In recent years, the positioning applications of Internet-of-Things (IoT) based systems have grown increasingly popular, and are found to be useful in tracking the daily activities of children, the elderly and vehicle tracking. It can be argued that the data obtained from GPS based systems may contain error, hence taking these factors into account, the proposed method for this study is based on the application of IoT-based positioning and the replacement of using IoT instead of GPS.  This cannot, however, be a reason for not using the GPS, and in order to enhance the reliability, a parallel combination of the modern system and traditional methods simultaneously can be applied. Although GPS signals can only be accessed in open spaces, GP

Sansevieriatrifasciata was studied as a potential biosorbent for chromium, copper and nickel removal in batch process from electroplating and tannery effluents. Different parameters influencing the biosorption process such as pH, contact time, and amount of biosorbent were optimized while using the 80 mm sized particles of the biosorbent. As high as 91.3 % Ni and 92.7 % Cu were removed at pH of 6 and 4.5 respectively, while optimum Cr removal of 91.34 % from electroplating and 94.6 % from tannery effluents was found at pH 6.0 and 4.0 respectively. Pseudo second order model was found to best fit the kinetic data for all the metals as evidenced by their greater R2 values. FTIR characterization of biosorbent revealed the presence of carboxyl a

Continual learning on edge platforms remains challenging because recurrent networks depend on energy-intensive training procedures and frequent data movement that are impractical for embedded deployments. This work introduces M2RU, a mixed-signal architecture that implements the minion recurrent unit for efficient temporal processing with on-chip continual learning. The architecture integrates weighted-bit streaming, which enables multi-bit digital inputs to be processed in crossbars without high-resolution conversion, and an experience replay mechanism that stabilizes learning under domain shifts. M2RU achieves ∼13 GOPS at 16.76 mW, corresponding to 776 GOPS per watt, and maintains accuracy within 5 percent of software baselines on seque

In this paper, membrane-based computing image segmentation, both region-based and edge-based, is proposed for medical images that involve two types of neighborhood relations between pixels. These neighborhood relations—namely, 4-adjacency and 8-adjacency of a membrane computing approach—construct a family of tissue-like P systems for segmenting actual 2D medical images in a constant number of steps; the two types of adjacency were compared using different hardware platforms. The process involves the generation of membrane-based segmentation rules for 2D medical images. The rules are written in the P-Lingua format and appended to the input image for visualization. The findings show that the neighborhood relations between pixels o

In the last years, a new technology called Cloud computing has been developed. Empirical and previous studies, commonly examined in business field and other domains. In this study, the significant factors that affecting the adoption of cloud computing have been examined using a frequency analysis that have been explored by the previous studies. The results showed that the most effected factors were relative advantage which followed by security and privacy, complexity, innovativeness, and external support. In this study the model of technology organization-environment was used to examine the significant factors that affecting the adoption of cloud computing.