Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6666

Search results for: application categorization

6666 Network Traffic Classification Scheme for Internet Network Based on Application Categorization for Ipv6

Authors: Yaser Miaji, Mohammed Aloryani

Abstract:

The rise of recent applications in everyday implementation like videoconferencing, online recreation and voice speech communication leads to pressing the need for novel mechanism and policy to serve this steep improvement within the application itself and users‟ wants. This diversity in web traffics needs some classification and prioritization of the traffics since some traffics merit abundant attention with less delay and loss, than others. This research is intended to reinforce the mechanism by analysing the performance in application according to the proposed mechanism implemented. The mechanism used is quite direct and analytical. The mechanism is implemented by modifying the queue limit in the algorithm.

Keywords: traffic classification, IPv6, internet, application categorization

Procedia PDF Downloads 427
6665 A Mega-Analysis of the Predictive Power of Initial Contact within Minimal Social Network

Authors: Cathal Ffrench, Ryan Barrett, Mike Quayle

Abstract:

It is accepted in social psychology that categorization leads to ingroup favoritism, without further thought given to the processes that may co-occur or even precede categorization. These categorizations move away from the conceptualization of the self as a unique social being toward an increasingly collective identity. Subsequently, many individuals derive much of their self-evaluations from these collective identities. The seminal literature on this topic argues that it is primarily categorization that evokes instances of ingroup favoritism. Apropos to these theories, we argue that categorization acts to enhance and further intergroup processes rather than defining them. More accurately, we propose categorization aids initial ingroup contact and this first contact is predictive of subsequent favoritism on individual and collective levels. This analysis focuses on Virtual Interaction APPLication (VIAPPL) based studies, a software interface that builds on the flaws of the original minimal group studies. The VIAPPL allows the exchange of tokens in an intra and inter-group manner. This token exchange is how we classified the first contact. The study involves binary longitudinal analysis to better understand the subsequent exchanges of individuals based on who they first interacted with. Studies were selected on the criteria of evidence of explicit first interactions and two-group designs. Our findings paint a compelling picture in support of a motivated contact hypothesis, which suggests that an individual’s first motivated contact toward another has strong predictive capabilities for future behavior. This contact can lead to habit formation and specific favoritism towards individuals where contact has been established. This has important implications for understanding how group conflict occurs, and how intra-group individual bias can develop.

Keywords: categorization, group dynamics, initial contact, minimal social networks, momentary contact

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6664 A Methodology for Automatic Diversification of Document Categories

Authors: Dasom Kim, Chen Liu, Myungsu Lim, Su-Hyeon Jeon, ByeoungKug Jeon, Kee-Young Kwahk, Namgyu Kim

Abstract:

Recently, numerous documents including unstructured data and text have been created due to the rapid increase in the usage of social media and the Internet. Each document is usually provided with a specific category for the convenience of the users. In the past, the categorization was performed manually. However, in the case of manual categorization, not only can the accuracy of the categorization be not guaranteed but the categorization also requires a large amount of time and huge costs. Many studies have been conducted towards the automatic creation of categories to solve the limitations of manual categorization. Unfortunately, most of these methods cannot be applied to categorizing complex documents with multiple topics because the methods work by assuming that one document can be categorized into one category only. In order to overcome this limitation, some studies have attempted to categorize each document into multiple categories. However, they are also limited in that their learning process involves training using a multi-categorized document set. These methods therefore cannot be applied to multi-categorization of most documents unless multi-categorized training sets are provided. To overcome the limitation of the requirement of a multi-categorized training set by traditional multi-categorization algorithms, we previously proposed a new methodology that can extend a category of a single-categorized document to multiple categorizes by analyzing relationships among categories, topics, and documents. In this paper, we design a survey-based verification scenario for estimating the accuracy of our automatic categorization methodology.

Keywords: big data analysis, document classification, multi-category, text mining, topic analysis

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6663 Categorization of Biosolids, a Vital Biological Resource for Sustainable Agriculture

Authors: Susmita Sharma, Pankaj Pathak

Abstract:

Biosolids are by-products of municipal and industrial wastewater treatment process. The generation of the biosolids is increasing at an alarming rate due to the implementation of strict environmental legislation to improve the quality of discharges from wastewater treatment plant. As such, proper management and safe disposal of sewage sludge have become a worldwide topic of research. Biosolids, rich in organic matter and essential micro and macronutrients; can be used as a soil conditioner, to cut fertilizer costs and create favorable conditions for vegetation. However, it also contains pathogens and heavy metals which are undesirable as they are harmful to both humans and the environment. Therefore, for safe utilization of biosolids for land application purposes, categorization of the contaminant and pathogen is mandatory. In this context, biosolids collected from a wastewater treatment plant in Maharashtra are utilized to determine its physical, chemical and microbiological attributes. This study would ascertain, if the use of these materials from the specific site, are suitable for agriculture. Further, efforts have also been made to present the internationally acceptable legal standards and guidelines for biosolids management or application.

Keywords: biosolids, sewage, heavy metal, sustainable agriculture

Procedia PDF Downloads 253
6662 Human Errors in IT Services, HFACS Model in Root Cause Categorization

Authors: Kari Saarelainen, Marko Jantti

Abstract:

IT service trending of root causes of service incidents and problems is an important part of proactive problem management and service improvement. Human error related root causes are an important root cause category also in IT service management, although it’s proportion among root causes is smaller than in the other industries. The research problem in this study is: How root causes of incidents related to human errors should be categorized in an ITSM organization to effectively support service improvement. Categorization based on IT service management processes and based on Human Factors Analysis and Classification System (HFACS) taxonomy was studied in a case study. HFACS is widely used in human error root cause categorization across many industries. Combining these two categorization models in a two dimensional matrix was found effective, yet impractical for daily work.

Keywords: IT service management, ITIL, incident, problem, HFACS, swiss cheese model

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6661 Role-Governed Categorization and Category Learning as a Result from Structural Alignment: The RoleMap Model

Authors: Yolina A. Petrova, Georgi I. Petkov

Abstract:

The paper presents a symbolic model for category learning and categorization (called RoleMap). Unlike the other models which implement learning in a separate working mode, role-governed category learning and categorization emerge in RoleMap while it does its usual reasoning. The model is based on several basic mechanisms known as reflecting the sub-processes of analogy-making. It steps on the assumption that in their everyday life people constantly compare what they experience and what they know. Various commonalities between the incoming information (current experience) and the stored one (long-term memory) emerge from those comparisons. Some of those commonalities are considered to be highly important, and they are transformed into concepts for further use. This process denotes the category learning. When there is missing knowledge in the incoming information (i.e. the perceived object is still not recognized), the model makes anticipations about what is missing, based on the similar episodes from its long-term memory. Various such anticipations may emerge for different reasons. However, with time only one of them wins and is transformed into a category member. This process denotes the act of categorization.

Keywords: analogy-making, categorization, category learning, cognitive modeling, role-governed categories

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6660 Role of Physical Appearance in Associating People with a Group Identity

Authors: Gurleen Kaur

Abstract:

Being tall-short, fat-thin, black-white, etc. is an inevitable part of how people perceive you. This association of people with your external appearance carves out an identity for you. This paper will look at the reasons why people relate a person to a particular categorization on the basis of his/her physical appearance. The paper delves into reasons for this categorization into groups: Subconscious grouping, personal gain, ease of relating to the group, and social acceptance. Development of certain unique physical features also leads to a person relating himself to a collective identity. Thus, this paper will support the fact that physical appearance plays a crucial role in categorization of people into groups and hence forming a group identity for them. This paper is divided into three parts. The first part will discuss what physical appearance is and how is it linked to our daily lives. The second part will talk about why it works i.e. why this factor of external appearance is important in formation of identity. The last part will talk about the factors which lead to categorization of identity because of physical appearance.

Keywords: group identity, physical appearance, subconscious grouping, collective identity

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6659 Amharic Text News Classification Using Supervised Learning

Authors: Misrak Assefa

Abstract:

The Amharic language is the second most widely spoken Semitic language in the world. There are several new overloaded on the web. Searching some useful documents from the web on a specific topic, which is written in the Amharic language, is a challenging task. Hence, document categorization is required for managing and filtering important information. In the classification of Amharic text news, there is still a gap in the domain of information that needs to be launch. This study attempts to design an automatic Amharic news classification using a supervised learning mechanism on four un-touch classes. To achieve this research, 4,182 news articles were used. Naive Bayes (NB) and Decision tree (j48) algorithms were used to classify the given Amharic dataset. In this paper, k-fold cross-validation is used to estimate the accuracy of the classifier. As a result, it shows those algorithms can be applicable in Amharic news categorization. The best average accuracy result is achieved by j48 decision tree and naïve Bayes is 95.2345 %, and 94.6245 % respectively using three categories. This research indicated that a typical decision tree algorithm is more applicable to Amharic news categorization.

Keywords: text categorization, supervised machine learning, naive Bayes, decision tree

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6658 A New Categorization of Image Quality Metrics Based on a Model of Human Quality Perception

Authors: Maria Grazia Albanesi, Riccardo Amadeo

Abstract:

This study presents a new model of the human image quality assessment process: the aim is to highlight the foundations of the image quality metrics proposed in literature, by identifying the cognitive/physiological or mathematical principles of their development and the relation with the actual human quality assessment process. The model allows to create a novel categorization of objective and subjective image quality metrics. Our work includes an overview of the most used or effective objective metrics in literature, and, for each of them, we underline its main characteristics, with reference to the rationale of the proposed model and categorization. From the results of this operation, we underline a problem that affects all the presented metrics: the fact that many aspects of human biases are not taken in account at all. We then propose a possible methodology to address this issue.

Keywords: eye-tracking, image quality assessment metric, MOS, quality of user experience, visual perception

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6657 Electricity Market Categorization for Smart Grid Market Testing

Authors: Rebeca Ramirez Acosta, Sebastian Lenhoff

Abstract:

Decision makers worldwide need to determine if the implementation of a new market mechanism will contribute to the sustainability and resilience of the power system. Due to smart grid technologies, new products in the distribution and transmission system can be traded; however, the impact of changing a market rule will differ between several regions. To test systematically those impacts, a market categorization has been compiled and organized in a smart grid market testing toolbox. This toolbox maps all actual energy products and sets the basis for running a co-simulation test with the new rule to be implemented. It will help to measure the impact of the new rule, based on the sustainable and resilience indicators.

Keywords: co-simulation, electricity market, smart grid market, market testing

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6656 Preoperative Anxiety Evaluation: Comparing the Visual Facial Anxiety Scale/Yumul Faces Anxiety Scale, Numerical Verbal Rating Scale, Categorization Scale, and the State-Trait Anxiety Inventory

Authors: Roya Yumul, Chse, Ofelia Loani Elvir Lazo, David Chernobylsky, Omar Durra

Abstract:

Background: Preoperative anxiety has been shown to be caused by the fear associated with surgical and anesthetic complications. However, the current gold standard for assessing patient anxiety, the STAI, is problematic to use in the preoperative setting, given the duration and concentration required to complete the 40-item extensive questionnaire. Our primary aim in the study is to investigate the correlation of the Visual Facial Anxiety Scale (VFAS) and Numerical Verbal Rating Scale (NVRS) to State-Trait Anxiety Inventory (STAI) to determine the optimal anxiety scale to use in the perioperative setting. Methods: A clinical study of patients undergoing various surgeries was conducted utilizing each of the preoperative anxiety scales. Inclusion criteria included patients undergoing elective surgeries, while exclusion criteria included patients with anesthesia contraindications, inability to comprehend instructions, impaired judgment, substance abuse history, and those pregnant or lactating. 293 patients were analyzed in terms of demographics, anxiety scale survey results, and anesthesia data via Spearman Coefficients, Chi-Squared Analysis, and Fischer’s exact test utilized for comparative analysis. Results: Statistical analysis showed that VFAS had a higher correlation to STAI than NVRS (rs=0.66, p<0.0001 vs rs=0.64, p<0.0001). The combined VFAS-Categorization Scores showed the highest correlation with the gold standard (rs=0.72, p<0.0001). Subgroup analysis showed similar results. STAI evaluation time (247.7 ± 54.81 sec) far exceeds VFAS (7.29 ± 1.61 sec), NVRS (7.23 ± 1.60 sec), and Categorization scales (7.29 ± 1.99 sec). Patients preferred VFAS (54.4%), Categorization (11.6%), and NVRS (8.8%). Anesthesiologists preferred VFAS (63.9%), NVRS (22.1%) and Categorization Scales (14.0%). Of note, the top five causes of preoperative anxiety where determine to be waiting (56.5%), pain (42.5%), family concerns (40.5%), no information about surgery (40.1%), or anesthesia (31.6%). Conclusions: Combined VFAS-Categorization Score (VCS) demonstrates the highest correlation to the gold standard, STAI. Both VFAS and Categorization tests also take significantly less time than STAI, which is critical in the preoperative setting. Among both patients and anesthesiologists, VFAS was the most preferred scale. This forms the basis of the Yumul FACES Anxiety Scale, designed for quick quantization and assessment in the preoperative setting while maintaining a high correlation to the golden standard. Additional studies using the formulated Yumul FACES Anxiety Scale are merited.

Keywords: preoperative anxiety, visual facial anxiety scale, numerical verbal anxiety scale, state-trait anxiety inventory

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6655 Comparison of the Yumul Faces Anxiety Scale to the Categorization Scale, the Numerical Verbal Rating Scale (NVRS), and the State-Trait Anxiety Inventory (STAI) for Preoperative Anxiety Evaluation

Authors: Ofelia Loani Elvir Lazo, Roya Yumul, David Chernobylsky, Omar Durra

Abstract:

Background:It is crucial to detect the patient’s existing anxiety to assist patients in perioperative setting which isto be cause by fear associated with surgical and anesthetic complications. However, the current gold standard for assessing patient anxiety, the STAI, is problematic to use in the preoperative setting given the duration and concentration required to complete the 40-item questionnaire. Our primary aim in the study is to investigate the correlation of the Yumul Visual Facial Anxiety Scale (VFAS) and Numerical Verbal Rating Scale (NVRS) to State-Trait Anxiety Inventory (STAI) to determine the optimal anxiety scale to use in the perioperative setting. Methods: A clinical study of patients undergoing various surgeries was conducted utilizing each of the preoperative anxiety scales. Inclusion criteria included patients undergoing elective surgeries, while exclusion criteria included patients with anesthesia contraindications, inability to comprehend instructions, impaired judgement, substance abuse history, and those pregnant or lactating. 293 patients were analyzed in terms of demographics, anxiety scale survey results, and anesthesia data via Spearman Coefficients, Chi-Squared Analysis, and Fischer’s exact test utilized for comparison analysis. Results: Statistical analysis showed that VFAS had a higher correlation to STAI than NVRS (rs=0.66, p<0.0001 vs rs=0.64, p<0.0001). The combined VFAS-Categorization Scores showed the highest correlation with the gold standard (rs=0.72, p<0.0001). Subgroup analysis showed similar results. STAI evaluation time (247.7 ± 54.81 sec) far exceed VFAS (7.29 ± 1.61 sec), NVRS (7.23 ± 1.60 sec), and Categorization scales (7.29 ± 1.99 sec). Patients preferred VFAS (54.4%), Categorization (11.6%), and NVRS (8.8%). Anesthesiologists preferred VFAS (63.9%), NVRS (22.1%) and Categorization Scales (14.0%). Of note, the top five causes of preoperative anxiety where determine to be waiting (56.5%), pain (42.5%), family concerns (40.5%), no information about surgery (40.1%) or anesthesia (31.6%). Conclusion:Both VFAS and Categorization tests also take significantly less time than STAI, which is critical in the preoperative setting. Combined VFAS-Categorization Score (VCS) demonstrates the highest correlation to the gold standard, STAI. Among both patients and anesthesiologists, VFAS was the most preferred scale. This forms the basis of the Yumul Faces Anxiety Scale, designed for quick quantization and assessment in the preoperative setting while maintaining a high correlation to the golden standard. Additional studies using the formulated Yumul Faces Anxiety Scale are merited.

Keywords: numerical verbal anxiety scale, preoperative anxiety, state-trait anxiety inventory, visual facial anxiety scale

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6654 Discovering the Dimension of Abstractness: Structure-Based Model that Learns New Categories and Categorizes on Different Levels of Abstraction

Authors: Georgi I. Petkov, Ivan I. Vankov, Yolina A. Petrova

Abstract:

A structure-based model of category learning and categorization at different levels of abstraction is presented. The model compares different structures and expresses their similarity implicitly in the forms of mappings. Based on this similarity, the model can categorize different targets either as members of categories that it already has or creates new categories. The model is novel using two threshold parameters to evaluate the structural correspondence. If the similarity between two structures exceeds the higher threshold, a new sub-ordinate category is created. Vice versa, if the similarity does not exceed the higher threshold but does the lower one, the model creates a new category on higher level of abstraction.

Keywords: analogy-making, categorization, learning of categories, abstraction, hierarchical structure

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6653 Deep-Learning Coupled with Pragmatic Categorization Method to Classify the Urban Environment of the Developing World

Authors: Qianwei Cheng, A. K. M. Mahbubur Rahman, Anis Sarker, Abu Bakar Siddik Nayem, Ovi Paul, Amin Ahsan Ali, M. Ashraful Amin, Ryosuke Shibasaki, Moinul Zaber

Abstract:

Thomas Friedman, in his famous book, argued that the world in this 21st century is flat and will continue to be flatter. This is attributed to rapid globalization and the interdependence of humanity that engendered tremendous in-flow of human migration towards the urban spaces. In order to keep the urban environment sustainable, policy makers need to plan based on extensive analysis of the urban environment. With the advent of high definition satellite images, high resolution data, computational methods such as deep neural network analysis, and hardware capable of high-speed analysis; urban planning is seeing a paradigm shift. Legacy data on urban environments are now being complemented with high-volume, high-frequency data. However, the first step of understanding urban space lies in useful categorization of the space that is usable for data collection, analysis, and visualization. In this paper, we propose a pragmatic categorization method that is readily usable for machine analysis and show applicability of the methodology on a developing world setting. Categorization to plan sustainable urban spaces should encompass the buildings and their surroundings. However, the state-of-the-art is mostly dominated by classification of building structures, building types, etc. and largely represents the developed world. Hence, these methods and models are not sufficient for developing countries such as Bangladesh, where the surrounding environment is crucial for the categorization. Moreover, these categorizations propose small-scale classifications, which give limited information, have poor scalability and are slow to compute in real time. Our proposed method is divided into two steps-categorization and automation. We categorize the urban area in terms of informal and formal spaces and take the surrounding environment into account. 50 km × 50 km Google Earth image of Dhaka, Bangladesh was visually annotated and categorized by an expert and consequently a map was drawn. The categorization is based broadly on two dimensions-the state of urbanization and the architectural form of urban environment. Consequently, the urban space is divided into four categories: 1) highly informal area; 2) moderately informal area; 3) moderately formal area; and 4) highly formal area. In total, sixteen sub-categories were identified. For semantic segmentation and automatic categorization, Google’s DeeplabV3+ model was used. The model uses Atrous convolution operation to analyze different layers of texture and shape. This allows us to enlarge the field of view of the filters to incorporate larger context. Image encompassing 70% of the urban space was used to train the model, and the remaining 30% was used for testing and validation. The model is able to segment with 75% accuracy and 60% Mean Intersection over Union (mIoU). In this paper, we propose a pragmatic categorization method that is readily applicable for automatic use in both developing and developed world context. The method can be augmented for real-time socio-economic comparative analysis among cities. It can be an essential tool for the policy makers to plan future sustainable urban spaces.

Keywords: semantic segmentation, urban environment, deep learning, urban building, classification

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6652 Functional Dyspepsia and Irritable Bowel Syndrome: Life sketches of Functional Illnesses (Non-Organic) in West Bengal, India

Authors: Urmita Chakraborty

Abstract:

To start with, Organic Illnesses are no longer considered as only health difficulties. Functional Illnesses that are emotional in origin have become the search areas in many investigations. In the present study, an attempt has made to study the psychological nature of Functional Gastro-Intestinal Disorders (FGID) in West Bengal. In the specialty of Gastroenterology, the medically unexplained symptom-based conditions are known as Functional Gastrointestinal Disorder (FGID). In the present study, Functional Dyspepsia (FD) and Irritable Bowel Syndrome (IBS) have been taken for investigations. 72 cases have been discussed in this context. Results of the investigation have been analyzed in terms of a qualitative framework. Theoretical concepts on persistent thoughts and behaviors will be delineated in the analysis. Processes of self-categorization will be implemented too. Aspects of Attachments and controlling of affect as well as meta-cognitive appraisals are further considered for the depiction.

Keywords: functional dyspepsia, irritable bowel syndrome, self-categorization

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6651 System Response of a Variable-Rate Aerial Application System

Authors: Daniel E. Martin, Chenghai Yang

Abstract:

Variable-rate aerial application systems are becoming more readily available; however, aerial applicators typically only use the systems for constant-rate application of materials, allowing the systems to compensate for upwind and downwind ground speed variations. Much of the resistance to variable-rate aerial application system adoption in the U.S. pertains to applicator’s trust in the systems to turn on and off automatically as desired. The objectives of this study were to evaluate a commercially available variable-rate aerial application system under field conditions to demonstrate both the response and accuracy of the system to desired application rate inputs. This study involved planting oats in a 35-acre fallow field during the winter months to establish a uniform green backdrop in early spring. A binary (on/off) prescription application map was generated and a variable-rate aerial application of glyphosate was made to the field. Airborne multispectral imagery taken before and two weeks after the application documented actual field deposition and efficacy of the glyphosate. When compared to the prescription application map, these data provided application system response and accuracy information. The results of this study will be useful for quantifying and documenting the response and accuracy of a commercially available variable-rate aerial application system so that aerial applicators can be more confident in their capabilities and the use of these systems can increase, taking advantage of all that aerial variable-rate technologies have to offer.

Keywords: variable-rate, aerial application, remote sensing, precision application

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6650 A Collaborative Problem Driven Approach to Design an HR Analytics Application

Authors: L. Atif, C. Rosenthal-Sabroux, M. Grundstein

Abstract:

The requirements engineering process is a crucial phase in the design of complex systems. The purpose of our research is to present a collaborative problem-driven requirements engineering approach that aims at improving the design of a Decision Support System as an Analytics application. This approach has been adopted to design a Human Resource management DSS. The Requirements Engineering process is presented as a series of guidelines for activities that must be implemented to assure that the final product satisfies end-users requirements and takes into account the limitations identified. For this, we know that a well-posed statement of the problem is “a problem whose crucial character arises from collectively produced estimation and a formulation found to be acceptable by all the parties”. Moreover, we know that DSSs were developed to help decision-makers solve their unstructured problems. So, we thus base our research off of the assumption that developing DSS, particularly for helping poorly structured or unstructured decisions, cannot be done without considering end-user decision problems, how to represent them collectively, decisions content, their meaning, and the decision-making process; thus, arise the field issues in a multidisciplinary perspective. Our approach addresses a problem-driven and collaborative approach to designing DSS technologies: It will reflect common end-user problems in the upstream design phase and in the downstream phase these problems will determine the design choices and potential technical solution. We will thus rely on a categorization of HR’s problems for a development mirroring the Analytics solution. This brings out a new data-driven DSS typology: Descriptive Analytics, Explicative or Diagnostic Analytics, Predictive Analytics, Prescriptive Analytics. In our research, identifying the problem takes place with design of the solution, so, we would have to resort a significant transformations of representations associated with the HR Analytics application to build an increasingly detailed representation of the goal to be achieved. Here, the collective cognition is reflected in the establishment of transfer functions of representations during the whole of the design process.

Keywords: DSS, collaborative design, problem-driven requirements, analytics application, HR decision making

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6649 Pharmacy-Station Mobile Application

Authors: Taissir Fekih Romdhane

Abstract:

This paper proposes a mobile web application named Pharmacy-Station that sells medicines and permits user to search for medications based on their symptoms, making it is easy to locate a specific drug online without the need to visit a pharmacy where it may be out of stock. This application is developed using the jQuery Mobile framework, which uses many web technologies and languages such as HTML5, PHP, JavaScript and CSS3. To test the proposed application, we used data from popular pharmacies in Saudi Arabia that included important information such as location, contact, and medicines in stock, etc. This document describes the different steps followed to create the Pharmacy-Station application along with screenshots. Finally, based on the results, the paper concludes with recommendations and further works planned to improve the Pharmacy-Station mobile application.

Keywords: pharmacy, mobile application, jquery mobile framework, search, medicine

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6648 Application Layer Distributed Denial of Service Attack Detection Using Machine Learning

Authors: Songyuan Sui, Chen Zhu

Abstract:

Distributed denial of service (DDoS) attacks are regarded as one of the most network threats nowadays. The attackers dominate a large portion of network traffic from multiple nodes to launch the DDoS attacks. With the improvement of a large number of defense methods for the network layer and the increasing popularity of many application scenarios focusing on the application layer, defense against application-layer DDoS attacks is becoming more and more important. This paper presented a literature review about machine learning-based DDoS detection on three popular application scenarios. It illustrated the fact that application-layer DDoS attacks detection is important but overlooked to some extent. We also performed an experimental analysis of five machine learning models for application-layer DDoS detection specifically. These results indicated that application layer servers could use typical machine learning models with fewer resources cost and better performance to detect application-layer DDoS attacks automatically.

Keywords: anomaly detection, application layer, distributed denial of service, machine learning

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6647 Technological Advancement of Socratic Supported by Artificial Intelligence

Authors: Amad Nasseef, Layan Zugail, Joud Musalli, Layan Shaikan

Abstract:

Technology has become an essential part of our lives. We have also witnessed the significant emergence of artificial intelligence in so many areas. Throughout this research paper, the following will be discussed: an introduction on AI and Socratic application, we also did an overview on the application’s background and other similar applications, as for the methodology, we conducted a survey to collect results on users experience in using the Socratic application. The results of the survey strongly supported the usefulness and interest of users in the Socratic application. Finally, we concluded that Socratic is a meaningful tool for learning purposes due to it being supported by artificial intelligence, which made the application easy to use and familiar to users to deal with through a click of a button.

Keywords: Socratic, artificial intelligence, application, features

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6646 Trash Dash: An Educational Android Game Application for Proper Waste Segregation

Authors: Marylene S. Eder, Dorothy M. Jao, Paolo Marc Nicolas S. Laspiñas, Pukilan A. Malim, Sarah Jean D. Raterta

Abstract:

Trash Dash is an android game application developed to serve as an alternative tool to practice proper waste segregation for children ages 3 years old and above. The researchers designed the application using Unity 3D and developed the text file that served as the database of the game application. An observation of a pre-school teacher shows that children know how to throw their garbage but they do not know yet how to segregate wastes. After launching the mobile application to K-2 pupils 4 – 5 years of age, the researchers have noticed that children within this age are active and motivated to learn the difference between biodegradable and non-biodegradable. Based on the result of usability test conducted, it was concluded that the game is easy to use and children will most likely use this application frequently. Furthermore, the children may need assistance from their parents and teachers when playing the game. An actual testing of the application has been conducted to different devices as well as functionality test by Thwack Application and it can be concluded that the mobile application can be launched and installed on a device with a minimum API requirement of Gingerbread (2.3.1).

Keywords: waste segregation, android application, biodegradable, non-biodegradable

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6645 Research on Malware Application Patterns of Using Permission Monitoring System

Authors: Seung-Hwan Ju, Yo-Han Choi, Hee-Suk Seo, Tae-Kyung Kim

Abstract:

This study investigates the permissions requested by Android applications, and the possibility of identifying suspicious applications based only on information presented to the user before an application is downloaded. The pattern analysis is based on a smaller data set consisting of confirmed malicious applications. The method is evaluated based on its ability to recognize malicious potential in the analyzed applications. In this study, we develop a system to monitor that mobile application permission at application update. This study is a service-based malware analysis. It will be based on the mobile security study.

Keywords: malware patterns, application permission, application analysis, security

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6644 Development of a Hamster Knowledge System Based on Android Application

Authors: Satien Janpla, Thanawan Boonpuck, Pattarapan Roonrakwit

Abstract:

In this paper, we present a hamster knowledge system based on android application. The objective of this system is to advice user to upkeep and feed hamsters based on mobile application. We describe the design approaches and functional components of this system. The system was developed based on knowledge based of hamster experts. The results were divided by the research purposes into 2 parts: developing the mobile application for advice users and testing and evaluating the system. Black box technique was used to evaluate application performances and questionnaires were applied to measure user satisfaction with system usability by specialists and users.

Keywords: hamster knowledge, Android application, black box, questionnaires

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6643 Android-Based Edugame Application for Earthquakes Disaster Mitigation Education

Authors: Endina P. Purwandari, Yolanda Hervianti, Feri Noperman, Endang W. Winarni

Abstract:

The earthquakes disaster is an event that can threaten at any moment and cause damage and loss of life. Game earthquake disaster mitigation is a useful educational game to enhance children insight, knowledge, and understanding in the response to the impact of the earthquake. This study aims to build an educational games application on the Android platform as a learning media for earthquake mitigation education and to determine the effect of the application toward children understanding of the earthquake disaster mitigation. The methods were research and development. The development was to develop edugame application for earthquakes mitigation education. The research involved elementary students as a research sample to test the developed application. The research results were valid android-based edugame application, and its the effect of application toward children understanding. The application contains an earthquake simulation video, an earthquake mitigation video, and a game consisting three stages, namely before the earthquake, when the earthquake occur, and after the earthquake. The results of the feasibility test application showed that this application was included in the category of 'Excellent' which the average percentage of the operation of applications by 76%, view application by 67% and contents of application by 74%. The test results of students' responses were 80% that showed that a positive their responses toward the application. The student understanding test results show that the average score of children understanding pretest was 71,33, and post-test was 97,00. T-test result showed that t value by 8,02 more than table t by 2,001. This indicated that the earthquakes disaster mitigation edugame application based on Android platform affects the children understanding about disaster earthquake mitigation.

Keywords: android, edugame, mitigation, earthquakes

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6642 Design and Implementation of Remote Control Application for Elderly People Who Live Alone

Authors: Cristina Nieves Perdomo Delgado

Abstract:

The study consists of the design and use of an application for cell phones called “Me Cuido” that consists of remote control of elderly people who live alone with their families. The objective of the study is to analyze the usability of the application by 40-year-olds using the Questionnaire for User Interaction Satisfaction (QUIS) method. The results highlight that the application has a design adapted to the elderly and that it is easy to use and understand.

Keywords: design, assistive technology, elderly people, independence

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6641 Identity Conflict between Social and Business Entrepreneurs: The Challenge of Constructing a Novel Social Identity

Authors: Rui G. Serôdio, Carina Martins, Alexandra Serra, José A. Lima, Luísa Catita, Paula Lopes

Abstract:

Building on social identity approach, we tested the impact of social categorization and comparison in the psychosocial process by which social entrepreneurs define their group identity. Specifically, we address how both differentiation and assimilation processes are set of in the context of constructing a novel, distinctive and socially salient – social entrepreneurs. As part of a larger research line, a quasi-experimental study with Social and Business Entrepreneurs, as well as “Lay People” provided evidence consistent with our predictions: (1) Social Entrepreneurs, in contrast with Lay People and Business Entrepreneurs, value more strongly social identity than personal identity, and the later is the only group that values Personal Differentiation; (2) unlike Entrepreneurs, Social Entrepreneurs display an ingroup bias across group evaluations; (3) Lay People, display a self-serving bias, although, overall, they allocate a more positive image to the target groups; (4) combining own vs. others evaluations across all groups, Social Entrepreneurs receive the more positive value. From the standpoint of social identity and self-categorization theories and their approach to group process, we discuss the processes of intergroup comparison and differentiation as core processes in the construction of a positive social identity. We illustrate it within the context of social entrepreneurship, a political and social “wave” that flows across Europe at this time.

Keywords: group processes, social entrepreneurship, social identity, business entrepreneurs

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6640 Classification of Sequential Sports Using Automata Theory

Authors: Aniket Alam, Sravya Gurram

Abstract:

This paper proposes a categorization of sport that is based on the system of rules that a sport must adhere to. We focus on these systems of rules to examine how a winner is produced in different sports. The rules of a sport dictate the game play and the direction it takes. We propose to break down the game play into events. At this junction, we observe two kinds of events that constitute the game play of a sport –ones that follow sequential logic and ones that do not. Our focus is pertained to sports that are comprised of sequential events. To examine these events further, to understand how a winner emerges, we take the help of finite-state automaton from the theory of computation (Automata theory). We showcase how sequential sports are eligible to be represented as finite state machines. We depict these finite state machines as state diagrams. We examine these state diagrams to observe how a team/player reaches the final states of the sport, with a special focus on one final state –the final state which determines the winner. This exercise has been carried out for the following sports: Hurdles, Track, Shot Put, Long Jump, Bowling, Badminton, Pacman and Weightlifting (Snatch). Based on our observations of how this final state of winning is achieved, we propose a categorization of sports.

Keywords: sport classification, sport modelling, ontology, automata theory

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6639 System and Method for Providing Web-Based Remote Application Service

Authors: Shuen-Tai Wang, Yu-Ching Lin, Hsi-Ya Chang

Abstract:

With the development of virtualization technologies, a new type of service named cloud computing service is produced. Cloud users usually encounter the problem of how to use the virtualized platform easily over the web without requiring the plug-in or installation of special software. The object of this paper is to develop a system and a method enabling process interfacing within an automation scenario for accessing remote application by using the web browser. To meet this challenge, we have devised a web-based interface that system has allowed to shift the GUI application from the traditional local environment to the cloud platform, which is stored on the remote virtual machine. We designed the sketch of web interface following the cloud virtualization concept that sought to enable communication and collaboration among users. We describe the design requirements of remote application technology and present implementation details of the web application and its associated components. We conclude that this effort has the potential to provide an elastic and resilience environment for several application services. Users no longer have to burden the system maintenances and reduce the overall cost of software licenses and hardware. Moreover, this remote application service represents the next step to the mobile workplace, and it lets user to use the remote application virtually from anywhere.

Keywords: virtualization technology, virtualized platform, web interface, remote application

Procedia PDF Downloads 200
6638 The Application of Green Technology to Residential Architecture in Hangzhou

Authors: Huiru Chen, Xuran Zhang

Abstract:

At present, the residential architecture in China are still causing high energy consumption and high pollution during their whole life cycle, which can be backward compared with the developed countries. The aim of this paper is to discuss the application of green technology to residential architecture in Hangzhou. This article will start with the development of green buildings, then analyzes the use status of green technology in Hangzhou from several specific measures. Analysis of the typical existing green residential buildings in Hangzhou is an attempt to form a preliminary Hangzhou’s green technology application strategy system. Through research, it has been found that the application of green technology in Hangzhou has changed from putting green to the facade, to the combination of the preservation of the traditional green concept and the modern green technology.

Keywords: application, green technology, Hangzhou, residential architecture

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6637 Using the Smith-Waterman Algorithm to Extract Features in the Classification of Obesity Status

Authors: Rosa Figueroa, Christopher Flores

Abstract:

Text categorization is the problem of assigning a new document to a set of predetermined categories, on the basis of a training set of free-text data that contains documents whose category membership is known. To train a classification model, it is necessary to extract characteristics in the form of tokens that facilitate the learning and classification process. In text categorization, the feature extraction process involves the use of word sequences also known as N-grams. In general, it is expected that documents belonging to the same category share similar features. The Smith-Waterman (SW) algorithm is a dynamic programming algorithm that performs a local sequence alignment in order to determine similar regions between two strings or protein sequences. This work explores the use of SW algorithm as an alternative to feature extraction in text categorization. The dataset used for this purpose, contains 2,610 annotated documents with the classes Obese/Non-Obese. This dataset was represented in a matrix form using the Bag of Word approach. The score selected to represent the occurrence of the tokens in each document was the term frequency-inverse document frequency (TF-IDF). In order to extract features for classification, four experiments were conducted: the first experiment used SW to extract features, the second one used unigrams (single word), the third one used bigrams (two word sequence) and the last experiment used a combination of unigrams and bigrams to extract features for classification. To test the effectiveness of the extracted feature set for the four experiments, a Support Vector Machine (SVM) classifier was tuned using 20% of the dataset. The remaining 80% of the dataset together with 5-Fold Cross Validation were used to evaluate and compare the performance of the four experiments of feature extraction. Results from the tuning process suggest that SW performs better than the N-gram based feature extraction. These results were confirmed by using the remaining 80% of the dataset, where SW performed the best (accuracy = 97.10%, weighted average F-measure = 97.07%). The second best was obtained by the combination of unigrams-bigrams (accuracy = 96.04, weighted average F-measure = 95.97) closely followed by the bigrams (accuracy = 94.56%, weighted average F-measure = 94.46%) and finally unigrams (accuracy = 92.96%, weighted average F-measure = 92.90%).

Keywords: comorbidities, machine learning, obesity, Smith-Waterman algorithm

Procedia PDF Downloads 233