We report on 3D printing of artifacts with a structured, inhomogeneous interior. The interior is decomposed into cells defined by a 3D Voronoi diagram and their sites. When printing such objects, ...most slices the printer deposits are topologically the same and change only locally in the interior. The slicing algorithm capitalizes on this coherence and minimizes print head moves that do not deposit material. This approach has been implemented on a client/server architecture that computes the slices on the geometry side. The slices are printed by fused deposition, and are communicated upon demand.
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•We explore 3D Voronoi-based heterogeneous printing.•We utilize Euler loops to minimize non-extruding fast travels.•The motion paths of consecutive slices are almost the same.•The motion paths are not generated from scratch at every slice.•Only 3 local cases can arise when updating the motion paths.
•Bert is embedded into the federated learning framework with C-S architecture.•Federated Bert Network integrates an improved local-model aggregation algorithm.•Length Alignment Algorithm adapts ...multi-attribute time series to batch calculating.•Our model is superior in cross-lingual verification and privacy data protection.
Online signature verification has a great challenge due to the poor performance of deep learning techniques on cross-lingual datasets under privacy constraints. In this paper, we propose a novel Federated Bert Network (FBN) by embedding the Bidirectional Encoder Representations from Transformers (Bert) into a Federated Learning (FL) framework with client-server architecture. A new Length Alignment Algorithm is employed to unify the signature pairs’ sequence length, and the input representations are fed into the different clients to complete the independent learning of local-models. In addition, the server (coordinator) uses the improved Federated Average Algorithm with Reward-Punishment Mechanism (FedAvgRP) to aggregate these local-models and further generate a global-model. After multiple iterations, the optimal model can be obtained and cross-tested on four datasets (SVC 2004, MCYT-330, BioecurID, and Ours) with skilled forged (random forged) EERs of 7.65% (4.76%), 10.73% (8.46%), 10.09% (7.13%), and 8.28% (5.74%), respectively, far higher than that of the independent learning of state-of-the-art methods. Compared with the domain adaptation and improved FL models, our FBN model performs best in random and skilled forgery scenarios. Moreover, the FedAvgRP algorithm helps our model maintain high performance in the face of data attacks.
Climate is an essential component of environmental models. Over the last two decades, many weather generators have been presented in the literature. Although their implementation into software has ...been of great help to environmental modellers, their lack of integration into modelling frameworks still represents a challenge for end users. In many cases, end users have to retrieve the climate variables by themselves in order to use an environmental model. In some other cases, the weather generator software is embedded into the modelling framework, but this increases the maintenance effort.
In this paper, we present a different approach: the deployment of a weather generator as a Web API. A few application examples are provided to illustrate the benefits of this implementation. In summary, a Web API facilitates the integration into modelling frameworks, decreases the maintenance effort and avoid interoperability issues due to different programming languages.
Currently, the urgent task is developing the methods and tools for increasing Smart Parking software system security. The purpose of this study is conducting analysis of requirements for Smart ...Parking System software security in order to find the bottlenecks and parts of the software that are most vulnerable to external threats and develop the methods and tools for increasing their security. The paper proposes the method of increasing Smart Parking software system security based on integrating the middleware in Smart Parking System software architecture. The proposed method takes into account all the criteria for Smart Parking System software security, i.e. parameters of safe access to the database, client program security, server security and API security and provides a complex solution for increasing the safety of Smart Parking software system. The proposed method differs from the known ones in that it allows taking into account all the criteria for increasing the Smart Parking System software security in complex using security middleware.
Background. To improve the accuracy of detection and classification of emotional states in the areas of human activity associated with the risk of man-made and biogenic accidents has become an urgent ...task. The aim of the study is to improve the efficiency of a system to detect and classify human emotional states from speech signals. The object of the research is the structure and software and hardware implementation of the system for detecting and classifying emotional states. The subject of the study is the means and techniques for software and hardware implementation. Materials and methods. The client-server methods for hardware and software implementation of the system based on the original software modules for speech signal processing and classifying emotional disorders, as well as several hardware implementations of the server device have been used. Results. The article presents hardware and software implementation of a system to detect and classify human emotional states from speech signals based on the client-server architecture. The novelty of the proposed concept is the creation of server clusters interconnected by a high-speed channel. This approach to the organization of the client-server architecture of the system allows increasing productivity and the speed of data processing, ensuring stability and timely delivery of results in real time. Results and conclusions. The research results have evidenced the accuracy of the developed system for the classification of emotional states being 94.7–95.6 %, and that for the classification of emotions being 93.1–95.6 %. The accuracy of the developed system is on average 3.15 % and 2.35 % higher for the classification of emotional states and emotions, respectively, as compared with related products on the speech technology market. In the future, it is planned to conduct further research on the performance of hardware and software implementation of the system to detect and classify human emotional states from speech signals.
Control of Remote Robots by Means of Cell Phones Zaatri, Abdelouahab; Kelaiaia, Ridha
Acta Universitatis Sapientiae. Electrical and Mechanical Engineering,
12/2022, Letnik:
14, Številka:
1
Journal Article
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Since about two decades, cellular phones coupled to internet and wireless communications are offering many possibilities that can be exploited by classical telerobotics to free human operators from ...many constraints providing mobility and ubiquitous applications.
This paper presents the design and implementation of an experimental telerobotics system where the human operator supervises and controls remote robots by means of cell phones. To achieve this application, we used Java software namely J2ME platform which is dedicated for programming cell phones and J2SE platform for programming PCs. The adopted software technology of connection between the human operator and the remote robots uses the socket technique with client-server model. The cell phone held by the operator acts as a Client while a PC, situated at the remote robot site, acts as a Server. This application corresponds to Midlet-to-Servlet in Java terminology. Basic simulations and preliminary experiments have been successfully carried out with a three Degrees-of-Freedom (D.O.F) serial robot. These telerobotics systems based on cell phones are effectively offering interesting means to opening new perspectives for mobile and ubiquitous applications.
Client-server sessions in linear logic Qian, Zesen; Kavvos, G. A.; Birkedal, Lars
Proceedings of ACM on programming languages,
08/2021, Letnik:
5, Številka:
ICFP
Journal Article
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We introduce coexponentials, a new set of modalities for Classical Linear Logic. As duals to exponentials, the coexponentials codify a distributed form of the structural rules of weakening and ...contraction. This makes them a suitable logical device for encapsulating the pattern of a server receiving requests from an arbitrary number of clients on a single channel. Guided by this intuition we formulate a system of session types based on Classical Linear Logic with coexponentials, which is suited to modelling client-server interactions. We also present a session-typed functional programming language for client-server programming, which we translate to our system of coexponentials.
In today's world, where the need for security is paramount and biometric access control systems are gaining mass acceptance due to their increased reliability, research in this area is quite ...relevant. Also with the advent of IOT devices and increased community support for cheap and small computers like Raspberry Pi its convenient than ever to design a complete standalone system for any purpose. This paper proposes a Facial Biometric System built on the client-server paradigm using Raspberry Pi 3 model B running a novel local descriptor based parallel algorithm. This paper also proposes an extended version of Local Gradient Hexa Pattern with improved accuracy. The proposed extended version of LGHP improved performance as shown in performance analysis. Extended LGHP shows improvement over other state-of-the-art descriptors namely LDP, LTrP, MLBP and LVP on the most challenging benchmark facial image databases, i.e. Cropped Extended Yale-B, CMU-PIE, color-FERET, LFW, and Ghallager database. Proposed system is also compared with various patents having similar system design and intent to emphasize the difference and novelty of the system proposed.
The learning analytics community has matured significantly over the past few years as a middle space where technology and pedagogy combine to support learning experiences. To continue to grow and ...connect these perspectives, research needs to move beyond the level of basic support actions. This means exploring the use of data to prove richer forms of actions, such as personalized feedback, or hybrid approaches where instructors interpret the outputs of algorithms and select an appropriate course of action. This paper proposes the following three contributions to connect data extracted from the learning experience with such personalized student support actions: 1) a student–instructor centred conceptual model connecting a representation of the student information with a basic set of rules created by instructors to deploy Personalized Learning Support Actions (PLSAs); 2) a software architecture based on this model with six categories of functional blocks to deploy the PLSAs; and 3) a description of the implementation of this architecture as an open-source platform to promote the adoption and exploration of this area.
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