ANALYSIS AND ESTIMATION OF TIME OF ARRIVAL AND RECEIVED SIGNAL STRENGTH IN WIRELESS COMMUNICATION FOR INDOOR GEOLOCATION

Analysis and estimation of the time of  arrival and received signal strength  for indoor geolocation using MATLAB describes an indoor geolocation localization  which either  use the received signal strength (RSS) or time of arrival (TOA) of the received signal as their localization  metric. Though time of arrival based systems are sensitive to the available bandwidth and also to the occurrence of undetected direct path (UDP) channel conditions which RSS based system are less sensitive to the bandwidth as more resilient to undetected conditions.  This paper demonstrate the availability of radio channel modeling techniques to eliminate the costly finger printing process in pattern recognition algorithms by introducing ray tracing (RT) assisted  by RSS and TOA based algorithms. The results in figure 8 which shows the effect of pathloss on signal reception, showing free path loss reduces when plotted with rhe height  of the building  which can be used for achieving localization. it was also disovered that path loss also contributes to signal delay, the plot in figure 12  which is a probability distribution of received signal strength at different location which detect signal at the point where maximum signal was received , this RSS at fixed positions can be used to determine  geolocation

Advanced Strategies for Robot Manipulators

Amongst the robotic systems, robot manipulators have proven themselves to be of increasing importance and are widely adopted to substitute for human in repetitive and/or hazardous tasks. Modern manipulators are designed complicatedly and need to do more precise, crucial and critical tasks. So, the simple traditional control methods cannot be efficient, and advanced control strategies with considering special constraints are needed to establish. In spite of the fact that groundbreaking researches have been carried out in this realm until now, there are still many novel aspects which have to be explored

Text Similarity Between Concepts Extracted from Source Code and Documentation

Context: Constant evolution in software systems often results in its documentation losing sync with the content of the source code. The traceability research field has often helped in the past with the aim to recover links between code and documentation, when the two fell out of sync. Objective: The aim of this paper is to compare the concepts contained within the source code of a system with those extracted from its documentation, in order to detect how similar these two sets are. If vastly different, the difference between the two sets might indicate a considerable ageing of the documentation, and a need to update it. Methods: In this paper we reduce the source code of 50 software systems to a set of key terms, each containing the concepts of one of the systems sampled. At the same time, we reduce the documentation of each system to another set of key terms. We then use four different approaches for set comparison to detect how the sets are similar. Results: Using the well known Jaccard index as the benchmark for the comparisons, we have discovered that the cosine distance has excellent comparative powers, and depending on the pre-training of the machine learning model. In particular, the SpaCy and the FastText embeddings offer up to 80% and 90% similarity scores. Conclusion: For most of the sampled systems, the source code and the documentation tend to contain very similar concepts. Given the accuracy for one pre-trained model (e.g., FastText), it becomes also evident that a few systems show a measurable drift between the concepts contained in the documentation and in the source code.</p