Communication Networks with Endogenous Link Strength

This paper analyzes the formation of communication networks when players choose endogenously their investment on communication links. We consider two alternative de?nitions of network reliability ; product reliability, where the decay of information depends on the product of the strength of communication links, and min reliability where the speed of connection is a¤ected by the weakest communication link. When investments are separable, the architecture of the efficient network depends crucially on the shape of the transformation function linking investments to the quality of communication links. With increasing marginal returns to investment, the efficient network is a star ; with decreasing marginal returns, the con?ict between maximization of direct and indirect bene?ts prevents a complete characterization of efficient networks. However, with min reliability, the efficient network must be a tree. Furthermore, in the particular case of linear transformation functions, in an e¢ cient network, all links must have equal strength. When investments are perfect complements, the results change drastically : under product reliability, the efficient network must contain a cycle, and is in fact a circle for small societies. With min reliability, the e¢ cient network is either a circle or a line. As in classical models of network formation, e fficient networks may not be supported by private invesment decisions. We provide examples to show that the star may not be stable when the transformation functions is strictly convex. We also note that with perfect substitutes and perfect complements (when the e¢ cient network displays a very symmetric structure), the e¢ cient network can indeed be supported by private investments when the society is large.communication networks ; network reliability

Neural approximation of Wasserstein distance via a universal architecture for symmetric and factorwise group invariant functions

Learning distance functions between complex objects, such as the Wasserstein distance to compare point sets, is a common goal in machine learning applications. However, functions on such complex objects (e.g., point sets and graphs) are often required to be invariant to a wide variety of group actions e.g. permutation or rigid transformation. Therefore, continuous and symmetric product functions (such as distance functions) on such complex objects must also be invariant to the product of such group actions. We call these functions symmetric and factor-wise group invariant (or SFGI functions in short). In this paper, we first present a general neural network architecture for approximating SFGI functions. The main contribution of this paper combines this general neural network with a sketching idea to develop a specific and efficient neural network which can approximate the $p$-th Wasserstein distance between point sets. Very importantly, the required model complexity is independent of the sizes of input point sets. On the theoretical front, to the best of our knowledge, this is the first result showing that there exists a neural network with the capacity to approximate Wasserstein distance with bounded model complexity. Our work provides an interesting integration of sketching ideas for geometric problems with universal approximation of symmetric functions. On the empirical front, we present a range of results showing that our newly proposed neural network architecture performs comparatively or better than other models (including a SOTA Siamese Autoencoder based approach). In particular, our neural network generalizes significantly better and trains much faster than the SOTA Siamese AE. Finally, this line of investigation could be useful in exploring effective neural network design for solving a broad range of geometric optimization problems (e.g., $k$-means in a metric space).Comment: Accepted to NeurIPS 202

Investigative Studies Of Embedded Assembly Line Automation System With Dual Rfid Platform

The lack of control and outdated inventory system have increased the management complexity of factory production lines, especially by the increase of sales and demand in the industry. An unmanageable system in the assembly line leads to inefficiency problems in tracking the volume of the product. The objective of this research is to develop a new design of embedded dual RFID architecture (passive and active systems) into a single system to track and monitor the product delivery process at the assembly lines in the industries. A new combination of 2.4 GHz ZigBee-based RFID operating in wireless sensor network platform is proposed as the solution to the product management problem. Meanwhile, the proposed system involved hardware and software designs which were embedded with the passive RFID reader at Ultra High Frequency (UHF). Results from the experiments conducted showed that the embedded system namely Passive and Active RFID (PAR) produced better overall performance compared to the standalone which Passive RFID (PR) system. The indoor range test was measured from 0 up to 60 m distance. The measurements obtained at 1 m and 60 m of transmission range are -33 dB and -51 dB respectively. It was also observed that embedded system has better signal strength value 7.84 % compared to the standalone system at 60 m. For the highest power level, which is level 4 (10 dBm) it is found that only 0.02 dB of signal loss occurred and matches 99.8 % to the theoretical value for PAR system. The throughput values for the embedded are between 12 kbps to 29 kbps for 17 bytes of data per packet. In the latency test, the embedded PAR system has better and therefore lower delay of 10.9 %, 40.6 % and 74.7 % for up to 3 tags compared to the standalone system. Experimental studies using Design of Experiment (DOE) were also developed using factorial and statistical data analysis to validate the eligibility of the proposed system to be applied in industrial environment and requirements. The factorial analysis on the effects on the conveyor speed, product orientation, tag orientation, type of tags, linear distance and type of product materials had been studied in DOE experiments for guidelines to the industry. The percentage of successful product detection indicates a very high prediction at 97.8 %. The proposed path loss model also provides the estimation of wireless distance and number of assembly lines required for establishing an efficient product management system. From the path loss model at distance 10 m the RSSI value for the NLOS indoor environment of assembly line gave -72 dBm

Software Product Line for Metaverse: Preliminary Results

The Metaverse is a network of eXtended Reality applications (XR apps) connected to each other, over the Internet infrastructure, allowing network users, systems, and devices to access them. It is very challenging to implement solutions for XR apps, due to the combination of complex concerns that should be addressed: multiple users with non-traditional input and output devices, different hardware platforms that should be addressed, forceful interactive rates, and experimental interaction techniques, among other issues. Therefore, this work aims to present a Software Product Line (SPL)-based approach to support the development of Web XR apps. More specifically, we define a features model that represents similarities and variables (domain analysis); we defined a core composed of generic and reusable software artifacts (domain project); and we developed an interface to support the instantiation of a Web XR app family, named MetaSee Features Model Editor (domain implementation). This approach integrates with a component of the MetaSEE architecture (Metaverse for Software Engineering Education). A preliminary assessment found that Features Model has conceptual consistency from the point of view of the complexity of Web XR Apps multimodal interaction. As future work, features model and artifacts will be increased with improvements and an evaluation with a significant number of participants will be made

Software test automation : a design and tool selection approach for a heterogeneous environment

textThis report describes a design approach for implementing a software test automation solution that can accommodate existing test processes in an organization. The process of implementing a software test automation solution is a large undertaking and requires careful planning to avoid unsuccessful implementations. This report outlines a design that can integrate with existing business and development processes in an organization, and recommends automation and development frameworks for achieving the test automation goals. Considerations for a heterogeneous test environment with varying types of supported operating systems, such as Windows and Linux, and multiple test execution environments, such as Java and .NET, have been made in this design and in the tool selections for the system implementation. The report also describes some of the challenges and caveats of automation in a heterogeneous environment along with recommended solutions to these challenges.Electrical and Computer Engineerin