Hybrid Variational Autoencoder for Recommender Systems

E-commerce platforms heavily rely on automatic personalized recommender systems, e.g., collaborative filtering models, to improve customer experience. Some hybrid models have been proposed recently to address the deficiency of existing models. However, their performances drop significantly when the dataset is sparse. Most of the recent works failed to fully address this shortcoming. At most, some of them only tried to alleviate the problem by considering either user side or item side content information. In this article, we propose a novel recommender model called Hybrid Variational Autoencoder (HVAE) to improve the performance on sparse datasets. Different from the existing approaches, we encode both user and item information into a latent space for semantic relevance measurement. In parallel, we utilize collaborative filtering to find the implicit factors of users and items, and combine their outputs to deliver a hybrid solution. In addition, we compare the performance of Gaussian distribution and multinomial distribution in learning the representations of the textual data. Our experiment results show that HVAE is able to significantly outperform state-of-the-art models with robust performance.

Estimation of Nutrient Loads With the Use of Mass-balance and Modelling Approaches on the Wełna River Catchment Example (Central Poland)

Nitrogen and phosphorus budgeting is considered to be a useful tool for policy makers and stakeholders when dealing with nutrient contamination issues. Although a variety of budgeting approaches have been employed in countries affected by this problem, the direct comparison of possible options for the same area is quite limited. The current study offers a detailed insight into the estimations of nutrient loads and their distribution between different sources for a middle-sized agricultural catchment, with the use of two approaches: mass balance method and SWAT modelling. As a result of their comparison, both methods revealed similar contributions of analysed nutrient sources, although the absolute loads were heterogeneous, which stems from drawbacks related to the quality of the monitoring data, the performance of the model and omission of some catchment processes. However, in light of the performed comparison, we suggest a hybrid solution, combining the best features of both approaches.

Hybrid Autoscaling Strategy on Container-based Cloud Platform

The container has several advantages over the traditional virtual machine technology such as light-weight, fast booting time, and fast recovery. Kubernetes is one the most outstanding container management and deployment platforms. The Kubernetes provides autoscaling function, which will increase and decrease the hardware resources to adapt with the current traffic load situation to keep the user experience. Two popular autoscaling methods are horizontal autoscaling and vertical autoscaling. Based on the monitoring resource utilization, horizontal autoscaling will increase the number of PoDs (point of deployment) or vertical autoscaling will increase the hardware resources of each PoD to achieve the target utilization. In this paper, we present a hybrid solution that combines the advantages of both autoscaling solutions and proposes a bandwidth-efficient scheduler strategy. By numerical analysis, our hybrid approach is better than the normal HPA approach in terms of bandwidth cost and has lower autoscaling latency than the VPA approach

A Paradigm Shift in Monitoring Pipeline Leaks - Combining Sensorless NPW with RTTM

Leak detection solutions in pipelines use several known methods and technologies. However, each method and its underlying technology has their benefits and drawbacks. This article will present and evaluate a hybrid solution that combines two methods based on different physical measurements and quantities to ensure a superior detection probability, short detection time, accurate localization of faults, and minimal false alarm rates. In addition, this solution also features preventive capabilities by pointing out problematic areas in a pipeline that may need more attention. The article presents a novel approach for pipeline monitoring using a combined solution with the strengths of real-time transient model (RTTM) technology and the power of next-generation fiber sensing geared towards leak detection. On top of acoustic sensing for leaks, it features continuous pipeline integrity monitoring where, using subtle characteristics of propagating negative pressure waves (NPW), pipeline sections signatures are tracked, aiming to detect changes that might expose pipeline integrity issues that can enable the operator to take preventive measures and plan maintenance events. Such a hybrid solution, from AVEVA™ (RTTM) and Prisma Photonics (fiber sensing), will obtain higher levels of performance and reliability. In addition, such a hybrid approach responds to the increasing regulatory demand to have two continuously working solutions based on different physical measures to ensure leak detection and prevention of substance spillage. This article intends to introduce such a hybrid solution with new applications in predictive maintenance for pipeline operators and shed more light on the benefits of such a solution facing further regulatory demands.

Simulation of an Advanced Geothermal Energy Conversion Plant in Perú

This investigation aims to simulate an efficient plant that generates energy through a solar-geothermal hybrid energy conversion system with supercritical steam, Therminol VP1, geothermal fluid and R134a refrigerant. The goal is to exemplify a hybrid solution that optimizes and takes advantage of the existing properties of the solar and geothermal power cycles. The geothermal part of the process, the primary cycle, is augmented by the solar thermal cycle to obtain a high-efficiency result. In addition, it allows the reader to understand the ideal process of this type of plant and a thermodynamic analysis represented by creating a detailed model block flow diagram, which is then turned into a dynamic one used to examine the selected parameters such as temperature, flow rate, and pressure variations. The dynamic model approximated the thermal values of the heat exchangers and the working fluids in the exchangers, solar collectors, piping and in the storage tanks.

Improving the performance of photovoltaic module during partial shading using ANN

<span lang="EN-US">Photovoltaic (PV) panels have drawback of having their peak power reduced when clouds or shade are present. Furthermore, it is only available while the sun shine. Nearby structures, plants, bird droppings, and other obstacles shade operating photovoltaic (PV) devices, effectively reducing the incident solar radiation produced by the modules. When these PV panels are exposed to partial shading, their power efficiency is reduced. A neural network with a kind of artificial neural network is used in the suggested hybrid method (ANN). The key focus of this article is to use environmental effects dependent on partial shading to get the maximum performance from a solar system. The suggested hybrid solution is tested in the MATLAB/Simulink working platform using partial shading test cases, and the efficiency is compared to other approaches. Additionally, the best options for the suggested procedure, current, voltage, and power are examined.</span>

Towards post-quantum security for cyber-physical systems: Integrating PQC into industrial M2M communication1

The threat of a cryptographically relevant quantum computer contributes to an increasing interest in the field of post-quantum cryptography (PQC). Compared to existing research efforts regarding the integration of PQC into the Transport Layer Security (TLS) protocol, industrial communication protocols have so far been neglected. Since industrial cyber-physical systems (CPS) are typically deployed for decades, protection against such long-term threats is needed. In this work, we propose two novel solutions for the integration of post-quantum (PQ) primitives (digital signatures and key establishment) into the industrial protocol Open Platform Communications Unified Architecture (OPC UA): a hybrid solution combining conventional cryptography with PQC and a solution solely based on PQC. Both approaches provide mutual authentication between client and server and are realized with certificates fully compliant to the X.509 standard. We implement the two solutions and measure and evaluate their performance across three different security levels. All selected algorithms (Kyber, Dilithium, and Falcon) are candidates for standardization by the National Institute of Standards and Technology (NIST). We show that Falcon is a suitable option – especially – when using floating-point hardware provided by our ARM-based evaluation platform. Our proposed hybrid solution provides PQ security for early adopters but comes with additional performance and communication requirements. Our solution solely based on PQC shows superior performance across all evaluated security levels in terms of handshake duration compared to conventional OPC UA but comes at the cost of increased handshake sizes. In addition to our performance evaluation, we provide a proof of security in the symbolic model for our two PQC-based variants of OPC UA. For this proof, we use the cryptographic protocol verifier ProVerif and formally verify confidentiality and authentication properties of our quantum-resistant variants.

Two-Layer Optimization Algorithm for Multi-UAV Conflict Resolution considering Individual Fairness

In order to solve the unfair individual payment costs problem in the low-altitude unmanned aerial vehicle (UAV) conflict resolution process, a multi-UAV conflict resolution algorithm based on the cooperative game concept “coalition complaint value” is proposed. Firstly, based on the low-altitude multi-UAV conflict scene characteristics, according to the “coalition complaint value” concept, the UAV conflict resolution payment matrix is established. Secondly, combined with the advantages of the artificial potential field (APF) method and the genetic algorithm (GA), a hybrid solution strategy for conflict resolution based on APF-GA is proposed. The final simulation results show that the APF-GA hybrid solution strategy has the best efficiency by combining the three evaluation indicators of calculation time, feasibility, and system efficiency. The reliability of the proposed algorithm is verified based on the Monte Carlo algorithm. The solution strategy based on the cooperative game “coalition complaint value” can improve individual fairness to a certain extent. At the same time, it can achieve the rapid planning goal with priority drones at the expense of a small amount of overall benefits.

A GIS-Based AHP Approach for Emergency Warehouse Site Selection: A Case Close to Turkey-Syria Border

Although the term “disaster” includes natural events like earthquake, flood and drought, it also covers; the wars, intense migration waves, industrial accidents and even epidemic diseases. In recent years, the number and severity of both natural and man-made disasters has been increasing. In this context Gaziantep –the border city of Turkey to Syria- is facing many logistical problems because of the crisis in the region that has a broad repercussion in press. In addition, the corona virus pandemic increased the supply traffic in the region. The region is in need for many emergency warehouses to store the emergency supplies and send to the needy. Thus, a three step hybrid solution method is developed to solve this real life problem. The first stage is the determination of selection criteria; secondly the spatial database is created by using a Geographical Information System (GIS). Then, Analytic Hierarchy Process (AHP) technique is applied to assign the importance levels to the selection criteria to generate the suitability map to choose the most appropriate emergency warehouse site selection in Gaziantep. Additionally, scenario analyses are conducted to understand the effects of importance levels on the problem results. As a result, 1.3% of the study area is determined as “quite suitable” for establishing an emergency warehouse.