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Goswami, Prashant
Publikasjoner (10 av 11) Visa alla publikasjoner
Peng, C. & Goswami, P. (2019). Meaningful Integration of Data from Heterogeneous Health Services and Home Environment Based on Ontology. Sensors, 19(8), Article ID 1747.
Åpne denne publikasjonen i ny fane eller vindu >>Meaningful Integration of Data from Heterogeneous Health Services and Home Environment Based on Ontology
2019 (engelsk)Inngår i: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 19, nr 8, artikkel-id 1747Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

The development of electronic health records, wearable devices, health applications and Internet of Things (IoT)-empowered smart homes is promoting various applications. It also makes health self-management much more feasible, which can partially mitigate one of the challenges that the current healthcare system is facing. Effective and convenient self-management of health requires the collaborative use of health data and home environment data from different services, devices, and even open data on the Web. Although health data interoperability standards including HL7 Fast Healthcare Interoperability Resources (FHIR) and IoT ontology including Semantic Sensor Network (SSN) have been developed and promoted, it is impossible for all the different categories of services to adopt the same standard in the near future. This study presents a method that applies Semantic Web technologies to integrate the health data and home environment data from heterogeneously built services and devices. We propose a Web Ontology Language (OWL)-based integration ontology that models health data from HL7 FHIR standard implemented services, normal Web services and Web of Things (WoT) services and Linked Data together with home environment data from formal ontology-described WoT services. It works on the resource integration layer of the layered integration architecture. An example use case with a prototype implementation shows that the proposed method successfully integrates the health data and home environment data into a resource graph. The integrated data are annotated with semantics and ontological links, which make them machine-understandable and cross-system reusable.

sted, utgiver, år, opplag, sider
MDPI, 2019
Emneord
FHIR; REST; Semantic Web; Web service; WoT; eHealth; health data integration; ontology; smart homes
HSV kategori
Identifikatorer
urn:nbn:se:bth-17810 (URN)10.3390/S19081747 (DOI)000467644500001 ()
Merknad

open access

Tilgjengelig fra: 2019-04-12 Laget: 2019-04-12 Sist oppdatert: 2019-06-13bibliografisk kontrollert
Peng, C., Goswami, P. & Bai, G. (2018). An Ontological Approach to Integrate Health Resources from Different Categories of Services. In: HEALTHINFO 2018, The Third International Conference on Informatics and Assistive Technologies for Health-Care, Medical Support and Wellbeing: . Paper presented at The Third International Conference on Informatics and Assistive Technologies for Health-Care, Medical Support and Wellbeing,HEALTHINFO, 2018-10-14 ~ 2018-10-18, Nice, France (pp. 48-54). International Academy, Research and Industry Association (IARIA)
Åpne denne publikasjonen i ny fane eller vindu >>An Ontological Approach to Integrate Health Resources from Different Categories of Services
2018 (engelsk)Inngår i: HEALTHINFO 2018, The Third International Conference on Informatics and Assistive Technologies for Health-Care, Medical Support and Wellbeing, International Academy, Research and Industry Association (IARIA), 2018, s. 48-54Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Effective and convenient self-management of health requires collaborative utilization of health data from different services provided by healthcare providers, consumer-facing products and even open data on the Web. Although health data interoperability standards include Fast Healthcare Interoperability Resources (FHIR) have been developed and promoted, it is impossible for all the different categories of services to adopt in the near future. The objective of this study aims to apply Semantic Web technologies to integrate the health data from heterogeneously built services. We present an Web Ontology Language (OWL)-based ontology that models together health data from FHIR standard implemented services, normal Web services and Linked Data. It works on the resource integration layer of the presented layered integration architecture. An example use case that demonstrates how this method integrates the health data into a linked semantic health resource graph with the proposed ontology is presented.

sted, utgiver, år, opplag, sider
International Academy, Research and Industry Association (IARIA), 2018
Emneord
Health data integration; ontology; FHIR; Semantic Web; Web service; eHealth; REST
HSV kategori
Identifikatorer
urn:nbn:se:bth-17171 (URN)978-1-61208-675-0 (ISBN)
Konferanse
The Third International Conference on Informatics and Assistive Technologies for Health-Care, Medical Support and Wellbeing,HEALTHINFO, 2018-10-14 ~ 2018-10-18, Nice, France
Tilgjengelig fra: 2018-10-28 Laget: 2018-10-28 Sist oppdatert: 2018-11-16bibliografisk kontrollert
Peng, C., Goswami, P. & Bai, G. (2018). Fuzzy Matching of OpenAPI Described REST Services. In: Procedia Computer Science: . Paper presented at 22nd International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2018; Metropol Palace HotelBelgrade; Serbia; 3 September 2018 through 5 September (pp. 1313-1322). Elsevier, 126
Åpne denne publikasjonen i ny fane eller vindu >>Fuzzy Matching of OpenAPI Described REST Services
2018 (engelsk)Inngår i: Procedia Computer Science, Elsevier, 2018, Vol. 126, s. 1313-1322Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

The vast amount of Web services brings the problem of discovering desired services for composition and orchestration. The syntactic service matching methods based on the classical set theory have a difficulty to capture the imprecise information. Therefore, an approximate service matching approach based on fuzzy control is explored in this paper. A service description matching model to the OpenAPI specification, which is the most widely used standard for describing the defacto REST Web services, is proposed to realize the fuzzy service matching with the fuzzy inference method developed by Mamdani and Assilian. An evaluation shows that the fuzzy service matching approach performed slightly better than the weighted approach in the setting context.

sted, utgiver, år, opplag, sider
Elsevier, 2018
Serie
Procedia Computer Science, ISSN 1877-0509
Emneord
service matching; fuzzy inference; OpenAPI; REST; fuzzy set theory
HSV kategori
Identifikatorer
urn:nbn:se:bth-16947 (URN)10.1016/j.procs.2018.08.081 (DOI)
Konferanse
22nd International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2018; Metropol Palace HotelBelgrade; Serbia; 3 September 2018 through 5 September
Merknad

Open access

Tilgjengelig fra: 2018-08-30 Laget: 2018-08-30 Sist oppdatert: 2018-11-29bibliografisk kontrollert
Peng, C., Goswami, P. & Bai, G. (2018). Linking Health Web Services as Resource Graph by Semantic REST Resource Tagging. In: Shakshuki E.,Yasar A. (Ed.), Procedia Computer Science: . Paper presented at 9th International Conference on Emerging Ubiquitous Systems and Pervasive Networks, EUSPN 2018; Leuven; Belgium; 5 November 2018 through 8 November 2018 (pp. 319-326). Elsevier, 141
Åpne denne publikasjonen i ny fane eller vindu >>Linking Health Web Services as Resource Graph by Semantic REST Resource Tagging
2018 (engelsk)Inngår i: Procedia Computer Science / [ed] Shakshuki E.,Yasar A., Elsevier, 2018, Vol. 141, s. 319-326Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Various health Web services host a huge amount of health data about patients. The heterogeneity of the services hinders the collaborative utilization of these health data, which can provide a valuable support for the self-management of chronic diseases. The combination of REST Web services and Semantic Web technologies has proven to be a viable approach to address the problem. This paper proposes a method to add semantic annotations to the REST Web services. The service descriptions and the resource representations with semantic annotations can be transformed into a resource graph. It integrates health data from different services, and can link to the health-domain ontologies and Linked Open Health Data to support health management and imaginative applications. The feasibility of out method is demonstrated by realizing with OpenAPI service description and JSON-LD representation in an example use case.

sted, utgiver, år, opplag, sider
Elsevier, 2018
Emneord
health data integration; eHealth; Web service description; Semantic Web; REST
HSV kategori
Identifikatorer
urn:nbn:se:bth-16850 (URN)10.1016/j.procs.2018.10.194 (DOI)000471261700040 ()
Konferanse
9th International Conference on Emerging Ubiquitous Systems and Pervasive Networks, EUSPN 2018; Leuven; Belgium; 5 November 2018 through 8 November 2018
Merknad

open access

Tilgjengelig fra: 2018-08-12 Laget: 2018-08-12 Sist oppdatert: 2019-09-06bibliografisk kontrollert
Sun, B., Cheng, W., Goswami, P. & Bai, G. (2018). Short-Term Traffic Forecasting Using Self-Adjusting k-Nearest Neighbours. IET Intelligent Transport Systems, 12(1), 41-48
Åpne denne publikasjonen i ny fane eller vindu >>Short-Term Traffic Forecasting Using Self-Adjusting k-Nearest Neighbours
2018 (engelsk)Inngår i: IET Intelligent Transport Systems, ISSN 1751-956X, E-ISSN 1751-9578, Vol. 12, nr 1, s. 41-48Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Short-term traffic forecasting is becoming more important in intelligent transportation systems. The k-nearest neighbours (kNN) method is widely used for short-term traffic forecasting.However, kNN parameters self-adjustment has been a problem due to dynamic traffic characteristics. This paper proposes a fully automatic dynamic procedure kNN (DP-kNN) that makes the kNN parameters self-adjustable and robust without predefined models or training. We used realworld data with more than one-year traffic records to conduct experiments. The results show that DP-kNN can perform better than manually adjusted kNN and other benchmarking methods with regards to accuracy on average. This study also discusses the difference between holiday and workday traffic prediction as well as the usage of neighbour distance measurement.

sted, utgiver, år, opplag, sider
Institution of Engineering and Technology, 2018
Emneord
intelligent transportation systems; short-term traffic forecasting; road traffic; DP-kNN; dynamic procedure kNN; self-adjusting k-nearest neighbours
HSV kategori
Identifikatorer
urn:nbn:se:bth-15727 (URN)10.1049/iet-its.2016.0263 (DOI)000426045200006 ()
Tilgjengelig fra: 2018-01-09 Laget: 2018-01-09 Sist oppdatert: 2018-11-01bibliografisk kontrollert
Sun, B., Cheng, W., Bai, G. & Goswami, P. (2017). Correcting and complementing freeway traffic accident data using mahalanobis distance based outlier detection. Technical Gazette, 24(5), 1597-1607
Åpne denne publikasjonen i ny fane eller vindu >>Correcting and complementing freeway traffic accident data using mahalanobis distance based outlier detection
2017 (engelsk)Inngår i: Technical Gazette, ISSN 1330-3651, E-ISSN 1848-6339, Vol. 24, nr 5, s. 1597-1607Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

A huge amount of traffic data is archived which can be used in data mining especially supervised learning. However, it is not being fully used due to lack of accurate accident information (labels). In this study, we improve a Mahalanobis distance based algorithm to be able to handle differential data to estimate flow fluctuations and detect accidents and use it to support correcting and complementing accident information. The outlier detection algorithm provides accurate suggestions for accident occurring time, duration and direction. We also develop a system with interactive user interface to realize this procedure. There are three contributions for data handling. Firstly, we propose to use multi-metric traffic data instead of single metric for traffic outlier detection. Secondly, we present a practical method to organise traffic data and to evaluate the organisation for Mahalanobis distance. Thirdly, we describe a general method to modify Mahalanobis distance algorithms to be updatable. © 2017, Strojarski Facultet. All rights reserved.

sted, utgiver, år, opplag, sider
Strojarski Facultet, 2017
Emneord
Accident data, Data labelling, Differential distance, Mahalanobis distance, Outlier detection, Traffic data, Updatable algorithm, Accidents, Data mining, Statistics, User interfaces, Mahalanobis distances, Data handling
HSV kategori
Identifikatorer
urn:nbn:se:bth-15472 (URN)10.17559/TV-20150616163905 (DOI)000417100300037 ()2-s2.0-85032512786 (Scopus ID)
Merknad

Funded by National Natural Science Foundation of China

Funding nr. 61364019

Tilgjengelig fra: 2017-11-10 Laget: 2017-11-10 Sist oppdatert: 2018-11-01bibliografisk kontrollert
Bertilsson, E. & Goswami, P. (2016). Dynamic Creation of Multi-resolution Triangulated Irregular Network. In: M. Hayashi (Ed.), Proceedings of SIGRAD 2016: . Paper presented at SIGRAD (The Swedish Chapter of Eurographics), Visby.
Åpne denne publikasjonen i ny fane eller vindu >>Dynamic Creation of Multi-resolution Triangulated Irregular Network
2016 (engelsk)Inngår i: Proceedings of SIGRAD 2016 / [ed] M. Hayashi, 2016Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Triangulated irregular network (TIN) can produce terrain meshes with a reduced triangle count compared toregular grid. At the same time, TIN meshes are more challenging to optimize in real-time in comparison to otherapproaches. This paper explores efficient generation of view-dependent, adaptive TIN meshes for terrain duringruntime with no or minimal preprocessing. This is achieved by reducing the problem of mesh simplification to thatof inexpensive 2D Delaunay triangulation and lifting it back to 3D. The approach and its efficiency is validatedwith suitable datasets.

Emneord
terrain rendering, triangulated irregular networks, TIN
HSV kategori
Identifikatorer
urn:nbn:se:bth-11990 (URN)
Konferanse
SIGRAD (The Swedish Chapter of Eurographics), Visby
Tilgjengelig fra: 2016-06-07 Laget: 2016-06-07 Sist oppdatert: 2018-01-10bibliografisk kontrollert
Frid Kastrati, M. & Goswami, P. (2016). Selective rasterized ray-traced reflections on the GPU. In: Andrea Giachetti and Silvia Biasotti and Marco Tarini (Ed.), Eurographics Proceedings STAG 2016: . Paper presented at Smart Tools and Apps in Computer Graphics (STAG), Genova, Italy. Eurographics - European Association for Computer Graphics
Åpne denne publikasjonen i ny fane eller vindu >>Selective rasterized ray-traced reflections on the GPU
2016 (engelsk)Inngår i: Eurographics Proceedings STAG 2016 / [ed] Andrea Giachetti and Silvia Biasotti and Marco Tarini, Eurographics - European Association for Computer Graphics, 2016Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Ray-tracing achieves impressive effects such as realistic reflections on complex surfaces but is also more computationally expensive than classic rasterization. Rasterized ray-tracing methods can accelerate ray-tracing by taking advantage of the massive parallelization available in the rasterization pipeline on the GPU. In this paper, we propose a selective rasterized raytracing method that optimizes the rasterized ray-tracing by selectively allocating computational resources to reflective regions in the image. Our experiments suggest that the method can speed-up the computation by up to 4 times and also reduce the memory footprint by almost 66% without affecting the image quality. We demonstrate the effectiveness of our method using complex scenes and animations.

sted, utgiver, år, opplag, sider
Eurographics - European Association for Computer Graphics, 2016
HSV kategori
Identifikatorer
urn:nbn:se:bth-13242 (URN)
Konferanse
Smart Tools and Apps in Computer Graphics (STAG), Genova, Italy
Tilgjengelig fra: 2016-10-10 Laget: 2016-10-10 Sist oppdatert: 2018-05-22bibliografisk kontrollert
Che, X., Niu, Y., Shui, B., Fu, J., Fei, G., Goswami, P. & Zhang, Y. (2015). A novel simulation framework based on information asymmetry to evaluate evacuation plan. The Visual Computer, 31(6-8), 853-861
Åpne denne publikasjonen i ny fane eller vindu >>A novel simulation framework based on information asymmetry to evaluate evacuation plan
Vise andre…
2015 (engelsk)Inngår i: The Visual Computer, ISSN 0178-2789, E-ISSN 1432-2315, Vol. 31, nr 6-8, s. 853-861Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

In this paper, we present a novel framework to simulate the crowd behavior under emergency situations in a confined space with multiple exits. In our work, we take the information asymmetry into consideration, which is used to model the different behaviors presented by pedestrians because of their different knowledge about the environment. We categorize the factors influencing the preferred velocity into two groups, the intrinsic and extrinsic factors, which are unified into a single space called influence space. At the same time, a finite state machine is employed to control the individual behavior. Different strategies are used to compute the preferred velocity in different states, so that our framework can produce the phenomena of decision change. Our experimental results prove that our framework can be employed to analyze the factors influencing the escape time, such as the number and location of exits, the density distribution of the crowd and so on. Thus it can be used to design and evaluate the evacuation plans. © 2015 Springer-Verlag Berlin Heidelberg

Emneord
Logic circuits, Crowd Simulation; Density distributions; Emergency evacuation; Emergency situation; Individual behavior; Influence space; Information asymmetry; Simulation framework, Behavioral research
HSV kategori
Identifikatorer
urn:nbn:se:bth-713 (URN)10.1007/s00371-015-1119-6 (DOI)000357487500011 ()2-s2.0-84928669865 (Scopus ID)
Tilgjengelig fra: 2015-06-01 Laget: 2015-05-28 Sist oppdatert: 2018-01-11bibliografisk kontrollert
Goswami, P., Eliasson, A. & Franzén, P. (2015). Implicit Incompressible SPH on the GPU. In: Proceedings of Workshop on Virtual Reality Interaction and Physical Simulation (VRIPHYS): . Paper presented at 12th Workshop on Virtual Reality Interaction and Physical Simulation (VRIPHYS 2015), Lyon. Eurographics - European Association for Computer Graphics
Åpne denne publikasjonen i ny fane eller vindu >>Implicit Incompressible SPH on the GPU
2015 (engelsk)Inngår i: Proceedings of Workshop on Virtual Reality Interaction and Physical Simulation (VRIPHYS), Eurographics - European Association for Computer Graphics, 2015Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

This paper presents CUDA-based parallelization of implicit incompressible SPH (IISPH) on the GPU. Along with the detailed exposition of our implementation, we analyze various components involved for their costs. We show that our CUDA version achieves near linear scaling with the number of particles and is faster than the multi-core parallelized IISPH on the CPU. We also present a basic comparison of IISPH with the standard SPH on GPU.

sted, utgiver, år, opplag, sider
Eurographics - European Association for Computer Graphics, 2015
Emneord
IISPH, GPU
HSV kategori
Identifikatorer
urn:nbn:se:bth-10997 (URN)
Konferanse
12th Workshop on Virtual Reality Interaction and Physical Simulation (VRIPHYS 2015), Lyon
Tilgjengelig fra: 2015-11-21 Laget: 2015-11-21 Sist oppdatert: 2018-05-23bibliografisk kontrollert
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