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Existing approaches solving multi-vehicle pickup and delivery problems with soft time windows typically use common benchmark sets to verify their performance. However, there is a gap from these benchmark sets to real world problems with respect to instance size and problem complexity. In this paper we show that a combination of existing approaches together with improved heuristics is able to deal with the instance sizes and complexity of real world problems. The cost savings potential of the heuristics is compared to human dispatching plans generated from the data of a European carrier.
Today's network landscape consists of quite different network technologies, wide range of end-devices with large scale of capabilities and power, and immense quantity of information and data represented in different formats. Research on 3D imaging, virtual reality and holographic techniques will result in new user interfaces (UI) for mobile devices and will increase their diversity and variety. A lot of efforts are being done in order to establish open, scalable and seamless integration of various technologies and content presentation for different devices including mobile considering individual situation of the end user. This is very difficult because various kinds of devices used by different users or in different times/parallel by the same user which are not predictable and have to be recognized by the system in order to identify device capabilities. Not only the devices but also Content and User Interfaces are big issues because they could include different kinds of data format like text, image, audio, video, 3D Virtual Reality data and other upcoming formats. A very suitable and useful example of the use of such a system is mobile learning because of the large amount of varying devices with significantly different features and functionalities. This is true not only to support different learners, e.g. all learners within one learning community, but also to support the same learner using different equipment parallel and/or at different times. Those applications may be significantly enhanced by including virtual reality content presentation. Whatever the purposes are, it is impossible to develop and adapt content for all kind of devices including mobiles individually due to different capabilities of the devices, cost issues and author‘s requirement. A solution should be found to enable the automation of the content adaptation process.
The concept of m-learning which differs from other forms of e-learning covers a wide range of possibilities opened up by the convergence of new mobile technologies, wireless communication structure and distance learning development. This process of converging has launched some new goals to support m-learning where heterogeneity of devices, their operating systems (Linux, Windows, Symbian, Android etc) and supported markup languages (WML, XHTML etc), adaptive content, preferences or characteristics of user have become some of the major problems to be solved. To facilitate the learning process even more and to establish literally anytime anywhere learning, learning material/content should be available to the user always even if the user is in offline. Multiple devices used by the same user should also be synchronized among themselves and with server to provide updated learning content and to give a freedom to the user to choose any device as per his/her convenience. In this paper software architecture has been proposed to solve these problems and has been implemented by using a multidimensional flashcard learning system which synchronizes among all the devices that are being used by the user.
In large aircrafts the cabling is very complex and often causes reliability problems. This is specially true for modern In-flight Entertainment (IFE) systems, where every passenger can select a preferred movie, play computer games or be able to communicate with other travellers. Due to EMC problems, wireless communication systems (WiFi etc.) didn't succeed in solving these problems. In this paper an innovative communication system is proposed which perfectly supplements an aircraft IFE system. The key innovation of this system is to use structures that are essential parts of the airframe for data transfer, such as seat rails. Those rails consist of rectangular shapes and could easily be modified to fulfill the function of waveguides for microwaves. A waveguide as part of the seat rail would provide enormous benefits for aircrafts, such as a large bandwidth and consequently high data rates, no problems with EMC, unlimited flexibility of seat configuration, mechanical robustness with associated increase of reliability and a few additional advantages related to aircrafts such as reduction of weight and costs.
In previous work we [1] and other authors (e.g. [2]) have shown that agent-based systems are successful in optimizing delivery plans of single logistics companies and are meanwhile successfully productive in industry. In this paper we show that agent-based systems are particularly useful to also optimize transport across logistics companies. In intercompany optimization, privacy is of major importance between the otherwise competing companies. Some data has to be treated strictly private like the cost model or the constraint model. Other data like order information has to be shared. However, typically the amount of orders released to other companies has also to be limited. We show that our agent-based approach can be easily fine tuned to trade off privacy against the benefit of cooperation.
Home Care Applications and Ambient Assisted Living become increasingly attractive. This is caused as well by market pull, as the number of elderly people grows monotonously, as well as by technology push, as technological advances and attractive products pave the way to economically advantageous offerings. However, in real-life applications, a significant number of challenges remain. Those include seamless communication between products from different supplier, due to the lack of sufficiently standardized solutions, energy budgets, and scalability of solutions. This paper presents the experience from the InCASA project (Integrated Network for Completely Assisted Senior Citizen's Autonomy), where architectures for heterogeneous physical and logical communication flows are examined.
The efficient support of Hardwae-In-theLoop (HIL) in the design process of hardwaresoftware-co-designed systems is an ongoing challenge. This paper presents a network-based integration of hardware elements into the softwarebased image processing tool „ADTF“, based on a high-performance Gigabit Ethernet MAC and a highly-efficient TCP/IP-stack. The MAC has been designed in VHDL. It was verified in a SystemCsimulation environment and tested on several Altera FPGAs.
Semi-invasive electromechanical target interval to guide left ventricular electrode placement
(2011)
Electrical velocimetry to optimize VV delay in biventricular VVIR and DDD pacing for heart failure
(2011)
Introduction: VV delay (VVD) is the only parameter to hemodynamically optimize cardiac resynchronization therapy (CRT) for patients with atrial fibrillation (AF). Electrical velocimetry (EV) has been established to monitor thoracic electrical conductivity and to calculate hemodynamic surrogate parameters. We compared the response of this method to hemodynamic parameter changes between CRT patients with sinus rhythm (SR) and patients with AF.
Methods: VVD was individualized in 17 CRT patients in SR (12m, 5f, 67.0±7.2yrs.) after echo AV delay optimization and in 11 CRT patients in AF (10m, 1f, 69.8±9.6yrs.) using the Aesculon Cardiovascular Monitor (Osypka Medical, Berlin, Germany). Serial 30s EV recordings were accomplished, decreasing the VVD stepwise by 10ms from +60ms to -60ms between right and left ventricular stimulus. Optimal VVD was determined by the maximum of at least two of the three averaged parameters stroke volume (SV), cardiac output (CO) and cardiac index (CI). The response of SV, CO and CI was tested comparing their values in optimal VVD and suboptimal VVD. Suboptimal VVD was defined by optimal VVD±20ms.
Results: In all 28 patients in SR and AF, EV recordings resulted in optimal VVD. Between suboptimal and optimal mean VVD of 18.6±30.8ms between left and right ventricular stimulus, SV increased by 7.2±6.8%, CO by 7.8±7.2% and CI by 10.0±13.3% (all p<0.02). In the SR group with VVD of 18.8± 29.6ms, SV increased by 4.6±2.9%, CO by 5.0±2.9% and CI by 4.9±2.9% (all p<0.02). In the AF group with VVD of 18.2±4.0ms, SV increased by 10.4±8.9%, CO by 11.3±9.5% and CI by 16.4±18.2% (all p<0.02). Significant differences were not found between optimal VVD in SR and AF patients.
Conclusion: EV is a feasible serial method to individualize VVD in DDD and VVIR pacing for heart failure. Its response to hemodynamic changes demonstrates the value of EV for VVD fine-tuning.