Method of Location of a Mobile Station in the WCDMA System without Knowledge of Relative Time Differences

2007 ◽  
Author(s):  
J. Stefanski
Keyword(s):  
Mobile Station ◽  
Relative Time

GRAVITY CAN BE OBSERVED IN THE ABSENCE OF CURVED SPACETIME, THUS CURVED SPACETIME IS NOT RESPONCIBLE FOR GRAVITY

2015 ◽  
Vol 8 (1) ◽  
pp. 1976-1981
Author(s):  
Casey McMahon
Keyword(s):  
General Relativity ◽  
Special Relativity ◽  
Relative Position ◽  
Gravitational Force ◽  
Curved Spacetime ◽  
Relative Time ◽  
Curved Space ◽  
Spacetime Curvature ◽  
Equivalence Model ◽  
The Universe

The principle postulate of general relativity appears to be that curved space or curved spacetime is gravitational, in that mass curves the spacetime around it, and that this curved spacetime acts on mass in a manner we call gravity. Here, I use the theory of special relativity to show that curved spacetime can be non-gravitational, by showing that curve-linear space or curved spacetime can be observed without exerting a gravitational force on mass to induce motion- as well as showing gravity can be observed without spacetime curvature. This is done using the principles of special relativity in accordance with Einstein to satisfy the reader, using a gravitational equivalence model. Curved spacetime may appear to affect the apparent relative position and dimensions of a mass, as well as the relative time experienced by a mass, but it does not exert gravitational force (gravity) on mass. Thus, this paper explains why there appears to be more gravity in the universe than mass to account for it, because gravity is not the resultant of the curvature of spacetime on mass, thus the “dark matter” and “dark energy” we are looking for to explain this excess gravity doesn’t exist.

SIMULASI NEURAL NETWORK UNTUK PREDIKSI LOKASI USER PADA MOBILE NETWORK

2016 ◽  
Vol 9 (1) ◽  
Author(s):  
Alexander Driyarkoro ◽  
Nurain Silalahi ◽  
Joko Haryatno
Keyword(s):  
Neural Network ◽  
Mobile Station ◽  
Mobile Network ◽  
Learning Rate ◽  
Noise Factor ◽  
Optimal Learning ◽  
Air Interface ◽  
Location Area ◽  
Optimal Learning Rate

Prediksi lokasi user pada mobile network merupakan hal sangat penting, karena routing panggilan pada mobile station (MS) bergantung pada posisi MS saat itu. Mobilitas MS yang cukup tinggi, terutama di daerah perkotaan, menyebabkan pencarian (tracking) MS akan berpengaruh pada kinerja sistem mobile network, khususnya dalam hal efisiensi kanal kontrol pada air interface. Salah satu bentuk pencarian adalah dengan mengetahui perilaku gerakan yang menentukan posisi MS. Dari MSC/VLR dapat diketahui posisi MS pada waktu tertentu. Karena location area suatu MS selalu unik dari waktu ke waktu, dan hal itu merupakan perilaku (behaviour) MS, maka dapat dibuat profil pergerakannya. Dengan menggunakan Neural Network (NN) akan diperoleh location area MS pada masa yang akan datang. Model NN yang digunakan pada penelitian ini adalah Propagasi Balik. Beberapa parameter NN yang diteliti dalam mempengaruhi kinerja prediksi lokasi user meliputi noise factor, momentum dan learning rate. Pada penelitian ini diperoleh nilai optimal learning rate = 0,5 dan noise factor = 1.

Design strategy of ultrasmall Gd2O3 nanoparticles for T1 MRI with high performance

2021 ◽  
Author(s):  
Jianfeng Yang ◽  
Pengyuan Shan ◽  
Qingling Zhao ◽  
Shuquan Zhang ◽  
Lanlan Li ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
High Performance ◽  
Design Strategy ◽  
Resonance Imaging ◽  
Relative Time ◽  
Time Parameters ◽  
Gd2o3 Nanoparticles

It is still a big challenge for designing Gd3+ based nanoparticles (NPs) for T1 MRI (Magnetic Resonance Imaging) with high performance and clarifying the effects of relative time parameters for...

Polysomnographic features differentiating disorder of arousals from sleep-related hypermotor epilepsy

SLEEP ◽  
2019 ◽  
Author(s):  
Paola Proserpio ◽  
Giuseppe Loddo ◽  
Frederic Zubler ◽  
Luigi Ferini-Strambi ◽  
Laura Licchetta ◽  
...  
Keyword(s):  
Group Analysis ◽  
Definite Diagnosis ◽  
Major Event ◽  
Relative Time ◽  
Discriminative Performance ◽  
Sleep Period ◽  
Distribution Index ◽  
Event Distribution ◽  
Disorders Of Arousal ◽  
Total P

Abstract Objective The differential diagnosis between sleep-related hypermotor epilepsy (SHE) and disorders of arousal (DOA) may be challenging. We analyzed the stage and the relative time of occurrence of parasomnic and epileptic events to test their potential diagnostic accuracy as criteria to discriminate SHE from DOA. Methods Video-polysomnography recordings of 89 patients with a definite diagnosis of DOA (59) or SHE (30) were reviewed to define major or minor events and to analyze their stage and relative time of occurrence. The “event distribution index” was defined on the basis of the occurrence of events during the first versus the second part of sleep period time. A group analysis was performed between DOA and SHE patients to identify candidate predictors and to quantify their discriminative performance. Results The total number of motor events (i.e. major and minor) was significantly lower in DOA (3.2 ± 2.4) than in SHE patients (6.9 ± 8.3; p = 0.03). Episodes occurred mostly during N3 and N2 in DOA and SHE patients, respectively. The occurrence of at least one major event outside N3 was highly suggestive for SHE (p = 2*e-13; accuracy = 0.898, sensitivity = 0.793, specificity = 0.949). The occurrence of at least one minor event during N3 was highly suggestive for DOA (p = 4*e-5; accuracy = 0.73, sensitivity = 0.733, specificity = 0.723). The “event distribution index” was statistically higher in DOA for total (p = 0.012) and major events (p = 0.0026). Conclusion The stage and the relative time of occurrence of minor and major motor manifestations represent useful criteria to discriminate DOA from SHE episodes.

Design of Solar System for LTE Networks

2020 ◽  
Vol 11 (2) ◽  
pp. 1-15
Author(s):  
Naglaa Kamel Bahgaat ◽  
Nariman Abdel Salam ◽  
Monika Mady Roshdy ◽  
Sandy Abd Elrasheed Sakr
Keyword(s):  
Mobile Networks ◽  
Renewable Energy Sources ◽  
Mobile Station ◽  
Electrical Energy ◽  
Environmental Problems ◽  
Base Stations ◽  
Energy Sources ◽  
Solar Panels ◽  
Lte Networks ◽  
Photovoltaic Panel

Rapid growth in mobile networks and the increase of the number of cellular base stations requires more energy sources, but the traditional sources of energy cause pollution and environmental problems. Therefore, modern facilities tend to use renewable energy sources instead of traditional sources. One renewable source is the photovoltaic panel, which made from semiconductor materials which absorb sunlight to generate electricity. This article discusses the importance of using solar panels to produce energy for mobile stations and also a solution to some environmental problems such as pollution. This article provides a design for a solar-power plant to feed the mobile station. Also, in this article is a prediction of all loads, the power consumed, the number of solar panels used, and solar batteries can be used to store electrical energy. Finally, an estimation of the costs of all components will be presented. Good discussion and conclusion will be presented about the results obtained. The results obtained are promising. In addition, a future plan is described to complete this important study.

A mobile station modem VLSI for CDMA2000-1x

2002 ◽  
Author(s):  
Sung-Chul Han ◽  
Tae Hee Han ◽  
Yong-Chan Kim ◽  
Chul-Jin Kim ◽  
Kyung-Hal Lee ◽  
...  
Keyword(s):  
Mobile Station
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