Search results for: internet data science
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 27592

Search results for: internet data science

24982 An Examination of Low Engagement in a Group-Based ACT Intervention for Chronic Pain Management: Highlighting the Need for User-Attainment Focused Digitalised Interventions

Authors: Orestis Kasinopoulos, Maria Karekla, Vasilis Vasiliou, Evangelos Karademas

Abstract:

Acceptance and Commitment Therapy (ACT) is an empirically supported intervention for treating Chronic Pain Patients, yet its effectiveness for some chronic conditions or when adapted to other languages, has not been explored. An ACT group intervention was designed to explore the effectiveness of treating a Greek speaking heterogeneous sample of Chronic Pain patients with the aim of increasing quality of life, acceptance of pain and functionality. Sixty-nine patients were assessed and randomly assigned to an ACT or control group (relaxation techniques) for eight, 90-minute, sessions. Results are currently being analysed and follow-ups (6 and 12 month) are being completed. Low adherence rates and high attrition rates observed in the study, however point to the direction of future modified interventions. Such modifications may include web-based and smartphone interventions and their benefits in being implemented in chronic pain patients.

Keywords: chronic pain, ACT, internet-delivered, digitalised intervention, adherence, attrition

Procedia PDF Downloads 363
24981 Optimal Design Solution in "The Small Module" Within the Possibilities of Ecology, Environmental Science/Engineering, and Economics

Authors: Hassan Wajid

Abstract:

We will commend accommodating an environmentally friendly architectural proposal that is extremely common/usual but whose features will make it a sustainable space. In this experiment, the natural and artificial built space is being proposed in such a way that deals with Environmental, Ecological, and Economic Criteria under different climatic conditions. Moreover, the criteria against ecology-environment-economics reflect in the different modules which are being experimented with and analyzed by multiple research groups. The ecological, environmental, and economic services are provided used as units of production side by side, resulting in local job creation and saving resources, for instance, conservation of rainwater, soil formation or protection, less energy consumption to achieve Net Zero, and a stable climate as a whole. The synthesized results from the collected data suggest several aspects to consider when designing buildings for beginning the design process under the supervision of instructors/directors who are responsible for developing curricula and sustainable goals. Hence, the results of the research and the suggestions will benefit the sustainable design through multiple results, heat analysis of different small modules, and comparisons. As a result, it is depleted as the resources are either consumed or the pollution contaminates the resources.

Keywords: optimization, ecology, environment, sustainable solution

Procedia PDF Downloads 73
24980 Integrated Model for Enhancing Data Security Processing Time in Cloud Computing

Authors: Amani A. Saad, Ahmed A. El-Farag, El-Sayed A. Helali

Abstract:

Cloud computing is an important and promising field in the recent decade. Cloud computing allows sharing resources, services and information among the people of the whole world. Although the advantages of using clouds are great, but there are many risks in a cloud. The data security is the most important and critical problem of cloud computing. In this research a new security model for cloud computing is proposed for ensuring secure communication system, hiding information from other users and saving the user's times. In this proposed model Blowfish encryption algorithm is used for exchanging information or data, and SHA-2 cryptographic hash algorithm is used for data integrity. For user authentication process a simple user-name and password is used, the password uses SHA-2 for one way encryption. The proposed system shows an improvement of the processing time of uploading and downloading files on the cloud in secure form.

Keywords: cloud computing, data security, SAAS, PAAS, IAAS, Blowfish

Procedia PDF Downloads 359
24979 Comparison of Statistical Methods for Estimating Missing Precipitation Data in the River Subbasin Lenguazaque, Colombia

Authors: Miguel Cañon, Darwin Mena, Ivan Cabeza

Abstract:

In this work was compared and evaluated the applicability of statistical methods for the estimation of missing precipitations data in the basin of the river Lenguazaque located in the departments of Cundinamarca and Boyacá, Colombia. The methods used were the method of simple linear regression, distance rate, local averages, mean rates, correlation with nearly stations and multiple regression method. The analysis used to determine the effectiveness of the methods is performed by using three statistical tools, the correlation coefficient (r2), standard error of estimation and the test of agreement of Bland and Altmant. The analysis was performed using real rainfall values removed randomly in each of the seasons and then estimated using the methodologies mentioned to complete the missing data values. So it was determined that the methods with the highest performance and accuracy in the estimation of data according to conditions that were counted are the method of multiple regressions with three nearby stations and a random application scheme supported in the precipitation behavior of related data sets.

Keywords: statistical comparison, precipitation data, river subbasin, Bland and Altmant

Procedia PDF Downloads 467
24978 Hyperspectral Data Classification Algorithm Based on the Deep Belief and Self-Organizing Neural Network

Authors: Li Qingjian, Li Ke, He Chun, Huang Yong

Abstract:

In this paper, the method of combining the Pohl Seidman's deep belief network with the self-organizing neural network is proposed to classify the target. This method is mainly aimed at the high nonlinearity of the hyperspectral image, the high sample dimension and the difficulty in designing the classifier. The main feature of original data is extracted by deep belief network. In the process of extracting features, adding known labels samples to fine tune the network, enriching the main characteristics. Then, the extracted feature vectors are classified into the self-organizing neural network. This method can effectively reduce the dimensions of data in the spectrum dimension in the preservation of large amounts of raw data information, to solve the traditional clustering and the long training time when labeled samples less deep learning algorithm for training problems, improve the classification accuracy and robustness. Through the data simulation, the results show that the proposed network structure can get a higher classification precision in the case of a small number of known label samples.

Keywords: DBN, SOM, pattern classification, hyperspectral, data compression

Procedia PDF Downloads 341
24977 Evaluation and Control of Cracking for Bending Rein-forced One-way Concrete Voided Slab with Plastic Hollow Inserts

Authors: Mindaugas Zavalis

Abstract:

Analysis of experimental tests data of bending one-way reinforced concrete slabs from various articles of science revealed that voided slabs with a grid of hollow plastic inserts inside have smaller mechani-cal and physical parameters compared to continuous cross-section slabs (solid slabs). The negative influence of a reinforced concrete slab is impacted by hollow plastic inserts, which make a grid of voids in the middle of the cross-sectional area of the reinforced concrete slab. A formed grid of voids reduces the slab’s stiffness, which influences the slab’s parameters of serviceability, like deflection and cracking. Prima-ry investigation of data established during experiments illustrates that cracks occur faster in the tensile surface of the voided slab under bend-ing compared to bending solid slab. It means that the crack bending moment force for the voided slab is smaller than the solid slab and the reduction can variate in the range of 14 – 40 %. Reduce of resistance to cracking can be controlled by changing a lot of factors: the shape of the plastic hallow insert, plastic insert height, steps between plastic in-serts, usage of prestressed reinforcement, the diameter of reinforcement bar, slab effective depth, the bottom cover thickness of concrete, effec-tive cross-section of the concrete area about reinforcement and etc. Mentioned parameters are used to evaluate crack width and step of cracking, but existing analytical calculation methods for cracking eval-uation of voided slab with plastic inserts are not so exact and the re-sults of cracking evaluation in this paper are higher than the results of analyzed experiments. Therefore, it was made analytically calculations according to experimental bending tests of voided reinforced concrete slabs with hollow plastic inserts to find and propose corrections for the evaluation of cracking for reinforced concrete voided slabs with hollow plastic inserts.

Keywords: voided slab, cracking, hallow plastic insert, bending, one-way reinforced concrete, serviceability

Procedia PDF Downloads 68
24976 Assessing Performance of Data Augmentation Techniques for a Convolutional Network Trained for Recognizing Humans in Drone Images

Authors: Masood Varshosaz, Kamyar Hasanpour

Abstract:

In recent years, we have seen growing interest in recognizing humans in drone images for post-disaster search and rescue operations. Deep learning algorithms have shown great promise in this area, but they often require large amounts of labeled data to train the models. To keep the data acquisition cost low, augmentation techniques can be used to create additional data from existing images. There are many techniques of such that can help generate variations of an original image to improve the performance of deep learning algorithms. While data augmentation is potentially assumed to improve the accuracy and robustness of the models, it is important to ensure that the performance gains are not outweighed by the additional computational cost or complexity of implementing the techniques. To this end, it is important to evaluate the impact of data augmentation on the performance of the deep learning models. In this paper, we evaluated the most currently available 2D data augmentation techniques on a standard convolutional network which was trained for recognizing humans in drone images. The techniques include rotation, scaling, random cropping, flipping, shifting, and their combination. The results showed that the augmented models perform 1-3% better compared to a base network. However, as the augmented images only contain the human parts already visible in the original images, a new data augmentation approach is needed to include the invisible parts of the human body. Thus, we suggest a new method that employs simulated 3D human models to generate new data for training the network.

Keywords: human recognition, deep learning, drones, disaster mitigation

Procedia PDF Downloads 95
24975 Emotional Artificial Intelligence and the Right to Privacy

Authors: Emine Akar

Abstract:

The majority of privacy-related regulation has traditionally focused on concepts that are perceived to be well-understood or easily describable, such as certain categories of data and personal information or images. In the past century, such regulation appeared reasonably suitable for its purposes. However, technologies such as AI, combined with ever-increasing capabilities to collect, process, and store “big data”, not only require calibration of these traditional understandings but may require re-thinking of entire categories of privacy law. In the presentation, it will be explained, against the background of various emerging technologies under the umbrella term “emotional artificial intelligence”, why modern privacy law will need to embrace human emotions as potentially private subject matter. This argument can be made on a jurisprudential level, given that human emotions can plausibly be accommodated within the various concepts that are traditionally regarded as the underlying foundation of privacy protection, such as, for example, dignity, autonomy, and liberal values. However, the practical reasons for regarding human emotions as potentially private subject matter are perhaps more important (and very likely more convincing from the perspective of regulators). In that respect, it should be regarded as alarming that, according to most projections, the usefulness of emotional data to governments and, particularly, private companies will not only lead to radically increased processing and analysing of such data but, concerningly, to an exponential growth in the collection of such data. In light of this, it is also necessity to discuss options for how regulators could address this emerging threat.

Keywords: AI, privacy law, data protection, big data

Procedia PDF Downloads 88
24974 Classification of Poverty Level Data in Indonesia Using the Naïve Bayes Method

Authors: Anung Style Bukhori, Ani Dijah Rahajoe

Abstract:

Poverty poses a significant challenge in Indonesia, requiring an effective analytical approach to understand and address this issue. In this research, we applied the Naïve Bayes classification method to examine and classify poverty data in Indonesia. The main focus is on classifying data using RapidMiner, a powerful data analysis platform. The analysis process involves data splitting to train and test the classification model. First, we collected and prepared a poverty dataset that includes various factors such as education, employment, and health..The experimental results indicate that the Naïve Bayes classification model can provide accurate predictions regarding the risk of poverty. The use of RapidMiner in the analysis process offers flexibility and efficiency in evaluating the model's performance. The classification produces several values to serve as the standard for classifying poverty data in Indonesia using Naive Bayes. The accuracy result obtained is 40.26%, with a moderate recall result of 35.94%, a high recall result of 63.16%, and a low recall result of 38.03%. The precision for the moderate class is 58.97%, for the high class is 17.39%, and for the low class is 58.70%. These results can be seen from the graph below.

Keywords: poverty, classification, naïve bayes, Indonesia

Procedia PDF Downloads 56
24973 Algorithm for Information Retrieval Optimization

Authors: Kehinde K. Agbele, Kehinde Daniel Aruleba, Eniafe F. Ayetiran

Abstract:

When using Information Retrieval Systems (IRS), users often present search queries made of ad-hoc keywords. It is then up to the IRS to obtain a precise representation of the user’s information need and the context of the information. This paper investigates optimization of IRS to individual information needs in order of relevance. The study addressed development of algorithms that optimize the ranking of documents retrieved from IRS. This study discusses and describes a Document Ranking Optimization (DROPT) algorithm for information retrieval (IR) in an Internet-based or designated databases environment. Conversely, as the volume of information available online and in designated databases is growing continuously, ranking algorithms can play a major role in the context of search results. In this paper, a DROPT technique for documents retrieved from a corpus is developed with respect to document index keywords and the query vectors. This is based on calculating the weight (

Keywords: information retrieval, document relevance, performance measures, personalization

Procedia PDF Downloads 241
24972 Extracting Terrain Points from Airborne Laser Scanning Data in Densely Forested Areas

Authors: Ziad Abdeldayem, Jakub Markiewicz, Kunal Kansara, Laura Edwards

Abstract:

Airborne Laser Scanning (ALS) is one of the main technologies for generating high-resolution digital terrain models (DTMs). DTMs are crucial to several applications, such as topographic mapping, flood zone delineation, geographic information systems (GIS), hydrological modelling, spatial analysis, etc. Laser scanning system generates irregularly spaced three-dimensional cloud of points. Raw ALS data are mainly ground points (that represent the bare earth) and non-ground points (that represent buildings, trees, cars, etc.). Removing all the non-ground points from the raw data is referred to as filtering. Filtering heavily forested areas is considered a difficult and challenging task as the canopy stops laser pulses from reaching the terrain surface. This research presents an approach for removing non-ground points from raw ALS data in densely forested areas. Smoothing splines are exploited to interpolate and fit the noisy ALS data. The presented filter utilizes a weight function to allocate weights for each point of the data. Furthermore, unlike most of the methods, the presented filtering algorithm is designed to be automatic. Three different forested areas in the United Kingdom are used to assess the performance of the algorithm. The results show that the generated DTMs from the filtered data are accurate (when compared against reference terrain data) and the performance of the method is stable for all the heavily forested data samples. The average root mean square error (RMSE) value is 0.35 m.

Keywords: airborne laser scanning, digital terrain models, filtering, forested areas

Procedia PDF Downloads 139
24971 Estimating the Life-Distribution Parameters of Weibull-Life PV Systems Utilizing Non-Parametric Analysis

Authors: Saleem Z. Ramadan

Abstract:

In this paper, a model is proposed to determine the life distribution parameters of the useful life region for the PV system utilizing a combination of non-parametric and linear regression analysis for the failure data of these systems. Results showed that this method is dependable for analyzing failure time data for such reliable systems when the data is scarce.

Keywords: masking, bathtub model, reliability, non-parametric analysis, useful life

Procedia PDF Downloads 562
24970 Preliminary Design of Maritime Energy Management System: Naval Architectural Approach to Resolve Recent Limitations

Authors: Seyong Jeong, Jinmo Park, Jinhyoun Park, Boram Kim, Kyoungsoo Ahn

Abstract:

Energy management in the maritime industry is being required by economics and in conformity with new legislative actions taken by the International Maritime Organization (IMO) and the European Union (EU). In response, the various performance monitoring methodologies and data collection practices have been examined by different stakeholders. While many assorted advancements in operation and technology are applicable, their adoption in the shipping industry stays small. This slow uptake can be considered due to many different barriers such as data analysis problems, misreported data, and feedback problems, etc. This study presents a conceptual design of an energy management system (EMS) and proposes the methodology to resolve the limitations (e.g., data normalization using naval architectural evaluation, management of misrepresented data, and feedback from shore to ship through management of performance analysis history). We expect this system to make even short-term charterers assess the ship performance properly and implement sustainable fleet control.

Keywords: data normalization, energy management system, naval architectural evaluation, ship performance analysis

Procedia PDF Downloads 449
24969 Geospatial Data Complexity in Electronic Airport Layout Plan

Authors: Shyam Parhi

Abstract:

Airports GIS program collects Airports data, validate and verify it, and stores it in specific database. Airports GIS allows authorized users to submit changes to airport data. The verified data is used to develop several engineering applications. One of these applications is electronic Airport Layout Plan (eALP) whose primary aim is to move from paper to digital form of ALP. The first phase of development of eALP was completed recently and it was tested for a few pilot program airports across different regions. We conducted gap analysis and noticed that a lot of development work is needed to fine tune at least six mandatory sheets of eALP. It is important to note that significant amount of programming is needed to move from out-of-box ArcGIS to a much customized ArcGIS which will be discussed. The ArcGIS viewer capability to display essential features like runway or taxiway or the perpendicular distance between them will be discussed. An enterprise level workflow which incorporates coordination process among different lines of business will be highlighted.

Keywords: geospatial data, geology, geographic information systems, aviation

Procedia PDF Downloads 416
24968 Cost-Effective Hybrid Cloud Framework for Higher Educational Institutes

Authors: Shah Muhammad Butt, Ahmed Masaud Ansair

Abstract:

Present financial crisis in Higher Educational Institutes (HEIs) is causing lots of problems such as considerable budget cuts, which makes it difficult to meet the ever growing IT based research and learning needs. Institutions are rapidly planning and promoting cloud based approaches for their academic and research needs. A cost-effective hybrid cloud framework for HEIs will provide educational services for campus or intercampus communication. Hybrid cloud framework comprises private and public cloud approaches. This paper will propose the framework based on the Open Source Cloud (OpenNebula for Virtualization, Eucalyptus for Infrastructure and Aneka for programming development environment) combined with CSPs services which are delivered to the end-user via the internet from public clouds such as Google, Microsoft, Zoho, and Salesforce.

Keywords: educational services, hybrid campus cloud, open source, higher educational institutes

Procedia PDF Downloads 482
24967 The Influence of Online Marketing Tactics in Tourist Destination Reputation: Egypt as a Case Study

Authors: Alyaa Darwish, Peter Burns, Sofia Reino

Abstract:

Online marketing has been the key focus of attention for the majority of destinations since the Internet became the primarily information tool for travel marketing. Tourism is a reputation-dependent industry; potential travelers who do not have previous experience with the destination face numerous risks during the process of decision-making. An accurate perception of the destination’s reputation helps to minimize risk against unsatisfying travel experiences. However, there has been limited investigation with regards to the reputation of tourist destination. Taking the importance of reputation to the tourism industry, this research aims to: 1) Develop a destination reputation model; 2) Assess the tourist destination approach towards online marketing tactics; 3) Evaluate the impact of differentiated online marketing tactics on reputation; and 4) Measure the potential for using online marketing tactics to manage the destination’s online reputation. This research follows an interpretivism epistemological research approach through using four research methods; interviews, questionnaire, content analysis, and experiment to achieve the research goals.

Keywords: destination reputation, online marketing, reputation, tactics

Procedia PDF Downloads 355
24966 Anisotropic Total Fractional Order Variation Model in Seismic Data Denoising

Authors: Jianwei Ma, Diriba Gemechu

Abstract:

In seismic data processing, attenuation of random noise is the basic step to improve quality of data for further application of seismic data in exploration and development in different gas and oil industries. The signal-to-noise ratio of the data also highly determines quality of seismic data. This factor affects the reliability as well as the accuracy of seismic signal during interpretation for different purposes in different companies. To use seismic data for further application and interpretation, we need to improve the signal-to-noise ration while attenuating random noise effectively. To improve the signal-to-noise ration and attenuating seismic random noise by preserving important features and information about seismic signals, we introduce the concept of anisotropic total fractional order denoising algorithm. The anisotropic total fractional order variation model defined in fractional order bounded variation is proposed as a regularization in seismic denoising. The split Bregman algorithm is employed to solve the minimization problem of the anisotropic total fractional order variation model and the corresponding denoising algorithm for the proposed method is derived. We test the effectiveness of theproposed method for synthetic and real seismic data sets and the denoised result is compared with F-X deconvolution and non-local means denoising algorithm.

Keywords: anisotropic total fractional order variation, fractional order bounded variation, seismic random noise attenuation, split Bregman algorithm

Procedia PDF Downloads 207
24965 NSBS: Design of a Network Storage Backup System

Authors: Xinyan Zhang, Zhipeng Tan, Shan Fan

Abstract:

The first layer of defense against data loss is the backup data. This paper implements an agent-based network backup system used the backup, server-storage and server-backup agent these tripartite construction, and we realize the snapshot and hierarchical index in the NSBS. It realizes the control command and data flow separation, balances the system load, thereby improving the efficiency of the system backup and recovery. The test results show the agent-based network backup system can effectively improve the task-based concurrency, reasonably allocate network bandwidth, the system backup performance loss costs smaller and improves data recovery efficiency by 20%.

Keywords: agent, network backup system, three architecture model, NSBS

Procedia PDF Downloads 459
24964 A t-SNE and UMAP Based Neural Network Image Classification Algorithm

Authors: Shelby Simpson, William Stanley, Namir Naba, Xiaodi Wang

Abstract:

Both t-SNE and UMAP are brand new state of art tools to predominantly preserve the local structure that is to group neighboring data points together, which indeed provides a very informative visualization of heterogeneity in our data. In this research, we develop a t-SNE and UMAP base neural network image classification algorithm to embed the original dataset to a corresponding low dimensional dataset as a preprocessing step, then use this embedded database as input to our specially designed neural network classifier for image classification. We use the fashion MNIST data set, which is a labeled data set of images of clothing objects in our experiments. t-SNE and UMAP are used for dimensionality reduction of the data set and thus produce low dimensional embeddings. Furthermore, we use the embeddings from t-SNE and UMAP to feed into two neural networks. The accuracy of the models from the two neural networks is then compared to a dense neural network that does not use embedding as an input to show which model can classify the images of clothing objects more accurately.

Keywords: t-SNE, UMAP, fashion MNIST, neural networks

Procedia PDF Downloads 198
24963 Investigation a New Approach "AGM" to Solve of Complicate Nonlinear Partial Differential Equations at All Engineering Field and Basic Science

Authors: Mohammadreza Akbari, Pooya Soleimani Besheli, Reza Khalili, Davood Domiri Danji

Abstract:

In this conference, our aims are accuracy, capabilities and power at solving of the complicated non-linear partial differential. Our purpose is to enhance the ability to solve the mentioned nonlinear differential equations at basic science and engineering field and similar issues with a simple and innovative approach. As we know most of engineering system behavior in practical are nonlinear process (especially basic science and engineering field, etc.) and analytical solving (no numeric) these problems are difficult, complex, and sometimes impossible like (Fluids and Gas wave, these problems can't solve with numeric method, because of no have boundary condition) accordingly in this symposium we are going to exposure an innovative approach which we have named it Akbari-Ganji's Method or AGM in engineering, that can solve sets of coupled nonlinear differential equations (ODE, PDE) with high accuracy and simple solution and so this issue will emerge after comparing the achieved solutions by Numerical method (Runge-Kutta 4th). Eventually, AGM method will be proved that could be created huge evolution for researchers, professors and students in whole over the world, because of AGM coding system, so by using this software we can analytically solve all complicated linear and nonlinear partial differential equations, with help of that there is no difficulty for solving all nonlinear differential equations. Advantages and ability of this method (AGM) as follow: (a) Non-linear Differential equations (ODE, PDE) are directly solvable by this method. (b) In this method (AGM), most of the time, without any dimensionless procedure, we can solve equation(s) by any boundary or initial condition number. (c) AGM method always is convergent in boundary or initial condition. (d) Parameters of exponential, Trigonometric and Logarithmic of the existent in the non-linear differential equation with AGM method no needs Taylor expand which are caused high solve precision. (e) AGM method is very flexible in the coding system, and can solve easily varieties of the non-linear differential equation at high acceptable accuracy. (f) One of the important advantages of this method is analytical solving with high accuracy such as partial differential equation in vibration in solids, waves in water and gas, with minimum initial and boundary condition capable to solve problem. (g) It is very important to present a general and simple approach for solving most problems of the differential equations with high non-linearity in engineering sciences especially at civil engineering, and compare output with numerical method (Runge-Kutta 4th) and Exact solutions.

Keywords: new approach, AGM, sets of coupled nonlinear differential equation, exact solutions, numerical

Procedia PDF Downloads 464
24962 Challenges in Adopting 3R Concept in the Heritage Building Restoration

Authors: H. H. Goh, K. C. Goh, T. W. Seow, N. S. Said, S. E. P. Ang

Abstract:

Malaysia is rich with historic buildings, particularly in Penang and Malacca states. Restoration activities are increasingly important as these states are recognized under UNESCO World Heritage Sites. Restoration activities help to maintain the uniqueness and value of a heritage building. However, increasing in restoration activities has resulted in large quantities of waste. To cope with this problem, the 3R concept (reduce, reuse and recycle) is introduced. The 3R concept is one of the waste management hierarchies. This concept is still yet to apply in the building restoration industry compared to the construction industry. Therefore, this study aims to promote the 3R concept in the heritage building restoration industry. This study aims to examine the importance of 3R concept and to identify challenges in applying the 3R concept in the heritage building restoration industry. This study focused on contractors and consultants who are involved in heritage restoration projects in Penang. Literature review and interviews helps to reach the research objective. Data that obtained is analyzed by using content analysis. For the research, application of 3R concept is important to conserve natural resources and reduce pollution problems. However, limited space to organise waste is the obstruction during the implementation of this concept. In conclusion, the 3R concept plays an important role in promoting environmental conservation and helping in reducing the construction waste

Keywords: 3R Concept, heritage building, restoration activities, building science

Procedia PDF Downloads 314
24961 Composite Kernels for Public Emotion Recognition from Twitter

Authors: Chien-Hung Chen, Yan-Chun Hsing, Yung-Chun Chang

Abstract:

The Internet has grown into a powerful medium for information dispersion and social interaction that leads to a rapid growth of social media which allows users to easily post their emotions and perspectives regarding certain topics online. Our research aims at using natural language processing and text mining techniques to explore the public emotions expressed on Twitter by analyzing the sentiment behind tweets. In this paper, we propose a composite kernel method that integrates tree kernel with the linear kernel to simultaneously exploit both the tree representation and the distributed emotion keyword representation to analyze the syntactic and content information in tweets. The experiment results demonstrate that our method can effectively detect public emotion of tweets while outperforming the other compared methods.

Keywords: emotion recognition, natural language processing, composite kernel, sentiment analysis, text mining

Procedia PDF Downloads 218
24960 Writing Hybridized Narratives to Enact Scientific Literacy and the Myth of the Scientific Method

Authors: Ajaz Shaheen, Jawaid Ahmed Siddqui

Abstract:

This world has purely become scientific and technological, and therefore it demands more from our young learners to be more intellectual in learning sciences. A point of concern that is dragging the attention of educationists is that young learners are gradually detaching from science and scientific theory. To deal with this matter, we must arrange such engaging activities that may improve the imaginative skills of our young learners. Our ongoing research program highlights the effects of such activities that demand the learners to interpret scientific information in the form of text they possess. These mixed stories are also known as what we call BioStories. Learners upload their narratives on different websites to let their peers go through their manuscripts. That, as a result, brings more refinement to their works. Moreover, stories allow the learners to read, understand and learn on a broader spectrum. We have conducted separate studies with learners from Grades 6, 9, and 12 that involve case studies and quasi-experimental designs. The conclusion we drew from the analysis of Grade 6 learners was that the alignment of stories helped them become more familiar with the scientific issue. Not only this but also the learners of the respective grade built up their interest in the subject and also developed a clear understanding of related subject topics. On the other hand, results from the 8th and 9th grades study support the argument that learners reflected a positive attitude toward writing scientific information. Lastly, we concluded from the 12th-grade learners that they took pride in their writing skills and built up their strength, determination, and interest. The students became self-conscious as they wrote hybridized scientific narratives in science.

Keywords: BioStories, hybridized writing, scientific literacy, scientific method

Procedia PDF Downloads 80
24959 A Contemplation of Iranian Islamic Architecture in the Age of Globalization

Authors: Maziar Asefi, Safa Salkhi Khasraghi

Abstract:

Despite the great development of Islamic Architecture in its conquered lands, its active performance in a vast geographical area, faded by the advent of industrial age. Now in the Information Age with great advances in technologies and increased interconnection among many societies, every aspect of life is affected by rapid spreading phenomenon called globalization which resulted in the world with less regional and cultural boundaries. So being proudly globalized in the past and becoming inactive in today's globalized world puts Islamic Architecture in a great challenge. Indeed, its important role has changed from transmitting cultural values to the world to importing dominated values even defectively. This study aimed to determine the factors influenced this controversial situation of Islamic Architecture, especially in current age. The paper focuses on performance of Islamic architecture in relation with Globalization as an ancient process. So qualitative method in terms of logic analysis was chosen to evaluate how Islamic architecture of Iran has contributed in Globalization subject in different time periods. Several works were analyzed as case studies in three categories: religious, monumental, commercial utilities and climate element. Theoretical and practical findings indicate that there is a mutual relationship between Islamic Architecture and Globalization which is transformed from the active mode to passive mode gradually in three periods of Globalization: proto, modern and communication Globalization. The proposed solution in the response to this challenge is finding a solution that makes an equilibrium between science, art, and technology, as well as taking the global performance of architecture.

Keywords: Islamic architecture, globalisation, the relationship among art, science and technology, Iranian architecture

Procedia PDF Downloads 300
24958 An Intrusion Detection Systems Based on K-Means, K-Medoids and Support Vector Clustering Using Ensemble

Authors: A. Mohammadpour, Ebrahim Najafi Kajabad, Ghazale Ipakchi

Abstract:

Presently, computer networks’ security rise in importance and many studies have also been conducted in this field. By the penetration of the internet networks in different fields, many things need to be done to provide a secure industrial and non-industrial network. Fire walls, appropriate Intrusion Detection Systems (IDS), encryption protocols for information sending and receiving, and use of authentication certificated are among things, which should be considered for system security. The aim of the present study is to use the outcome of several algorithms, which cause decline in IDS errors, in the way that improves system security and prevents additional overload to the system. Finally, regarding the obtained result we can also detect the amount and percentage of more sub attacks. By running the proposed system, which is based on the use of multi-algorithmic outcome and comparing that by the proposed single algorithmic methods, we observed a 78.64% result in attack detection that is improved by 3.14% than the proposed algorithms.

Keywords: intrusion detection systems, clustering, k-means, k-medoids, SV clustering, ensemble

Procedia PDF Downloads 221
24957 Analysis of Interleaving Scheme for Narrowband VoIP System under Pervasive Environment

Authors: Monica Sharma, Harjit Pal Singh, Jasbinder Singh, Manju Bala

Abstract:

In Voice over Internet Protocol (VoIP) system, the speech signal is degraded when passed through the network layers. The speech signal is processed through the best effort policy based IP network, which leads to the network degradations including delay, packet loss and jitter. The packet loss is the major issue of the degradation in the VoIP signal quality; even a single lost packet may generate audible distortion in the decoded speech signal. In addition to these network degradations, the quality of the speech signal is also affected by the environmental noises and coder distortions. The signal quality of the VoIP system is improved through the interleaving technique. The performance of the system is evaluated for various types of noises at different network conditions. The performance of the enhanced VoIP signal is evaluated using perceptual evaluation of speech quality (PESQ) measurement for narrow band signal.

Keywords: VoIP, interleaving, packet loss, packet size, background noise

Procedia PDF Downloads 479
24956 Graph Based Traffic Analysis and Delay Prediction Using a Custom Built Dataset

Authors: Gabriele Borg, Alexei Debono, Charlie Abela

Abstract:

There on a constant rise in the availability of high volumes of data gathered from multiple sources, resulting in an abundance of unprocessed information that can be used to monitor patterns and trends in user behaviour. Similarly, year after year, Malta is also constantly experiencing ongoing population growth and an increase in mobilization demand. This research takes advantage of data which is continuously being sourced and converting it into useful information related to the traffic problem on the Maltese roads. The scope of this paper is to provide a methodology to create a custom dataset (MalTra - Malta Traffic) compiled from multiple participants from various locations across the island to identify the most common routes taken to expose the main areas of activity. This use of big data is seen being used in various technologies and is referred to as ITSs (Intelligent Transportation Systems), which has been concluded that there is significant potential in utilising such sources of data on a nationwide scale. Furthermore, a series of traffic prediction graph neural network models are conducted to compare MalTra to large-scale traffic datasets.

Keywords: graph neural networks, traffic management, big data, mobile data patterns

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24955 Investigation of Delivery of Triple Play Services

Authors: Paramjit Mahey, Monica Sharma, Jasbinder Singh

Abstract:

Fiber based access networks can deliver performance that can support the increasing demands for high speed connections. One of the new technologies that have emerged in recent years is Passive Optical Networks. This paper is targeted to show the simultaneous delivery of triple play service (data, voice and video). The comparative investigation and suitability of various data rates is presented. It is demonstrated that as we increase the data rate, number of users to be accommodated decreases due to increase in bit error rate.

Keywords: BER, PON, TDMPON, GPON, CWDM, OLT, ONT

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24954 A Bibliometric Assessment of the Nexus Between Corporate Social Responsibility and Sustainable Development

Authors: Trilochana Dash, Chandan Kumar Sahoo

Abstract:

In today's environment of intensive industrialization, the role of business in societal modernization is critical. The concept of corporate social responsibility (CSR) arose due to rising societal awareness of company conduct. Corporations that practice CSR devote a portion of their profits to society’s sustainable development (SD). The concept of CSR and SD has increased the impact of industries on society. In this study, bibliometric analysis was conducted using the “R” programming language to determine the comprehensiveness of CSR and SD. From 2003 to 2022, bibliometric data was collected from two databases: Scopus and Web of Science (WOS). According to the findings, CSR and SD research has risen exponentially in the past two decades, and “Corporate Social Responsibility and Environment Management” emerged as the most influential journal in this field. The findings also show that relatively very few researchers collaborate in CSR and SD research in the last twenty years. It is widely acknowledged that most CSR and SD research is conducted in developed countries and developing countries undergoing fast industrialization. Thematic evolution and cluster analysis clearly show that the notion of CSR and SD among scholars has been quite popular over the last two decades. Finally, limitations and future directions are discussed.

Keywords: corporate social responsibility, sustainable development, bibliometric analysis, “R” programming language, visualization, holistic picture

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24953 SWOT Analysis on the Prospects of Carob Use in Human Nutrition: Crete, Greece

Authors: Georgios A. Fragkiadakis, Antonia Psaroudaki, Theodora Mouratidou, Eirini Sfakianaki

Abstract:

Research: Within the project "Actions for the optimal utilization of the potential of carob in the Region of Crete" which is financed-supervised by the Region, with collaboration of Crete University and Hellenic Mediterranean University, a SWOT (strengths, weaknesses, opportunities, threats) survey was carried out, to evaluate the prospects of carob in human nutrition, in Crete. Results and conclusions: 1). Strengths: There exists a local production of carob for human consumption, based on international reports, and local-product reports. The data on products in the market (over 100 brands of carob food), indicates a sufficiency of carob materials offered in Crete. The variety of carob food products retailed in Crete indicates a strong demand-production-consumption trend. There is a stable number (core) of businesses that invest significantly (Creta carob, Cretan mills, etc.). The great majority of the relevant food stores (bakery, confectionary etc.) do offer carob products. The presence of carob products produced in Crete is strong on the internet (over 20 main professionally designed websites). The promotion of the carob food-products is based on their variety and on a few historical elements connected with the Cretan diet. 2). Weaknesses: The international prices for carob seed affect the sector; the seed had an international price of €20 per kg in 2021-22 and fell to €8 in 2022, causing losses to carob traders. The local producers do not sort the carobs they deliver for processing, causing 30-40% losses of the product in the industry. The occasional high price triggers the collection of degraded raw material; large losses may emerge due to the action of insects. There are many carob trees whose fruits are not collected, e.g. in Apokoronas, Chania. The nutritional and commercial value of the wild carob fruits is very low. Carob trees-production is recorded by Greek statistical services as "other cultures" in combination with prickly pear i.e., creating difficulties in retrieving data. The percentage of carob used for human nutrition, in contrast to animal feeding, is not known. The exact imports of carob are not closely monitored. We have no data on the recycling of carob by-products in Crete. 3). Opportunities: The development of a culture of respect for carob trade may improve professional relations in the sector. Monitoring carob market and connecting production with retailing-industry needs may allow better market-stability. Raw material evaluation procedures may be implemented to maintain carob value-chain. The state agricultural services may be further involved in carob-health protection. The education of farmers on carob cultivation/management, can improve the quality of the product. The selection of local productive varieties, may improve the sustainability of the culture. Connecting the consumption of carob with health-food products, may create added value in the sector. The presence and extent of wild carob threes in Crete, represents, potentially, a target for grafting. 4). Threats: The annual fluctuation of carob yield challenges the programming of local food industry activities. Carob is a forest species also - there is danger of wrong classification of crops as forest areas, where land ownership is not clear.

Keywords: human nutrition, carob food, SWOT analysis, crete, greece

Procedia PDF Downloads 92