Search results for: Information communication

Authors: Rattanathip Rattanachai, Piyachai Petchyen, Kunyanuth Kularbphettong

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This paper describes the development of a Weight- Balancing Control System based on the Android Operating System and it provides recommendations on ways of balancing of user’s weight based on daily metabolism process and need so that user can make informed decisions on his or her weight controls. The system also depicts more information on nutrition details. Furthermore, it was designed to suggest to users what kinds of foods they should eat and how to exercise in the right ways. We describe the design methods and functional components of this prototype. To evaluate the system performance, questionnaires for system usability and Black Box Testing were used to measure expert and user satisfaction. The results were satisfactory as followed: Means for experts and users were 3.94 and 4.07 respectively.

Keywords: weight-balancing control, Android operating system, daily metabolism, black box testing

Procedia PDF Downloads 457

Authors: Anod H. Alhazmi, Hanaa A. Yamani

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The lack of digital transformation professionals could prevent Saudi Arabia’s universities from providing digital services. The task of understanding what digital skills are needed within an organization, measuring the existing skills, and developing or attracting talents is a complex task. This paper provides a comprehensive analysis of the digital transformation skills needed in the organizations who seek digital transformation and identifies the skills and competencies framework DigSC built on Skills Framework for the Informational Age (SFIA) framework that is adopted by the Ministry of Communications and Information Technology (MCIT) in Saudi Arabia. The framework adopted identifies the main digital transformation skills clusters, categories and levels of responsibilities for each job description to fill the gap between this requirement and the digital skills supplied by the Umm Alqura University (UQU).

Keywords: competencies, digital transformation, framework, skills, Umm Alqura university

Procedia PDF Downloads 171

Authors: Abdulmajeed Almansour

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Learning a foreign language with the assistant of technological tools has become an interest of learners and educators. Increased use of smartphones among undergraduate students has made them popular for not only social communication but also for entertainment and educational purposes. Smartphones have provided remarkable advantages in language learning process. Learning vocabulary is an important part of learning a language. The use of smartphone applications for English vocabulary learning provides an opportunity for learners to improve vocabulary knowledge beyond the classroom wall anytime anywhere. Recently, various smartphone applications were created specifically for vocabulary learning. This paper aims to explore the use of smartphone application Memrise designed for vocabulary learning to enhance academic vocabulary among undergraduate students. It examines whether the use of a Memrise smartphone application designed course enhances the academic vocabulary learning among ESL learners. The research paradigm used in this paper followed a mixed research model combining quantitative and qualitative research. The study included two hundred undergraduate students randomly assigned to the experimental and controlled group during the first academic year at the Faculty of English Language, Imam University. The research instruments included an attitudinal questionnaire and an English vocabulary pre-test administered to students at the beginning of the semester whereas post-test and semi-structured interviews administered at the end of the semester. The findings of the attitudinal questionnaire revealed a positive attitude towards using smartphones in learning vocabulary. The post-test scores showed a significant difference in the experimental group performance. The results from the semi-structure interviews showed that there were positive attitudes towards Memrise smartphone application. The students found the application enjoyable, convenient and efficient learning tool. From the study, the use of the Memrise application is seen to have long-term and motivational benefits to students. For this reason, there is a need for further research to identify the long-term optimal effects of learning a language using smartphone applications.

Keywords: second language vocabulary learning, academic vocabulary, mobile learning technologies, smartphone applications

Procedia PDF Downloads 146

Authors: M. Bertsiou, E. Feloni, E. Baltas

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The proper management of the water supply and electricity is the key issue, especially in small islands, where sustainability has been combined with the autonomy and covering of water needs and the fast development in potential sectors of economy. In this research work a hybrid system in Fournoi island (Icaria), a small island of Aegean, has been evaluated in order to produce hydropower and cover water demands, as it can provide solutions to acute problems, such as the water scarcity or the instability of local power grids. The meaning and the utility of hybrid system and the cooperation with a desalination plant has also been considered. This kind of project has not yet been widely applied, so the consideration will give us valuable information about the storage of water and the controlled distribution of the generated clean energy. This process leads to the conclusions about the functioning of the system and the profitability of this project, covering the demand for water and electricity.

Keywords: hybrid system, water, electricity, island

Procedia PDF Downloads 310

Authors: Balbasatu Ibrahim

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In the 19th century, Hausaland an Islamic revolution known as the Sokoto Jihad took place that led to the establishment of the Sokoto Caliphate in 1804 under the leadership of the famous Sheik Uthman Bn Fodiye. Before the Jihad movement in Hausaland (now Northern Nigeria), women were left in ignorance and were used and dumped like old kitchen utensils. The sheik and his followers did their best to actualising women’s right to education by using their female family members as role models who were highly educated and renowned scholars. After the Jihad with the establishment of an Islamic state, the women scholars initiated different strategies to teach the generality of the women. The most efficient strategy was the ‘Yantaru Movement founded by Nana Asma’u the daughter of Sheikh Uthman Bn Fodiye in collaboration with her sisters around 1840. The ‘Yantaru movement is a women’s educational movement aimed at enlightening women in rural and urban areas. The move helped in massively mobilizing women for education. In addition to town pupils, women from villages and throughout the nooks and crannies of metropolitan Sokoto participated in the movement in the search for knowledge. Thus, the birth of the ‘Yantaru system of women’s education. The ‘Yantaru operates the three-tier system at village, town and the metropolitan capital of Sokoto. ‘Yantaru functions include imparting knowledge to elderly women and young girls. Step down enlightenment program on returning home. The most effective medium of communication in the ‘Yantaru movement was through poetry where scholars composed educational poems which were memorized by the ‘Yantaru, who on return recite it to fellow women at home. Through this system, many women were educated. This paper translated and examines one of such educative poems written by the second leader of the ‘Yantaru Movement Maryam Bn Uthman Bn Fodiye in 1855.

Keywords: English, Hausa language, public enlightenment, Maryam Bint Uthman Ibn Foduye

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Authors: Ravija Gunawardana, Banuka Athuraliya

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Machine learning has emerged as a powerful tool for disease diagnosis and prediction. The use of machine learning algorithms has the potential to improve the accuracy of disease prediction, thereby enabling medical professionals to provide more effective and personalized treatments. This study focuses on developing a machine-learning model for disease prediction using symptoms and X-ray images. The importance of this study lies in its potential to assist medical professionals in accurately diagnosing diseases, thereby improving patient outcomes. Respiratory diseases are a significant cause of morbidity and mortality worldwide, and chest X-rays are commonly used in the diagnosis of these diseases. However, accurately interpreting X-ray images requires significant expertise and can be time-consuming, making it difficult to diagnose respiratory diseases in a timely manner. By incorporating machine learning algorithms, we can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The study utilized the Mask R-CNN algorithm, which is a state-of-the-art method for object detection and segmentation in images, to process chest X-ray images. The model was trained and tested on a large dataset of patient information, which included both symptom data and X-ray images. The performance of the model was evaluated using a range of metrics, including accuracy, precision, recall, and F1-score. The results showed that the model achieved an accuracy rate of over 90%, indicating that it was able to accurately detect and segment regions of interest in the X-ray images. In addition to X-ray images, the study also incorporated symptoms as input data for disease prediction. The study used three different classifiers, namely Random Forest, K-Nearest Neighbor and Support Vector Machine, to predict diseases based on symptoms. These classifiers were trained and tested using the same dataset of patient information as the X-ray model. The results showed promising accuracy rates for predicting diseases using symptoms, with the ensemble learning techniques significantly improving the accuracy of disease prediction. The study's findings indicate that the use of machine learning algorithms can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The model developed in this study has the potential to assist medical professionals in diagnosing respiratory diseases more accurately and efficiently. However, it is important to note that the accuracy of the model can be affected by several factors, including the quality of the X-ray images, the size of the dataset used for training, and the complexity of the disease being diagnosed. In conclusion, the study demonstrated the potential of machine learning algorithms for disease prediction using symptoms and X-ray images. The use of these algorithms can improve the accuracy of disease diagnosis, ultimately leading to better patient care. Further research is needed to validate the model's accuracy and effectiveness in a clinical setting and to expand its application to other diseases.

Keywords: K-nearest neighbor, mask R-CNN, random forest, support vector machine

Procedia PDF Downloads 125

Authors: Dimitriya A. Mihaylova, Zlatka V. Valkova-Jarvis, Georgi L. Iliev

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One possible approach for maintaining the security of communication systems relies on Physical Layer Security mechanisms. However, in wireless time division duplex systems, where uplink and downlink channels are reciprocal, the channel estimate procedure is exposed to attacks known as pilot contamination, with the aim of having an enhanced data signal sent to the malicious user. The Shifted 2-N-PSK method involves two random legitimate pilots in the training phase, each of which belongs to a constellation, shifted from the original N-PSK symbols by certain degrees. In this paper, legitimate pilots’ offset values and their influence on the detection capabilities of the Shifted 2-N-PSK method are investigated. As the implementation of the technique depends on the relation between the shift angles rather than their specific values, the optimal interconnection between the two legitimate constellations is investigated. The results show that no regularity exists in the relation between the pilot contamination attacks (PCA) detection probability and the choice of offset values. Therefore, an adversary who aims to obtain the exact offset values can only employ a brute-force attack but the large number of possible combinations for the shifted constellations makes such a type of attack difficult to successfully mount. For this reason, the number of optimal shift value pairs is also studied for both 100% and 98% probabilities of detecting pilot contamination attacks. Although the Shifted 2-N-PSK method has been broadly studied in different signal-to-noise ratio scenarios, in multi-cell systems the interference from the signals in other cells should be also taken into account. Therefore, the inter-cell interference impact on the performance of the method is investigated by means of a large number of simulations. The results show that the detection probability of the Shifted 2-N-PSK decreases inversely to the signal-to-interference-plus-noise ratio.

Keywords: channel estimation, inter-cell interference, pilot contamination attacks, wireless communications

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Authors: B. J. Sandesh, Saurabha Jirgi, S. Vidya, Prakash Eljer, Gowri Srinivasa

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In this paper, we propose a framework to help users to search and retrieve the portions in the lecture video of their interest. This is achieved by temporally segmenting and indexing the lecture video using the topic keywords. We use transcribed text from the video and documents relevant to the video topic extracted from the web for this purpose. The keywords for indexing are found by applying the non-negative matrix factorization (NMF) topic modeling techniques on the web documents. Our proposed technique first creates indices on the transcribed documents using the topic keywords, and these are mapped to the video to find the start and end time of the portions of the video for a particular topic. This time information is stored in the index table along with the topic keyword which is used to retrieve the specific portions of the video for the query provided by the users.

Keywords: video indexing and retrieval, lecture videos, content based video search, multimodal indexing

Procedia PDF Downloads 237

Authors: Alana C. M. Santana, Mary L. G. S. Senna

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T Sustainable development is very important for the existence of life on the planet. The use of any space without planning can cause impacts on the environment, which depending on the proportion may be irreversible. Buritis beach is very frequented by visitors, but it has no information on use and does not have enough infrastructure to collaborate with the preservation of the environment. Therefore, the objective of this study was to adopt a simple control list of environmental impacts in river beaches, in order to identify the environmental impacts generated in the post-holiday seasons of Buritis beach and to characterize the beach in terms of infrastructure. The holidays that carried out the analyzes were the nationals of the second half of 2017, as well as the universal fraternization holiday of 2018. The results show that the beach needs investments in its infrastructure and educational campaigns to minimize environmental impacts caused by anthropic action.

Keywords: environmental impacts, sustainable development, Buritis Beach, Brazil.

Procedia PDF Downloads 140

Authors: R. Burahee, B. Chassinat, T. de Laclos, A. Dépée, A. Sastim

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The purpose of this paper is to propose a solution to detect, predict and reconstitute rain drops in real time – during the night – using an embedded material with an infrared camera. To prevent the system from needing too high hardware resources, simple models are considered in a powerful image treatment algorithm reducing considerably calculation time in OpenCV software. Using a smart model – drops will be matched thanks to a process running through two consecutive pictures for implementing a sophisticated tracking system. With this system drops computed trajectory gives information for predicting their future location. Thanks to this technique, treatment part can be reduced. The hardware system composed by a Raspberry Pi is optimized to host efficiently this code for real time execution.

Keywords: reconstitution, prediction, detection, rain drop, real time, raspberry, infrared

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Authors: M. U. Arshid, M. A. Kamal

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The engineering design process is the activities formulation, to help an engineer raising a plan with a specified goal and performance. The engineering design process is a multi-stage course of action including the conceptualization, research, feasibility studies, establishment of design parameters, preliminary and finally the detailed design. It is a progression from the abstract to the concrete; starting with probably abstract ideas about need, and thereafter elaborating detailed specifications of the object that would satisfy the needs, identified. Engineering design issues, problems, and solutions are discussed in this paper using qualitative approach from an information structure perspective. The objective is to identify the problems, to analyze them and propose solutions by integrating; innovation, practical experience, time and resource management, communications skills, isolating the problem in coordination with all stakeholders. Consequently, this would be beneficial for the engineering community to improve the Engineering design practices.

Keywords: engineering design, engineering design issues, innovation, public sector projects

Procedia PDF Downloads 327

Authors: Canan Duzan

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For most language learners, mastery of the speaking skill is the proof of the mastery of the foreign language. On the other hand, the speaking skill is considered as the most difficult aspect of language learning to develop for both learners and teachers. Especially in countries like Turkey where exposure to the target language is minimum and resources and opportunities provided for language practice are scarce, teaching and learning to speak the language become a real struggle for teachers and learners alike. Data collected from students, instructors, faculty members and the business sector in needs analysis studies conducted previously at Middle East Technical University (METU) consistently revealed the need for addressing the problem of lack of confidence in speaking English. Action was taken during the design of the only EAP speaking course offered in Modern Languages Department since lack of confidence is considered to be a serious barrier for effective communication and causes learners to suffer from insecurity, uncertainty and fear. “Confidence building” served as the guiding principle in the syllabus design, nature of the tasks created for the course and the assessment procedures to help learners become more confident speakers of English. In order to see the effectiveness of the decisions made during the design phase of the course and whether students become more confident speakers upon completion of the course, a case study was carried out with 100 students at METU. A questionnaire including both Likert-Scale and open-ended items were administered to students to collect data and this data were analyzed using the SPSS program. Group interviews were also carried out to gain more insight into the effectiveness of the course in terms of building speaking confidence. This presentation will explore the specific actions taken to develop students’ confidence based on the findings of program evaluation studies and to what extent the students believe these actions to be effective in improving their confidence. The unique design of this course and strategies adopted for confidence building are highly applicable in other EAP contexts and may yield similar positive results.

Keywords: confidence, EAP, speaking, strategy

Procedia PDF Downloads 389

Authors: Ziad Abdallah, Mohamad Oueidat, Ali El-Zaart

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Image Multi-label Classification (IMC) assigns a label or a set of labels to an image. The big demand for image annotation and archiving in the web attracts the researchers to develop many algorithms for this application domain. The existing techniques for IMC have two drawbacks: The description of the elementary characteristics from the image and the correlation between labels are not taken into account. In this paper, we present an algorithm (MIML-HOGLPP), which simultaneously handles these limitations. The algorithm uses the histogram of gradients as feature descriptor. It applies the Label Priority Power-set as multi-label transformation to solve the problem of label correlation. The experiment shows that the results of MIML-HOGLPP are better in terms of some of the evaluation metrics comparing with the two existing techniques.

Keywords: data mining, information retrieval system, multi-label, problem transformation, histogram of gradients

Procedia PDF Downloads 358

Authors: Roshanak Nouralian

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The primary focus of my Ph.D. dissertation revolves around the interconnection between language and culture, as well as the crucial role that language plays in facilitating communication and fostering integration within the host society for immigrants. This research specifically focuses on Iranian students studying at various universities in Vienna. Throughout this study, I have attempted to examine and analyze their challenges in various life situations in Austria. The broad dimensions of the research question led the research process to apply a constructivist grounded theory strategy. I have also used critical discourse analysis that is in line with constructivist GT's point of view to look closely at the borders, contradictions, and inequalities that came up in the participants' real-life experiences. Data from individual interviews and group discussions have expanded the research trajectory beyond disciplinary boundaries toward a transdisciplinary approach. The research findings indicate how the language policy of the host society leads to the establishment of power relationships and the arousal of a sense of cultural dominance among the research participants. This study investigates the problems experienced by participants in their daily interactions within the host society. Additionally, the results illustrate the development of a dependency relationship between participants and their host society despite linguistic policies that cause a sense of cultural hegemony. Conversely, the obtained data allowed me to examine the participants' language ideologies. The findings of this study show that social linguistics has the potential to go beyond the boundaries of its field. This is possible by using a variety of research strategies and analyzing people's real-life experiences to find out how language affects different parts of their daily lives. Therefore, in this conference, discussing the logic of employing a constructivist GT strategy along with critical discourse analysis (CDA) in this research, I intend to discuss the achieved results.

Keywords: cultural adapttaion, language policy, language ideology, cultural hegemony, transdisciplinary research, constructivist grounded theory, critical discourse analysis

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Authors: Sudha Subramani, Hua Wang

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Domestic Violence (DV) against women is now recognized to be a serious and widespread problem worldwide. There is a growing concern that violence against women has a global public health impact, as well as a violation of human rights. From the existing statistical surveys, it is revealed that there exists a strong relationship between DV and health issues of women like bruising, lacerations, depression, anxiety, flashbacks, sleep disturbances, hyper-arousal, emotional distress, sexually transmitted diseases and so on. This social problem is still considered as behind the closed doors issue and stigmatized topic. Women conceal their sufferings from family and friends, as they experience a lack of trust in others, feelings of shame and embarrassment among the society. Hence, women survivors of DV experience some barriers in seeking the support of specialized services such as health care access, crisis support, and legal guidance. Fortunately, with the popularity of social media like Facebook and Twitter, people share their opinions and emotional feelings to seek the social and emotional support, for sympathetic encouragement, to show compassion and empathy among the public. Considering the DV, social media plays a predominant role in creating the awareness and promoting the support services to the public, as we live in the golden era of social media. The various professional people like the public health researchers, clinicians, psychologists, social workers, national family health organizations, lawyers, and victims or their family and friends share the unprecedentedly valuable information (personal opinions and experiences) in a single platform to improve the social welfare of the community. Though each tweet or post contains a less informational value, the consolidation of millions of messages can generate actionable knowledge and provide valuable insights about the public opinion in general. Hence, this paper reports on an exploratory analysis of the effectiveness of social media for unobtrusive assessment of attitudes and awareness towards DV. In this paper, mixed methods such as qualitative analysis and text mining approaches are used to understand the social media disclosures of DV through the lenses of opinion sharing, anonymity, and support seeking. The results of this study could be helpful to avoid the cost of wide scale surveys, while still maintaining appropriate research conditions is to leverage the abundance of data publicly available on the web. Also, this analysis with data enrichment and consolidation would be useful in assisting advocacy and national family health organizations to provide information about resources and support, raise awareness and counter common stigmatizing attitudes about DV.

Keywords: domestic violence, social media, social stigma and support, women health

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Authors: Marcela De Oliveira, Marina P. Da Silva, Fernando C. G. Da Rocha, Jorge M. Santos, Jaime S. Cardoso, Paulo N. Lisboa-Filho

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Multiple Sclerosis (MS) is an immune-mediated disease of the central nervous system characterized by neurodegeneration, inflammation, demyelination, and axonal loss. Magnetic resonance imaging (MRI), due to the richness in the information details provided, is the gold standard exam for diagnosis and follow-up of neurodegenerative diseases, such as MS. Brain atrophy, the gradual loss of brain volume, is quite extensive in multiple sclerosis, nearly 0.5-1.35% per year, far off the limits of normal aging. Thus, the brain volume quantification becomes an essential task for future analysis of the occurrence atrophy. The analysis of MRI has become a tedious and complex task for clinicians, who have to manually extract important information. This manual analysis is prone to errors and is time consuming due to various intra- and inter-operator variability. Nowadays, computerized methods for MRI segmentation have been extensively used to assist doctors in quantitative analyzes for disease diagnosis and monitoring. Thus, the purpose of this work was to evaluate the brain volume in MRI of MS patients. We used MRI scans with 30 slices of the five patients diagnosed with multiple sclerosis according to the McDonald criteria. The computational methods for the analysis of images were carried out in two steps: segmentation of the brain and brain volume quantification. The first image processing step was to perform brain extraction by skull stripping from the original image. In the skull stripper for MRI images of the brain, the algorithm registers a grayscale atlas image to the grayscale patient image. The associated brain mask is propagated using the registration transformation. Then this mask is eroded and used for a refined brain extraction based on level-sets (edge of the brain-skull border with dedicated expansion, curvature, and advection terms). In the second step, the brain volume quantification was performed by counting the voxels belonging to the segmentation mask and converted in cc. We observed an average brain volume of 1469.5 cc. We concluded that the automatic method applied in this work can be used for the brain extraction process and brain volume quantification in MRI. The development and use of computer programs can contribute to assist health professionals in the diagnosis and monitoring of patients with neurodegenerative diseases. In future works, we expect to implement more automated methods for the assessment of cerebral atrophy and brain lesions quantification, including machine-learning approaches. Acknowledgements: This work was supported by a grant from Brazilian agency Fundação de Amparo à Pesquisa do Estado de São Paulo (number 2019/16362-5).

Keywords: brain volume, magnetic resonance imaging, multiple sclerosis, skull stripper

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Authors: Attila Vámosi, Tamás Mankovits, Dávid Huri, Imre Kocsis, Tamás Szabó

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Non-linear FEM calculations are indispensable when important technical information like operating performance of a rubber component is desired. Rubber bumpers built into air-spring structures may undergo large deformations under load, which in itself shows non-linear behavior. The changing contact range between the parts and the incompressibility of the rubber increases this non-linear behavior further. The material characterization of an elastomeric component is also a demanding engineering task. The shape optimization problem of rubber parts led to the study of FEM based calculation processes. This type of problems was posed and investigated by several authors. In this paper the time demand of certain calculation methods are studied and the possibilities of time reduction is presented.

Keywords: rubber bumper, data acquisition, finite element analysis, support vector regression

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Authors: Shagufta Tabassum, V. P. Pawar

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The study of static dielectric properties in a binary mixture of 1,2 dichloroethane (DE) and n,n dimethylformamide (DMF) polar liquids has been carried out in the frequency range of 10 MHz to 30 GHz for 11 different concentration using time domain reflectometry technique at 10ºC temperature. The dielectric relaxation study of solute-solvent mixture at microwave frequencies gives information regarding the creation of monomers and multimers as well as interaction between the molecules of the binary mixture. The least squares fit method is used to determine the values of dielectric parameters such as static dielectric constant (ε₀), dielectric constant at high frequency (ε_∞) and relaxation time (τ).

Keywords: shagufta shaikhexcess parameters, relaxation time, static dielectric constant, time domain reflectometry

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Authors: A. Kavita Murugkar, B. Anurag Kashyap

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With the Rights for Persons with Disabilities Act (RPWD Act) 2016, the Indian government has made it mandatory for all establishments, including Heritage Sites, to be accessible for People with Disabilities. However, recent access audit surveys done under the Accessible India Campaign by Ministry of Culture indicate that there are very few accessibility measures provided in the Heritage sites for people with disabilities. Though there are some measures for the mobility impaired, surveys brought out that there are almost no provisions for people with vision impairment (PwVI) in heritage sites thus depriving them of a reasonable physical & intellectual access that facilitates an enjoyable experience and enriching interpretation of the Heritage Site. There is a growing need to develop multisensory interpretative tools that can help the PwVI in perceiving heritage sites in the absence of vision. The purpose of this research was to examine the usability of an audio-tactile model as a haptic and sound-based strategy for augmenting the perception and experience of PwVI in a heritage site. The first phase of the project was a multi-stage phenomenological experimental study with visually impaired users to investigate the design parameters for developing an audio-tactile model for PwVI. The findings from this phase included user preferences related to the physical design of the model such as the size, scale, materials, details, etc., and the information that it will carry such as braille, audio output, tactile text, etc. This was followed by the second phase in which a working prototype of an audio-tactile model is designed and developed for a heritage site based on the findings from the first phase of the study. A nationally listed heritage site from the author’s city was selected for making the model. The model was lastly tested by visually impaired users for final refinements and validation. The prototype developed empowers People with Vision Impairment to navigate independently in heritage sites. Such a model if installed in every heritage site, can serve as a technological guide for the Person with Vision Impairment, giving information of the architecture, details, planning & scale of the buildings, the entrances, location of important features, lifts, staircases, and available, accessible facilities. The model was constructed using 3D modeling and digital printing technology. Though designed for the Indian context, this assistive technology for the blind can be explored for wider applications across the globe. Such an accessible solution can change the otherwise “incomplete’’ perception of the disabled visitor, in this case, a visually impaired visitor and augment the quality of their experience in heritage sites.

Keywords: accessibility, architectural perception, audio tactile model , inclusive heritage, multi-sensory perception, visual impairment, visitor experience

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Authors: Nitin Shravan, Sudarsun Santhiappan, B. Sivaselvan

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Subsection identification, in the context of Electronic Health Records (EHRs), is identifying the important sections for down-stream tasks like auto-coding. In this work, we classify the text present in EHRs according to their information, using machine learning and deep learning techniques. We initially describe briefly about the problem and formulate it as a text classification problem. Then, we discuss upon the methods from the literature. We try two approaches - traditional feature extraction based machine learning methods and deep learning methods. Through experiments on a private dataset, we establish that the deep learning methods perform better than the feature extraction based Machine Learning Models.

Keywords: deep learning, machine learning, semantic clinical classification, subsection identification, text classification

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Authors: Omar Romero-Hernandez, Federico Castillo, Armando Sanchez, Sergio Romero, Andrea Romero, Michael Mitchell

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Environmental policies for resource conservation in rural areas include subsidies on services and social programs to cover living expenses. Government's expectation is that rural communities who benefit from social programs, such as payment for ecosystem services, are provided with an incentive to conserve natural resources and preserve natural sinks for greenhouse gases. At the same time, global climate change has affected the lives of people worldwide. The capability to adapt to global warming depends on the available resources and the standard of living, putting rural communities at a disadvantage. This paper explores whether rural entrepreneurship can represent a solution to resource conservation and global warming adaptation in rural communities. The research focuses on a sample of two coffee communities in Oaxaca, Mexico. Researchers used geospatial information contained in aerial photographs of the geographical areas of interest. Households were identified in the photos via the roofs of households and georeferenced via coordinates. From the household population, a random selection of roofs was performed and received a visit. A total of 112 surveys were completed, including questions of socio-demographics, perception to climate change and adaptation activities. The population includes two groups of study: entrepreneurs and non-entrepreneurs. Data was sorted, filtered, and validated. Analysis includes descriptive statistics for exploratory purposes and a multi-regression analysis. Outcomes from the surveys indicate that coffee farmers, who demonstrate entrepreneurship skills and hire employees, are more eager to adapt to climate change despite the extreme adverse socioeconomic conditions of the region. We show that farmers with entrepreneurial tendencies are more creative in using innovative farm practices such as the planting of shade trees, the use of live fencing, instead of wires, and watershed protection techniques, among others. This result counters the notion that small farmers are at the mercy of climate change and have no possibility of being able to adapt to a changing climate. The study also points to roadblocks that farmers face when coping with climate change. Among those roadblocks are a lack of extension services, access to credit, and reliable internet, all of which reduces access to vital information needed in today’s constantly changing world. Results indicate that, under some circumstances, funding and supporting entrepreneurship programs may provide more benefit than traditional social programs.

Keywords: entrepreneurship, global warming, rural communities, climate change adaptation

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Authors: Issam Ben Jami

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Information retrieval in digital libraries is very important because most famous historical documents occupy a significant value. The word spotting in historical documents is a very difficult notion, because automatic recognition of such documents is naturally cursive, it represents a wide variability in the level scale and translation words in the same documents. We first present a system for the automatic recognition, based on the extraction of interest points words from the image model. The extraction phase of the key points is chosen from the representation of the image as a synthetic description of the shape recognition in a multidimensional space. As a result, we use advanced methods that can find and describe interesting points invariant to scale, rotation and lighting which are linked to local configurations of pixels. We test this approach on documents of the 15th century. Our experiments give important results.

Keywords: feature matching, historical documents, pattern recognition, word spotting

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Authors: Shahab Khan, Damiya Saghir

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With the advent of space technology, a new era began where space, considered the new ‘High ground,’ is used for a variety of commercial (communications, weather and navigational information, Earth resources monitoring and imagery) and military applications (surveillance, tracking, reconnaissance and espionage of adversaries). With the ever-evolving geo-political environment, where now the US foreseeing India as a counterbalance to China’s economic and military rise, significant growth in strategic collaboration between US and India has been witnessed, particularly in the space domain. This is creating a strategic imbalance in South Asia with implications for all regional countries. This research explores the present and future of Indo-US strategic collaboration in the space domain with envisaged effects and challenges for countries in the South Asian region.

Keywords: space, satellites, Indo-US strategic agreements in space domain, balance of power in South Asian region

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Authors: Selin Tosun

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The improvements in technology have started to transform the way we live, work, play, and commute in our cities. The emerging smart city understanding has been paving the way for more efficient, more useful, and more profitable cities. Smart sensors, smart lighting, smart waste, water and electricity management, smart transportation and communication systems are introduced to cities at a rapid pace. In today's world, innovation is often correlated with start-up companies and technological pioneers seeking broader economic objectives such as production and competitiveness. The government's position is primarily that of an enabler, with creativity mostly coming from the private sector. The paper argues that to achieve sustainable development, the ways in which smart and sustainable city approaches are being applied to cities need to be redefined. The research aims to address common discussions in the discourse of smart and sustainable cities criticizing the priority of lifestyle sterilization over human-centered sustainable interventions and social innovation strategies. The dichotomy between the fact that smart cities are mostly motivated by the competitive global market and the fact that the delocalization is, in fact, their biggest problem in the way of becoming authentic, sustainable cities is the main challenge that we face today. In other words, the key actors in smart cities have different and somewhat conflicting interests and demands. By reviewing the roles of the public and private actors in smart city making, the paper aspires to reconceptualize the understanding of “smartness” in achieving sustainable development in which the “smartness” is understood as a multi-layered complex phenomenon that can be channeled through different dynamics. The case cities around the world are explored and compared in terms of their technological innovations, governance and policy innovations, public-private stakeholder relationships, and the understanding of the public realm. The study aims to understand the current trends and general dynamics in the field, key issues that are being addressed, the scale that is preferred to reflect upon and the projects that are designed for the particular issues.

Keywords: smart city, sustainable development, technological innovation, social innovation

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Authors: Nestor A. Garcia Fragoso, Tetyana Baydyk, Ernst Kussul

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This article contains information from our investigation in the field of voice recognition. For this purpose, we created a voice database that contains different phrases in two languages, English and Spanish, for men and women. As a classifier, the LIRA (Limited Receptive Area) grayscale neural classifier was selected. The LIRA grayscale neural classifier was developed for image recognition tasks and demonstrated good results. Therefore, we decided to develop a recognition system using this classifier for voice recognition. From a specific set of speakers, we can recognize the speaker’s voice. For this purpose, the system uses spectrograms of the voice signals as input to the system, extracts the characteristics and identifies the speaker. The results are described and analyzed in this article. The classifier can be used for speaker identification in security system or smart buildings for different types of intelligent devices.

Keywords: extreme learning, LIRA neural classifier, speaker identification, voice recognition

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Authors: C. Angel, S. Asha

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Despite the advances made in various new technologies, application of these technologies for agriculture still remains a formidable task, as it involves integration of diverse domains for monitoring the different process involved in agricultural management. Advances in ambient intelligence technology represents one of the most powerful technology for increasing the yield of agricultural crops and to mitigate the impact of water scarcity, climatic change and methods for managing pests, weeds, and diseases. This paper proposes a GPS-assisted, machine to machine solutions that combine information collected by multiple sensors for the automated management of paddy crops. To maintain the economic viability of paddy cultivation, the various techniques used in agriculture are discussed and a novel system which uses ambient intelligence technique is proposed in this paper. The ambient intelligence based agricultural system gives a great scope.

Keywords: ambient intelligence, agricultural technology, smart agriculture, precise farming

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Authors: Prateep Wajeetongratana

Abstract:

This research aims to study the audit quality that affected to the reputation of the certified public accountants in Thailand. The researcher defined the population for this research as a group of the certified public accountants in Thailand who are the member of the federation of accounting professions under the royal patronage of his majesty the king also disclose their information .The total sampling size is 325. The results showed the audit quality factor has influence to the reputation of the certified public accountants in Thailand by accuracy auditing, objectiveness auditing and clearness auditing .These factors show by y1 = 1.381 + .372x1.1 + .309x1.2 + .305x1.3 can be describe as professional standard strictly factor (Y.1.1) and the new clients raised from word of mount of old clients regularly factor (Y.1.2) by regression coefficient (R2) as.242, this shows that such variables could predict the audit quality variable as 24.2 percent.

Keywords: audit quality, certified public accountants in Thailand, reputation

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Authors: Chang Liu, Rui Xing, Liyan Tang, Guohong Wang

Abstract:

Entrepreneurial actions are based on entrepreneurial decisions. The quality of decisions influences entrepreneurial activities and subsequent new venture performance. Uncertainty of surroundings put heightened demands on the team as a whole, and each team member. Diverse team composition provides rich information, which a team can draw when making complex decisions. However, team heterogeneity may cause emotional conflicts, which is adverse to team outcomes. Thus, the effects of team heterogeneity on team outcomes are complex. Although team heterogeneity is an essential factor influencing entrepreneurial decision-making, there is a lack of empirical analysis on under what conditions team heterogeneity plays a positive role in promoting decision-making quality. Entrepreneurial teams always struggle with complex tasks. How a team shapes its teamwork is key in resolving constant issues. As a collective regulatory process, team reflexivity is characterized by continuous joint evaluation and discussion of team goals, strategies, and processes, and adapt them to current or anticipated circumstances. It enables diversified information to be shared and overtly discussed. Instead of hostile interpretation of opposite opinions team members take them as useful insights from different perspectives. Team reflexivity leads to better integration of expertise to avoid the interference of negative emotions and conflict. Therefore, we propose that team reflexivity is a conditional factor that influences the impact of team heterogeneity on high-quality entrepreneurial decisions. In this study, we identify team heterogeneity as a crucial determinant of entrepreneurial decision quality. Integrating the literature on decision-making and team heterogeneity, we investigate the relationship between team heterogeneity and entrepreneurial decision-making quality, treating team reflexivity as a moderator. We tested our hypotheses using the hierarchical regression method and the data gathered from 63 teams and 205 individual members from 45 new firms in China's first-tier cities such as Beijing, Shanghai, and Shenzhen. This research found that both teams' education heterogeneity and teams' functional background heterogeneity were significantly positively related to entrepreneurial decision-making quality, and the positive relation was stronger in teams with a high level of team reflexivity. While teams' specialization of education heterogeneity was negatively related to decision-making quality, and the negative relationship was weaker in teams with a high level of team reflexivity. We offer two contributions to decision-making and entrepreneurial team literatures. Firstly, our study enriches the understanding of the role of entrepreneurial team heterogeneity in entrepreneurial decision-making quality. Different from previous entrepreneurial decision-making literatures, which focus more on decision-making modes of entrepreneurs and the top management team, this study is a significant attempt to highlight that entrepreneurial team heterogeneity makes a unique contribution to generating high-quality entrepreneurial decisions. Secondly, this study introduced team reflexivity as the moderating variable, to explore the boundary conditions under which the entrepreneurial team heterogeneity play their roles.

Keywords: decision-making quality, entrepreneurial teams, education heterogeneity, functional background heterogeneity, specialization of education heterogeneity

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Authors: Ajayi Olusola Olajide, Alonge Olaide Moses

Abstract:

Predicting the outcome of soccer matches poses an interesting challenge for which it is realistically impossible to successfully do so for every match. Despite this, there are lots of resources that are being expended on the correct prediction of soccer matches weekly, and all over the world. Soccer Match Result Prediction System Model (SMRPSM) is a system that is proposed whereby the results of matches between two soccer teams are auto-generated, with the added excitement of giving users a chance to test their predictive abilities. Soccer teams from different league football are loaded by the application, with each team’s corresponding manager and other information like team location, team logo and nickname. The user is also allowed to interact with the system by selecting the match to be predicted and viewing of the results of completed matches after registering/logging in.

Keywords: predicting, soccer match, outcome, soccer, matches, result prediction, system, model

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Authors: Muhammad Afzal, Shahbaz Mushtaq, Duc-Anh-An-Vo, Kathryn Reardon Smith, Thanh Ma

Abstract:

Climate change has become one of the most challenging environmental issues in the 21st century. Climate change-induced natural disasters, especially floods, are the major factors of livelihood vulnerability, impacting millions of individuals worldwide. Evaluating and mitigating the effects of floods requires an in-depth understanding of the relationship between vulnerability and livelihood capital assets. Using an integrated approach, sustainable livelihood framework, and system thinking approach, the study developed a conceptual model of a generalized livelihood system in District Rajanpur, Pakistan. The model visualizes the livelihood vulnerability system as a whole and identifies the key feedback loops likely to influence the livelihood vulnerability. The study suggests that such conceptual models provide effective communication and understanding tools to stakeholders and decision-makers to anticipate the problem and design appropriate policies. It can also serve as an evaluation technique for rural livelihood policy and identify key systematic interventions. The key finding of the study reveals that household income, health, and education are the major factors behind the livelihood vulnerability of the rural poor of District Rajanpur. The Pakistani government tried to reduce the livelihood vulnerability of the region through different income, health, and education programs, but still, many changes are required to make these programs more effective especially during the flood times. The government provided only cash to vulnerable and marginalized families through income support programs, but this study suggests that along with the cash, the government must provide seed storage facilities and access to crop insurance to the farmers. Similarly, the government should establish basic health units in villages and frequent visits of medical mobile vans should be arranged with advanced medical lab facilities during and after the flood.

Keywords: livelihood vulnerability, rural communities, flood, sustainable livelihood framework, system dynamics, Pakistan

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