| viXra.org > Data Structures and Algorithms > 2008 |
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| viXra.org > Data Structures and Algorithms > 2008 |
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[4] viXra:2008.0138 [pdf] submitted on 2020-08-19 11:01:55
Authors: Alexander Garyfallos
Comments: 26 Pages.
Forecasting forthcoming "health events" is an extremely challenging task for the Remote Patient Monitoring systems (RPM systems) sector, which relies in real time information and communication technologies. Remote patient monitoring is a medical service which includes following and observing patients that are not in the same location with their health care provider. In general, the patient is equipped with a “smart” monitoring device, and the recorded data (vital signs) are securely transmitted via telecommunication networks to the health care provider. Modern remote patient monitoring devices are small, discrete and easy to wear, allowing "bearers" to move freely and with comfort. In this framework, MOKAAL pc has developed the IFS_RPM service (Integrated Facilitation Services for Remote Patient Monitoring) supplying the necessary ICT infrastructure, which is necessary for the provision of the RPM services. Following the completion of IFS_RPM project, MOKAAL pc launched a research project under the code name "PROPHETTM" .
PROPHETTM main objective is to investigate the possibilities of introducing a real time predicting model based on remotely collected vital signs, that would utilize time series of metric data in conjunction with the information stored in the Electronic Health Records (EHR) of the "bearer", attempting to predict in real time, the probability of a "health event" occurring in the near future. To meet this objective, the PROPHETTM project team designed an evolutionary prototype of the "health event" forecasting model, which was developed and tested in a laboratory environment and it will be upgraded to a working prototype to be tested in real conditions, in order to be incorporated into the IFS_RPM system, after reaching its maturity state.
Category: Data Structures and Algorithms
[3] viXra:2008.0122 [pdf] replaced on 2022-03-22 04:01:19
Authors: James Dow Allen
Comments: 12 Pages.
The theoretical minimum storage needed to represent a set of size N drawn from a universe of size M is about N * (log_2(M/N) + 1.4472) bits (assuming neither N nor M/N is very small). I review the technique of `quotienting' which is used to approach this minimum, and look at the actual memory costs achieved by practical designs. Instead of somehow implementing and exploiting 1.4472 bits of steering information, most practical schemes use two bits (or more). In the conclusion I mention a scheme to reduce the overhead cost from two bits to a single trit.
Category: Data Structures and Algorithms
[2] viXra:2008.0092 [pdf] submitted on 2020-08-13 07:49:42
Authors: Rahul Kumar Singh, Sanjeev Saxena
Comments: 4 Pages.
In this note, we present a simpler algorithm for joint seat allocation problem in case there are two or more merit lists. In case of two lists (the current situation for Engineering seats in India), the running time of the algorithm is proportional to sum of running time for two separate (delinked) allocations. The algorithm is straight forward and natural and is not (at least directly) based on deferred acceptance algorithm of Gale and Shapley. Each person can only move higher in his or her preference list. Thus, all steps of the algorithm can be made public. This will improve transparency and trust in the system.
Category: Data Structures and Algorithms
[1] viXra:2008.0073 [pdf] submitted on 2020-08-11 19:36:48
Authors: Leslie Nneji Ndugbu
Comments: 13 Pages.
This work is concerned with road traffic offence information management in Nigeria. It focused on
trends in road traffic offences information and carried out a critical review of current information and communication and technology compliance state of FRSC with a view to identifying its defects in road traffic offence information management. A system to correct road traffic offence information management failure as identified in the existing system was then proposed. Road traffic offence records and details of current safety measures obtained from FRSC and online in addition to research works
provided the basic data for the study. The result showed the high rate of road traffic offence as a result of poor road traffic offence information management and failure to improve on the existing road traffic information management.
Category: Data Structures and Algorithms
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