Search results for: Arena 14 automatic rockwell
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1072

Search results for: Arena 14 automatic rockwell

682 Short Association Bundle Atlas for Lateralization Studies from dMRI Data

Authors: C. Román, M. Guevara, P. Salas, D. Duclap, J. Houenou, C. Poupon, J. F. Mangin, P. Guevara

Abstract:

Diffusion Magnetic Resonance Imaging (dMRI) allows the non-invasive study of human brain white matter. From diffusion data, it is possible to reconstruct fiber trajectories using tractography algorithms. Our previous work consists in an automatic method for the identification of short association bundles of the superficial white matter (SWM), based on a whole brain inter-subject hierarchical clustering applied to a HARDI database. The method finds representative clusters of similar fibers, belonging to a group of subjects, according to a distance measure between fibers, using a non-linear registration (DTI-TK). The algorithm performs an automatic labeling based on the anatomy, defined by a cortex mesh parcelated with FreeSurfer software. The clustering was applied to two independent groups of 37 subjects. The clusters resulting from both groups were compared using a restrictive threshold of mean distance between each pair of bundles from different groups, in order to keep reproducible connections. In the left hemisphere, 48 reproducible bundles were found, while 43 bundles where found in the right hemisphere. An inter-hemispheric bundle correspondence was then applied. The symmetric horizontal reflection of the right bundles was calculated, in order to obtain the position of them in the left hemisphere. Next, the intersection between similar bundles was calculated. The pairs of bundles with a fiber intersection percentage higher than 50% were considered similar. The similar bundles between both hemispheres were fused and symmetrized. We obtained 30 common bundles between hemispheres. An atlas was created with the resulting bundles and used to segment 78 new subjects from another HARDI database, using a distance threshold between 6-8 mm according to the bundle length. Finally, a laterality index was calculated based on the bundle volume. Seven bundles of the atlas presented right laterality (IP_SP_1i, LO_LO_1i, Op_Tr_0i, PoC_PoC_0i, PoC_PreC_2i, PreC_SM_0i, y RoMF_RoMF_0i) and one presented left laterality (IP_SP_2i), there is no tendency of lateralization according to the brain region. Many factors can affect the results, like tractography artifacts, subject registration, and bundle segmentation. Further studies are necessary in order to establish the influence of these factors and evaluate SWM laterality.

Keywords: dMRI, hierarchical clustering, lateralization index, tractography

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681 Optimizing Cell Culture Performance in an Ambr15 Microbioreactor Using Dynamic Flux Balance and Computational Fluid Dynamic Modelling

Authors: William Kelly, Sorelle Veigne, Xianhua Li, Zuyi Huang, Shyamsundar Subramanian, Eugene Schaefer

Abstract:

The ambr15™ bioreactor is a single-use microbioreactor for cell line development and process optimization. The ambr system offers fully automatic liquid handling with the possibility of fed-batch operation and automatic control of pH and oxygen delivery. With operating conditions for large scale biopharmaceutical production properly scaled down, micro bioreactors such as the ambr15™ can potentially be used to predict the effect of process changes such as modified media or different cell lines. In this study, gassing rates and dilution rates were varied for a semi-continuous cell culture system in the ambr15™ bioreactor. The corresponding changes to metabolite production and consumption, as well as cell growth rate and therapeutic protein production were measured. Conditions were identified in the ambr15™ bioreactor that produced metabolic shifts and specific metabolic and protein production rates also seen in the corresponding larger (5 liter) scale perfusion process. A Dynamic Flux Balance model was employed to understand and predict the metabolic changes observed. The DFB model-predicted trends observed experimentally, including lower specific glucose consumption when CO₂ was maintained at higher levels (i.e. 100 mm Hg) in the broth. A Computational Fluid Dynamic (CFD) model of the ambr15™ was also developed, to understand transfer of O₂ and CO₂ to the liquid. This CFD model predicted gas-liquid flow in the bioreactor using the ANSYS software. The two-phase flow equations were solved via an Eulerian method, with population balance equations tracking the size of the gas bubbles resulting from breakage and coalescence. Reasonable results were obtained in that the Carbon Dioxide mass transfer coefficient (kLa) and the air hold up increased with higher gas flow rate. Volume-averaged kLa values at 500 RPM increased as the gas flow rate was doubled and matched experimentally determined values. These results form a solid basis for optimizing the ambr15™, using both CFD and FBA modelling approaches together, for use in microscale simulations of larger scale cell culture processes.

Keywords: cell culture, computational fluid dynamics, dynamic flux balance analysis, microbioreactor

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680 Road Condition Monitoring Using Built-in Vehicle Technology Data, Drones, and Deep Learning

Authors: Judith Mwakalonge, Geophrey Mbatta, Saidi Siuhi, Gurcan Comert, Cuthbert Ruseruka

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Transportation agencies worldwide continuously monitor their roads' conditions to minimize road maintenance costs and maintain public safety and rideability quality. Existing methods for carrying out road condition surveys involve manual observations of roads using standard survey forms done by qualified road condition surveyors or engineers either on foot or by vehicle. Automated road condition survey vehicles exist; however, they are very expensive since they require special vehicles equipped with sensors for data collection together with data processing and computing devices. The manual methods are expensive, time-consuming, infrequent, and can hardly provide real-time information for road conditions. This study contributes to this arena by utilizing built-in vehicle technologies, drones, and deep learning to automate road condition surveys while using low-cost technology. A single model is trained to capture flexible pavement distresses (Potholes, Rutting, Cracking, and raveling), thereby providing a more cost-effective and efficient road condition monitoring approach that can also provide real-time road conditions. Additionally, data fusion is employed to enhance the road condition assessment with data from vehicles and drones.

Keywords: road conditions, built-in vehicle technology, deep learning, drones

Procedia PDF Downloads 117
679 Securing the Electronic Commerce - The Way Forward: A Comparative Ananlysis

Authors: Sarthak Mishra, Astha Sinha

Abstract:

There’s no doubt about the convenience of making commercial and business transactions over the Internet under the new business model known as the e-Commerce. The term 'Electronic commerce' or e-Commerce refers to the use of an electronic medium to carry out commercial transactions. E-Commerce is one of the parts of Information Science framework and its uses are gradually becoming popular. Thus, the threat of security issues in Information Science has now become an important subject of discussion amongst the concerned users. These two issues i.e. security and privacy are required to be looked into through social, organizational, technical and economic perspectives. The current paper analyses the effect of these two issues in the arena of e-commerce. Here, no specification has been discussed rather an attempt has been made to provide a general overview. Further, attempts have been made to discuss the security and privacy issues in relation to the E-Commerce financial transactions. We shall also discuss in particular different steps required to be taken before online shopping and also shall discuss the purpose of security and privacy in E-Commerce and why it has currently become the need of the present hour. Lastly, an attempt has been made to discuss the plausible future course of development of this practice and its impact upon the global economy and if any changes should be bought about to ensure a smooth evolution of the practice. This paper has adopted a descriptive methodology to undertake its major area of study, wherein the major source of information has been via the secondary resources. Also, the study is of a comparative nature wherein the position of the various national regimes have compared with regards to the research question.

Keywords: business-business transaction (B2B), business-consumer transaction (B2C), e-commerce, online transaction, privacy and security threats

Procedia PDF Downloads 224
678 Optimizing Machine Vision System Setup Accuracy by Six-Sigma DMAIC Approach

Authors: Joseph C. Chen

Abstract:

Machine vision system provides automatic inspection to reduce manufacturing costs considerably. However, only a few principles have been found to optimize machine vision system and help it function more accurately in industrial practice. Mostly, there were complicated and impractical design techniques to improve the accuracy of machine vision system. This paper discusses implementing the Six Sigma Define, Measure, Analyze, Improve, and Control (DMAIC) approach to optimize the setup parameters of machine vision system when it is used as a direct measurement technique. This research follows a case study showing how Six Sigma DMAIC methodology has been put into use.

Keywords: DMAIC, machine vision system, process capability, Taguchi Parameter Design

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677 Assessing Online Learning Paths in an Learning Management Systems Using a Data Mining and Machine Learning Approach

Authors: Alvaro Figueira, Bruno Cabral

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Nowadays, students are used to be assessed through an online platform. Educators have stepped up from a period in which they endured the transition from paper to digital. The use of a diversified set of question types that range from quizzes to open questions is currently common in most university courses. In many courses, today, the evaluation methodology also fosters the students’ online participation in forums, the download, and upload of modified files, or even the participation in group activities. At the same time, new pedagogy theories that promote the active participation of students in the learning process, and the systematic use of problem-based learning, are being adopted using an eLearning system for that purpose. However, although there can be a lot of feedback from these activities to student’s, usually it is restricted to the assessments of online well-defined tasks. In this article, we propose an automatic system that informs students of abnormal deviations of a 'correct' learning path in the course. Our approach is based on the fact that by obtaining this information earlier in the semester, may provide students and educators an opportunity to resolve an eventual problem regarding the student’s current online actions towards the course. Our goal is to prevent situations that have a significant probability to lead to a poor grade and, eventually, to failing. In the major learning management systems (LMS) currently available, the interaction between the students and the system itself is registered in log files in the form of registers that mark beginning of actions performed by the user. Our proposed system uses that logged information to derive new one: the time each student spends on each activity, the time and order of the resources used by the student and, finally, the online resource usage pattern. Then, using the grades assigned to the students in previous years, we built a learning dataset that is used to feed a machine learning meta classifier. The produced classification model is then used to predict the grades a learning path is heading to, in the current year. Not only this approach serves the teacher, but also the student to receive automatic feedback on her current situation, having past years as a perspective. Our system can be applied to online courses that integrate the use of an online platform that stores user actions in a log file, and that has access to other student’s evaluations. The system is based on a data mining process on the log files and on a self-feedback machine learning algorithm that works paired with the Moodle LMS.

Keywords: data mining, e-learning, grade prediction, machine learning, student learning path

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676 Conceptual Modeling of the Relationship between Project Management Practices and Knowledge Absorptive Capacity Using Interpretive Structural Modeling Method

Authors: Seyed Abdolreza Mosavi, Alireza Babakhan, Elham Sadat Hoseinifard

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Knowledge-based firms need to design mechanisms for continuous absorptive and creation of knowledge in order to ensure their survival in the competitive arena and to follow the path of development. Considering the project-oriented nature of product development activities in knowledge-based firms on the one hand and the importance of analyzing the factors affecting knowledge absorptive capacity in these firms on the other, the purpose of this study is to identify and classify the factors affecting project management practices on absorptive knowledge capacity. For this purpose, we have studied and reviewed the theoretical literature in the field of project management and absorptive knowledge capacity so as to clarify its dimensions and indexes. Then, using the ISM method, the relationship between them has been studied. To collect data, 21 questionnaires were distributed in project-oriented knowledge-based companies. The results of the ISM method analysis provide a model for the relationship between project management activities and knowledge absorptive capacity, which includes knowledge acquisition capacity, scope management, time management, cost management, quality management, human resource management, communications management, procurement management, risk management, stakeholders management and integration management. Having conducted the MICMAC analysis, we divided the variables into three groups of independent, relational and dependent variables and came up with no variables to be included in the group of autonomous variables.

Keywords: knowledge absorptive capacity, project management practices, knowledge-based firms, interpretive structural modeling

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675 Temporal Case-Based Reasoning System for Automatic Parking Complex

Authors: Alexander P. Eremeev, Ivan E. Kurilenko, Pavel R. Varshavskiy

Abstract:

In this paper, the problem of the application of temporal reasoning and case-based reasoning in intelligent decision support systems is considered. The method of case-based reasoning with temporal dependences for the solution of problems of real-time diagnostics and forecasting in intelligent decision support systems is described. This paper demonstrates how the temporal case-based reasoning system can be used in intelligent decision support systems of the car access control. This work was supported by RFBR.

Keywords: analogous reasoning, case-based reasoning, intelligent decision support systems, temporal reasoning

Procedia PDF Downloads 525
674 Automatic Segmentation of 3D Tomographic Images Contours at Radiotherapy Planning in Low Cost Solution

Authors: D. F. Carvalho, A. O. Uscamayta, J. C. Guerrero, H. F. Oliveira, P. M. Azevedo-Marques

Abstract:

The creation of vector contours slices (ROIs) on body silhouettes in oncologic patients is an important step during the radiotherapy planning in clinic and hospitals to ensure the accuracy of oncologic treatment. The radiotherapy planning of patients is performed by complex softwares focused on analysis of tumor regions, protection of organs at risk (OARs) and calculation of radiation doses for anomalies (tumors). These softwares are supplied for a few manufacturers and run over sophisticated workstations with vector processing presenting a cost of approximately twenty thousand dollars. The Brazilian project SIPRAD (Radiotherapy Planning System) presents a proposal adapted to the emerging countries reality that generally does not have the monetary conditions to acquire some radiotherapy planning workstations, resulting in waiting queues for new patients treatment. The SIPRAD project is composed by a set of integrated and interoperabilities softwares that are able to execute all stages of radiotherapy planning on simple personal computers (PCs) in replace to the workstations. The goal of this work is to present an image processing technique, computationally feasible, that is able to perform an automatic contour delineation in patient body silhouettes (SIPRAD-Body). The SIPRAD-Body technique is performed in tomography slices under grayscale images, extending their use with a greedy algorithm in three dimensions. SIPRAD-Body creates an irregular polyhedron with the Canny Edge adapted algorithm without the use of preprocessing filters, as contrast and brightness. In addition, comparing the technique SIPRAD-Body with existing current solutions is reached a contours similarity at least 78%. For this comparison is used four criteria: contour area, contour length, difference between the mass centers and Jaccard index technique. SIPRAD-Body was tested in a set of oncologic exams provided by the Clinical Hospital of the University of Sao Paulo (HCRP-USP). The exams were applied in patients with different conditions of ethnology, ages, tumor severities and body regions. Even in case of services that have already workstations, it is possible to have SIPRAD working together PCs because of the interoperability of communication between both systems through the DICOM protocol that provides an increase of workflow. Therefore, the conclusion is that SIPRAD-Body technique is feasible because of its degree of similarity in both new radiotherapy planning services and existing services.

Keywords: radiotherapy, image processing, DICOM RT, Treatment Planning System (TPS)

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673 The Holistic Nursing WebQuest: An Interactive Teaching/Learning Strategy

Authors: Laura M. Schwarz

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WebQuests are an internet-based interactive teaching/learning tool and utilize a scaffolded methodology. WebQuests employ critical thinking, afford inquiry-based constructivist learning, and readily employ Bloom’s Taxonomy. WebQuests have generally been used as instructional technology tools in primary and secondary education and have more recently grown in popularity in higher education. The study of the efficacy of WebQuests as an instructional approach to learning, however, has been limited, particularly in the nursing education arena. The purpose of this mixed-methods study was to determine nursing students’ perceptions of the effectiveness of the Nursing WebQuest as a teaching/learning strategy for holistic nursing-related content. Quantitative findings (N=42) suggested that learners were active participants, used reflection, thought of new ideas, used analysis skills, discovered something new, and assessed the worth of something while taking part in the WebQuests. Qualitative findings indicated that participants found WebQuest positives as easy to understand and navigate; clear and organized; interactive; good alternative learning format, and used a variety of quality resources. Participants saw drawbacks as requiring additional time and work; and occasional failed link or link causing them to lose their location in the WebQuest. Recommendations include using larger sample size and more diverse populations from various programs and universities. In conclusion, WebQuests were found to be an effective teaching/learning tool as positively assessed by study participants.

Keywords: holistic nursing, nursing education, teaching/learning strategy, WebQuests

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672 Intelligent Recognition Tools for Industrial Automation

Authors: Amin Nazerzadeh, Afsaneh Nouri Houshyar , Azadeh Noori Hoshyar

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With the rapid growing of information technology, the industry and manufacturing systems are becoming more automated. Therefore, achieving the highly accurate automatic systems with reliable security is becoming more critical. Biometrics that refers to identifying individual based on physiological or behavioral traits are unique identifiers provide high reliability and security in different industrial systems. As biometric cannot easily be transferred between individuals or copied, it has been receiving extensive attention. Due to the importance of security applications, this paper provides an overview on biometrics and discuss about background, types and applications of biometric as an effective tool for the industrial applications.

Keywords: Industial and manufacturing applications, intelligence and security, information technology, recognition; security technology; biometrics

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671 Highly Accurate Tennis Ball Throwing Machine with Intelligent Control

Authors: Ferenc Kovács, Gábor Hosszú

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The paper presents an advanced control system for tennis ball throwing machines to improve their accuracy according to the ball impact points. A further advantage of the system is the much easier calibration process involving the intelligent solution of the automatic adjustment of the stroking parameters according to the ball elasticity, the self-calibration, the use of the safety margin at very flat strokes and the possibility to placing the machine to any position of the half court. The system applies mathematical methods to determine the exact ball trajectories and special approximating processes to access all points on the aimed half court.

Keywords: control system, robot programming, robot control, sports equipment, throwing machine

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670 Automatic Segmentation of Lung Pleura Based On Curvature Analysis

Authors: Sasidhar B., Bhaskar Rao N., Ramesh Babu D. R., Ravi Shankar M.

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Segmentation of lung pleura is a preprocessing step in Computer-Aided Diagnosis (CAD) which helps in reducing false positives in detection of lung cancer. The existing methods fail in extraction of lung regions with the nodules at the pleura of the lungs. In this paper, a new method is proposed which segments lung regions with nodules at the pleura of the lungs based on curvature analysis and morphological operators. The proposed algorithm is tested on 06 patient’s dataset which consists of 60 images of Lung Image Database Consortium (LIDC) and the results are found to be satisfactory with 98.3% average overlap measure (AΩ).

Keywords: curvature analysis, image segmentation, morphological operators, thresholding

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669 Semantic Data Schema Recognition

Authors: Aïcha Ben Salem, Faouzi Boufares, Sebastiao Correia

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The subject covered in this paper aims at assisting the user in its quality approach. The goal is to better extract, mix, interpret and reuse data. It deals with the semantic schema recognition of a data source. This enables the extraction of data semantics from all the available information, inculding the data and the metadata. Firstly, it consists of categorizing the data by assigning it to a category and possibly a sub-category, and secondly, of establishing relations between columns and possibly discovering the semantics of the manipulated data source. These links detected between columns offer a better understanding of the source and the alternatives for correcting data. This approach allows automatic detection of a large number of syntactic and semantic anomalies.

Keywords: schema recognition, semantic data profiling, meta-categorisation, semantic dependencies inter columns

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668 Metaphorical Devices in Political Cartoons with Reference to Political Confrontation in Pakistan after Panama Leaks

Authors: Ayesha Ashfaq, Muhammad Ajmal Ashfaq

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It has been assumed that metaphorical and symbolic contests are waged with metaphors, captions, and signs in political cartoons that play a significant role in image construction of political actors, situations or events in the political arena. This paper is an effort to explore the metaphorical devices in political cartoons related to the political confrontation in Pakistan between the ruling party Pakistan Muslim League Nawaz (PMLN) and opposition parties especially after Panama leaks. For this purpose, political cartoons sketched by five renowned political cartoonists on the basis of their belongings to the most highly circulated mainstream English newspapers of Pakistan and their professional experiences in their genre, were selected. The cartoons were analyzed through the Barthes’s model of Semiotics under the umbrella of the first level of agenda setting theory ‘framing’. It was observed that metaphorical devices in political cartoons are one of the key weapons of cartoonists’ armory. These devices are used to attack the candidates and contribute to the image and character building. It was found that all the selected political cartoonists used different forms of metaphors including situational metaphors and embodying metaphors. Not only the physical stature but also the debates and their activities were depicted metaphorically in the cartoons that create the scenario of comparison between the cartoons and their real political confrontation. It was examined that both forms of metaphors shed light on cartoonist’s perception and newspaper’s policy about political candidates, political parties and particular events. In addition, it was found that zoomorphic metaphors and metaphors of diminishments were also predominantly used to depict the conflict between two said political actors.

Keywords: metaphor, Panama leaks, political cartoons, political communication

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667 Design of a Drift Assist Control System Applied to Remote Control Car

Authors: Sheng-Tse Wu, Wu-Sung Yao

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In this paper, a drift assist control system is proposed for remote control (RC) cars to get the perfect drift angle. A steering servo control scheme is given powerfully to assist the drift driving. A gyroscope sensor is included to detect the machine's tail sliding and to achieve a better automatic counter-steering to prevent RC car from spinning. To analysis tire traction and vehicle dynamics is used to obtain the dynamic track of RC cars. It comes with a control gain to adjust counter-steering amount according to the sensor condition. An illustrated example of 1:10 RC drift car is given and the real-time control algorithm is realized by Arduino Uno.

Keywords: drift assist control system, remote control cars, gyroscope, vehicle dynamics

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666 JREM: An Approach for Formalising Models in the Requirements Phase with JSON and NoSQL Databases

Authors: Aitana Alonso-Nogueira, Helia Estévez-Fernández, Isaías García

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This paper presents an approach to reduce some of its current flaws in the requirements phase inside the software development process. It takes the software requirements of an application, makes a conceptual modeling about it and formalizes it within JSON documents. This formal model is lodged in a NoSQL database which is document-oriented, that is, MongoDB, because of its advantages in flexibility and efficiency. In addition, this paper underlines the contributions of the detailed approach and shows some applications and benefits for the future work in the field of automatic code generation using model-driven engineering tools.

Keywords: conceptual modelling, JSON, NoSQL databases, requirements engineering, software development

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665 Post Covid-19 Landscape of Global Pharmaceutical Industry

Authors: Abu Zafor Sadek

Abstract:

Pharmaceuticals were one of the least impacted business sectors during the corona pandemic as they are the center point of Covid-19 fight. Emergency use authorization, unproven indication of some commonly used drugs, self-medication, research and production capacity of an individual country, capacity of producing vaccine by many countries, Active Pharmaceutical Ingredients (APIs) related uncertainty, information gap among manufacturer, practitioners and user, export restriction, duration of lock-down, lack of harmony in transportation, disruption in the regulatory approval process, sudden increased demand of hospital items and protective equipment, panic buying, difficulties in in-person product promotion, e-prescription, geo-politics and associated issues added a new dimension to this industry. Although the industry maintains a reasonable growth throughout Covid-19 days; however, it has been characterized by both long- and short-term effects. Short-term effects have already been visible to so many countries, especially those who are import-dependent and have limited research capacity. On the other hand, it will take a few more time to see the long-term effects. Nevertheless, supply chain disruption, changes in strategic planning, new communication model, squeezing of job opportunity, rapid digitalization are the major short-term effects, whereas long-term effects include a shift towards self-sufficiency, growth pattern changes of certain products, special attention towards clinical studies, automation in operations, the increased arena of ethical issues etc. Therefore, this qualitative and exploratory study identifies the post-covid-19 landscape of the global pharmaceutical industry.

Keywords: covid-19, pharmaceutical, businees, landscape

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664 Interactive, Topic-Oriented Search Support by a Centroid-Based Text Categorisation

Authors: Mario Kubek, Herwig Unger

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Centroid terms are single words that semantically and topically characterise text documents and so may serve as their very compact representation in automatic text processing. In the present paper, centroids are used to measure the relevance of text documents with respect to a given search query. Thus, a new graphbased paradigm for searching texts in large corpora is proposed and evaluated against keyword-based methods. The first, promising experimental results demonstrate the usefulness of the centroid-based search procedure. It is shown that especially the routing of search queries in interactive and decentralised search systems can be greatly improved by applying this approach. A detailed discussion on further fields of its application completes this contribution.

Keywords: search algorithm, centroid, query, keyword, co-occurrence, categorisation

Procedia PDF Downloads 277
663 Grain Boundary Detection Based on Superpixel Merges

Authors: Gaokai Liu

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The distribution of material grain sizes reflects the strength, fracture, corrosion and other properties, and the grain size can be acquired via the grain boundary. In recent years, the automatic grain boundary detection is widely required instead of complex experimental operations. In this paper, an effective solution is applied to acquire the grain boundary of material images. First, the initial superpixel segmentation result is obtained via a superpixel approach. Then, a region merging method is employed to merge adjacent regions based on certain similarity criterions, the experimental results show that the merging strategy improves the superpixel segmentation result on material datasets.

Keywords: grain boundary detection, image segmentation, material images, region merging

Procedia PDF Downloads 162
662 War and the Battle of Lebanese Television over Gender

Authors: Natalie M. Khazaal

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The effects of the civil war on Lebanese women have been challenging to conceptualize. For some, war is a liberating and empowering force for women, while for others it is one that subjugates women and disempowers them in new ways. Scholars have explored the impact on the Lebanese civil war (1975-1990) on women in the fields of labor history, political activism and literary production. In all these arenas, women’s role and visibility were contested and negotiated in diverse ways. But probably the most visible arena where this contestation took place was television. Dramatized entertainment series were crucial sites where fictional women battled out the gender question, and which reflected and participated in the negotiations of gender politics. Even more stunningly, actual television stations became part of this battle through the plots and portrayals of women that they created. The state-backed Tele-Liban (TL) peddled patriarchal articulations of gender that directly competed with the edgy vision of liberated, independent women on the pirate Lebanese Broadcasting Corporation (LBC). This presentation explores how LBC used gender to distinguish its brand against the retrograde TL programing. Television series are an important medium for creating, testing and reenacting gender politics. They are even more consequential in another way. They are the sites where a dramatic shift in the relationship between Arab television and Arab publics—from benign neglect of public concerns towards engagement with audiences—took place for the first time. As this shift is at the heart of why Arab media was seen as a participant in the Arab uprisings, it is important to explore the roots of the shift in the dramas and comedy series of the mid-1980s Lebanese television. This presentation argues that television battles over gender were consequential and need serious consideration as sites of unexpected meaning.

Keywords: gender, Lebanon, television, war, women

Procedia PDF Downloads 631
661 Estimating Destinations of Bus Passengers Using Smart Card Data

Authors: Hasik Lee, Seung-Young Kho

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Nowadays, automatic fare collection (AFC) system is widely used in many countries. However, smart card data from many of cities does not contain alighting information which is necessary to build OD matrices. Therefore, in order to utilize smart card data, destinations of passengers should be estimated. In this paper, kernel density estimation was used to forecast probabilities of alighting stations of bus passengers and applied to smart card data in Seoul, Korea which contains boarding and alighting information. This method was also validated with actual data. In some cases, stochastic method was more accurate than deterministic method. Therefore, it is sufficiently accurate to be used to build OD matrices.

Keywords: destination estimation, Kernel density estimation, smart card data, validation

Procedia PDF Downloads 347
660 Secondary Prisonization and Mental Health: A Comparative Study with Elderly Parents of Prisoners Incarcerated in Remote Jails

Authors: Luixa Reizabal, Inaki Garcia, Eneko Sansinenea, Ainize Sarrionandia, Karmele Lopez De Ipina, Elsa Fernandez

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Although the effects of incarceration in prisons close to prisoners’ and their families’ residences have been studied, little is known about the effects of remote incarceration. The present study shows the impact of secondary prisonization on mental health of elderly parents of Basque prisoners who are incarcerated in prisons located far away from prisoners’ and their families’ residences. Secondary prisonization refers to the effects that imprisonment of a family member has on relatives. In the study, psychological effects are analyzed by means of comparative methodology. Specifically, levels of psychopathology (depression, anxiety, and stress) and positive mental health (psychological, social, and emotional well-being) are studied in a sample of parents over 65 years old of prisoners incarcerated in prisons located a long distance away (concretely, some of them in a distance of less than 400 km, while others farther than 400 km) from the Basque Country. The dataset consists of data collected through a questionnaire and from a spontaneous speech recording. The statistical and automatic analyses show that levels of psychopathology and positive mental health of elderly parents of prisoners incarcerated in remote jails are affected by the incarceration of their sons or daughters. Concretely, these parents show higher levels of depression, anxiety, and stress and lower levels of emotional (but not psychological or social) wellbeing than parents with no imprisoned daughters or sons. These findings suggest that parents with imprisoned sons or daughters suffer the impact of secondary prisonization on their mental health. When comparing parents with sons or daughters incarcerated within 400 kilometers from home and parents whose sons or daughters are incarcerated farther than 400 kilometers from home, the latter present higher levels of psychopathology, but also higher levels of positive mental health (although the difference between the two groups is not statistically significant). These findings might be explained by resilience. In fact, in traumatic situations, people can develop a force to cope with the situation, and even present a posttraumatic growth. Bearing in mind all these findings, it could be concluded that secondary prisonization implies for elderly parents with sons or daughters incarcerated in remote jails suffering and, in consequence, that changes in the penitentiary policy applied to Basque prisoners are required in order to finish this suffering.

Keywords: automatic spontaneous speech analysis, elderly parents, machine learning, positive mental health, psychopathology, remote incarceration, secondary prisonization

Procedia PDF Downloads 282
659 Brainbow Image Segmentation Using Bayesian Sequential Partitioning

Authors: Yayun Hsu, Henry Horng-Shing Lu

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This paper proposes a data-driven, biology-inspired neural segmentation method of 3D drosophila Brainbow images. We use Bayesian Sequential Partitioning algorithm for probabilistic modeling, which can be used to detect somas and to eliminate cross talk effects. This work attempts to develop an automatic methodology for neuron image segmentation, which nowadays still lacks a complete solution due to the complexity of the image. The proposed method does not need any predetermined, risk-prone thresholds since biological information is inherently included in the image processing procedure. Therefore, it is less sensitive to variations in neuron morphology; meanwhile, its flexibility would be beneficial for tracing the intertwining structure of neurons.

Keywords: brainbow, 3D imaging, image segmentation, neuron morphology, biological data mining, non-parametric learning

Procedia PDF Downloads 481
658 Social Identification among Employees: A System Dynamic Approach

Authors: Muhammad Abdullah, Salman Iqbal, Mamoona Rasheed

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Social identity among people is an important source of pride and self-esteem, consequently, people struggle to preserve a positive perception of their groups and collectives. The purpose of this paper is to explain the process of social identification and to highlight the underlying causal factors of social identity among employees. There is a little research about how the social identity of employees is shaped in Pakistan’s organizational culture. This study is based on social identity theory. This study uses Systems’ approach as a research methodology. The feedback loop approach is applied to explain the underlying key elements of employee behavior that collectively form social identity among social groups in corporate arena. The findings of this study reveal that effective, evaluative and cognitive components of an individual’s personality are associated with the social identification. The system dynamic feedback loop approach has revealed the underlying structure that is associated with social identity, social group formation, and effective component proved to be the most associated factor. This may also enable to understand how social groups become stable and individuals act according to the group requirements. The value of this paper lies in the understanding gained about the underlying key factors that play a crucial role in social group formation in organizations. It may help to understand the rationale behind how employees socially categorize themselves within organizations. It may also help to design effective and more cohesive teams for better operations and long-term results. This may help to share knowledge among employees as well. The underlying structure behind the social identification is highlighted with the help of system modeling.

Keywords: affective commitment, cognitive commitment, evaluated commitment, system thinking

Procedia PDF Downloads 132
657 The National Socialist and Communist Propaganda Activities in the Turkish Press during the World War II

Authors: Asuman Tezcan Mirer

Abstract:

This proposed paper discusses nationalist socialist and communist propaganda struggles in the Turkish press during World War II. The paper aspires to analyze how government agencies directed and organized the Turkish press to prevent the "5th column" from influencing public opinion. During the Second World War, one of the most emphasized issues was propaganda and how Turkish citizens would be protected from the effects of disinformation. Istanbul became a significant headquarters for belligerent countries' intelligence services, and these services were involved in gathering intelligence and disseminating propaganda. The main motive of national socialist propaganda was "anti-communism" in Turkey. Subsidizing certain magazines, controlling German companies' advertisements and paper trade, spreading rumors, printing propaganda brochures, and showing German propaganda films are some tactics that the nationalist socialists applied before and during the Second World War. On the other hand, the communists targeted Turkish racist/ultra-nationalist groups and their publications, which were influenced by the Nazi regime. They were also involved in distributing Marxist publications, printing brochures, and broadcasting radio programs. This study composes of three parts. The first part describes the nationalist socialist and communist propaganda activities in Turkey during the Second World War. The second part addresses the debates over propaganda among selected newspapers representing different ideologies. Finally, the last part analyzes the Turkish government's press policy. It explains why the government allowed ideological debates in the press despite its authoritarian press policy and "active neutrality" stance in the international arena.

Keywords: propaganda, press, 5th column, World War II, Turkey

Procedia PDF Downloads 95
656 Multiple Fault Diagnosis in Digital Circuits using Critical Path Tracing and Enhanced Deduction Algorithm

Authors: Mohamed Mahmoud

Abstract:

This paper has developed an effect-cause analysis technique for fault diagnosis in digital circuits. The main algorithm of our technique is based on the Enhanced Deduction Algorithm, which processes the real response of the CUT to the applied test T to deduce the values of the internal lines. An experimental version of the algorithm has been implemented in C++. The code takes about 7592 lines. The internal values are determined based on the logic values under the permanent stuck-fault model. Using a backtracking strategy guarantees that the actual values are covered by at least one solution, or no solution is found.

Keywords: enhanced deduction algorithm, backtracking strategy, automatic test equipment, verfication

Procedia PDF Downloads 111
655 Towards a Conscious Design in AI by Overcoming Dark Patterns

Authors: Ayse Arslan

Abstract:

One of the important elements underpinning a conscious design is the degree of toxicity in communication. This study explores the mechanisms and strategies for identifying toxic content by avoiding dark patterns. Given the breadth of hate and harassment attacks, this study explores a threat model and taxonomy to assist in reasoning about strategies for detection, prevention, mitigation, and recovery. In addition to identifying some relevant techniques such as nudges, automatic detection, or human-ranking, the study suggests the use of major metrics such as the overhead and friction of solutions on platforms and users or balancing false positives (e.g., incorrectly penalizing legitimate users) against false negatives (e.g., users exposed to hate and harassment) to maintain a conscious design towards fairness.

Keywords: AI, ML, algorithms, policy, system design

Procedia PDF Downloads 117
654 ICT-Driven Cataloguing and Classification Practical Classes: Perception of Nigerian Library and Information Science Students on Motivational Factors

Authors: Abdulsalam Abiodun Salman, Abdulmumin Isah

Abstract:

The study investigated the motivational factors that could enhance the teaching and understanding of ICT-driven cataloguing and classification (Cat and Class) practical classes among students of library and information science (LIS) in Kwara State Library Schools, Nigeria. It deployed a positivist research paradigm using a quantitative method by deploying the use of questionnaires for data collection. The population of the study is one thousand, one hundred and twenty-five (1,125) which was obtained from the department of each respective library school (the University of Ilorin, Ilorin (Unilorin); Federal Polytechnic Offa, (Fedpoffa); and Kwara State University (KWASU). The sample size was determined using the research advisor table. Hence, the study sample of one hundred and ten (110) was used. The findings revealed that LIS students were averagely motivated toward ICT-driven Cataloguing and Classification practical classes. The study recommended that modern cataloguing and classification tools for practical classes should be made available in the laboratories as motivational incentives for students. It was also recommended that library schools should motivate the students beyond the provision of these ICT-driven tools but also extend the practical class periods. Availability and access to medical treatment in case of injuries during the practical classes should be made available. Technologists/Tutors of Cat and Class practical classes should also be exposed to further training in modern trends, especially emerging digital knowledge and skills in cataloguing and classification. This will keep both the tutors and students abreast of the new development in the technological arena.

Keywords: cataloguing and classification, motivational factors, ICT-driven practical classes, LIS students, Nigeria

Procedia PDF Downloads 125
653 An Automatic Method for Building Learners’ Groups in Virtual Environment

Authors: O. Bourkoukou, Essaid El Bachari

Abstract:

The group composing is one of the key issue in collaborative learning to achieve a positive educational experience. The goal of this work is to propose for teachers and tutors a method to create effective collaborative learning groups in e-learning environment based on the learner profile. For this purpose, a new function was defined to rate implicitly learning objects used by the learner during his learning experience. This paper describes the proposed algorithm to build an adequate collaborative learning group. In order to verify the performance of the proposed algorithm, several experiments were conducted in real data set in virtual environment. Results show the effectiveness of the method for which it appears that the proposed approach may be promising to produce better outcomes.

Keywords: building groups, collaborative learning, e-learning, learning objects

Procedia PDF Downloads 295