Search results for: RBF neural network

Authors: R. Güçlü, E. Küçüksakarya

Abstract:

Word association (WA) gives the broadest information on how knowledge is structured in the human mind. Cognitive linguistics, psycholinguistics, and applied linguistics are the disciplines that consider WA tests as substantial in gaining insights into the very nature of the human cognitive system and semantic knowledge. In this study, Berlin and Kay’s basic 11 color terms (1969) are presented as the stimuli words to a total number of 300 Turkish university students. The responses are analyzed according to Fitzpatrick’s model (2007), including four categories, namely meaning-based responses, position-based responses, form-based responses, and erratic responses. In line with the findings, the responses to free association tests are expected to give much information about Turkish university students’ psychological structuring of vocabulary, especially morpho-syntactic and semantic relationships among words. To conclude, theoretical and practical implications are discussed to make an in-depth evaluation of how associations of basic color terms are represented in the mental lexicon of Turkish university students.

Keywords: color term, gender, mental lexicon, word association task

Procedia PDF Downloads 90

Authors: K. Indra Gandhi

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Wireless Sensor Networks (WSNs) have always been characterized for application-specific sensing, relaying and collection of information for further analysis. However, software development was not considered as a separate entity in this process of data collection which has posed severe limitations on the software development for WSN. Software development for WSN is a complex process since the components involved are data-driven, network-driven and application-driven in nature. This implies that there is a tremendous need for the separation of concern from the software development perspective. A layered approach for developing data acquisition design based on Model Driven Development (MDD) has been proposed as the sensed data collection process itself varies depending upon the application taken into consideration. This work focuses on the layered view of the data acquisition process so as to ease the software point of development. A metamodel has been proposed that enables reusability and realization of the software development as an adaptable component for WSN systems. Further, observing users perception indicates that proposed model helps in improving the programmer's productivity by realizing the collaborative system involved.

Keywords: data acquisition, model-driven development, separation of concern, wireless sensor networks

Procedia PDF Downloads 405

Authors: Ali Al-Dahoud, Mohamed Fezari, Thamer Al-Rawashdeh, Ismail Jannoud

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Monitoring and detecting faults on a set of Solar panels, using a wireless sensor network (WNS) is our contribution in this paper, This work is part of the project we are working on at Al-Zaytoonah University. The research problem has been exposed by engineers and technicians or operators dealing with PV panels maintenance, in order to monitor and detect faults within solar panels which affect considerably the energy produced by the solar panels. The proposed solution is based on installing WSN nodes with appropriate sensors for more often occurred faults on the 45 solar panels installed on the roof of IT faculty. A simulation has been done on nodes distribution and a study for the design of a node with appropriate sensors taking into account the priorities of the processing faults. Finally, a graphic user interface is designed and adapted to telemonitoring panels using WSN. The primary tests of hardware implementation gave interesting results, the sensors calibration and interference transmission problem have been solved. A friendly GUI using high level language Visial Basic was developed to carry out the monitoring process and to save data on Exel File.

Keywords: Arduino Mega microcnotroller, solar panels, fault-detection, simulation, node design

Procedia PDF Downloads 438

Authors: Yasamin Rahimi, Ali Kamandi, Abbas Hoseini, Hesam Haddad

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Online/offline chat is a convenient approach in the electronic markets of second-hand products in which potential customers would like to have more information about the products to fill the information gap between buyers and sellers. Online peer in peer market is trying to create artificial intelligence-based systems that help customers ask more informative questions in an easier way. In this article, we introduce a method for the question/answer system that we have developed for the top-ranked electronic market in Iran called Divar. When it comes to secondhand products, incomplete product information in a purchase will result in loss to the buyer. One way to balance buyer and seller information of a product is to help the buyer ask more informative questions when purchasing. Also, the short time to start and achieve the desired result of the conversation was one of our main goals, which was achieved according to A/B tests results. In this paper, we propose and evaluate a method for suggesting questions and answers in the messaging platform of the e-commerce website Divar. Creating such systems is to help users gather knowledge about the product easier and faster, All from the Divar database. We collected a dataset of around 2 million messages in Persian colloquial language, and for each category of product, we gathered 500K messages, of which only 2K were Tagged, and semi-supervised methods were used. In order to publish the proposed model to production, it is required to be fast enough to process 10 million messages daily on CPU processors. In order to reach that speed, in many subtasks, faster and simplistic models are preferred over deep neural models. The proposed method, which requires only a small amount of labeled data, is currently used in Divar production on CPU processors, and 15% of buyers and seller’s messages in conversations is directly chosen from our model output, and more than 27% of buyers have used this model suggestions in at least one daily conversation.

Keywords: smart reply, spell checker, information retrieval, intent detection, question answering

Procedia PDF Downloads 153

Authors: Mane Darbinyan, Lusine Hayrapetyan, Elen Matevosyan

Abstract:

Artificial Intelligence in Education (AIED) has been created to help students get ready for the workforce, and over the past 25 years, it has grown significantly, offering a variety of technologies to support academic, institutional, and administrative services. However, this is still challenging, especially considering the labor market's rapid change. While choosing a career, people face various obstacles because they do not take into consideration their own preferences, which might lead to many other problems like shifting jobs, work stress, occupational infirmity, reduced productivity, and manual error. Besides preferences, people should properly evaluate their technical and non-technical skills, as well as their personalities. Professional counseling has become a difficult undertaking for counselors due to the wide range of career choices brought on by changing technological trends. It is necessary to close this gap by utilizing technology that makes sophisticated predictions about a person's career goals based on their personality. Hence, there is a need to create an automated model that would help in decision-making based on user inputs. Improving career guidance can be achieved by embedding machine learning into the career consulting ecosystem. There are various systems of career guidance that work based on the same logic, such as the classification of applicants, matching applications with appropriate departments or jobs, making predictions, and providing suitable recommendations. Methodologies like KNN, Neural Networks, K-means clustering, D-Tree, and many other advanced algorithms are applied in the fields of data and compute some data, which is helpful to predict the right careers. Besides helping users with their career choice, these systems provide numerous opportunities which are very useful while making this hard decision. They help the candidate to recognize where he/she specifically lacks sufficient skills so that the candidate can improve those skills. They are also capable to offer an e-learning platform, taking into account the user's lack of knowledge. Furthermore, users can be provided with details on a particular job, such as the abilities required to excel in that industry.

Keywords: career guidance system, machine learning, career prediction, predictive decision, data mining, technical and non-technical skills

Procedia PDF Downloads 48

Authors: João Coutinho-Rodrigues, Nuno Sousa, Luís Alçada-Almeida

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Transportation infrastructure systems are fundamental in modern society and economy. However, they need modernizing, maintaining, and reinforcing interventions which require large investments. In many countries, accumulated intervention delays arise from aging and intense use, being magnified by financial constraints of the past. The decision problem of managing the renewal of large backlogs is common to several types of important transportation infrastructures (e.g., railways, roads). This problem requires considering financial aspects as well as operational constraints under a multidimensional framework. The present research introduces a linear programming multiobjective model for managing railway infrastructure asset renewal. The model aims at minimizing three objectives: (i) yearly investment peak, by evenly spreading investment throughout multiple years; (ii) total cost, which includes extra maintenance costs incurred from renewal backlogs; (iii) priority delays related to work start postponements on the higher priority railway sections. Operational constraints ensure that passenger and freight services are not excessively delayed from having railway line sections under intervention. Achieving a balanced annual investment plan, without compromising the total financial effort or excessively postponing the execution of the priority works, was the motivation for pursuing the research which is now presented. The methodology, inspired by a real case study and tested with real data, reflects aspects of the practice of an infrastructure management company and is generalizable to different types of infrastructure (e.g., railways, highways). It was conceived for treating renewal interventions in infrastructure assets, which is a railway network may be rails, ballasts, sleepers, etc.; while a section is under intervention, trains must run at reduced speed, causing delays in services. The model cannot, therefore, allow for an accumulation of works on the same line, which may cause excessively large delays. Similarly, the lines do not all have the same socio-economic importance or service intensity, making it is necessary to prioritize the sections to be renewed. The model takes these issues into account, and its output is an optimized works schedule for the renewal project translatable in Gantt charts The infrastructure management company provided all the data for the first test case study and validated the parameterization. This case consists of several sections to be renewed, over 5 years and belonging to 17 lines. A large instance was also generated, reflecting a problem of a size similar to the USA railway network (considered the largest one in the world), so it is not expected that considerably larger problems appear in real life; an average of 25 years backlog and ten years of project horizon was considered. Despite the very large increase in the number of decision variables (200 times as large), the computational time cost did not increase very significantly. It is thus expectable that just about any real-life problem can be treated in a modern computer, regardless of size. The trade-off analysis shows that if the decision maker allows some increase in max yearly investment (i.e., degradation of objective ii), solutions improve considerably in the remaining two objectives.

Keywords: transport infrastructure, asset renewal, railway maintenance, multiobjective modeling

Procedia PDF Downloads 119

Authors: A. Y. Mukhtar, J. B. Munyakazi, R. Ouifki

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Over the past few decades, the unprecedented increase in mobility has raised considerable concern about the relationship between mobility and vector-borne diseases and malaria in particular. Thus, one can claim that human mobility is one of the contributing factors to the resurgence of malaria. To assess human mobility on malaria burden among hosts, we formulate a movement-based model on a network of patches. We then extend human multi-group SEIAR deterministic epidemic models into a system of stochastic differential equations (SDEs). Our quantitative stochastic model which is expressed in terms of average rates of movement between compartments is fitted to time-series data (weekly malaria data of 2011 for each patch) using the maximum likelihood approach. Using the metapopulation (multi-group) model, we compute and analyze the basic reproduction number. The result shows that human movement is sufficient to preserve malaria disease firmness in the patches with the low transmission. With these results, we concluded that the sensitivity of malaria to the human mobility is turning to be greatly important over the implications of future malaria control in South Sudan.

Keywords: basic reproduction number, malaria, maximum likelihood, movement, stochastic model

Procedia PDF Downloads 106

Authors: Mohamad Ibrahim Al Ladan

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Social networks, such as Facebook, Myspace, LinkedIn, Google+, and Twitter have experienced exponential growth and a remarkable adoption rate in recent years. They provide attractive means of online social interactions and communications with family, friends, and colleagues from around the corner or across the globe, and they have become an important part of daily digital interactions for more than one and a half billion users around the world. The various personal information sharing practices that social network providers encourage have led to their success as innovative social interaction platforms. However, these practices have resulted in ample concerns with respect to privacy and security from different stakeholders. Addressing these privacy and security concerns in social networks is a must for these networks to be sustainable. Existing security and privacy tools may not be enough to address existing concerns. Some guidelines should be followed to protect users from the existing risks. In this paper, we have investigated and discussed the various privacy and security issues and concerns pertaining to social networks. Moreover, we have classified these privacy and security issues and presented a thorough discussion of the implications of these issues and concerns on the future of the social networks. In addition, we have presented a set of guidelines as precaution measures that users can consider to address these issues and concerns.

Keywords: social networks privacy issues, social networks security issues, social networks privacy precautions measures, social networks security precautions measures

Procedia PDF Downloads 269

Authors: Nafiah Solikhah Thoha

Abstract:

One area that has spatial character as Heritage area is Kauman Villages. Kauman village in The City of Surakarta, Central Java, Indonesia was formed in 1757 by Paku Buwono III as the King of Kasunanan kingdom (Mataram Kingdom) for Kasunanan kingdom courtiers and scholars of Madrasa. Spatial character of Kauman village influenced by Islamic planning and socio-cultural rules of Kasunanan Kingdom. As traditional settlements influenced by Islamic planning, the Grand Mosque is a binding part of the whole area. Circulation pattern forming network (labyrinth) with narrow streets that ended at the Grand Mosque. The outdoor space can be used for circulation. Social activity is dominated by step movement from one place to a different place. Stalemate (the fina/cul de sac) generally only passable on foot, bicycles, and motorcycles. While the pass (main and branch) can be traversed by motor, vehicles. Kauman village has an area that can not be used as a public road that penetrates and serves as a liaison between the outside world to the other. Hierarchy of hall in Kauman village shows that the existence of a space is getting into more important. Firstly, woman in Kauman make the handmade batik for themself. In 2005 many people improving batik tradisional into commercial, and developed program named "Batik Tourism village of Kauman". That program affects the spatial transformations. This study aimed to explore the influence of tourism program towards spatial transformations. The factors that studied are the organization of space, circulation patterns, hierarchical space, and orientation through the descriptive-evaluation approach methods. Based on the study, tourism activity engenders transformations on the spatial scale (macro), residential block (mezo), homes (micro). First, the Grand Mosque and madrasa (religious school) as a binding zoning; tangle of roads as forming the structure of the area developed as a liaison with outside Kauman; organization of space in the residential of batik entrepreneurs firstly just a residential, then develop into residential, factory of batik including showroom. Second, the circulation pattern forming network (labyrinth) and ends at the Grand Mosque. Third, the hierarchy in the form of public space (the shari), semi-public, and private (the fina/culdesac) is no longer to provide protection to women, only as hierarchy of circulation path. Fourth, cluster building orientation does not follow the kiblat direction or axis oriented to cosmos, but influence by the new function as the showroom. It was need the direction of the main road. Kauman grow as an appropriate area for the community. During its development, the settlement function changes according to community activities, especially economic activities. The new function areas as tourism area affect spatial pattern of Kauman village. Spatial existence and activity as a local wisdom that has been done for generations have meaning of holistic, encompassing socio-cultural sustainability, economics, and the heritage area. By reviewing the local wisdom and the way of life of that society, we can learn how to apply the culture as education for sustainable of heritage area.

Keywords: impact of tourism, Kauman village, spatial transformation, sustainable of heritage area

Procedia PDF Downloads 401

Authors: Mane Darbinyan, Lusine Hayrapetyan, Elen Matevosyan

Abstract:

Artificial Intelligence in Education (AIED) has been created to help students get ready for the workforce, and over the past 25 years, it has grown significantly, offering a variety of technologies to support academic, institutional, and administrative services. However, this is still challenging, especially considering the labor market's rapid change. While choosing a career, people face various obstacles because they do not take into consideration their own preferences, which might lead to many other problems like shifting jobs, work stress, occupational infirmity, reduced productivity, and manual error. Besides preferences, people should evaluate properly their technical and non-technical skills, as well as their personalities. Professional counseling has become a difficult undertaking for counselors due to the wide range of career choices brought on by changing technological trends. It is necessary to close this gap by utilizing technology that makes sophisticated predictions about a person's career goals based on their personality. Hence, there is a need to create an automated model that would help in decision-making based on user inputs. Improving career guidance can be achieved by embedding machine learning into the career consulting ecosystem. There are various systems of career guidance that work based on the same logic, such as the classification of applicants, matching applications with appropriate departments or jobs, making predictions, and providing suitable recommendations. Methodologies like KNN, neural networks, K-means clustering, D-Tree, and many other advanced algorithms are applied in the fields of data and compute some data, which is helpful to predict the right careers. Besides helping users with their career choice, these systems provide numerous opportunities which are very useful while making this hard decision. They help the candidate to recognize where he/she specifically lacks sufficient skills so that the candidate can improve those skills. They are also capable of offering an e-learning platform, taking into account the user's lack of knowledge. Furthermore, users can be provided with details on a particular job, such as the abilities required to excel in that industry.

Keywords: career guidance system, machine learning, career prediction, predictive decision, data mining, technical and non-technical skills

Procedia PDF Downloads 40

Authors: Saeed Sayyad Hagh Shomar

Abstract:

Traffic congestion pricing as one of the demand management strategies constrains expenditure to network users so that it helps reduction in traffic congestion and environment pollution like air pollution. Despite the development of congestion pricing schemes for traffic in our country, the matters of traditional toll collection, drivers’ waste of time and delay in traffic are still widespread. Electronic toll collection as a part of the intelligent transportation system provides the possibility of collecting tolls without car-stop and traffic disruption. Unlike the satisfying outcomes of using intelligent systems in congestion pricing schemes, implementation costs and technological problems are the barriers in these schemes. In this research first, a variety of electronic pay toll systems and their components are introduced then their functional usage is discussed. In the following, by analyzing and comparing the barriers, limitations and advantages, the selection criteria of intelligent systems are described and the results show that the choice of the best technology depends on the various parameters which, by examining them, it is concluded that in a long-term run and by providing the necessary conditions, DSRC technology as the main system in the schemes and ANPR as a major backup system of the main one can be employed.

Keywords: congestion pricing, electronic toll collection, intelligent systems, technology, traffic

Procedia PDF Downloads 571

Authors: Victor Pesco Kassa

Abstract:

This research deals with the assessment of the contribution of GIS Technology in NRW. This research was conducted at Dar, Kawe Mzimuni Street. The data collection was obtained from existing source which is DAWASA HQ. The interpretation of the data was processed by using ArcGIS software. The data collected from the existing source reveals a good coverage of DAWASA’s water network at Mzimuni Street. Most of residents are connected to the DAWASA’s customer service. Also the collected data revealed that by using GIS DAWASA’s customer Geodatabase has been improved. Through GIS we can prepare customer location map purposely for site surveying also this map will be able to show different type of customer that are connected to DAWASA’s water service. This is a perfect contribution of the GIS Technology to address and manage the problem of NRW in DAWASA. Finally, the study recommends that the same study should be conducted in other DAWASA’s zones such as Temeke, Boko and Bagamoyo not only at Kawe Mzimuni Street. Through this study it is observed that ArcGIS software can offer powerful tools for managing and processing information geographically and in water and sanitation authorities such as DAWASA.

Keywords: DAWASA, NRW, Esri, EURA, ArcGIS

Procedia PDF Downloads 48

Authors: Ramón Cruzat, Sergio F. Ochoa, Ignacio Casas, Luis A. Guerrero, José Bravo

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Patients under health treatments that involve long stays at a hospital or health centre (e.g. cancer, organ transplants and severe burns), tend to get bored or depressed because of the lack of social interaction with family and friends. Such a situation also affects the evolution and effectiveness of their treatments. In many cases, the solution to this problem involves extra challenges, since many patients need to rest quietly (or remain in bed) to their being contagious. Considering the weak health condition in which usually are these kinds, keeping them motivated and quiet represents an important challenge for nurses and caregivers. This article presents a mobile ubiquitous game called MagicRace, which allows hospitalized kinds to interact socially with one another without putting to risk their sensitive health conditions. The game does not require a communication infrastructure at the hospital, but instead, it uses a mobile ad hoc network composed of the handheld devices used by the kids to play. The usability and performance of this application was tested in two different sessions. The preliminary results show that users experienced positive feelings from this experience.

Keywords: ubiquitous game, children's emotional support, social isolation, mobile collaborative interactions

Procedia PDF Downloads 398

Authors: Yongmei Li, Chang-Gun Park

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China-Japan-South Korea (CJK) trilateral cooperation has experienced historical challenges in recent years, which negatively influenced the development of their relationship. Results of the interviews with three citizens on trilateral relations illustrate that most people are concerned with the historical conflicts among CJK. This paper specifically focuses on managing historical issues, including comfort women issues, territorial disputes, and divergence in historical education. Accordingly, the effectiveness of management of tensions productively provides a method for detecting historical concerns, managing issues, and connecting the three countries and citizens through advocating for fair media reporting, effective network institutionalization, and active local government cooperation. Furthermore, this paper contributes to providing government solutions for reinforcing the CJK partnership. It specially involves history education, East Asian identity and mutual trust establishment, East Asia intra-regional exchange programs, and reorganization of the role of the Trilateral Cooperation Secretariat (TCS).

Keywords: China-Japan-South Korea, trilateral cooperation, government solutions, effectiveness of management, historical conflicts

Procedia PDF Downloads 75

Authors: Linda Torresin

Abstract:

This paper is devoted to the Russian as a Foreign Language (RFL) textbook, which is understood as a fundamental element of the RFL system. The aim of the study is to explore the role of the RFL textbook in modern RFL teaching theories and practices. It is suggested that the RFL textbook is not a secondary factor but contributes to the advancement and rewriting of both RFL theories and practices. This study applies to the RFL textbook theory's recent pedagogical developments in education. Therefore, the RFL system is conceived as a complex adaptive system whose elements (teacher, textbook, students, etc.) interact in a dynamic network of interconnections. In particular, the author shows that the textbook plays a central role in the RFL system since it may change and even renew RFL teaching from both theoretical and practical perspectives. On the one hand, in fact, the use of an RFL textbook may impact teaching theories: that is, the textbook may either consolidate preexisting theories or launch new approaches. On the other hand, the RFL textbook may also influence teaching practices by reinforcing the preexisting ones or encouraging teachers to try new strategies instead. All this allows the RFL textbook, within the RFL complex adaptive system, to exert an influence on the specific teaching contexts in which Russian is taught, interacting with the other elements of the system itself. Through its findings, this paper contributes to the advancement of research on RFL textbook theory.

Keywords: adaptive system, foreign language textbook, teaching Russian as a foreign language, textbook of Russian as a foreign language

Procedia PDF Downloads 60

Authors: Maria Nabakooza

Abstract:

Efficient agricultural production is very significant in attaining food sufficiency and security in the world. Many methods are employed by the farmers while attending to their gardens, from manual to mechanized, with Farmers range from subsistence to commercial depending on the motive. This creates a lacuna in the modes of operation in this field as different farmers will take different approaches. This has led to many e-Learning courses being introduced to address this gap. Many e-learning systems use advanced network technologies like Web services, grid computing to promote learning at any time and any place. Many of the existing systems have not inculcated the applicability of the modules in them, the tools to be used and further access whether they are the right tools for the right job. A thorough investigation into the applicability of adaptive eLearning in the agricultural sector has not been taken into account; enabling the assumption that eLearning is the right tool for boosting productivity in this sector. This study comes in to provide an insight and thorough analysis as to whether adaptive eLearning is the right tool for boosting agricultural productivity. The Simulation will adopt a system dynamics modeling approach as a way of examining causality and effect relationship. This study will provide teachers with an insight into which tools they should adopt in designing, and provide students the opportunities to achieve an orderly learning experience through adaptive navigating e-learning services.

Keywords: agriculture, adaptive, e-learning, technology

Procedia PDF Downloads 222

Authors: Usman Adekunle Ojedokun, Adeyinka Abideen Aderinto

Abstract:

Migration remains an important course of action often resort-to by human and some other classes of animal for survival in the face of life-threatening conditions. However, the activity of certain group of immigrants, who are exploiting the socio-economic and environmental challenges in their home countries to conduct street begging across different countries in Africa, is fast becoming a major cause for concern. This paper examined the migratory trajectory of transnational street beggars in South Western, Nigeria. Strain and Migration Network Theories were adopted for the study. The methods of data collection were survey questionnaire, in-depth interview, and key informant interview. Convenience and purposive sampling techniques were employed for the selection of 395 transnational street beggars and 4 key informants were purposively chosen. Findings revealed that transnational street beggars immigrated into Nigeria all year round and all of them came by road. Also, while some of them entered the country officially, others gained entry illegally. The majority (29.3%) arrived through Sokoto, a border State to some neighbouring countries. This study calls for more security measures at the Nigerian borders as a way of controlling the influx of this category of beggars into the country.

Keywords: transnational street beggars, street begging, migration, Nigeria

Procedia PDF Downloads 221

Authors: J. Andrade-Garda, A. Anguera, J. Ares-Casal, M. Hidalgo-Lorenzo, J.-A. Lara, D. Lizcano, S. Suárez-Garaboa

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In the current constantly changing economic context, collaborative networks allow partners to undertake projects that would not be possible if attempted by them individually. These projects usually involve the performance of a group of tasks (named roles) that have to be distributed among the partners. Thus, an allocation/matching problem arises that will be referred to as Role-Partner Allocation problem. In real life this situation is addressed by negotiation between partners in order to reach ad hoc agreements. Besides taking a long time and being hard work, both historical evidence and economic analysis show that such approach is not recommended. Instead, the allocation process should be automated by means of a centralized matching scheme. However, as a preliminary step to start the search for such a matching mechanism (or even the development of a new one), the problem and its core components must be specified. To this end, this paper establishes (i) the definition of the problem and its constraints, (ii) the key features of the involved elements (i.e., roles and partners); and (iii) how to create preference lists both for roles and partners. Only this way it will be possible to conduct subsequent methodological research on the solution method.     

Keywords: collaborative network, matching, partner, preference list, role

Procedia PDF Downloads 197

Authors: Javier Muro, Anja Linstadter, Florian Manner, Lisa Schwarz, Stephan Wollauer, Paul Magdon, Gohar Ghazaryan, Olena Dubovyk

Abstract:

Monitoring the trade-off between biomass production and biodiversity in grasslands is critical to evaluate the effects of management practices across environmental gradients. New generations of remote sensing sensors and machine learning approaches can model grasslands’ characteristics with varying accuracies. However, studies often fail to cover a sufficiently broad range of environmental conditions, and evidence suggests that prediction models might be case specific. In this study, biomass production and biodiversity indices (species richness and Fishers’ α) are modeled in 150 grassland plots for three sites across Germany. These sites represent a North-South gradient and are characterized by distinct soil types, topographic properties, climatic conditions, and management intensities. Predictors used are derived from Sentinel-1 & 2 and a set of topoedaphic variables. The transferability of the models is tested by training and validating at different sites. The performance of feed-forward deep neural networks (DNN) is compared to a random forest algorithm. While biomass predictions across gradients and sites were acceptable (r2 0.5), predictions of biodiversity indices were poor (r2 0.14). DNN showed higher generalization capacity than random forest when predicting biomass across gradients and sites (relative root mean squared error of 0.5 for DNN vs. 0.85 for random forest). DNN also achieved high performance when using the Sentinel-2 surface reflectance data rather than different combinations of spectral indices, Sentinel-1 data, or topoedaphic variables, simplifying dimensionality. This study demonstrates the necessity of training biomass and biodiversity models using a broad range of environmental conditions and ensuring spatial independence to have realistic and transferable models where plot level information can be upscaled to landscape scale.

Keywords: ecosystem services, grassland management, machine learning, remote sensing

Procedia PDF Downloads 182

Authors: Saba Ebrahimi, Saeed Ahmadian, Hedie Ashrafi

Abstract:

Selecting appropriate patients for surgery is one of the main issues in thoracic surgery (TS). Both short-term and long-term risks and benefits of surgery must be considered in the patient selection criteria. There are some limitations in the existing datasets of TS patients because of missing values of attributes and imbalanced distribution of survival classes. In this study, a novel ensemble architecture of deep learning networks is proposed based on stacking different linear and non-linear layers to deal with imbalance datasets. The categorical and numerical features are split using different layers with ability to shrink the unnecessary features. Then, after extracting the insight from the raw features, a novel biased-kernel layer is applied to reinforce the gradient of the minority class and cause the network to be trained better comparing the current methods. Finally, the performance and advantages of our proposed model over the existing models are examined for predicting patient survival after thoracic surgery using a real-life clinical data for lung cancer patients.

Keywords: deep learning, ensemble models, imbalanced classification, lung cancer, TS patient selection

Procedia PDF Downloads 110

Authors: Jun Zhou, Xingping Wang, Paul Milbourne

Abstract:

Evidences in the world shows that the industry and population have being greatly concentrated in metropolitan regions which is getting to be the most important area for the economic power and people living standard in the future. In the meanwhile, the relevant innovation theories of Agglomeration, New Industrial Geography and Modern Evolutionary innovation prove that the reason why the agglomeration in world-class city and metropolitan areas and also verify innovation is the key point for the development of metropolis. The primary purpose of this paper is to analyze the geographical spatial characteristics of innovative subjects which contain firm, university, research institution, government and intermediary organ in metropolis throughout the amount data analysis in Yangtze River Metropolis in China. The results show three main conclusions. The first is different subjects in different regions have different spatial characteristics. The second one is different structure and pattern between the subjects also can produce different innovative effect. The last but not the least is agglomeration of innovative subjects’ is not only influenced by the innovative network or local policies but also affected by the localized industry characteristics and culture which are getting to be the most important crucial factors.

Keywords: metropolitan development, innovative subject, spatial, Yangtze River Metropolis, China

Procedia PDF Downloads 345

Authors: Samaneh Nazeri, Bagher Mojazi Amiri, Hamid Farahmand

Abstract:

Production of high quality fish eggs with reasonable hatching rate makes a success in aquaculture industries. It is influenced by the environmental stimulators and inhibitors. Diazinon is a widely-used pesticide in Golestan province (Southern Caspian Sea, North of Iran) which is washed to the aquatic environment (3 mg/L in the river). It is little known about the effect of this pesticide on the embryogenesis of sturgeon fish, the valuable species of the Caspian Sea. Hormonal content of the egg is an important factor to guaranty the successful passes of embryonic stages. In this study, the fate of Persian sturgeon embryo to 24, 48, 72, and 96-hours exposure of diazinon (LC₅₀ dose) was tested. Also, the effect of thyroid hormones (T3 and T4) on these embryos was tested concurrently or separately with diazinon LC ₅₀ dose. Fertilized eggs are exposed to T3 (low dose: 1 ng/ml, high dose: 10 ng/ml), T4 (low dose: 1 ng/ml, high dose: 10 ng/ml). Six eggs were randomly selected from each treatment (with three replicates) in five developmental stages (two cell- division, neural, heart present, heart beaten, and hatched larvae). The possibility of changing T3, T4, and cortisol contents of the embryos were determined in all treated groups and in every mentioned embryonic stage. The hatching rate in treated groups was assayed at the end of the embryogenesis to clarify the effect of thyroid hormones and diazinon. The results indicated significant differences in thyroid hormone contents, but no significant differences were recognized in cortisol levels at various early life stages of embryos. There was also significant difference in thyroid hormones in (T3, T4) + diazinon treated embryos (P˂0.05), while no significant difference between control and treatments in cortisol levels was observed. The highest hatching rate was recorded in HT3 treatment, while the lowest hatching rate was recorded for diazinon LC₅₀ treatment. The result confirmed that Persian sturgeon embryo is less sensitive to diazinon compared to teleost embryos, and thyroid hormones may increase hatching rate even in the presence of diazinon.

Keywords: Persian sturgeon, diazinon, thyroid hormones, cortisol, embryo

Procedia PDF Downloads 274

Authors: Satya S. N. Narayana, P. Parthiban, T. Niranjan, N. Kannan

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Enterprises adopt methodologies to increase their business performance and to stay competent in the volatile global market. Lean manufacturing is one such manufacturing paradigm which focuses on reduction of cost by elimination of wastes or non-value added activities. With increased awareness about social responsibility and the necessary to meet the terms of the environmental policy, green manufacturing is becoming increasingly important for industries. Large plants have more resources, have started implementing lean and green practices and they are getting good results. Small and medium scale enterprises (SMEs) are facing problems in implementing lean and green concept. This paper aims to identify the key issues for implementation of lean and green concept in Indian SMEs. The key factors identified based on literature review and expert opinions are grouped into different levels by Modified Interpretive Structural Modeling (MISM) to explore the importance among the factors to implement lean and green manufacturing. Finally, Fuzzy Analytic Network Process (FANP) method has been used to determine the extent to which the main principles of lean and green manufacturing have been carried out in the six Indian medium scale manufacturing industries.

Keywords: lean manufacturing, green manufacturing, MISM, FANP

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Authors: Chengfang Wang, Zichao Wu, Jianying Zhou

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At present, much attention is paid to the development of new industrial parks in the era of inventory planning. Generally speaking, there are two types of development models: incremental development models and stock development models. The former relies on key projects to build a value innovation park, and the latter relies on the iterative update of the park to build a value innovation park. Take the Baiyun Western Digital Park as an example, considering the growth model of value units, determine the evaluation target. Based on a GIS platform, comprehensive land-use status, regulatory detailed planning, land use planning, blue-green ecological base, rail transit system, road network system, industrial park distribution, public service facilities, and other factors are used to carry out the land use within the planning multi-factor superimposed comprehensive evaluation, constructing a value unit evaluation system, and delineating value units based on implementation orientation and combining two different development models. The research hopes to provide a reference for the planning and construction of new domestic industrial parks.

Keywords: value units, GIS, multi-factor evaluation, implementation orientation

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Authors: N. David, H. O. Gao

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Air pollution is a serious environmental threat on a global scale and can cause harm to human health, morbidity and premature mortality. Reliable monitoring and control systems are therefore necessary to develop coping skills against the hazards associated with this phenomenon. However, existing environmental monitoring means often do not provide a sufficient response due to practical and technical limitations. Commercial microwave links that form the infrastructure for transmitting data between cell phone towers can be harnessed to map rain at high tempo-spatial resolution. Rainfall causes a decrease in the signal strength received by these wireless communication links allowing it to be used as a built-in sensor network to map the phenomenon. In this study, we point to the potential that lies in this system to indirectly monitor areas where air pollution is reduced. The relationship between pollutant wash-off and rainfall provides an opportunity to acquire important spatial information about air quality using existing cell-phone tower signals. Since the density of microwave communication networks is high relative to any dedicated sensor arrays, it could be possible to rely on this available observation tool for studying precipitation scavenging on air pollutants, for model needs and more.

Keywords: air pollution, commercial microwave links, rainfall, washout

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Authors: James Britton, Vijaya Krishna, Manus Biggs, Abhay Pandit

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Regeneration of the spinal cord after injury remains a great challenge due to the complexity of this organ. Inflammation and gliosis at the injury site hinder the outgrowth of axons and hence prevent synaptic reconnection and reinnervation. Hyaluronic acid (HA) is the main component of the spinal cord extracellular matrix and plays a vital role in cell proliferation and axonal guidance. In this study, we have synthesized and characterized a photo-cross-linkable HA-tyramine (tyr) hydrogel from a chemical, mechanical, electrical, biological and structural perspective. From our experimentation, we have found that HA-tyr can be synthesized with controllable degrees of tyramine substitution using click chemistry. The complex modulus (G*) of HA-tyr can be tuned to mimic the mechanical properties of the native spinal cord via optimization of the photo-initiator concentration and UV exposure. We have examined the degree of tyramine-tyramine covalent bonding (polymerization) as a function of UV exposure and photo-initiator use via Photo and Nuclear magnetic resonance spectroscopy. Both swelling and enzymatic degradation assays were conducted to examine the resilience of our 3D printed hydrogel constructs in-vitro. Using a femtosecond 780nm laser, the two-photon polymerization of HA-tyr hydrogel in the presence of riboflavin photoinitiator was optimized. A laser power of 50mW and scan speed of 30,000 μm/s produced high-resolution spatial patterning within the hydrogel with sustained mechanical integrity. Using dorsal root ganglion explants, the cytocompatibility of photo-crosslinked HA-tyr was assessed. Using potentiometry, the electrical conductivity of photo-crosslinked HA-tyr was assessed and compared to that of native spinal cord tissue as a function of frequency. In conclusion, we have developed a biocompatible hydrogel that can be used for photolithographic 3D printing to fabricate tissue engineered constructs for neural tissue regeneration applications.

Keywords: 3D printing, hyaluronic acid, photolithography, spinal cord injury

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Authors: Ali A. Abdollahi

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During the last several decades, scientists have consistently applied Multiple Criteria Decision-Making methods in making decisions about multi-faceted, complicated subjects. While making such decisions and in order to achieve more accurate evaluations, they have regularly used a variety of criteria instead of applying just one Optimum Evaluation Criterion. The method presented here utilizes both ‘quantity’ and ‘quality’ to assess the function of the Multiple-Criteria method. Applying Data envelopment analysis (DEA), weighted aggregated sum product assessment (WASPAS), Weighted Sum Approach (WSA), Analytic Network Process (ANP), and Charnes, Cooper, Rhodes (CCR) methods, we have analyzed thirteen parks in Kerman city. It further indicates that the functions of WASPAS and WSA are compatible with each other, but also that their deviation from DEA is extensive. Finally, the results for the CCR technique do not match the results of the DEA technique. Our study indicates that the ANP method, with the average rate of 1/51, ranks closest to the DEA method, which has an average rate of 1/49.

Keywords: multiple criteria decision making, Data envelopment analysis (DEA), Charnes Cooper Rhodes (CCR), Weighted Sum Approach (WSA)

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Authors: Marina Passero, Tianhua Zhai, Zuyi (Jacky) Huang

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Alzheimer’s disease has become a major public health issue, as indicated by the increasing populations of Americans living with Alzheimer’s disease. After decades of extensive research in Alzheimer’s disease, only seven drugs have been approved by Food and Drug Administration (FDA) to treat Alzheimer’s disease. Five of these drugs were designed to treat the dementia symptoms, and only two drugs (i.e., Aducanumab and Lecanemab) target the progression of Alzheimer’s disease, especially the accumulation of amyloid-b plaques. However, controversial comments were raised for the accelerated approvals of either Aducanumab or Lecanemab, especially with concerns on safety and side effects of these two drugs. There is still an urgent need for further drug discovery to target the biological processes involved in the progression of Alzheimer’s disease. Excessive cholesterol has been found to accumulate in the brain of those with Alzheimer’s disease. Cholesterol can be synthesized in both the blood and the brain, but the majority of biosynthesis in the adult brain takes place in astrocytes and is then transported to the neurons via ApoE. The blood brain barrier separates cholesterol metabolism in the brain from the rest of the body. Various proteins contribute to the metabolism of cholesterol in the brain, which offer potential targets for Alzheimer’s treatment. In the astrocytes, SREBP cleavage-activating protein (SCAP) binds to Sterol Regulatory Element-binding Protein 2 (SREBP2) in order to transport the complex from the endoplasmic reticulum to the Golgi apparatus. Cholesterol is secreted out of the astrocytes by ATP-Binding Cassette A1 (ABCA1) transporter. Lipoprotein receptors such as triggering receptor expressed on myeloid cells 2 (TREM2) internalize cholesterol into the microglia, while lipoprotein receptors such as Low-density lipoprotein receptor-related protein 1 (LRP1) internalize cholesterol into the neuron. Cytochrome P450 Family 46 Subfamily A Member 1 (CYP46A1) converts excess cholesterol to 24S-hydroxycholesterol (24S-OHC). Cholesterol has been approved for its direct effect on the production of amyloid-beta and tau proteins. The addition of cholesterol to the brain promotes the activity of beta-site amyloid precursor protein cleaving enzyme 1 (BACE1), secretase, and amyloid precursor protein (APP), which all aid in amyloid-beta production. The reduction of cholesterol esters in the brain have been found to reduce phosphorylated tau levels in mice. In this work, a computational pipeline was developed to identify the protein targets involved in cholesterol regulation in brain and further to identify chemical compounds as the inhibitors of a selected protein target. Since extensive evidence shows the strong correlation between brain cholesterol regulation and Alzheimer’s disease, a detailed literature review on genes or pathways related to the brain cholesterol synthesis and regulation was first conducted in this work. An interaction network was then built for those genes so that the top gene targets were identified. The involvement of these genes in Alzheimer’s disease progression was discussed, which was followed by the investigation of existing clinical trials for those targets. A ligand-protein docking program was finally developed to screen 1.5 million chemical compounds for the selected protein target. A machine learning program was developed to evaluate and predict the binding interaction between chemical compounds and the protein target. The results from this work pave the way for further drug discovery to regulate brain cholesterol to combat Alzheimer’s disease.

Keywords: Alzheimer’s disease, drug discovery, ligand-protein docking, gene-network analysis, cholesterol regulation

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Authors: Jesus Carretero, Mario Vasile, Javier Garcia-Blas, Felix Garcia-Carballeira

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Supporting cross-border secure and reliable exchange of data and documents and to promote data interoperability is critical for Europe to enhance sector (like eFinance, eJustice and eHealth). This work presents the status and results of the European Project MADE, a Research Project funded by Connecting Europe facility Programme, to provide secure e-invoicing and e-document exchange systems among Europe countries in compliance with the eIDAS Regulation (Regulation EU 910/2014 on electronic identification and trust services). The main goal of MADE is to develop six new AS4 Access Points and SMP in Europe to provide secure document exchanges using the eDelivery DSI (Digital Service Infrastructure) amongst both private and public entities. Moreover, the project demonstrates the feasibility and interest of the solution provided by providing several months of interoperability among the providers of the six partners in different EU countries. To achieve those goals, we have followed a methodology setting first a common background for requirements in the partner countries and the European regulations. Then, the partners have implemented access points in each country, including their service metadata publisher (SMP), to allow the access to their clients to the pan-European network. Finally, we have setup interoperability tests with the other access points of the consortium. The tests will include the use of each entity production-ready Information Systems that process the data to confirm all steps of the data exchange. For the access points, we have chosen AS4 instead of other existing alternatives because it supports multiple payloads, native web services, pulling facilities, lightweight client implementations, modern crypto algorithms, and more authentication types, like username-password and X.509 authentication and SAML authentication. The main contribution of MADE project is to open the path for European companies to use eDelivery services with cross-border exchange of electronic documents following PEPPOL (Pan-European Public Procurement Online) based on the e-SENS AS4 Profile. It also includes the development/integration of new components, integration of new and existing logging and traceability solutions and maintenance tool support for PKI. Moreover, we have found that most companies are still not ready to support those profiles. Thus further efforts will be needed to promote this technology into the companies. The consortium includes the following 9 partners. From them, 2 are research institutions: University Carlos III of Madrid (Coordinator), and Universidad Politecnica de Valencia. The other 7 (EDICOM, BIZbrains, Officient, Aksesspunkt Norge, eConnect, LMT group, Unimaze) are private entities specialized in secure delivery of electronic documents and information integration brokerage in their respective countries. To achieve cross-border operativity, they will include AS4 and SMP services in their platforms according to the EU Core Service Platform. Made project is instrumental to test the feasibility of cross-border documents eDelivery in Europe. If successful, not only einvoices, but many other types of documents will be securely exchanged through Europe. It will be the base to extend the network to the whole Europe. This project has been funded under the Connecting Europe Facility Agreement number: INEA/CEF/ICT/A2016/1278042. Action No: 2016-EU-IA-0063.

Keywords: security, e-delivery, e-invoicing, e-delivery, e-document exchange, trust

Procedia PDF Downloads 222

Authors: Yasemin Gülşen Yılmaz, Süleyman Hakan Yılmaz, Muhammet Erbay

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Social media is among the most important means of communication. Social media offers individuals and groups with an opportunity for participatory socialization over the internet, which is free of any time and place restrictions. Social media is a kind of interactive communication and bilateral social network. Various communication contents can be shared and put into mass circulation easily and quickly through social media. These sharings are not only limited to individuals but also happen to groups, institutions, and different constitutions. Their contents consist of any type of written message, audio and video files. We are living in the social media era now. It is not surprising that social media which has extensive communication facilities and massive prevalence is used in politics. Therefore, the use of social media (Facebook) by political parties during the Turkish general elections held on June 7, 2015, has been chosen as our research subject. Four parties namely, AKP, CHP, MHP and HDP who have the majority of votes in Turkey and participate in elections in Konya have been selected for our study. Their provincial centers’ and parliamentary candidates` use of social media (Facebook) on the last three days prior to the election have been examined and subjected to a qualitative analysis by means of content analysis.

Keywords: social media, June 7 general elections, politics, Facebook

Procedia PDF Downloads 365