Search results for: Oslo manual

Authors: Daniel Puciato, Piotr Oleśniewicz, Julita Markiewicz-Patkowska, Krzysztof Widawski, Michał Rozpara, Władysław Mynarski, Agnieszka Gawlik, Małgorzata Dębska, Soňa Jandová

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Physical activity as a part of people’s everyday life reduces the risk of many diseases, including those induced by lifestyle, e.g. obesity, type 2 diabetes, osteoporosis, coronary heart disease, degenerative arthritis, and certain types of cancer. That refers particularly to professionally active people, including the early senior group working on non-manual positions. The aim of the study is to evaluate the relationship between physical activity and the socio-economic status of non-manual workers from Wroclaw—one of the biggest cities in Poland, a model setting for such investigations in this part of Europe. The crucial problem in the research is to find out the percentage of respondents who meet the health-related recommendations of the World Health Organization (WHO) concerning the volume, frequency, and intensity of physical activity, as well as to establish if the most important socio-economic factors, such as gender, age, education, marital status, per capita income, savings and debt, determine the compliance with the WHO physical activity recommendations. During the research, conducted in 2013, 1,170 people (611 women and 559 men) aged 21–60 years were examined. A diagnostic poll method was applied to collect the data. Physical activity was measured with the use of the short form of the International Physical Activity Questionnaire with extended socio-demographic questions, i.e. concerning gender, age, education, marital status, income, savings or debts. To evaluate the relationship between physical activity and selected socio-economic factors, logistic regression was used (odds ratio statistics). Statistical inference was conducted on the adopted ex ante probability level of p<0.05. The majority of respondents met the volume of physical effort recommended for health benefits. It was particularly noticeable in the case of the examined men. The probability of compliance with the WHO physical activity recommendations was highest for workers aged 21–30 years with secondary or higher education who were single, received highest incomes and had savings. The results indicate the relations between physical activity and socio-economic status in the examined women and men. People with lower socio-economic status (e.g. manual workers) are physically active primarily at work, whereas those better educated and wealthier implement physical effort primarily in their leisure time. Among the investigated subjects, the youngest group of non-manual workers have the best chances to meet the WHO standards of physical activity. The study also confirms that secondary education has a positive effect on the public awareness on the role of physical activity in human life. In general, the analysis of the research indicates that there is a relationship between physical activity and some socio-economic factors of the respondents, such as gender, age, education, marital status, income per capita, and the possession of savings. Although the obtained results cannot be applied for the general population, they show some important trends that will be verified in subsequent studies conducted by the authors of the paper.

Keywords: IPAQ, nonmanual workers, physical activity, socioeconomic factors, WHO

Procedia PDF Downloads 535

Authors: Lior Davidovitch

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Traditional training based on static models and case studies is the backbone of most teaching and training programs of engineering education. However, project management learning is characterized by dynamics models that requires new and enhanced learning method. The results of empirical experiments evaluating the effectiveness and efficiency of using cognitive simulator as a new training technique are reported. The empirical findings are focused on the impact of keeping and reviewing learning history in a dynamic and interactive simulation environment of engineering education. The cognitive simulator for engineering project management learning had two learning history keeping modes: manual (student-controlled), automatic (simulator-controlled) and a version with no history keeping. A group of industrial engineering students performed four simulation-runs divided into three identical simple scenarios and one complicated scenario. The performances of participants running the simulation with the manual history mode were significantly better than users running the simulation with the automatic history mode. Moreover, the effects of using the undo enhanced further the learning process. The findings indicate an enhancement of engineering students’ learning and decision making when they use the record functionality of the history during their engineering training process. Furthermore, the cognitive simulator as educational innovation improves students learning and training. The practical implications of using simulators in the field of engineering education are discussed.

Keywords: cognitive simulator, decision making, engineering learning, project management

Procedia PDF Downloads 249

Authors: Bandojo Paula Maria Noella, Bernardo Bea Samantha B., Del Rosario Hanassa Mae S., Gomez Marian Louise D., Gomez Rome Voltaire M., Reyes Alessa Anne Therese A.

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The purpose of this study is to determine if there is a significant difference between the training program of Pan Pacific Hotel to other Five Star Hotels in terms of the technical, professional and personal competencies before and after their training. The theoretical framework of this study is the practicum manual of the University of Santo Tomas College of Tourism and Hospitality Management, Hotel and Restaurant Management Program Practicum Manual. This study was conducted using survey questionnaires that were distributed to 50 respondents. The results showed that there is a significant difference with the level of competencies of the practicum trainee before and after the training regardless if the training is structured or unstructured. Results also showed that the structured training program of Pan Pacific Hotel significantly improved the Technical Competencies in the different departments of the hotel industry. On the other hand, the findings also showed that there is no difference between the structured and unstructured training program in terms of Professional Competencies and Personal Competencies. The proponents concluded the study by providing recommendations to the partner hotels of the University of Santo Tomas College of Tourism and Hospitality Management that there should be a structured training program for the practicum trainees.

Keywords: structured and structured training program, practicum trainees, competencies, tourism

Procedia PDF Downloads 363

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 124

Authors: Hazlin Kadir Shahar, Razaleigh Muhamat Kawangit, Badlihisham Mohd Nasir, Rosmawati Mohamad Rasit

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Stigma and discrimination have become the main topic of discussion when dealing with HIV/AIDS issues. They affect the daily life of People Living With HIV(PLHIV), families, friends and people around them indirectly. This paper discusses the potential measurement in helping to reduce stigma and discrimination existence among Islamic Religious Officers towards PLHIV in Malaysia. These people have been trained with special programmes to tackle the HIV/AIDS issues by using a manual, namely as ‘The Manual of Islam and HIV/AIDS’, specifically designed by the Islamic Development Department of Malaysia (JAKIM). The objectives of the training programmes are to give the accurate information about HIV/AIDS and to suggest ways on how to handle the PLHIV issues in Islamic perspective. This research used quantitative methodology by survey. A pilot test had been done over thirty (30) trained Islamic Religious Officers in Malaysia. The findings have shown that the trainings have given a positive impact for them as they managed to acquire the knowledge of HIV/AIDS from both primer and authorized sources such as medical practitioners, Muslim chaplains and social workers. The knowledge they have acquired from the trainings has guided them in changing their perception, thus helping to reduce their own stigma and discrimination towards PLHIV. The training programmes have given them opportunities to practice what they have learned through several outreach sessions as they have had the opportunities to approach PLHIV directly.

Keywords: Islamic religious officers, people with HIV, stigma and discrimination, training programmes

Procedia PDF Downloads 505

Authors: Chaca Nugraha Zaid, Hikmat Ronaldo, Emerald Falah Brayoga, Azizah Eddy Setiawati, Soviandini Dwiki Kartika Putri, Novita Wijayanti

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In the tofu stick production, the manual cutting process takes a half of working day or 4 hours for 21 kg of tofu. This issue has hampered the small and medium enterprises (SMEs) to increase the capacity of production to fulfill the market demand. In order to address the issue, the cutting process should be automized to create fast, efficient, and effective tools. This innovation to tackle this problem is an automatic cutter tool that is able to move continuously to cut the tofu into stick size. The tool uses the 78,5-watt electric motor and automatic sensors to drive the cutting tool automatically, resulting faster process time with more uniform size compared to the manual cutter. The component of this tool, i.e., cutting knife and the driver, electric motor, limit switch sensors, riley, Arduino nano, and power supply. The cutting speed cutting speed of this tool is 101,25 mm/s producing 64 tofu sticks. Benefits that can be obtained from the use of automatic tofu stick cutter, i.e. (1) Faster process (2) More uniform cutting result; (3) The quality of the tofu stick is maintained due to minimal contact with humans so that contamination can be suppressed; (4) The cutting knife can be modified to the desired size of the owner.

Keywords: automatic, cutter, small and medium enterprise, tofu stick

Procedia PDF Downloads 166

Authors: Rumeysa Gunduz, Dirk Koester, Thomas Schack

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Previous behavioral studies have shown that working memory (WM) and manual actions share limited capacity cognitive resources, which in turn results in execution costs of manual actions in WM. However, to the best of our knowledge, there is no study investigating the neurophysiology of execution costs. The current study aims to fill this research gap investigating the neurophysiology of execution costs of grasping in WM phases (encoding, maintenance, retrieval) considering verbal and visuospatial domains of WM. A WM-grasping dual task paradigm was implemented to examine execution costs. Baseline single task required performing verbal or visuospatial version of a WM task. Dual task required performing the WM task embedded in a high precision grasp to place task. 30 participants were tested in a 2 (single vs. dual task) x 2 (visuo-spatial vs. verbal WM) within subject design. Event related potentials (ERPs) were extracted for each WM phase separately in the single and dual tasks. Memory performance for visuospatial WM, but not for verbal WM, was significantly lower in the dual task compared to the single task. Encoding related ERPs in the single task revealed different ERPs of verbal WM and visuospatial WM at bilateral anterior sites and right posterior site. In the dual task, bilateral anterior difference disappeared due to bilaterally increased anterior negativities for visuospatial WM. Maintenance related ERPs in the dual task revealed different ERPs of verbal WM and visuospatial WM at bilateral posterior sites. There was also anterior negativity for visuospatial WM. Retrieval related ERPs in the single task revealed different ERPs of verbal WM and visuospatial WM at bilateral posterior sites. In the dual task, there was no difference between verbal WM and visuospatial WM. Behavioral and ERP findings suggest that execution of grasping shares cognitive resources only with visuospatial WM, which in turn results in domain specific execution costs. Moreover, ERP findings suggest unique patterns of costs in each WM phase, which supports the idea that each WM phase reflects a separate cognitive process. This study not only contributes to the understanding of cognitive principles of manual action control, but also contributes to the understanding of WM as an entity consisting of separate modalities and cognitive processes.

Keywords: dual task, grasping execution, neurophysiology, working memory domains, working memory phases

Procedia PDF Downloads 426

Authors: Mohd Radzi Hilmi, Khairidzan Mohd Kamal, Che Azemin Mohd Zulfaezal, Ariffin Azrin Esmady

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Purpose: Corneal curvature (CC) is an important anterior segment parameter. This study compared CC measurements conducted with two optical devices in phakic eyes. Methods: Sixty phakic eyes of 30 patients were enrolled in this study. CC was measured three times with the optical biometer and topography-keratometer Tomey AO-2000 (Tomey Corporation, Nagoya, Japan), then with the standard partial optical coherence interferometry (PCI) IOL Master (Carl Zeiss Meditec, Dublin, CA) and data were statistically analysed. Results: The measurements resulted in a mean CC of 43.86 ± 1.57 D with Tomey AO-2000 and 43.84 ± 1.55 D with IOL Master. Distribution of data is normal, and no significance difference in CC values was detected (P = 0.952) between the two devices. Correlation between CC measurements was highly significant (r = 0. 99; P < 0.0001). The mean difference of CC values between devices was 0.017 D and 95% limit of agreement was -0.088 to 0.12. Duration taken for measurements with the standard biometer IOL Master was longer (55.17 ± 2.24 seconds) than with Tomey AO-2000 (39.88 ± 2.38 seconds) in automatic mode. Duration of manual measurement with Tomey AO-2000 in manual mode was the shortest (28.57 ± 2.71 seconds). Conclusion: In phakic eyes, CC measured with Tomey AO-2000 and IOL Master showed similar values, and high correlation was observed between these two devices. This shows that both devices can be used interchangeably. Tomey AO-2000 is better in terms of faster to operate and has its own topography systems.

Keywords: corneal topography, corneal curvature, IOL Master, Tomey AO2000

Procedia PDF Downloads 387

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

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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

Procedia PDF Downloads 272

Authors: Hatim Laalej, Salvador Sumohano-Verdeja, Thomas McLeay

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Monitoring of tool wear in milling operations is essential for achieving the desired dimensional accuracy and surface finish of a machined workpiece. Although there are numerous statistical models and artificial intelligence techniques available for monitoring the wear of cutting tools, these techniques cannot pin point which cutting edge of the tool, or which insert in the case of indexable tooling, is worn or broken. Currently, the task of monitoring the wear on the tool cutting edges is carried out by the operator who performs a manual inspection, causing undesirable stoppages of machine tools and consequently resulting in costs incurred from lost productivity. The present study is concerned with the development of a flute tracking system to segment signals related to each physical flute of a cutter with three flutes used in an end milling operation. The purpose of the system is to monitor the cutting condition for individual flutes separately in order to determine their progressive wear rates and to predict imminent tool failure. The results of this study clearly show that signals associated with each flute can be effectively segmented using the proposed flute tracking system. Furthermore, the results illustrate that by segmenting the sensor signal by flutes it is possible to investigate the wear in each physical cutting edge of the cutting tool. These findings are significant in that they facilitate the online condition monitoring of a cutting tool for each specific flute without the need for operators/engineers to perform manual inspections of the tool.

Keywords: machining, milling operation, tool condition monitoring, tool wear prediction

Procedia PDF Downloads 303

Authors: Mahawish Masud, Muhammad Iqbal, M. U. Khan, Farooque Azam

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Manual writing of test cases from functional requirements is a time-consuming task. Such test cases are not only difficult to write but are also challenging to maintain. Test cases can be drawn from the functional requirements that are expressed in natural language. However, manual test case generation is inefficient and subject to errors.  In this paper, we have presented a systematic procedure that could automatically derive test cases from user stories. The user stories are specified in a restricted natural language using a well-defined template.  We have also presented a detailed methodology for writing our test ready user stories. Our tool “Test-o-Matic” automatically generates the test cases by processing the restricted user stories. The generated test cases are executed by using open source Selenium IDE.  We evaluate our approach on a case study, which is an open source web based application. Effectiveness of our approach is evaluated by seeding faults in the open source case study using known mutation operators.  Results show that the test case generation from restricted user stories is a viable approach for automated testing of web applications.

Keywords: automated testing, natural language, restricted user story modeling, software engineering, software testing, test case specification, transformation and automation, user story, web application testing

Procedia PDF Downloads 387

Authors: Sarmin, S., Ologuin, R.S.

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Background: Rapid population growth and land constraints in Singapore results in a possible situation in which we face a higher number of casualties and lack of operational space in healthcare facilities during disasters and HAZMAT events, collectively known as Civil Emergencies. This creates a need for available working space within hospital grounds to be amphibious or multi-functional, to ensure the institution’s capability to respond efficiently to Civil Emergencies. The Emergency Department (ED) mitigates this issue by converting the Ambulance Assembly Area used during peacetime into an Open Decontamination Facility (ODF) during Civil Emergency Response, for decontamination of casualties before they proceed to treatment areas into Ambulance Assembly Area used during peacetime. Aims: To effectively operationalize the Open Decontamination Facility (ODF) through the reduction of manual handling. Methods: From past experiences on Civil Emergency exercises, it was labor-intensive for staff to set up the Open Decontamination Facility (ODF). Manual handling to set up the Decontamination lanes by bringing down the curtains and supply of water was required to be turned on. Conclusion: The effectiveness of the design construction of an Open Decontamination Facility (ODF) is based on the use of automation of bringing down the curtains on the various lanes. The use of control panels for water supply to decontaminate patients. Safety within the ODF was considered with the installation of panic buttons, intercom for staff communication, and perimeter curtains were installed with stability arm to manage the condition with high wind velocity.

Keywords: civil emergencies, disaster, emergency department, Hazmat

Procedia PDF Downloads 100

Authors: Xin Jiao, Xin Zhang, Jian Fan, Zhenwei Cai, Yiming Xu

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Tower cranes play a crucial role in the construction industry, facilitating the vertical and horizontal movement of materials and aiding in building construction, especially for high-rise structures. However, tower crane accidents can lead to severe consequences, highlighting the importance of effective safety management and inspection. This paper presents an innovative approach to tower crane inspection utilizing Unmanned Aerial Vehicles (UAVs) and an Intelligent Inspection APP System. The system leverages UAVs equipped with high-definition cameras to conduct efficient and comprehensive inspections, reducing manual labor, inspection time, and risk. By integrating advanced technologies such as Real-Time Kinematic (RTK) positioning and digital image processing, the system enables precise route planning and collection of safety hazards images. A case study conducted on a construction site demonstrates the practicality and effectiveness of the proposed method, showcasing its potential to enhance tower crane safety. On-site testing of UAV intelligent inspections reveals key findings: efficient tower crane hazard inspection within 30 minutes, with a full-identification capability coverage rates of 76.3%, 64.8%, and 76.2% for major, significant, and general hazards respectively and a preliminary-identification capability coverage rates of 18.5%, 27.2%, and 19%, respectively. Notably, UAVs effectively identify various tower crane hazards, except for those requiring auditory detection. The limitations of this study primarily involve two aspects: Firstly, during the initial inspection, manual drone piloting is required for marking tower crane points, followed by automated flight inspections and reuse based on the marked route. Secondly, images captured by the drone necessitate manual identification and review, which can be time-consuming for equipment management personnel, particularly when dealing with a large volume of images. Subsequent research efforts will focus on AI training and recognition of safety hazard images, as well as the automatic generation of inspection reports and corrective management based on recognition results. The ongoing development in this area is currently in progress, and outcomes will be released at an appropriate time.

Keywords: tower crane, inspection, unmanned aerial vehicle (UAV), intelligent inspection app system, safety management

Procedia PDF Downloads 42

Authors: Hichem Sassi

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Pneumonia, being a respiratory infection, has garnered global attention due to its rapid transmission and relatively high mortality rates. Timely detection and treatment play a crucial role in significantly reducing mortality associated with pneumonia. Presently, X-ray diagnosis stands out as a reasonably effective method. However, the manual scrutiny of a patient's X-ray chest radiograph by a proficient practitioner usually requires 5 to 15 minutes. In situations where cases are concentrated, this places immense pressure on clinicians for timely diagnosis. Relying solely on the visual acumen of imaging doctors proves to be inefficient, particularly given the low speed of manual analysis. Therefore, the integration of artificial intelligence into the clinical image diagnosis of pneumonia becomes imperative. Additionally, AI recognition is notably rapid, with convolutional neural networks (CNNs) demonstrating superior performance compared to human counterparts in image identification tasks. To conduct our study, we utilized a dataset comprising chest X-ray images obtained from Kaggle, encompassing a total of 5216 training images and 624 test images, categorized into two classes: normal and pneumonia. Employing five mainstream network algorithms, we undertook a comprehensive analysis to classify these diseases within the dataset, subsequently comparing the results. The integration of artificial intelligence, particularly through improved network architectures, stands as a transformative step towards more efficient and accurate clinical diagnoses across various medical domains.

Keywords: deep learning, computer vision, pneumonia, models, comparative study

Procedia PDF Downloads 64

Authors: Guilherme Giacomini, Ana Luiza Menegatti Pavan, Allan Felipe Fattori Alves, Marcela de Oliveira, Fernando Antonio Bacchim Neto, José Ricardo de Arruda Miranda, Seizo Yamashita, Diana Rodrigues de Pina

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The maxillary sinus (MS), part of the paranasal sinus complex, is one of the most enigmatic structures in modern humans. The literature has suggested that MSs function as olfaction accessories, to heat or humidify inspired air, for thermoregulation, to impart resonance to the voice and others. Thus, the real function of the MS is still uncertain. Furthermore, the MS anatomy is complex and varies from person to person. Many diseases may affect the development process of sinuses. The incidence of rhinosinusitis and other pathoses in the MS is comparatively high, so, volume analysis has clinical value. Providing volume values for MS could be helpful in evaluating the presence of any abnormality and could be used for treatment planning and evaluation of the outcome. The computed tomography (CT) has allowed a more exact assessment of this structure, which enables a quantitative analysis. However, this is not always possible in the clinical routine, and if possible, it involves much effort and/or time. Therefore, it is necessary to have a convenient, robust, and practical tool correlated with the MS volume, allowing clinical applicability. Nowadays, the available methods for MS segmentation are manual or semi-automatic. Additionally, manual methods present inter and intraindividual variability. Thus, the aim of this study was to develop an automatic tool to quantity the MS volume in CT scans of paranasal sinuses. This study was developed with ethical approval from the authors’ institutions and national review panels. The research involved 30 retrospective exams of University Hospital, Botucatu Medical School, São Paulo State University, Brazil. The tool for automatic MS quantification, developed in Matlab®, uses a hybrid method, combining different image processing techniques. For MS detection, the algorithm uses a Support Vector Machine (SVM), by features such as pixel value, spatial distribution, shape and others. The detected pixels are used as seed point for a region growing (RG) segmentation. Then, morphological operators are applied to reduce false-positive pixels, improving the segmentation accuracy. These steps are applied in all slices of CT exam, obtaining the MS volume. To evaluate the accuracy of the developed tool, the automatic method was compared with manual segmentation realized by an experienced radiologist. For comparison, we used Bland-Altman statistics, linear regression, and Jaccard similarity coefficient. From the statistical analyses for the comparison between both methods, the linear regression showed a strong association and low dispersion between variables. The Bland–Altman analyses showed no significant differences between the analyzed methods. The Jaccard similarity coefficient was > 0.90 in all exams. In conclusion, the developed tool to quantify MS volume proved to be robust, fast, and efficient, when compared with manual segmentation. Furthermore, it avoids the intra and inter-observer variations caused by manual and semi-automatic methods. As future work, the tool will be applied in clinical practice. Thus, it may be useful in the diagnosis and treatment determination of MS diseases. Providing volume values for MS could be helpful in evaluating the presence of any abnormality and could be used for treatment planning and evaluation of the outcome. The computed tomography (CT) has allowed a more exact assessment of this structure which enables a quantitative analysis. However, this is not always possible in the clinical routine, and if possible, it involves much effort and/or time. Therefore, it is necessary to have a convenient, robust and practical tool correlated with the MS volume, allowing clinical applicability. Nowadays, the available methods for MS segmentation are manual or semi-automatic. Additionally, manual methods present inter and intraindividual variability. Thus, the aim of this study was to develop an automatic tool to quantity the MS volume in CT scans of paranasal sinuses. This study was developed with ethical approval from the authors’ institutions and national review panels. The research involved 30 retrospective exams of University Hospital, Botucatu Medical School, São Paulo State University, Brazil. The tool for automatic MS quantification, developed in Matlab®, uses a hybrid method, combining different image processing techniques. For MS detection, the algorithm uses a Support Vector Machine (SVM), by features such as pixel value, spatial distribution, shape and others. The detected pixels are used as seed point for a region growing (RG) segmentation. Then, morphological operators are applied to reduce false-positive pixels, improving the segmentation accuracy. These steps are applied in all slices of CT exam, obtaining the MS volume. To evaluate the accuracy of the developed tool, the automatic method was compared with manual segmentation realized by an experienced radiologist. For comparison, we used Bland-Altman statistics, linear regression and Jaccard similarity coefficient. From the statistical analyses for the comparison between both methods, the linear regression showed a strong association and low dispersion between variables. The Bland–Altman analyses showed no significant differences between the analyzed methods. The Jaccard similarity coefficient was > 0.90 in all exams. In conclusion, the developed tool to automatically quantify MS volume proved to be robust, fast and efficient, when compared with manual segmentation. Furthermore, it avoids the intra and inter-observer variations caused by manual and semi-automatic methods. As future work, the tool will be applied in clinical practice. Thus, it may be useful in the diagnosis and treatment determination of MS diseases.

Keywords: maxillary sinus, support vector machine, region growing, volume quantification

Procedia PDF Downloads 504

Authors: Jareeluk Ratanaphan

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The purposed of this research were; 1. To survey the teacher’s needs on knowledge about special education management for special needs student 2. Development of distance training packages for teacher on special education management for special needs student 3. to study the effects of using the packages on trainee’s achievement 4. to study the effects of using the packages on trainee’s opinion on the distance training packages. The design of the experiment was research and development. The research sample for survey were 86 teachers, and 22 teachers for study the effects of using the packages on achievement and opinion. The research instrument comprised: 1) training packages on special education management for special needs student 2) achievement test 3) questionnaire. Mean, percentage, standard deviation, t-test and content analysis were used for data analysis. The findings of the research were as follows: 1. The teacher’s needs on knowledge about teaching for a learner with learning disability, mental retardation, autism, physical and health impairment and research in special education. 2. The package composed of special education management for special needs student document and manual of distance training packages. The document consisted by the name of packages, the explanation for the educator, content’s structure, concept, objectives, content and activities. Manual of distance training packages consisted by the explanation about a document, objectives, explanation about using the package, training schedule, and evaluation. The efficiency of packages was established at 79.50/81.35. 3. The results of using the packages were the posttest average scores of trainee’s achievement were higher than the pretest. 4. The trainee’s opinion on the package was at the highest level.

Keywords: distance training package, teacher, learner with special needs

Procedia PDF Downloads 489

Authors: Amit Barde, Dipali Khatave, Vaishali Savale, Atharva Chavan, Sapna Wagaj, Aditya Jilla

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AgriInnoConnect Pro is an advanced agricultural automation system designed to enhance irrigation efficiency and overall farm management through IoT technology. Using MIT App Inventor, Telegram, Arduino IDE, and Firebase Console, it provides a user-friendly interface for farmers. Key hardware includes soil moisture sensors, DHT11 sensors, a 12V motor, a solenoid valve, a stepdown transformer, Smart Fencing, and AC switches. The system operates in automatic and manual modes. In automatic mode, the ESP32 microcontroller monitors soil moisture and autonomously controls irrigation to optimize water usage. In manual mode, users can control the irrigation motor via a mobile app. Telegram bots enable remote operation of the solenoid valve and electric fencing, enhancing farm security. Additionally, the system upgrades conventional devices to smart ones using AC switches, broadening automation capabilities. AgriInnoConnect Pro aims to improve farm productivity and resource management, addressing the critical need for sustainable water conservation and providing a comprehensive solution for modern farm management. The integration of smart technologies in AgriInnoConnect Pro ensures precision farming practices, promoting efficient resource allocation and sustainable agricultural development.

Keywords: agricultural automation, IoT, soil moisture sensor, ESP32, MIT app inventor, telegram bot, smart farming, remote control, firebase console

Procedia PDF Downloads 43

Authors: Mohd Noah A. Rahman, Afzaal H. Seyal, Sharul T. Tajuddin, Hartiny Md Azmi

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Taking into consideration the real time situation specifically the higher academic institutions, small, medium to large companies, public to private sectors and the remaining sectors, do experience the inventory or asset shrinkages due to theft, loss or even inventory tracking errors. This happening is due to a zero or poor security systems and measures being taken and implemented in their organizations. Henceforth, implementing the Radio Frequency Identification (RFID) technology into any manual or existing web-based system or web application can simply deter and will eventually solve certain major issues to serve better data retrieval and data access. Having said, this manual or existing system can be enhanced into a mobile-based system or application. In addition to that, the availability of internet connections can aid better services of the system. Such involvement of various technologies resulting various privileges to individuals or organizations in terms of accessibility, availability, mobility, efficiency, effectiveness, real-time information and also security. This paper will look deeper into the integration of mobile devices with RFID technologies with the purpose of asset tracking and control. Next, it is to be followed by the development and utilization of MongoDB as the main database to store data and its association with RFID technology. Finally, the development of a web based system which can be viewed in a mobile based formation with the aid of Hypertext Preprocessor (PHP), MongoDB, Hyper-Text Markup Language 5 (HTML5), Android, JavaScript and AJAX programming language.

Keywords: RFID, asset tracking system, MongoDB, NoSQL

Procedia PDF Downloads 306

Authors: Rajib Husain, Munirujzaman Osmani, Mohammad Shamsal Islam

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Purpose: To compare the safety, efficacy and visual outcome of phacoemulsification vs. manual small-incision cataract surgery (SICS) for the treatment of cataract in Bangladesh. Objectives: 1. To assess the Visual outcome after cataract surgery 2. To understand the post-operative complications and early rehabilitation 3. To identified which surgical procedure more attractive to the patients 4. To identify which surgical procedure is occurred fewer complications. 5. To find out the socio-economic and demographic characteristics of study patients Setting: Chittagong Eye Infirmary and Training Complex, Chittagong, Bangladesh. Design: Retrospective, randomised comparison of 300 patients with visually significant cataracts. Method: The present study was designed as a retrospective hospital-based research. The sample size was 300 and study period was from July, 2012 to July, 2013 and assigned randomly to receive either phacoemulsification or manual small-incision cataract surgery (SICS). Preoperative and post-operative data were collected through a well designed collection format. Three follow-up were done; i) during discharge ii) 1-3 weeks & iii) 4-11 weeks post operatively. All preoperative and surgical complications, uncorrected and best-corrected visual acuity (BCVA) and astigmatism were taken into consideration for comparison of outcome Result: Nearly 95% patients were more than 40 years of age. About 52% patients were female, and 48% were male. 52% (N=157) patients came to operate their first eye where 48% (N=143) patients were visited again to operate their second eye. Postoperatively, five eyes (3.33%) developed corneal oedema with >10 Descemets folds, and six eyes (4%) had corneal oedema with <10 Descemets folds for Phacoemulsification surgeries. For SICS surgeries, seven eyes (4.66%) developed corneal oedema with >10 Descemets folds and eight eyes (5.33%) had corneal oedema with < 10 descemets folds. However, both the uncorrected and corrected (4-11 weeks) visual acuities were better in the eyes that had phacoemulsification (p=0.02 and p=0.03), and there was less astigmatism (p=0.001) at 4-11 weeks in the eye that had phacoemulsification. Best-corrected visual acuity (BCVA) of final follow-up 95% (N=253) had a good outcome, borderline 3.10% (N=40) and poor outcome was 1.6% (N=7). The individual surgeon outcome were closer, 95% (BCVA) in SICS and 96% (BCVA) in Phacoemulsification at 4-11 weeks follow-up respectively. Conclusion: outcome of cataract surgery both Phacoemulsification and SICS in CEITC was more satisfactory according to who norms. Both Phacoemulsification and manual small-incision cataract surgery (SICS) shows excellent visual outcomes with low complication rates and good rehabilitation. Phacoemulsification is significantly faster, and modern technology based surgical procedure for cataract treatment.

Keywords: phacoemulsification, SICS, cataract, Bangladesh, visual outcome of SICS

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Authors: Minoru Moriguchi

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This research introduces the concept of a monolingual Japanese dictionary for non-native speakers of Japanese, whose temporal title is Dictionary of Contemporary Japanese for Advanced Learners (DCJAL). As the language market is very small compared with English, a monolingual Japanese dictionary for non-native speakers, containing sufficient entries, has not been published yet. In such a dictionary environment, Japanese-language learners are using bilingual dictionaries or monolingual Japanese dictionaries for Japanese people. This research started in 2017, as a project team which consists of four Japanese and two non-native speakers, all of whom are linguists of the Japanese language. The team has been trying to propose the concept of a monolingual dictionary for non-native speakers of Japanese and to provide the entry list, the definition samples, the list of defining vocabulary, and the writing manual. As the result of seven-year research, DCJAL has come to have 28,060 head words, 539 entry examples, 4,598-word defining vocabulary, and the writing manual. First, the number of the entry was determined as about 30,000, based on an experimental method using existing six dictionaries. To make the entry list satisfying this number, words suitable for DCJAL were extracted from the Tsukuba corpus of the Japanese language, and later the entry list was adjusted according to the experience as Japanese instructor. Among the head words of the entry list, 539 words were selected and added with lexicographical information such as proficiency level, pronunciation, writing system (hiragana, katakana, kanji, or alphabet), definition, example sentences, idiomatic expression, synonyms, antonyms, grammatical information, sociolinguistic information, and etymology. While writing the definition of the above 539 words, the list of the defining vocabulary was constructed, based on frequent vocabulary used in a Japanese monolingual dictionary. Although the concept of DCJAL has been almost perfected, it may need some more adjustment, and the research is continued.

Keywords: monolingual dictionary, the Japanese language, non-native speaker of Japanese, defining vocabulary

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Authors: Belgherbi Aicha, Bessaid Abdelhafid

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In the recent years a great deal of research work has been devoted to the development of semi-automatic and automatic techniques for the analysis of abdominal CT images. The first and fundamental step in all these studies is the semi-automatic liver and spleen segmentation that is still an open problem. In this paper, a semi-automatic liver and spleen segmentation method by the mathematical morphology based on watershed algorithm has been proposed. Our algorithm is currency in two parts. In the first, we seek to determine the region of interest by applying the morphological to extract the liver and spleen. The second step consists to improve the quality of the image gradient. In this step, we propose a method for improving the image gradient to reduce the over-segmentation problem by applying the spatial filters followed by the morphological filters. Thereafter we proceed to the segmentation of the liver, spleen. The aim of this work is to develop a method for semi-automatic segmentation liver and spleen based on watershed algorithm, improve the accuracy and the robustness of the liver and spleen segmentation and evaluate a new semi-automatic approach with the manual for liver segmentation. To validate the segmentation technique proposed, we have tested it on several images. Our segmentation approach is evaluated by comparing our results with the manual segmentation performed by an expert. The experimental results are described in the last part of this work. The system has been evaluated by computing the sensitivity and specificity between the semi-automatically segmented (liver and spleen) contour and the manually contour traced by radiological experts. Liver segmentation has achieved the sensitivity and specificity; sens Liver=96% and specif Liver=99% respectively. Spleen segmentation achieves similar, promising results sens Spleen=95% and specif Spleen=99%.

Keywords: CT images, liver and spleen segmentation, anisotropic diffusion filter, morphological filters, watershed algorithm

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Authors: Mohammed A. Al-Ajmi, Reem S. Al-Kandari

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This study is concerned with the behavior of engineering students in Kuwait University which became a concern due to the global issues of education in all levels. A survey has been conducted to identify academic and societal issues that affect the engineering student performance through. The study is drawing major conclusions with regard to private tutoring and the online availability of textbooks’ solution manuals.

Keywords: solution manual, engineering, textbook, ethics

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Authors: H. M. B. N Jayasinghe

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The water is found almost everywhere on Earth. Water resources contain a lot of pollution. Some diseases can be spread through the water to the living beings. So to be clean water it should undergo a number of treatments necessary to make it drinkable. So it is must to have purification technology for the wastewater. So the waste water treatment plants act a major role in these issues. When considering the procedures taken after the water treatment process was always based on manual calculations and recordings. Water purification plants may interact with lots of manual processes. It means the process taking much time consuming. So the final evaluation and chemical, biological treatment process get delayed. So to prevent those types of drawbacks there are some computerized programmable calculation and analytical techniques going to be introduced to the laboratory staff. To solve this problem automated system will be a solution in which guarantees the rational selection. A decision support system is a way to model data and make quality decisions based upon it. It is widely used in the world for the various kind of process automation. Decision support systems that just collect data and organize it effectively are usually called passive models where they do not suggest a specific decision but only reveal information. This web base system is based on global positioning data adding facility with map location. Most worth feature is SMS and E-mail alert service to inform the appropriate person on a critical issue. The technological influence to the system is HTML, MySQL, PHP, and some other web developing technologies. Current issues in the computerized water chemistry analysis are not much deep in progress. For an example the swimming pool water quality calculator. The validity of the system has been verified by test running and comparison with an existing plant data. Automated system will make the life easier in productively and qualitatively.

Keywords: automated system, wastewater, purification technology, map location

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Authors: Kumar Dron Shrivastav, Ankan Mukherjee Das, Arti Taneja, Harpreet Singh, Priya Ranjan, Rajiv Janardhanan

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Cervical cancer is one of the most common cancer among women worldwide which can be cured if detected early. Manual pathology which is typically utilized at present has many limitations. The current gold standard for cervical cancer diagnosis is exhaustive and time-consuming because it relies heavily on the subjective knowledge of the oncopathologists which leads to mis-diagnosis and missed diagnosis resulting false negative and false positive. To reduce time and complexities associated with early diagnosis, we require an interactive diagnostic tool for early detection particularly in developing countries where cervical cancer incidence and related mortality is high. Incorporation of digital pathology in place of manual pathology for cervical cancer screening and diagnosis can increase the precision and strongly reduce the chances of error in a time-specific manner. Thus, we propose a robust and interactive cervical cancer image analysis and diagnostic tool, which can categorically process both histopatholgical and cytopathological images to identify abnormal cells in the least amount of time and settings with minimum resources. Furthermore, incorporation of a set of specific parameters that are typically referred to for identification of abnormal cells with the help of open source software -’R’ is one of the major highlights of the tool. The software has the ability to automatically identify and quantify the morphological features, color intensity, sensitivity and other parameters digitally to differentiate abnormal from normal cells, which may improve and accelerate screening and early diagnosis, ultimately leading to timely treatment of cervical cancer.

Keywords: cervical cancer, early detection, digital Pathology, screening

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Authors: Ke Guek Nee, Wong Siew Fan, Nigel V. Marsh

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Excessive use of the Internet has become a cause for concern in many countries, including Malaysia. Such behaviour is reported to be more prevalent amongst young adults who are reported to be spending large amount of time on the Internet. The present study has three objectives. First one is designing a manual-based Cognitive Behavioural Therapy (CBT) programme to reduce problematic Internet use among young adults in Malaysia. Second one is examining the effectiveness of a manual-based CBT programme at the pilot study stage. Thirdly, the programme focuses on reducing the level of stress and anxiety in problematic Internet users. We adopted CBT with single subject experimental design method. A total of six participants completed the entire program. They were asked to report their daily Internet use and software was installed on their devices to record actual use. The data collection involved three time frame measurements: T1 (baseline), T2 (immediately during the last session of the intervention sessions), and T3 (follow-up). Three scales were used to measure the effectiveness of the program: Depression, Anxiety, Stress Scales (DASS), Social Interaction Anxiety Scale (SIAS), and Problematic Internet Use Questionnaire (PIUQ). The results revealed that the intervention programme has significantly improved two dimensions of problematic Internet use which were obsession and control disorder. The participants’ mental health also showed a deduction in means scores for depression, anxiety and stress with depression showing the greatest improvement after the intervention programme. The participants’ social anxiety showed a slight deduction in means scores. We concluded that the intervention programme designed was effective. However, its limitations need to be addressed in future research.

Keywords: excessive internet use, cognitive behavioral thearapy (CBT), psychological well-being, young adults

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Authors: Ali Ashtiani, Hamid Shirazi

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This paper reviews the status of existing practice and research related to measuring pavement cracking and using crack density as a pavement surface evaluation protocol. Crack density for pavement evaluation is currently not widely used within the airport community and its use by the highway community is limited. However, surface cracking is a distress that is closely monitored by airport staff and significantly influences the development of maintenance, rehabilitation and reconstruction plans for airport pavements. Therefore crack density has the potential to become an important indicator of pavement condition if the type, severity and extent of surface cracking can be accurately measured. A pavement distress survey is an essential component of any pavement assessment. Manual crack surveying has been widely used for decades to measure pavement performance. However, the accuracy and precision of manual surveys can vary depending upon the surveyor and performing surveys may disrupt normal operations. Given the variability of manual surveys, this method has shown inconsistencies in distress classification and measurement. This can potentially impact the planning for pavement maintenance, rehabilitation and reconstruction and the associated funding strategies. A substantial effort has been devoted for the past 20 years to reduce the human intervention and the error associated with it by moving toward automated distress collection methods. The automated methods refer to the systems that identify, classify and quantify pavement distresses through processes that require no or very minimal human intervention. This principally involves the use of a digital recognition software to analyze and characterize pavement distresses. The lack of established protocols for measurement and classification of pavement cracks captured using digital images is a challenge to developing a reliable automated system for distress assessment. Variations in types and severity of distresses, different pavement surface textures and colors and presence of pavement joints and edges all complicate automated image processing and crack measurement and classification. This paper summarizes the commercially available systems and technologies for automated pavement distress evaluation. A comprehensive automated pavement distress survey involves collection, interpretation, and processing of the surface images to identify the type, quantity and severity of the surface distresses. The outputs can be used to quantitatively calculate the crack density. The systems for automated distress survey using digital images reviewed in this paper can assist the airport industry in the development of a pavement evaluation protocol based on crack density. Analysis of automated distress survey data can lead to a crack density index. This index can be used as a means of assessing pavement condition and to predict pavement performance. This can be used by airport owners to determine the type of pavement maintenance and rehabilitation in a more consistent way.

Keywords: airport pavement management, crack density, pavement evaluation, pavement management

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Authors: Osman Turkoglu, Alvin Estilo, Ritu Gupta, Liliam Pineda-Salgado, Rajesh Pandey

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Background: Hepatotoxicity can be linked to a variety of clinical symptoms and histopathological signs, posing a great challenge in the surveillance of suspected drug-induced liver injury (DILI) cases in the safety database. Additionally, the majority of such cases are rare, idiosyncratic, highly unpredictable, and tend to demonstrate unique individual susceptibility; these qualities, in turn, lend to a pharmacovigilance monitoring process that is often tedious and time-consuming. Objective: Develop a multifactorial algorithm to assist pharmacovigilance physicians in identifying high-risk hepatotoxicity cases associated with DILI from the sponsor’s safety database (Argus). Methods: Multifactorial selection criteria were established using Structured Query Language (SQL) and the TIBCO Spotfire® visualization tool, via a combination of word fragments, wildcard strings, and mathematical constructs, based on Hy’s law criteria and pattern of injury (R-value). These criteria excluded non-eligible cases from monthly line listings mined from the Argus safety database. The capabilities and limitations of these criteria were verified by comparing a manual review of all monthly cases with system-generated monthly listings over six months. Results: On an average, over a period of six months, the algorithm accurately identified 92% of DILI cases meeting established criteria. The automated process easily compared liver enzyme elevations with baseline values, reducing the screening time to under 15 minutes as opposed to multiple hours exhausted using a cognitively laborious, manual process. Limitations of the algorithm include its inability to identify cases associated with non-standard laboratory tests, naming conventions, and/or incomplete/incorrectly entered laboratory values. Conclusions: The newly developed multifactorial algorithm proved to be extremely useful in detecting potential DILI cases, while heightening the vigilance of the drug safety department. Additionally, the application of this algorithm may be useful in identifying a potential signal for DILI in drugs not yet known to cause liver injury (e.g., drugs in the initial phases of development). This algorithm also carries the potential for universal application, due to its product-agnostic data and keyword mining features. Plans for the tool include improving it into a fully automated application, thereby completely eliminating a manual screening process.

Keywords: automation, drug-induced liver injury, pharmacovigilance, post-marketing

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Authors: Oumaima Khlifati, Khadija Baba

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Pavement distress is the main factor responsible for the deterioration of road structure durability, damage vehicles, and driver comfort. Transportation agencies spend a high proportion of their funds on pavement monitoring and maintenance. The auscultation of pavement distress was based on the manual survey, which was extremely time consuming, labor intensive, and required domain expertise. Therefore, the automatic distress detection is needed to reduce the cost of manual inspection and avoid more serious damage by implementing the appropriate remediation actions at the right time. Inspired by recent deep learning applications, this paper proposes an algorithm for automatic road distress detection and classification using on the Deep Convolutional Neural Network (DCNN). In this study, the types of pavement distress are classified as transverse or longitudinal cracking, alligator, pothole, and intact pavement. The dataset used in this work is composed of public asphalt pavement images. In order to learn the structure of the different type of distress, the DCNN models are trained and tested as a multi-label classification task. In addition, to get the highest accuracy for our model, we adjust the structural optimization hyper parameters such as the number of convolutions and max pooling, filers, size of filters, loss functions, activation functions, and optimizer and fine-tuning hyper parameters that conclude batch size and learning rate. The optimization of the model is executed by checking all feasible combinations and selecting the best performing one. The model, after being optimized, performance metrics is calculated, which describe the training and validation accuracies, precision, recall, and F1 score.

Keywords: distress pavement, hyperparameters, automatic classification, deep learning

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Authors: El Hadji Mamadou Sonko, Ndiogou Sankhare, Maïmouna Lo, Jean Birane Gning, Cheikh Diop

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In Senegal, access to water, hygiene, and sanitation in small island towns is a particular problem, which is still poorly understood by the public authorities and development aid actors. The main objective of this study carried out in the Municipality of Foundiougne is to contribute to the knowledge of the problems related to the supply of drinking water, access to sanitation, and hygiene in small island towns in Senegal. The methodology adopted consisted of a literature review and quantitative surveys of a sample of 100 households in the Municipality. Semi-structured interviews using interview guides and informal interviews were also conducted with mechanical and manual emptiers, municipal authorities, public toilet managers, and neighbourhood leaders. Direct observation with photography was also used. The results show that, with regard to access to drinking water, 35% of households have unimproved water services, 46% have a limited level of service, and 19% have a basic level of service. Regarding sanitation, 77% of households are considered to have access to basic sanitation services, compared to 23% with limited sanitation services. However, these figures hide the dysfunctions of the sanitation system. Indeed, manual emptying is practiced exclusively by 4% of households, while 17% of households combine it with mechanical emptying. In addition, domestic wastewater is mainly evacuated outside the sanitation facilities, and all the sludge extracted from the pits is discharged directly into the environment without treatment. As a matter of fact, the surveys showed that 52% of households do not have access to a basic level of hygiene-related to handwashing when leaving the toilet. These results show that there is real work to be done at the level of small urban centres if we want to achieve MDG 6.

Keywords: Foundiougne, Senegal, small island, small town, water-sanitation, hygiene

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Authors: Rony Reátegui, Cesar Chácara, Benjamin Castañeda, Rafael Aguilar

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Nowadays, heritage building information modeling (HBIM) is considered an efficient tool to represent and manage information of cultural heritage (CH). The basis of this tool relies on a 3D model generally obtained from a cloud-to-BIM procedure. There are different methods to create an HBIM model that goes from manual modeling based on the point cloud to the automatic detection of shapes and the creation of objects. The selection of these methods depends on the desired level of development (LOD), level of information (LOI), grade of generation (GOG), as well as on the availability of commercial software. This paper presents the 3D modeling of a stone masonry chapel using Recap Pro, Revit, and Dynamo interface following a three-step methodology. The first step consists of the manual modeling of simple structural (e.g., regular walls, columns, floors, wall openings, etc.) and architectural (e.g., cornices, moldings, and other minor details) elements using the point cloud as reference. Then, Dynamo is used for generative modeling of complex structural elements such as vaults, infills, and domes. Finally, semantic information (e.g., materials, typology, state of conservation, etc.) and pathologies are added within the HBIM model as text parameters and generic models families, respectively. The application of this methodology allows the documentation of CH following a relatively simple to apply process that ensures adequate LOD, LOI, and GOG levels. In addition, the easy implementation of the method as well as the fact of using only one BIM software with its respective plugin for the scan-to-BIM modeling process means that this methodology can be adopted by a larger number of users with intermediate knowledge and limited resources since the BIM software used has a free student license.

Keywords: cloud-to-BIM, cultural heritage, generative modeling, HBIM, parametric modeling, Revit

Procedia PDF Downloads 142