Improved trilateration for indoor localization: Neural network and centroid-based approach

[EN] Location awareness is the key to success to many location-based services applications such as indoor navigation, elderly tracking, emergency management, and so on. Trilateration-based localization using received signal strength measurements is widely used in wireless sensor network-based localization and tracking systems due to its simplicity and low computational cost. However, localization accuracy obtained with the trilateration technique is generally very poor because of fluctuating nature of received signal strength measurements. The reason behind such notorious behavior of received signal strength is dynamicity in target motion and surrounding environment. In addition, the significant localization error is induced during each iteration step during trilateration, which gets propagated in the next iterations. To address this problem, this article presents an improved trilateration-based architecture named Trilateration Centroid Generalized Regression Neural Network. The proposed Trilateration Centroid Generalized Regression Neural Network-based localization algorithm inherits the simplicity and efficiency of three concepts namely trilateration, centroid, and Generalized Regression Neural Network. The extensive simulation results indicate that the proposed Trilateration Centroid Generalized Regression Neural Network algorithm demonstrates superior localization performance as compared to trilateration, and Generalized Regression Neural Network algorithm.Jondhale, SR.; Jondhale, AS.; Deshpande, PS.; Lloret, J. (2021). Improved trilateration for indoor localization: Neural network and centroid-based approach. International Journal of Distributed Sensor Networks (Online). 17(11):1-14. https://doi.org/10.1177/15501477211053997114171

Clinical Study of Chakramardadi Pralepa in the management of Dadru Kushta

Background: Skin is the largest organ of human body. Its size and external location makes it susceptible to a wide variety of disorders. In recent years there has been increase in incidence of skin problem due to various reasons like Poverty, Poor sanitation, Unhygienic condition, Pollution etc. Dadru is one among Kushta Roga affecting all the age of population. It is Kapha-Pitta Pradhan Vyadhi and presents clinically with the features of Kandu, Raga, Pidika, Daha, Rookshata, Udgata Mandala etc. and can be correlated with Tinea infection. Management of Dadru includes Shodhana, Shaman and Bahiparimarjan Chikitsa. Chakramarda is a wild crop grows in most part of India and it is known as Ringworm plant. So here in this study Chakramadadi Pralepa was used to evaluate the efficacy in Dadru

Lift Control System Based on PLC

In this paper we are scheming and construct three level elevator control system and increase its steady state & stability by using a (PLC) programmable logic controller (Allen Bradley Micrologix-1400 BXBA) the software used for communication is RSLogix-500/5000 PLC’S [1]. These are useful in industrial automation where numbers of equipments are replaced by contactor and switches. In this paper Elevator is nothing but the vertical carrying device which is used to transfer the goods and peoples. Limit switch is used for the floor suggestion. The limit switch is used for positioning of floor. DC motor is used for movement of elevator filing cabinet. Electromagnetic type relay is used in organize circuit to control elevator in upward and downward track. As the India is developing country and there are wide increase in high rise buildings and malls. Elevator is integral part of infrastructure by implementing such paper we can reduce the human efforts, accident due to breakage of rope, efficiency and speed of elevator is improved. Even the time can be consumed by using such system. This paper mainly concentrates on programmable logic controller to control the circuit and building the elevator model. In this paper Three level efficient elevator control system is designed which can be used for different elevator control system having different number of floors

Unwanted Message Filtering System from OSNs User’s Wall Using Customizable Filtering Rules and Black list Techniques.

Abstract- Users have ability to keep in touch with his/her friends by exchanging different types of information or messages like text, audio and video data. Today’s OSNs (Online Social Network System) do not provide much support to the users to avoid unwanted messages displayed on their own private space called in general wall. So, in this paper we present OSNs system which gives ability to users to control the messages posted on their own private space to avoid unwanted messages displayed. Customizable Filtering Rules are used to filter the unwanted messages from OSNs users wall as well as Machine learning approach, Short Text Classification and Black list techniques are applied on Users Wall

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Not AvailableEffect of Aegle marmelos and Ficus religiosa on the ovarian function in rats.Not Availabl

Heterosis Studies for Grain Yield and Yield Components in Rabi Sorghum [Sorghum bicolor (L.) Moench.]

The present investigation was conducted to assess the magnitude of heterosis of rabi sorghum (Sorghum bicolor (L.) Moench) developed by crossing four lines and twelve testers (in a line × tester design) to produce 48 F1 cross combinations at the Sorghum Improvement Project, MPKV., Rahuri, Maharashtra. To identify the high-yielding Rabi sorghum hybrids, promising hybrids were sorted out based on positive significant standard heterosis for grain yield per plant. A total of twenty-one hybrids exhibited significant standard heterosis for grain yield per plant. The best cross combination was 104A x RSR 1012 (86.59%) for maximum standard heterosis, followed by the cross 104A X RSR 1019 (73.17%) and 104 A X RSR 1003 (70.73%) for grain yield per plant. Heterosis has been considered a well-proven method for increasing yield and improving traits in crops, and the exploitation of heterosis for the hybrid development programme is considered one of the greatest breakthroughs in plant breeding

Energy-Constrained Target Localization Scheme for Wireless Sensor Networks Using Radial Basis Function Neural Network

The indoor object tracking by utilizing received signal strength indicator (RSSI) measurements with the help of wireless sensor network (WSN) is an interesting and important topic in the domain of location-based applications. Without the knowledge of location, the measurements obtained with WSN are of no use. The trilateration is a widely used technique to get location updates of target based on RSSI measurements from WSN. However, it suffers with high location estimation errors arising due to random variations in RSSI measurements. This paper presents a range-free radial basis function neural network (RBFN) and Kalman filtering- (KF-) based algorithm named RBFN+KF. The performance of the RBFN+KF algorithm is evaluated using simulated RSSIs and is compared against trilateration, multilayer perceptron (MLP), and RBFN-based estimations. The simulation results reveal that the proposed RBFN+KF algorithm shows very low location estimation errors compared to the rest of the three approaches. Additionally, it is also seen that RBFN-based approach is more energy efficient than trilateration and MLP-based localization approaches

TB case fatality and recurrence in a private sector cohort in Mumbai, India

BACKGROUND: Half of India´s three million TB patients are treated in the largely unregulated private sector, where quality of care is often poor. Private provider interface agencies (PPIAs) seek to improve private sector quality of care, which can be measured in terms of case fatality and recurrence rates.METHODS: We conducted a retrospective cohort survey of 4,000 private sector patients managed by the PATH PPIA between 2014 and 2017. We estimated treatment and post-treatment case-fatality ratios (CFRs) and recurrence rates. We used Cox proportional hazards models to identify predictors of fatality and recurrence. Patient loss to follow-up was adjusted for using selection weighting.RESULTS: The treatment CFR was 7.1% (95% CI 6.0-8.2). At 24 months post-treatment, the CFR was 2.4% (95% CI 1.7-3.0) and the recurrence rate was 1.9% (95% CI 1.3-2.5). Treatment fatality was associated with age (HR 1.02, 95% CI 1.02-1.03), clinical diagnosis (HR 0.61, 95% CI 0.45-0.84), treatment duration (HR 0.09, 95% CI 0.06-0.10) and adherence. Post-treatment fatality was associated with treatment duration (HR 0.87, 95% CI 0.79-0.91) and adherence.CONCLUSIONS: We found a moderate treatment phase CFR among PPIA-managed private sector patient with low rates of post-treatment fatality and recurrence. Routine monitoring of patient outcomes after treatment would strengthen PPIAs and inform future post TB interventions

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Not AvailableEffect of Aegle marmelos and Ficus religiosa on the onset of puberty in female rats.Not Availabl