The swift embrace of Industry 4.0 paradigms has led to the growing convergence Information Technology (IT) networks and Operational (OT) networks. Traditionally isolated on air-gapped fully trusted networks, OT are now becoming more interconnected with IT due advancement applications IoT. This expanded attack surface vulnerabilities in Cyber–Physical Systems (CPSs), resulting increasingly frequent compromises substantial economic life safety repercussions. existing methods for anomaly...

Cloud computing can be defined as the use of new or existing hardware and virtualization technologies to form a shared infrastructure that enables web-based value added services. The three predominant service models are infrastructure, platform, software-asa-service. Infrastructure-as-a-Service (IaaS) servers, storage, enable utility like services for users. Security is big concern within IaaS, especially considering rest cloud run on top related layers. Platform-as-a-Service (PaaS)...

This study aimed to develop an algorithm using the explainable artificial intelligence (XAI) approaches for early prediction of mortality in intensive care unit (ICU) patients with acute kidney injury (AKI). gathered clinical data AKI from Medical Information Mart Intensive Care IV (MIMIC-IV) US between 2008 and 2019. All were further randomly divided into a training cohort validation cohort. Seven machine learning methods used models assessing in-hospital mortality. The optimal model was...

This research investigates the application of deep learning in sentiment analysis Canadian maritime case law. It offers a framework for improving law and legal analytic policy-making procedures. The automation document extraction takes center stage, underscoring vital role plays at level. Therefore, this study introduces novel strategy law, combining approaches with state-of-the-art techniques. overarching goal is to systematically unearth hidden biases within investigate their impact on...

Multi-robot path planning has evolved from research to real applications in warehouses and other domains; the knowledge on this topic is reflected large amount of related published recent years international journals. The main focus existing relates generation efficient routes, relying collision detection local sensory system creating a solution based search methods. This approach implies robots having good also computation capabilities take decisions fly. In some controlled environments,...

Abstract Stress significantly impacts individuals, particularly in professions like nursing and driving, leading to severe health risks accidents. Accurate stress measurement is critical for effective interventions, yet research hindered by incomplete datasets inconsistent methodologies, slowing the development of reliable predictive models. This paper introduces a framework cross-contextual prediction, enabling generation general prediction models adaptable specific domain challenges. The...

Education Technology advances many aspects of learning. More and more learning is taking place online. Learners’ behaviors, style, performance can be easily profiled through analytics which collects their online footage. It enables encourages educational research, software application development, education practices towards personalized adaptive As we continue to see progress, must also pay attention the negative impacts that feed into our research. In this paper, will present introspection...

In the context of distance education, lab and field work are a considerable challenge for students, professors, institutions. This paper presents Telepresence Robot Empowered Smart Lab (TRESL) system as new emerging technology with potential to overcome this challenge. The main focus is propose conceptual model, define ultimate goals proposed solution, present its architecture modules support functions features. A pilot project was conducted also presented in paper. includes experimental...

Performance of dynamic clouds depends on the efficiency its load balancing and resource allocation. This paper is an exploratory study predictive approach for distribution cloud services. Efficient management can be achieved by simulating services based predictions incoming workloads, which more efficient than static allocation methods. introduces a rule-based workload-balancing algorithm end-to-end system called Cicada. A simulation service simulator CloudSim it will used to achieve with...

Many industry standards and methodologies were introduced which has brought forth the management of threats assessment risk information assets in a systematic manner.This paper will review analyze main processes followed IT frameworks from perspective threat analysis process using modeling methodology.In this study, authors propose new model shows that is an essential element to be considered as integrated within frameworks.The proposed complements fulfills gap practice assessing security risks.

In this research, a coevolutionary collision free multi-robot path planning that makes use of A* is proposed. To find collision-free paths for all robots, we generate route each robot using finding but introducing restrictions found. Afterward, co-evolutionary optimization process implemented changes in the initial to combination routes collision-free. The approach has been tested mazes with increasing number showing robust performance although at high time expenses. Nevertheless, several...

Colletotrichum gloeosporioides is one of the most serious diseases that causes damage to mangoes. Laccase, a copper-containing polyphenol oxidase, has been reported in many species with different functions and activities, fungal laccase could be closely related mycelial growth, melanin appressorium formation, pathogenicity, so on. Therefore, what relationship between pathogenicity? Do genes have functions? In this experiment, knockout mutant complementary strain Cglac13 were obtained through...

Abstract Historical information in the Canadian Maritime Judiciary increases with time because of need to archive data be utilized case references and for later application when determining verdicts similar cases. However, such are typically stored multiple systems, making its reachability technical. Utilizing technologies like deep learning sentiment analysis provides chances facilitate faster access court records. Such practice enhances impartial verdicts, minimizing workloads employees,...

This research investigates the application of deep learning in sentiment analysis Canadian maritime case law. It offers a framework for improving law and legal analytics policy-making procedures. The automation document extraction takes center stage, underscoring vital role plays at level. Therefore, this study introduces novel strategy law, combining approaches with state-of-the-art techniques. overarching goal is to systematically unearth hidden biases within investigate their impact on...

This meta-analysis covers 30 different interventions, as well 5 tests of bacteriostatic activity. The results showed that 10 mmol/L oxalic acid solution had the best inhibitory activity against Botryosphaeria dothidea. intervention to inhibit increase in morbidity kiwifruit was sprayed by 0.1 % sodium-rich calcium + 25 azoxystrobin SC 2000-times liquid. Applied pullulan-active-coating g/L potassium metabisulfite method lesion diameter and suppress accumulation soluble solids. chitosan 1 tea...

While frequently used herbicides display limited efficacy against herbicide-resistant weeds, it becomes imperative to explore novel that ensure both effective weed management and environmental safety. Though 4-hydroxyphenylpyruvate dioxygenase (HPPD) inhibitory like mesotrione are prevalent in maize management, their integration into rice production is hindered due the inherent sensitivity of HPPD (

Location-based adaptive mobile learning utilizes a unique feature: location awareness of devices in regards to other online implement location-based functionalities or features create and collaborative environment. There are many important research issues technical challenges the systems, including assessment In this paper, we present framework topics related undergoing project at Athabasca University towards development robust effective systems. addition, also brief some major outcomes...

This paper presents a collaborative mobile learning system: Mobile Virtual Campus (MVC) powered by the loction-based dynamic grouping algorithm. The MVC system has been developed to provide an innovative and interactive platform for online learners utilizing location awareness other built-in sensory compoments in devices. On platform, can learn collaboratively interactively either at distance or face-to-face environment.

In a client-server mobile learning system, client software must run on the phone to acquire, package, and send studentâ??s interaction data via communications network connected application server. The server will receive process in order offer appropriate content activities. To develop systems there are number of very important issues that be addressed. Mobile phones have scarce computing resources. They consist heterogeneous devices use various operating systems, they limitations with their...