks are a type of attack where an adversary node drops data forwarded through it and hence affecting the reliability and accuracy of the network. Since sensor nodes have limited battery power, it is essential that any solution to the sinkhole attack problem be very energy-aware. In this paper, we present a reliable and energy efficient scheme to forward data from source nodes to the base station while under sink-hole attack. The scheme also detects sink-hole attack nodes and avoid paths that includes them.

Keywords: energy-aware routing, reliability, sink-hole attack, WSN

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Authors: Masoumeh Mofarrah, Amir NahanMoghadam

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Higher oil prices and increasing oil demand are main reasons for great attention to Enhanced Oil Recovery (EOR). Comprehensive researches have been accomplished to develop, appraise, and improve EOR methods and their application. Recently, Artificial Intelligence (AI) gained popularity in petroleum industry that can help petroleum engineers to solve some fundamental petroleum engineering problems such as reservoir simulation, EOR project risk analysis, well log interpretation and well test model selection. This study presents a historical overview of most popular AI tools including neural networks, genetic algorithms, fuzzy logic, and expert systems in petroleum industry and discusses two case studies to represent the application of two mentioned AI methods for selecting an appropriate EOR method based on reservoir characterization infeasible and effective way.

Keywords: artificial intelligence, EOR, neural networks, expert systems

Procedia PDF Downloads 488

Authors: Halefom Kidane

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This study aims to assess the wind resource potential and characterize the urban area wind patterns in Hawassa City, Ethiopia. The estimation and characterization of wind resources are crucial for sustainable urban planning, renewable energy development, and climate change mitigation strategies. A secondary data collection method was used to carry out the study. The collected data at 2 meters was analyzed statistically and extrapolated to the standard heights of 10-meter and 30-meter heights using the power law equation. The standard deviation method was used to calculate the value of scale and shape factors. From the analysis presented, the maximum and minimum mean daily wind speed at 2 meters in 2016 was 1.33 m/s and 0.05 m/s in 2017, 1.67 m/s and 0.14 m/s in 2018, 1.61m and 0.07 m/s, respectively. The maximum monthly average wind speed of Hawassa City in 2016 at 2 meters was noticed in the month of December, which is around 0.78 m/s, while in 2017, the maximum wind speed was recorded in the month of January with a wind speed magnitude of 0.80 m/s and in 2018 June was maximum speed which is 0.76 m/s. On the other hand, October was the month with the minimum mean wind speed in all years, with a value of 0.47 m/s in 2016,0.47 in 2017 and 0.34 in 2018. The annual mean wind speed was 0.61 m/s in 2016,0.64, m/s in 2017 and 0.57 m/s in 2018 at a height of 2 meters. From extrapolation, the annual mean wind speeds for the years 2016,2017 and 2018 at 10 heights were 1.17 m/s,1.22 m/s, and 1.11 m/s, and at the height of 30 meters, were 3.34m/s,3.78 m/s, and 3.01 m/s respectively/Thus, the site consists mainly primarily classes-I of wind speed even at the extrapolated heights.

Keywords: artificial neural networks, forecasting, min-max normalization, wind speed

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Authors: Islam Elsayed Hussein

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The aim of this paper is to discover the impact of students’ attitude towards social media and the skills required to adopt social media as a university e-learning (2.0) platform. In addition, it measures the effect of social media adoption on interactive learning effectiveness. The population of this study was students at Faculty of tourism and Hotels, Fayoum University. A questionnaire was used as a research instrument to collect data from respondents, which had been selected randomly. Data had been analyzed using quantitative data analysis method. Findings showed that the students have a positive attitude towards adopting social networking in the learning process and they have also good skills for effective use of social networking tools. In addition, adopting social media is effectively affecting the interactive learning environment.

Keywords: attitude, skills, e-learning 2.0, interactive learning, Egypt

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Authors: Diogo Ferreira Lima Filho, José Roberto Amazonas

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Nanotechnology opens the door to new paradigms that introduces a variety of novel tools enabling a plethora of potential applications in the biomedical, industrial, environmental, and military fields. This work proposes an integrated node model by applying the same concepts of TCNet to networks of nanodevices where the nodes are cooperatively interconnected with a low-complexity Mealy Machine (MM) topology integrating in the same electronic system the modules necessary for independent operation in wireless sensor networks (WSNs), consisting of Rectennas (RF to DC power converters), Code Generators based on Finite State Machine (FSM) & Trellis Decoder and On-chip Transmit/Receive with autonomy in terms of energy sources applying the Energy Harvesting technique. This approach considers the use of a Graphene Composite Substrate (GCS) for the integrated electronic circuits meeting the following characteristics: mechanical flexibility, miniaturization, and optical transparency, besides being ecological. In addition, graphene consists of a layer of carbon atoms with the configuration of a honeycomb crystal lattice, which has attracted the attention of the scientific community due to its unique Electrical Characteristics.

Keywords: composite substrate, energy harvesting, finite state machine, graphene, nanotechnology, rectennas, wireless sensor networks

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Authors: Ravi Kumar Pandit

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Climate change is regarded as one of the most fundamental threats to sustainable livelihood and global development. There is growing a global concern in linking community-managed forests as potential climate change mitigation projects. This study was conducted to explore the local people’s perception on climate change and the role of community forestry (CF) to combat climate change impacts. Two active community forest user groups (CFUGs) from Kaski and Syangja Districts in Nepal were selected as study sites, and various participatory tools were applied to collect primary data. Although most of the respondents were unaware about the words “Climate Change” in study sites, they were quite familiar with the irregularities in rainfall season and other weather extremities. 60% of the respondents had the idea that, due to increase in precipitation, there is a frequent occurrence of erosion, floods and landslide. Around 85% of the people agreed that community forests help in stabilizing soil, reducing the natural hazards like erosion, landslide. Biogas as an alternative source of cooking energy, and changes in crops and their varieties are the common adaptation measures that local people start practicing in both CFUGs in Nepal.

Keywords: climate change, community forestry, global warming, adaptation in Nepal

Procedia PDF Downloads 254

Authors: Hefin Gwilym

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This paper will explore the political biographies of social workers in a neoliberal era. The findings are based on a research project for a successfully completed professional doctorate in social work. The methodology deployed for the research is a combination of constructivist grounded theory and biographical inquiry. The paper will present findings from 14 biographical interviews and will focus on one case study of a participant whose life story is richly informed by political social work. The 14 participants reflect different genders, ethnic identities, cultural and linguistic identities, age and length of social work careers. The participants also reflect different forms of political engagement, such as, as political activists and members of political parties, including parliamentarians. The findings demonstrate how deeply ingrained the social work identity is amongst the participants and how their political identity has remained strongly social democratic in nature despite the many changes in the social work profession since the rise of neoliberalism as a thought collective and policy package. The individual case study will explore the early roots of political identity in the childhood and nurturing years and the interface with subsequent social work and political careers. It will also explore the evolution of the participant’s political identity in the social work career. The case study will also present findings on how the participant has contributed to the political field with policy involvement and initiatives. The presentation will conclude with a discussion on how this particular group of social workers can best contribute to the future direction of the social work profession.

Keywords: political social work, political biographies, neoliberal, grounded theory

Procedia PDF Downloads 281

Authors: Shereif. H. Mahmoud

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Egypt has limited water resources, and it will be under water stress by the year 2030. Therefore, Egypt should consider natural and non-conventional water resources to overcome such a problem. Rain harvesting is one solution. This Paper presents a geographic information system (GIS) methodology - based on decision support system (DSS) that uses remote sensing data, filed survey, and GIS to identify potential RWH areas. The input into the DSS includes a map of rainfall surplus, slope, potential runoff coefficient (PRC), land cover/use, soil texture. In addition, the outputs are map showing potential sites for RWH. Identifying suitable RWH sites implemented in the ArcGIS model environment using the model builder of ArcGIS 10.1. Based on Analytical hierarchy process (AHP) analysis taking into account five layers, the spatial extents of RWH suitability areas identified using Multi-Criteria Evaluation (MCE). The suitability model generated a suitability map for RWH with four suitability classes, i.e. Excellent, Moderate, Poor, and unsuitable. The spatial distribution of the suitability map showed that the excellent suitable areas for RWH concentrated in the northern part of Egypt. According to their averages, 3.24% of the total area have excellent and good suitability for RWH, while 45.04 % and 51.48 % of the total area are moderate and unsuitable suitability, respectively. The majority of the areas with excellent suitability have slopes between 2 and 8% and with an intensively cultivated area. The major soil type in the excellent suitable area is loam and the rainfall range from 100 up to 200 mm. Validation of the used technique depends on comparing existing RWH structures locations with the generated suitability map using proximity analysis tool of ArcGIS 10.1. The result shows that most of exiting RWH structures categorized as successful.

Keywords: rainwater harvesting (RWH), geographic information system (GIS), analytical hierarchy process (AHP), multi-criteria evaluation (MCE), decision support system (DSS)

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Authors: Reihaneh Rafiemanzelat

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One of the most recent fields of investigation in urban issues focuses on the walkability in urban spaces. The paper aims to establish the theoretical relationship between the people's link with definite urban public spaces and the social identity processes derived from the relation with these places. The theoretical aspects which are examined for this purpose are: the concept of walkability and its developments and the social identity theories derived from walkable spaces. In fact, the paper presents the main results obtained from an empirical investigation which concern to the genesis of urban social identity in particular street as one of the main elements of public spaces in cities. İsmet İnönü Blvd which known as Salamis Street in Famagusta, North Cyprus is one of the main street in city whit high level of physical and social activities all the time. The urban social identity of users was analyzed, focusing on three main factors: walkability of space, social identification, and image of the space. These three factors were analyzed in relation to a series of items in the initial questionnaire, evaluation of existing natural resources, and environmental attitudes.

Keywords: walkability, urban public space, pedestrian, social activity, social identity

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Authors: Rabail Khalid

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Social media has changed the business communication strategies in the corporate world. Firms are using social media to reach their maximum stakeholders in minimum time at different social media forums. The current study examines the role of firm-created social media communication on consumer brand perceptions and their loyalty to brand. An online survey is conducted through social media forums including Facebook and Twitter to collect data regarding social media communication of a well-reputed clothing company’s brand in Pakistan. A link is sent to 900 customers of that company. Out of 900 questionnaires, 534 were received. So, the response rate is 59.33%. During data screening and entry, 13 questionnaires are rejected due to incomplete answer. Therefore, 521 questionnaires are completed in all respect and seem to be helpful for the study. So, the positive response rate is 57.89%. The empirical results report positive and significant influence of company-generated social media communication on brand trust, brand equity, and brand loyalty. The findings of this study provide important information to the marketing professionals and brand managers to understand consumer behavior through social media communication.

Keywords: firm-created social media communication, brand trust, brand equity, consumer behavior, brand loyalty

Procedia PDF Downloads 386

Authors: Cris Bravo

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Social entrepreneurship is a new and exciting topic that holds a great promise in helping alleviate the social problems of the world. As a new subject, the meaning of the term is too broad and this is counterproductive in trying to build understanding around the concept. The purpose of this study is to identify and compare the elements of social entrepreneurship as defined by seven international organizations leading social entrepreneurship projects: Ashoka Foundation, Skoll Foundation, Schwab Foundation and Yunus Center; as well as from three other institutions fostering social entrepreneurship: Global Social Benefit Institute, BRAC University, and Socialab. The study used document analysis from Skoll Foundation, Schwab Foundation, Yunus Center and Ashoka Foundation; and open ended interview to experts from the Global Social Benefit Institute at Santa Clara University in United States, BRAC University from Bangladesh, and Socialab from Argentina. The study identified three clearly differentiated schools of thought, based on their views on revenue, scalability, replicability and geographic location. While this study is by no means exhaustive, it provides an indication of the patterns of ideas fostered by important players in the field. By clearly identifying the similarities and differences in the concept of social entrepreneurship, research and practitioners are better equipped to build on the subject, and to promote more adequate and accurate social policies to foster the development of social entrepreneurship.

Keywords: replicability, revenue, scalability, schools of thought, social entrepreneurship

Procedia PDF Downloads 381

Authors: Roghayeh Karami, Ahmad Gharaei

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Backgrounds and objectives: This study was undertaken at four different sites (north polluted, south polluted, south healthy and north healthy) in Tehran, in order to examine whether there was a relationship between publicly available air quality data and the public’s perception of air quality and to suggest some guidelines for reducing air pollution. Materials and Methods: A total of 200 people were accidentally filled out the research questionnaires at mentioned sites and air quality data were obtained simultaneously from the Air Quality Control Department. Data was analyzed in Excel and SPSS software. Results: Clean air and secure job were of great importance to people comparing to other pleasant aspect of life. Also air pollution and fear of dangerous diseases were the most important of people concerns. The Indies bored /news paper services on air quality were little used by the public as a means of obtaining information on air pollution. Using public transportation and avoid unessential journeys are the most important ways for reducing air pollution. Conclusion: The results reveal that the public’s perception of air quality is not a reliable indicator of the actual levels of air pollution. Current earths to down actions are not effective and enough in reducing air pollution, therefore it seems participatory management and public participation is suitable guideline.

Keywords: air pollution, quality of life, opinion poll, public participation

Procedia PDF Downloads 487

Authors: Keshab Shrestha, Hung-Suck Park

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Emergy accounting of the systems networks is guided by a definite rule called ‘emergy algebra’. The systems networks consist of two types of branching. These are the co-product branching and split branching. The emergy accounting procedure for both the branching types is different. According to the emergy algebra, each branch in the co-product branching has different transformity values whereas the split branching has the same transformity value. After the transformity value of each branch is determined, the emergy is calculated by multiplying this with the energy. The aim of this research is to solve the problems in determining the transformity values in the co-product branching through the introduction of a new methodology, the modified physical quantity method. Initially, the existing methodologies for emergy accounting in the co-product branching is discussed and later, the modified physical quantity method is introduced with a case study of the Eucalyptus pulp production. The existing emergy accounting methodologies in the co-product branching has wrong interpretations with incorrect emergy calculations. The modified physical quantity method solves those problems of emergy accounting in the co-product branching systems. The transformity value calculated for each branch is different and also applicable in the emergy calculations. The methodology also strictly follows the emergy algebra rules. This new modified physical quantity methodology is a valid approach in emergy accounting particularly in the multi-production systems networks.

Keywords: co-product branching, emergy accounting, emergy algebra, modified physical quantity method, transformity value

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Authors: Vishnu Pratap Singh Kirar

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The main aim of the communication system is to achieve maximum performance. In cognitive radio, any user or transceiver have the ability to sense best suitable channel, while the channel is not in use. It means an unlicensed user can share the spectrum of licensed user without any interference. Though the spectrum sensing consumes a large amount of energy and it can reduce by applying various artificial intelligent methods for determining proper spectrum holes. It also increases the efficiency of Cognitive Radio Network (CRN). In this survey paper, we discuss the use of different learning models and implementation of Artificial Neural Network (ANN) to increase the learning and decision-making capacity of CRN without affecting bandwidth, cost and signal rate.

Keywords: artificial neural network, cognitive radio, cognitive radio networks, back propagation, spectrum sensing

Procedia PDF Downloads 609

Authors: Siti Dewi Aisyah

Abstract:

Islamic Muslim fashion has become a trend in Indonesia. It is said that social media has a huge impact on its development. Indonesia is ranked among the most users of social media. That is why people who wear hijab also use social media for different purposes, one of this is to introduce hijab fashion. Consequently, they are becoming famous in social media. Social media has become a tool for communicating their beliefs as a Muslim as well as personal branding as a good hijabi yet with a fashionable style. This research will examine the social media such as Blog and Instagram, how it triggers the consumer culture to hijabi, what is the actual meaning behind of their feed posts in their social media, how they produce good photograph in their social media and for what reason they use social media. This research had been conducted through in-depth interviews with several bloggers who created Hijabers Community who have made a new trend in Muslim fashion and also Instagrammers who made their feeds as a style inspiration. The methodology used for this research is by analyzing Blog and Instagram through visual analysis that also examines the semiotic meaning behind the photographs that are posted by the people on the social media especially about the Islamic Modest Fashion trend. The theoretical framework for this research is about studying social media that is examined through visual analysis. The Muslim fashion trend was lead by several bloggers and continued to Instagram which then created a consumption pattern. From colourful colors, pastel colors, monochrome colors to neutral coffee tone colors, it was influenced by the Muslim fashion designers that also become digital influencers in social media. It was concluded that social media had been a powerful promotional and effective tool to change the trend in Indonesian Muslim Fashion trend.

Keywords: blog, instagram, consumer culture, muslim fashion, social media, visual analysis

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Authors: Deyu Zhou, Xiao Xue, Lizhen Cui

Abstract:

With the increasing collaboration among various services and the growing complexity of user demands, there are more and more factors affecting the stable development of the cloud manufacturing service economic system (CMSE). This poses new challenges to the evolution analysis of the CMSE. Many researchers have modeled and analyzed the evolution process of CMSE from the perspectives of individual learning and internal factors influencing the system, but without considering other important characteristics of the system's individuals (such as heterogeneity, bounded rationality, etc.) and the impact of external environmental factors. Therefore, this paper proposes an integrated artificial social model for the cloud manufacturing service economic system, which considers both the characteristics of the system's individuals and the internal and external influencing factors of the system. The model consists of three parts: the Agent model, environment model, and rules model (Agent-Environment-Rules, AER): (1) the Agent model considers important features of the individuals, such as heterogeneity and bounded rationality, based on the adaptive behavior mechanisms of perception, action, and decision-making; (2) the environment model describes the activity space of the individuals (real or virtual environment); (3) the rules model, as the driving force of system evolution, describes the mechanism of the entire system's operation and evolution. Finally, this paper verifies the effectiveness of the AER model through computational and experimental results.

Keywords: cloud manufacturing service economic system (CMSE), AER model, artificial social modeling, integrated framework, computing experiment, agent-based modeling, social networks

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Authors: Pengfei Meng, Shuangcheng Jia, Qian Li

Abstract:

We proposed a real-time high-precision semantic segmentation network based on a multi-resolution feature fusion module, the auxiliary feature extracting module, upsampling module, and atrous spatial pyramid pooling (ASPP) module. We designed a feature fusion structure, which is integrated with sufficient features of different resolutions. We also studied the effect of side-branch structure on the network and made discoveries. Based on the discoveries about the side-branch of the network structure, we used a side-branch auxiliary feature extraction layer in the network to improve the effectiveness of the network. We also designed upsampling module, which has better results than the original upsampling module. In addition, we also re-considered the locations and number of atrous spatial pyramid pooling (ASPP) modules and modified the network structure according to the experimental results to further improve the effectiveness of the network. The network presented in this paper takes the backbone network of Bisenetv2 as a basic network, based on which we constructed a network structure on which we made improvements. We named this network deep multiple-resolution bilateral networks for real-time, referred to as DMBR-Net. After experimental testing, our proposed DMBR-Net network achieved 81.2% mIoU at 119FPS on the Cityscapes validation dataset, 80.7% mIoU at 109FPS on the CamVid test dataset, 29.9% mIoU at 78FPS on the COCOStuff test dataset. Compared with all lightweight real-time semantic segmentation networks, our network achieves the highest accuracy at an appropriate speed.

Keywords: multi-resolution feature fusion, atrous convolutional, bilateral networks, pyramid pooling

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Authors: Hsuan Yu Lai, Hsuan Hsuan Chang

Abstract:

The consumer decision process steps through problems by weighing evidence, examining alternatives, and choosing a decision path. Currently, the COVID 19 made the tourism industry encounter a huge challenge and suffer the biggest amount of economic loss. It would be very important to reexamine the decision-making process model, especially after the pandemic, and consider the differences among different generations. The tourism industry has been significantly impacted by the global outbreak of COVID-19, but as the pandemic subsides, the sector is recovering. This study addresses the scarcity of research on travel decision-making patterns among generations in Taiwan. Specifically targeting individuals who frequently traveled abroad before the pandemic, the study explores differences in decision-making at different stages post-outbreak. So this study investigates differences in travel decision-making among individuals from different generations during/after the COVID-19 pandemic and examines the moderating effects of social media usage and individuals' perception of health risks. The study hypotheses are “there are significant differences in the decision-making process including travel motivation, information searching preferences, and criteria for decision-making” and that social-media usage and health-risk perception would moderate the results of the previous study hypothesis. The X, Y, and Z generations are defined and categorized based on a literature review. The survey collected data including their social-economic background, travel behaviors, motivations, considerations for destinations, travel information searching preferences, and decision-making criteria before/after the pandemic based on the reviews of previous studies. Data from 656 online questionnaires were collected between January to May 2023 and from Taiwanese travel consumers who used to travel at least one time abroad before Covid-19. SPSS is used to analyze the data with One-Way ANOVA and Two-Way ANOVA. The analysis includes demand perception, information gathering, alternative comparison, purchase behavior, and post-travel experience sharing. Social media influence and perception of health risks are examined as moderating factors. The findings show that before the pandemic, the Y Generation preferred natural environments, while the X Generation favored historical and cultural sites compared to the Z Generation. However, after the outbreak, the Z Generation displayed a significant preference for entertainment activities. This study contributes to understanding changes in travel decision-making patterns following COVID-19 and the influence of social media and health risks. The findings have practical implications for the tourism industry.

Keywords: consumer decision-making, generation study, health risk perception, post-pandemic era, social media

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Authors: Kong Ngai Pei

Abstract:

The argument scheme approach to argumentation has two components. One is to identify the recurrent patterns of inferences used in everyday discourse. The second is to devise critical questions to evaluate the inferences in these patterns. Although this approach is intuitive and contains many insightful ideas, it has been noted to be not free of problems. One is that due to its disavowing the probability calculus, it cannot give the exact strength of an inference. In order to tackle this problem, thereby paving the way to a more complete normative account of argument strength, it has been proposed, the most promising way is to combine the scheme-based approach with Bayesian networks (BNs). This paper pursues this line of thought, attempting to combine three common schemes, Appeal to Ignorance, Composition, and Division, with BNs. In the first part, it is argued that most (if not all) formulations of the critical questions corresponding to these schemes in the current argumentation literature are incomplete and not very informative. To remedy these flaws, more thorough and precise formulations of these questions are provided. In the second part, how to use graphical idioms (e.g. measurement and synthesis idioms) to translate the schemes as well as their corresponding critical questions to graphical structure of BNs, and how to define probability tables of the nodes using functions of various sorts are shown. In the final part, it is argued that many misuses of these schemes, traditionally called fallacies with the same names as the schemes, can indeed be adequately accounted for by the BN models proposed in this paper.

Keywords: appeal to ignorance, argument schemes, Bayesian networks, composition, division

Procedia PDF Downloads 286