| 31. |
- Ahmed, Mobyen Uddin, Dr, 1976-, et al.
(författare)
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Data Analysis on Powered Two Wheelers Riders’ Behaviour using Machine Learning
- 2019
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Ingår i: First International Conference on Advances in Signal Processing and Artificial Intelligence ASPAI' 2019. - Barcelona, Spain.
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Konferensbidrag (refereegranskat)abstract
- Analyzing powered two-wheeler rider behavior, i.e. classification of riding patterns based on 3-D accelerometer/gyroscope sensors mounted on motorcycles is challenging. This paper presents machine learning approach to classify four different riding events performed by powered two wheeler riders’ as a step towards increasing traffic safety. Three machine learning algorithms, Random Forest (RF), Support Vector Machine (SVM) and Artificial Neural Network (ANN) have been used to classify riding patterns. The classification is conducted based on features extracted in time and frequency domains from accelerometer/gyroscope sensors signals. A comparison result between different filter frequencies, window sizes, features sets, as well as machine learning algorithms is presented. According to the results, the Random Forest method performs most consistently through the different data sets and scores best.
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| 32. |
- Ahmed, Mobyen Uddin, Dr, 1976-, et al.
(författare)
-
Dilemmas in designing e-learning experiences for professionals
- 2021
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Ingår i: Proceedings of the European Conference on e-Learning, ECEL. ; , s. 10-17
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Konferensbidrag (refereegranskat)abstract
- The aims of this research are to enhance industry-university collaboration and to design learning experiences connecting the research front to practitioners. We present an empirical study with a qualitative approach involving teachers who gathered data from newly developed advanced level courses in artificial intelligence, energy, environmental, and systems engineering. The study is part of FutureE, an academic development project over 3 years involving 12 courses. The project, as well as this study, is part of a cross-disciplinary collaboration effort. Empirical data comes from course evaluations, course analysis, teacher workshops, and semi-structured interviews with selected students, who are also professionals. This paper will discuss course design and course implementation by presenting dilemmas and paradoxes. Flexibility is key for the completion of studies while working. Academia needs to develop new ways to offer flexible education for students from a professional context, but still fulfil high quality standards and regulations as an academic institution. Student-to-student interactions are often suggested as necessary for qualified learning, and students support this idea but will often not commit to it during courses. Other dilemmas are micro-sized learning versus vast knowledge, flexibility versus deadlines as motivating factors, and feedback hunger versus hesitation to share work. Furthermore, we present the challenges of providing equivalent online experience to practical in-person labs. On a structural level, dilemmas appear in the communication between university management and teachers. These dilemmas are often the result of a culture designed for traditional campus education. We suggest a user-oriented approach to solve these dilemmas, which involves changes in teacher roles, culture, and processes. The findings will be relevant for teachers designing and running courses aiming to attract professionals. They will also be relevant for university management, building a strategy for lifelong e-learning based on co-creation with industry.
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| 33. |
- Ahmed, Mobyen Uddin, et al.
(författare)
-
Efficient Condition Monitoring and Diagnosis Using a Case-Based Experience Sharing System
- 2007
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Ingår i: The 20th International Congress and Exhibition on Condition Monitoring and Diagnostics Engineering Management, COMADEM 2007, Faro, Portugal. ; , s. 305-314
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Konferensbidrag (refereegranskat)abstract
- Industry has to adjust quickly to changes in their surroundings, for example reducing staff during recession and increasing staff when the market demands it. These factors may cause rapid loss of experience, collected during many years, or require experienced staff to spend considerable resources in training new staff, instead of focusing on production. This is recognised as very costly for companies and organisations today and also reduces competitiveness and productivity. Condition Monitoring, diagnostics and selection of efficient preventive or corrective actions is a task that often requires a high degree of expertise. This expertise is often gained through sometimes very expensive mistakes and can take many years to acquire leading to a few skilled experts. When they are not available due to changes in staff or retirements the company often faces serious problems that may be very expensive, e.g. leading to a reduced productivity.If some deviation occurs in a machine, a fault report is often written; an engineer makes a diagnosis and may order spare parts to repair the machine. Fault report, spare parts, required time and statistics on performance after repair are often stored in different databases but so far not systematically reused. In this paper we present a Case-Based experience sharing system that enables reuse of experience in a more efficient way compared with what is mostly practiced in industry today. The system uses Case-Based-Reasoning (CBR) and limited Natural Language Processing. An important aspect of the experience management tool is that it is user-friendly and web-based to promote efficient experience sharing. The system should be able to handle both experiences that are only in house as well as sharing experience with other industries when there is no conflicting interest. Such a CBR based tool enables efficient experience gathering, management and reuse in production industries. The tool will facilitate the users with an interactive environment to communicate with each other for sharing their experiences. Depend on the user; the security level of the system will be varied to share knowledge among the collaborating companies.The system identifies the most relevant experiences to assess and resolve the current situation. The experience is stored and retrieved as a case in the collaborative space where experience from various companies may have been stored under many years. Reusing experience and avoiding expensive mistakes will increase the participating companies' competitiveness and also transfer valuable experience to their employees. One of the benefits is also the opportunity and facility to identify people with similar tasks and problems at different companies and enable them to share their experience, e.g. if a technician has solved a similar problem recently and is in the near, the most efficient solution may be to call the expert and ask for assistance. In future, one may access this tool through his/her mobile device via wireless or mobile communications using Global Positioning System, GPS, enables the system to suggest experts nearby, willing and able to share the knowledge and quickly assist in resolve the problem.
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| 34. |
- Ahmed, Mobyen Uddin, 1976-, et al.
(författare)
-
FUZZY RULE-BASED CLASSIFICATION TO BUILD INITIAL CASE LIBRARY FOR CASE-BASED STRESS DIAGNOSIS
- 2009
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Ingår i: Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2009. - 9780889867802 ; , s. 225-230
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Konferensbidrag (refereegranskat)abstract
- Case-Based Reasoning (CBR) is receiving increasedinterest for applications in medical decision support.Clinicians appreciate the fact that the system reasons withfull medical cases, symptoms, diagnosis, actions takenand outcomes. Also for experts it is often appreciated toget a second opinion. In the initial phase of a CBR systemthere are often a limited number of cases available whichreduces the performance of the system. If past cases aremissing or very sparse in some areas the accuracy isreduced. This paper presents a fuzzy rule-basedclassification scheme which is introduced into the CBRsystem to initiate the case library, providing improvedperformance in the stress diagnosis task. Theexperimental results showed that the CBR system usingthe enhanced case library can correctly classify 83% ofthe cases, whereas previously the correctness of theclassification was 61%. Consequently the proposedsystem has an improved performance with 22% in termsof accuracy. In terms of the discrepancy in classificationcompared to the expert, the goodness-of-fit value of thetest results is on average 87%. Thus by employing thefuzzy rule-based classification, the new hybrid system cangenerate artificial cases to enhance the case library.Furthermore, it can classify new problem cases previouslynot classified by the system.
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| 35. |
- Ahmed, Mobyen Uddin, 1976-, et al.
(författare)
-
Health monitoring for elderly : an application using case-based reasoning and cluster analysis
- 2013
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Ingår i: ISRN Artificial Intelligence. - Sweden : Hindawi Limited. - 2090-7435 .- 2090-7443. ; 2013:2013, s. 1-11
-
Tidskriftsartikel (refereegranskat)abstract
- This paper presents a framework to process and analyze data from a pulse oximeter which measures pulse rate and blood oxygen saturation from a set of individuals remotely. Using case-based reasoning (CBR) as the backbone to the framework, records are analyzed and categorized according to how well they are similar. Record collection has been performed using a personalized health profiling approach where participants wore a pulse oximeter sensor for a fixed period of time and performed specific activities for pre-determined intervals. Using a variety of feature extraction in time, frequency and time-frequency domains, and data processing techniques, the data is fed into a CBR system which retrieves most similar cases and generates alarm and flag according to the case outcomes. The system has been compared with an expert's classification and 90% match is achieved between the expert's and CBR classification. Again, considering the clustered measurements the CBR approach classifies 93% correctly both for the pulse rate and oxygen saturation. Along with the proposed methodology, this paper provides a basis for which the system can be used in analysis of continuous health monitoring and be used as a suitable method as in home/remote monitoring systems.
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| 36. |
- Ahmed, Mobyen Uddin, et al.
(författare)
-
Healthcare Service at Home : An Intelligent Health Monitoring System for Elderly
- 2015
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Ingår i: Medicinteknikdagarna 2015 MFT 2015.
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Konferensbidrag (refereegranskat)abstract
- This paper presents an intelligent healthcare service to support active ageing by assisting seniors to participate in regular monitoring of elderly’s health condition. The proposed system is applicable to use in home environment and offers a self-service approach to monitor elderly’s health condition. According to the evaluation, the proposed system shows its necessity, competence and usefulness.
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| 37. |
- Ahmed, Mobyen Uddin, et al.
(författare)
-
Heart Rate and Inter-beat Interval Computation to Diagnose Stress
- 2010
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Problem in diagnosing of stress is an important issue. The variations in beat-to-beat alteration in the heart rate (HR) can provide an identification of stress. HR can be determined from the Electrocardiogram (ECG) signal. However, accurate detection of HR and inter-beat interval (IBI) values from the ECG waveform is important. This report presents a way of measuring the ECG signal together with the ECG component analysis such as QRS peak detection and HR calculation to use it in a computer-based stress diagnosis system.
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| 38. |
- Ahmed, Mobyen Uddin, et al.
(författare)
-
Intelligent Healthcare Services to Support Health Monitoring of Elderly
- 2014
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Ingår i: International Conference on IoT Technologies for HealthCare HealthyIoT. - Rome, Italy.
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Konferensbidrag (refereegranskat)abstract
- This paper proposed an approach of intelligent healthcare services to support health monitoring of old people through the project named SAAPHO. Here, definition and architecture of the proposed healthcare services are presented considering six different health parameters such as: 1) physical activity, 2) blood pressure, 3) glucose, 4) medication compliance, 5) pulse monitoring and 6) weight monitoring. The outcome of the proposed services is evaluated in a case study where total 201 subjects from Spain and Slovenia are involved for user requirements analysis considering 1) end users, 2) clinicians, and 3) field study analysis perspectives. The result shows the potentiality and competence of the proposed healthcare services for the users.
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| 39. |
- Ahmed, Mobyen Uddin, 1976-, et al.
(författare)
-
Intelligent Healthcare Services to Support Health Monitoring of Elderly
- 2015
-
Ingår i: INTERNET OF THINGS. - Cham : Springer. - 9783319196565 - 9783319196558 ; , s. 178-186
-
Konferensbidrag (refereegranskat)abstract
- This paper proposed an approach of intelligent healthcare services to support health monitoring of old people through the project named SAAPHO. Here, definition and architecture of the proposed healthcare services are presented considering six different health parameters such as: 1) physical activity, 2) blood pressure, 3) glucose, 4) medication compliance, 5) pulse monitoring and 6) weight monitoring. The outcome of the proposed services is evaluated in a case study where total 201 subjects from Spain and Slovenia are involved for user requirements analysis considering 1) end users, 2) clinicians, and 3) field study analysis perspectives. The result shows the potentiality and competence of the proposed healthcare services for the users.
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| 40. |
- Ahmed, Mobyen Uddin, et al.
(författare)
-
Intelligent Stress Management System
- 2009
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Ingår i: Medicinteknikdagarna 2009.
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Konferensbidrag (refereegranskat)abstract
- Today, in our daily life we are subjected to a wide range of pressures. When the pressures exceed the extent that we are able to deal with then stress is trigged. High level of stress may cause serious health problems i.e. it reduces awareness of bodily symptoms. So, people may first notice it weeks or months later meanwhile the stress could cause more serious effect in the body and health. A difficult issue in stress management is to use biomedical sensor signals in the diagnosis and treatment of stress. This paper presents a case-based system that assists a clinician in diagnosis and treatment of stress. The system uses a finger temperature sensor and the variation in the finger temperature is one of the key features in the system. Several artificial intelligence techniques such as textual information retrieval, rule-based reasoning (RBR), and fuzzy logic have been combined together with case-based reasoning to enable more reliable and efficient diagnosis and treatment of stress. The performance has been validated implementing a research prototype and close collaboration with experts.
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