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Henesey, Lawrence
Publikationer (10 of 33) Visa alla publikationer
Henesey, L., Lizneva, Y. & Anwar, M. (2019). A multi-agent system with blockchain for container stacking and dispatching.. In: 21st International Conference on Harbor, Maritime and Multimodal Logistics Modeling and Simulation, HMS 2019: . Paper presented at 21st International Conference on Harbor, Maritime and Multimodal Logistics Modeling and Simulation, HMS, Lisbon, 18 September 2019 through 20 September 2019 (pp. 79-87). Dime University of Genoa
Öppna denna publikation i ny flik eller fönster >>A multi-agent system with blockchain for container stacking and dispatching.
2019 (Engelska)Ingår i: 21st International Conference on Harbor, Maritime and Multimodal Logistics Modeling and Simulation, HMS 2019, Dime University of Genoa , 2019, s. 79-87Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

Port Logistical Supply chains play a very important role in society. Their complex and adaptive behaviours promote the suggested applications of combining a multiagent system with blockchain for solving complex problems. Several technologies have been proven positively to work in logistics, however the concept of combining converging technologies such as blockchain with deep reinforcement multi agent is viewed as a novel approach to solving the complexity that is associated with many facets of logistics. A simulator was developed and tested for the problem of container stacking. The simulation results indicate a more robust approach to currently used tools and methods. © Harbor, Maritime and Multimodal Logistics Modeling and Simulation, HMS 2019.All Rights Reserved.

Ort, förlag, år, upplaga, sidor
Dime University of Genoa, 2019
Nyckelord
Blockchain, Container Stacking Management, Multi Agent, Multi-agent Simulation, Containers, Ports and harbors, Supply chains, Adaptive behaviour, Complex problems, Converging technologies, Multi agent simulation, Robust approaches, Tools and methods, Multi agent systems
Nationell ämneskategori
Datavetenskap (datalogi)
Identifikatorer
urn:nbn:se:bth-18904 (URN)2-s2.0-85074204470 (Scopus ID)9788885741287 (ISBN)
Konferens
21st International Conference on Harbor, Maritime and Multimodal Logistics Modeling and Simulation, HMS, Lisbon, 18 September 2019 through 20 September 2019
Tillgänglig från: 2019-11-14 Skapad: 2019-11-14 Senast uppdaterad: 2019-11-18Bibliografiskt granskad
Anwar, M., Henesey, L. & Casalicchio, E. (2019). The feasibility of Blockchain solutions in the maritime industry. In: : . Paper presented at 31st NOFOMA CONFERENCE "Supply Chains and Sustainable Development of Societies", Oslo. Oslo, Norway: The Nordic Logistics Research Network (NOFOMA)
Öppna denna publikation i ny flik eller fönster >>The feasibility of Blockchain solutions in the maritime industry
2019 (Engelska)Konferensbidrag, Publicerat paper (Övrigt vetenskapligt)
Abstract [en]

Purpose / Value

The concept of Blockchain technology in supply chain management is well discussed, yet

inadequately theorized in terms of its applicability, especially within the maritime industry,

which forms a fundamental node of the entire supply chain network. More so, the assumptive

grounds associated with the technology have not been openly articulated, leading to unclear

ideas about its applicability.

Design/methodology/approach

The research is designed divided into two Stages. This paper (Stage one) enhanced

literature review for data collection in order to gauge the properties of the Blockchain

technology, and to understand and map those characteristics with the Bill of Lading

process within maritime industry. In Stage two an online questionnaire is conducted to

assess the feasibility of Blockchain technology for different maritime use-cases.

Findings

The research that was collected and analysed partly from deliverable in the

Connect2SmallPort Project and from other literature suggests that Blockchain can be an

enabler for improving maritime supply chain. The use-case presented in this paper highlights

the practicality of the technology. It was identified that Blockchain possess characteristics

suitable to mitigate the risks and issues pertaining to the paper-based Bill of Lading process.

Research limitations

The study would mature further after the execution of the Stage Two. By the end of both

Stages, a framework for Blockchain adoption with a focus on the maritime industry would

be proposed.

Practical implications

The proposed outcome indicated the practicality of technology, which could be beneficial

for the port stakeholders that wish to use Blockchain in processing Bill of Lading or

contracts.

Social implications

The study may influence the decision makers to consider the benefits of using the Blockchain

technology, thereby, creating opportunities for the maritime industry to leverage the

technology with government’s support.

Ort, förlag, år, upplaga, sidor
Oslo, Norway: The Nordic Logistics Research Network (NOFOMA), 2019. s. 5
Serie
Supply Chain Designs and Sustainable Development of Societies ; 1
Nyckelord
Digitalization, Blockchain, Maritime, Bill of Lading, Feasibility study
Nationell ämneskategori
Annan elektroteknik och elektronik
Identifikatorer
urn:nbn:se:bth-18483 (URN)
Konferens
31st NOFOMA CONFERENCE "Supply Chains and Sustainable Development of Societies", Oslo
Projekt
CONNECT2SMALLPORTS
Tillgänglig från: 2019-07-16 Skapad: 2019-07-16 Senast uppdaterad: 2019-09-06Bibliografiskt granskad
Martin Sagayam, K., Ho, C. C., Henesey, L. & Bestak, R. (2018). 3D scenery learning on solar system by using marker based augmented reality. In: 4th International Conference of the Virtual and Augmented Reality in Education, VARE 2018: . Paper presented at 4th International Conference of the Virtual and Augmented Reality in Education, VARE 2018; Budapest (pp. 139-143). Dime University of Genoa
Öppna denna publikation i ny flik eller fönster >>3D scenery learning on solar system by using marker based augmented reality
2018 (Engelska)Ingår i: 4th International Conference of the Virtual and Augmented Reality in Education, VARE 2018, Dime University of Genoa , 2018, s. 139-143Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

Augmented reality (AR) is the technology that works on computer vision based recognition algorithms to augment sound, video, graphics and other sensor based inputs and real world objects using the camera of your device. AR applications can become the backbone of education industry. Apps are being developed which are embed text, images and videos, as well as the real-world curriculums. With help of AR, travellers can access real-time information of historical places just by pointing their camera viewfinder to subjects. There are two major forms of augmented reality, marker-based AR and markerless AR. A marker based AR works on concept of target recognition. The target can be 3D object, text, image, QR Code or human-face called markers. Whereas marker-less AR, also known as location-based AR, uses GPS of mobile devices to record the device position and displays information relative to that location. Few drawbacks in marker-less AR like house resolution, size variation and time delay can be solved using marker based algorithms such as marker detection, triangle similarity for marker to camera distance and corner detection. Copyright © (2015) by CAL-TEK S.r.l.All rights reserved. . All Rights Reserved.

Ort, förlag, år, upplaga, sidor
Dime University of Genoa, 2018
Nyckelord
Augmented reality, Camera, Education technology, Marker, Tracking, Cameras, Display devices, Edge detection, Surface discharges, Education industry, Location-based AR, Real-time information, Real-world objects, Recognition algorithm, Target recognition
Nationell ämneskategori
Medieteknik
Identifikatorer
urn:nbn:se:bth-17356 (URN)2-s2.0-85056694573 (Scopus ID)9788885741218 (ISBN)
Konferens
4th International Conference of the Virtual and Augmented Reality in Education, VARE 2018; Budapest
Tillgänglig från: 2018-11-29 Skapad: 2018-11-29 Senast uppdaterad: 2018-11-29Bibliografiskt granskad
Paulauskas, V., Henesey, L., Paulauskas, D., Ronkaitytė, L., Gerlitz, L., Jankowski, S. & Canepa, M. (2018). LNG bunkering stations location optimization on basis graph theory. In: Transport Means - Proceedings of the International Conference: . Paper presented at 22nd International Scientific on Conference Transport Means 2018, 3 October 2018 through 5 October 2018, Trasalis, Lithuania (pp. 660-664). Kaunas University of Technology
Öppna denna publikation i ny flik eller fönster >>LNG bunkering stations location optimization on basis graph theory
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2018 (Engelska)Ingår i: Transport Means - Proceedings of the International Conference, Kaunas University of Technology , 2018, s. 660-664Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

As an alternative to traditional fuel and energy source LNG (Liquefied Natural Gas) has many advantages, such as lower emissions while providing a means of energy for trucks, trains and ships. In focusing on the maritime transport sector the reasons for using LNG make a convincing business case, but lead to many discussions on LNG investments. The key issue has been is: “should investment be implemented first on LNG bunkering stations and then wait for the market to build ships to use the facilities or should investment wait until there is a demand?” Obviously, this creates a “chicken-and-egg” situation on when and where to invest for LNG use to take place. The initial experiences in using LNG in maritime and road transport suggest that the transport firms often take the risk themselves by not only investing into the transport units (ships, trucks) themselves but also invest into the infrastructure as well, e.g., developing LNG bunkering facilities. At the same time with these large initial investments for developing LNG bunkering networks there are more and more requests for identifying optimal solutions, often are based on real LNG fuel demand in ports and on the roads. This paper is oriented on the study for optimal bunkering network creation, which is argued to help with improved efficiency in the supply of LNG fuel to transport users. In addition, optimal investments for LNG bunkering networks can be realized. © 2018 Kaunas University of Technology. All rights reserved.

Ort, förlag, år, upplaga, sidor
Kaunas University of Technology, 2018
Nyckelord
LNG bunkering, LNG fuel, Optimization LNG bunkering network, Transport corridors, Automobiles, Gas emissions, Graph theory, Investments, Liquefied natural gas, Tankers (ships), Trucks, Location optimization, Maritime transport, Network creation, Optimal investments, Optimal solutions, Traditional fuels, Natural gas transportation
Nationell ämneskategori
Transportteknik och logistik Datavetenskap (datalogi)
Identifikatorer
urn:nbn:se:bth-17270 (URN)2-s2.0-85055508566 (Scopus ID)
Konferens
22nd International Scientific on Conference Transport Means 2018, 3 October 2018 through 5 October 2018, Trasalis, Lithuania
Tillgänglig från: 2018-11-15 Skapad: 2018-11-15 Senast uppdaterad: 2018-11-16Bibliografiskt granskad
Sagayam, K. M., Hemanth, D. J., Vasanth, X. A., Henesey, L. & Ho, C. C. (2018). Optimization of a HMM-based hand gesture recognition system using a hybrid cuckoo search algorithm. In: Hybrid Metaheuristics for Image Analysis: (pp. 87-114). Springer International Publishing
Öppna denna publikation i ny flik eller fönster >>Optimization of a HMM-based hand gesture recognition system using a hybrid cuckoo search algorithm
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2018 (Engelska)Ingår i: Hybrid Metaheuristics for Image Analysis, Springer International Publishing , 2018, s. 87-114Kapitel i bok, del av antologi (Övrigt vetenskapligt)
Abstract [en]

The authors develop an advanced hand motion recognition system for virtual reality applications using a well defined stochastic mathematical approach. Hand gesture is a natural way of interaction with a computer by interpreting the primitive characteristics of gesture movement to the system. This concerns three basic issues: (1) there is no physical contact between the user and the system, (2) the rotation of the hand gesture can be determined by the geometric features, and (3) the model parameter must be optimized to improve measurement of performance. A comparative analysis of other classification techniques used in hand gesture recognition is carried out on the proposed work hybrid with the bio-inspired metaheuristic approach, namely the cuckoo search algorithm, for reducing the complex trajectory in the hidden Markov model (HMM) model. An experimental result is as to how to validate the HMM model, based on the cost value of the optimizer, in order to improve the performance measures of the system. © Springer International Publishing AG, part of Springer Nature 2018.

Ort, förlag, år, upplaga, sidor
Springer International Publishing, 2018
Nyckelord
Cuckoo search algorithm, Gesture recognition, Shape-based features, Stochastic mathematical approach, Virtual reality
Nationell ämneskategori
Datavetenskap (datalogi)
Identifikatorer
urn:nbn:se:bth-17873 (URN)10.1007/978-3-319-77625-5_4 (DOI)2-s2.0-85063801071 (Scopus ID)9783319776255 (ISBN)9783319776248 (ISBN)
Tillgänglig från: 2019-05-02 Skapad: 2019-05-02 Senast uppdaterad: 2019-05-02Bibliografiskt granskad
Paulauskas, V., Paulauskas, D., Placiene, B., Barzdziukas, R., Maksimavicius, R., Ronkaityte, I., . . . Henesey, L. (2017). Optimization modelling of LNG supply chains for development: Case study of Lithuania and Latvia. In: Transport Means - Proceedings of the International Conference: . Paper presented at International Scientific Conference Transport Means, Juodkrante, Lithuania (pp. 762-765). Kaunas University of Technology
Öppna denna publikation i ny flik eller fönster >>Optimization modelling of LNG supply chains for development: Case study of Lithuania and Latvia
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2017 (Engelska)Ingår i: Transport Means - Proceedings of the International Conference, Kaunas University of Technology , 2017, s. 762-765Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

The increasing demand for Liquid Natural Gas (LNG) is causing many challenges for users and suppliers worldwide. Though there is strong interest in using LNG, the research published in this paper indicates there are challenges in developing adequate delivery and distribution chains within the supply chain. Ideally, LNG distribution chains should be created on the basis of user demands and need. In this paper we have articulated an optimisation model that considers the various potential users and their characteristics in order to identify if possibilities and prospects exist in developing an adequate LNG supply chain. The case study of Lithuania and Latvia serves as a model from which we are able to use our tool to help identify the factors for success in creating such LNG supply chains. © 2017 Kaunas University of Technology. All rights reserved.

Ort, förlag, år, upplaga, sidor
Kaunas University of Technology, 2017
Nyckelord
LNG, LNG storage, LNG supply, Liquefied natural gas, Optimization, Distribution chains, Liquid natural gas, Lithuania, Optimisation models, Optimization modelling, Potential users, User demands, Supply chains
Nationell ämneskategori
Transportteknik och logistik
Identifikatorer
urn:nbn:se:bth-16138 (URN)2-s2.0-85045281470 (Scopus ID)
Konferens
International Scientific Conference Transport Means, Juodkrante, Lithuania
Tillgänglig från: 2018-04-26 Skapad: 2018-04-26 Senast uppdaterad: 2018-04-26Bibliografiskt granskad
Martin Sagayam, K., Vedha Viyas, T., Ho, C. C. & Henesey, L. (2017). Virtual Robotic Arm Control with Hand Gesture Recognition and Deep Learning Strategies. In: Deep Learning for Image Processing Applications: (pp. 50-67). IOS Press BV, 31
Öppna denna publikation i ny flik eller fönster >>Virtual Robotic Arm Control with Hand Gesture Recognition and Deep Learning Strategies
2017 (Engelska)Ingår i: Deep Learning for Image Processing Applications, IOS Press BV , 2017, Vol. 31, s. 50-67Kapitel i bok, del av antologi (Refereegranskat)
Abstract [en]

Hand gestures and Deep Learning Strategies can be used to control a virtual robotic arm for real-time applications. A robotic arm which is portable to carry various places and which can be easily programmed to do any work of a hand and is controlled by using deep learning techniques. Deep hand is a combination of both virtual reality and deep learning techniques. It estimated the active spatio-temporal feature and the corresponding pose parameter for various hand movements, to determine the unknown pose parameter of hand gestures by using various deep learning algorithms. A novel framework for hand gestures has been made to estimate by using a deep convolution neural network (CNN) and a deep belief network (DBN). A comparison in terms of accuracy and recognition rate has been drawn. This helps in analyzing the movement of a hand and its fingers which can be made to control a robotic arm with high recognition rate and less error rate. © 2017 The authors and IOS Press. All rights reserved.

Ort, förlag, år, upplaga, sidor
IOS Press BV, 2017
Serie
Advances in parallel Computing, ISSN 0927-5452 ; 31
Nyckelord
convolution neural network, Deep belief network, Deep learning, hand gesture recognition, kinetic, Restricted Boltzmann Machine, spatio-temporal feature, virtual reality
Nationell ämneskategori
Datavetenskap (datalogi)
Identifikatorer
urn:nbn:se:bth-16191 (URN)10.3233/978-1-61499-822-8-50 (DOI)2-s2.0-85046353694 (Scopus ID)9781614998211 (ISBN)
Tillgänglig från: 2018-05-18 Skapad: 2018-05-18 Senast uppdaterad: 2018-08-21Bibliografiskt granskad
Bakhtyar, S., Mbiydzenyuy, G. & Henesey, L. (2015). A Simulation Study of the Electronic Waybill Service. In: David Al-Dabas, Gregorio Romero, Alessandra Orsoni, Athanasios Pantelous (Ed.), Proceedings - EMS 2015: UKSim-AMSS 9th IEEE European Modelling Symposium on Computer Modelling and Simulation. Paper presented at 9th UKSim-AMSS IEEE European Modelling Symposium on Computer Modelling and Simulation, EMS (pp. 307-312). IEEE Computer Society
Öppna denna publikation i ny flik eller fönster >>A Simulation Study of the Electronic Waybill Service
2015 (Engelska)Ingår i: Proceedings - EMS 2015: UKSim-AMSS 9th IEEE European Modelling Symposium on Computer Modelling and Simulation / [ed] David Al-Dabas, Gregorio Romero, Alessandra Orsoni, Athanasios Pantelous, IEEE Computer Society, 2015, s. 307-312Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

We present results from a simulation study, whichwas designed for investigating the potential positive impacts, i.e., the invoicing and processing time, and financial savings,when using an electronic waybill instead of paper waybillsfor road-based freight transportation. The simulation modelis implemented in an experiment for three different scenarios,where the processing time for waybills at the freight loadingand unloading locations in a particular scenario differs fromother scenarios. The results indicate that a saving of 65%–99%in the invoicing time can be achieved when using an electronicwaybill instead of paper waybills. Our study can be helpful todecision makers, e.g., managers and staff dealing with paperwaybills, to estimate the potential benefits when making deci-sions concerning the implementation of an electronic waybillsolution for replacing paper waybills.

Ort, förlag, år, upplaga, sidor
IEEE Computer Society, 2015
Nyckelord
Freight transportation; Invoicing time; Simulation; Waybill
Nationell ämneskategori
Data- och informationsvetenskap
Identifikatorer
urn:nbn:se:bth-10878 (URN)10.1109/EMS.2015.53 (DOI)000411862000035 ()9781509002061 (ISBN)
Konferens
9th UKSim-AMSS IEEE European Modelling Symposium on Computer Modelling and Simulation, EMS
Tillgänglig från: 2015-10-25 Skapad: 2015-10-25 Senast uppdaterad: 2018-01-16Bibliografiskt granskad
Bakhtyar, S. & Henesey, L. (2014). Freight transport prediction using electronic waybills and machine learning. In: 2014 International Conference on Informative and Cybernetics for Computational Social Systems: . Paper presented at International Conference on Informative and Cybernetics for Computational Social Systems, Qingdao, Shandong, China (pp. 128-133). IEEE Computer Society
Öppna denna publikation i ny flik eller fönster >>Freight transport prediction using electronic waybills and machine learning
2014 (Engelska)Ingår i: 2014 International Conference on Informative and Cybernetics for Computational Social Systems, IEEE Computer Society, 2014, s. 128-133Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

A waybill is a document that accompanies the freight during transportation. The document contains essential information such as, origin and destination of the freight, involved actors, and the type of freight being transported. We believe, the information from a waybill, when presented in an electronic format, can be utilized for building knowledge about the freight movement. The knowledge may be helpful for decision makers, e.g., freight transport companies and public authorities. In this paper, the results from a study of a Swedish transport company are presented using order data from a customer ordering database, which is, to a larger extent, similar to the information present in paper waybills. We have used the order data for predicting the type of freight moving between a particular origin and destination. Additionally, we have evaluated a number of different machine learning algorithms based on their prediction performances. The evaluation was based on their weighted average true-positive and false-positive rate, weighted average area under the curve, and weighted average recall values. We conclude, from the results, that the data from a waybill, when available in an electronic format, can be used to improve knowledge about freight transport. Additionally, we conclude that among the algorithms IBk, SMO, and LMT, IBk performed better by predicting the highest number of classes with higher weighted average values for true-positive and false-positive, and recall.

Ort, förlag, år, upplaga, sidor
IEEE Computer Society, 2014
Nyckelord
machine learning; Waybill; freight mobility; IBk; SMO; LMT
Nationell ämneskategori
Data- och informationsvetenskap
Identifikatorer
urn:nbn:se:bth-10875 (URN)10.1109/ICCSS.2014.6961829 (DOI)000358127600024 ()978-1-4799-4753-9 (ISBN)
Konferens
International Conference on Informative and Cybernetics for Computational Social Systems, Qingdao, Shandong, China
Tillgänglig från: 2015-10-25 Skapad: 2015-10-25 Senast uppdaterad: 2018-01-10Bibliografiskt granskad
Bai, G. & Henesey, L. (2012). Coping with System Sustainability: A Sociocybernetics Framework for Social-Economic System Architecture. Systems research and behavioral science, 29(3), 263-273
Öppna denna publikation i ny flik eller fönster >>Coping with System Sustainability: A Sociocybernetics Framework for Social-Economic System Architecture
2012 (Engelska)Ingår i: Systems research and behavioral science, ISSN 1092-7026, E-ISSN 1099-1743, Vol. 29, nr 3, s. 263-273Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

This paper proposes an epistemological model based on cybernetic principles and activity theory to interpret two levels of problems that are intertwined in our social-economic system, namely the liveability and sustainability problems. In the first part of the paper, important principles and concepts from related fields of cybernetics and activity theory are introduced for later construction of a model. In the second part, a model is constructed based on the introduced concepts. To validate the proposed model, the current economic crisis is studied in the third part. An important contribution of the proposed model is a theoretical understanding of the two levels problems, and how to construct macro social-economical policies to avoid similar crisis in the future.

Ort, förlag, år, upplaga, sidor
Wiley Blackwell, 2012
Nyckelord
Feedback, Social Activities, Liveability, Sustainability, Autopoiesis.
Nationell ämneskategori
Tvärvetenskapliga studier inom samhällsvetenskap Sociologi Företagsekonomi
Identifikatorer
urn:nbn:se:bth-7194 (URN)10.1002/sres.1134 (DOI)000304315400004 ()oai:bth.se:forskinfoD08E9BA38CD0FCBBC125791F007306AB (Lokalt ID)oai:bth.se:forskinfoD08E9BA38CD0FCBBC125791F007306AB (Arkivnummer)oai:bth.se:forskinfoD08E9BA38CD0FCBBC125791F007306AB (OAI)
Externt samarbete:
Tillgänglig från: 2012-11-27 Skapad: 2011-10-04 Senast uppdaterad: 2018-01-11Bibliografiskt granskad
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