Intelligent Software Applications Research Articles

A Softwarized Intrusion Detection System for IoT-Enabled Smart Healthcare System

The Internet of Things-enabled Smart Healthcare System (IoT-SHS) is a networked infrastructure of intelligent wearables, software applications, health systems, and services that continuously monitors and transmits patient-sensitive data using an open wireless channel. The conventional security mechanisms are unsuitable for detecting attacks in the dynamic IoT-SHS context due to resource limitations and heterogeneity in low-cost healthcare devices. Deep Learning (DL) solutions for Intrusion Detection System (IDS) and softwarization of the network has the potential to achieve secure network services in the IoT-SHS environment. Motivated by the aforementioned discussion, we propose an intelligent softwarized IDS for protecting the critical infrastructure of the IoT-SHS ecosystem. Specifically, the DL-based IDS is designed using a hybrid cuda Long Short-Term Memory Deep Neural Network (cuLSTM-DNN) algorithm to assist network administrators in efficient decision-making for the generated intrusions. To further bolster the system’s resilience, we suggest a deployment architecture for the proposed CUDA-powered IDS using OpenStack Tacker in a real SDN environment, ensuring that virtual machines can directly utilize the host’s NVIDIA GPU, thereby streamlining and enhancing the network’s operational efficiency. The experimental results using the CICDDoS2019 dataset confirm the effectiveness of the proposed framework over some baseline and recent state-of-the-art techniques.

Application of app intelligent voice software based on dynamic heterogeneous network in TPACK oral English teaching

Application of app intelligent voice software based on dynamic heterogeneous network in TPACK oral English teaching

Research on Music Assisted Teaching System Based on Artificial Intelligence Technology

With the advent of the information age, computer technology has been greatly developed, especially the development of Artificial Intelligence(AI). And with the passage of time, AI began to involve various fields, music education is no exception. In this paper, after a detailed understanding of some research results of AI on music assisted instruction system, we mainly analyze the students’ video, audio and other related information, and save it in the database. This paper first introduces the evaluation process by using AI technology. In fact, it is necessary to find out the relationship between the influencing factors and evaluation of music assisted teaching system. Neural network(NN) is actually a model proposed by simulating the way people think in the brain. It has no strict requirements for data distribution. In terms of nonlinear data processing method, robustness and dynamics, it is very suitable to be used as a model for evaluating music assisted instruction system. Then each factor is taken as the input parameter of the NN. According to the evaluation index of music teaching, a special modeling system is designed. With the help of technical personnel, we obtained the sample data of music performance and completed the neural training. The experimental results show that the development of AI technology has broken the original situation of traditional teaching, especially the application of music system and intelligent music software based on AI in music teaching.

On the Characterization and Risk Assessment of AI-Powered Mobile Cloud Applications

Ultra-reliable low-latency communication supports powerful mission-critical applications such as artificial intelligence-enabled mobile cloud applications designed to deliver the quality of service and quality of experience to their users. However, whether existing security mechanisms are ready to address the risks emerging from these applications operating over ultra-fast 5G and 6G infrastructures is an open question. The complexity of finding answers to this question is partly due to the lack of means to measure software applications’ intelligence levels and partly due to the limitations of existing risk assessment approaches. In this paper, first, we propose an ability-based scale to characterize intelligent software applications. After that, we propose a semi-quantitative approach for threat modeling and risk analysis of intelligent software applications. Focusing on Android, we define three intelligent mobile cloud applications’ scenarios and demonstrate the feasibility of the proposed scale and approach. We perform their risk analyses for assessing the readiness of Android security mechanisms to mitigate their risks and identify open problems. We propose to rethink intelligent mobile cloud computing applications’ characterization and warn security experts to redesign their security mechanisms to serve evolving privacy, security, and trust requirements.

Preliminary Conception of Financial Decision Knowledge Engineering

In the era of digital economy, the intelligence of enterprise financial management has an important influence on the effect of enterprise financial activities. At present, the application of intelligent financial system and software focuses on providing analysis information for financial decision-making, and cannot effectively give complete financial decision-making suggestions, nor does it combine with enterprise strategy. This paper puts forward the idea of constructing knowledge engineering of financial decisionmaking based on frame, and uses frame representation to express the knowledge of financial decisionmaking and enterprise strategy, so as to promote the combination of intelligent financial decision-making and enterprise strategy, and promote the intelligence of enterprise financial decision-making through knowledge engineering.

Summary of Research and Development of Intelligent Combustion Optimization System

This paper summarizes the purpose and significance of intelligent combustion optimization, and mainly introduces the theoretical research on intelligent combustion optimization algorithm and the development and application of intelligent combustion optimization system software. It makes a comprehensive assessment to the research results and technology development of intelligent combustion optimization, and gives an in-depth analysis of the current challenges and future development direction of intelligent combustion optimization technology. Finally, considering the latest research results and the current domestic thermal power development situation, it points out the urgency and necessity of the development of intelligent combustion optimization system.

Industrial Intelligent Software Applications of the Overall Equipment Effectiveness (OEE) in Manufacturing

This paper aims to evaluate the solution behaviour of the “Overall Equipment Effectiveness” to determine the performance in innovative manufacturing environments. OEE literature categorizes six major losses: “Equipment failures and breakdowns”, “Setup/Adjustments”, “Idling and minor Stops”, “Reduced Speed Losses”, “Reduced Yields and Quality Defects and Rework”. The technical implementation method used by the authors to achieve their scope has been described using a hybrid of software development programs such as: SAP MII, SAP PCo and SAP ME in relation to the theoretical existing principles. The results presented conclude that losses in practice can occur at both high rates and low rates and therefore, an innovative manufacturing concept must be further enhanced. In terms of performance related to equipment utilization, the specific stoppages and downtimes need to be taken in consideration and adjust the OEE results accordingly. The actual situation in a real–life environment has increased in efficiency, but as technology improves, opportunities for further development appear at a high rate.

AI Communications track on agreement technologies

The area of agreement technologies is receiving increased attention within the Artificial Intelligence research community. This is because current intelligent software applications are often based on components that are autonomous, capable of sophisticated ways of interacting, massively distributed, and quite often embedded in all sorts of appliances and sensors. These autonomous components, usually termed agents, need to be socially-aware in order to successfully achieve their goals. The important research question is how can we build software systems as collections of these components and guarantee that they interoperate correctly, and are thus reliable, especially when the components are complex, with autonomic and adaptive features, and open? One of the basic assumptions in the development of agreement technologies is that the components are independently developed and thus no a priori assumptions on their workings can be made. Correct interoperability needs to be based on a two step process: first, the establishment of explicit agreements among the entities and then the execution of those agreements. The generation of agreements requires techniques that cover the two fundamental aspects of potential disagreement: semantics and co-ordinated action, for instance, semantic alignment techniques to allow compo-

Fuzzy Logic Inference Applications in Road Traffic and Parking Space Management

In modern motoring, many factors are considered to realize driving convenience and achieving safety at a reasonable cost. A drive towards effective management of traffic and parking space allocation in urban centres using intelligent software applications is currently being developed and deployed as GPS enabled service to consumers in automobiles or smartphone applications for convenience, safety and economic benefits. Building a fuzzy logic inference for such applications may have numerous approaches such as algorithms in Pascal or C-languages and of course using an effective fuzzy logic toolbox. Referring to a case report based on IrisNet project analysis, in this paper Matlab fuzzy logic toolbox is used in developing an inference for managing traffic flow and parking allocation with generalized feature that is open for modification. Being that modifications can be done within any or all among the tool’s universe of discourse, increment in the number of membership functions and changing input and output variables etc, the work here is limited within changes at input and output variables and bases of universe of discourse. The process implications is shown as plotted by the toolbox in surface and rule views, implying that the inference is flexibly open for modifications to suit area of application within reasonable time frame no matter how complex. The travel time to the parking space being an output variable in the current inference is recommended to be substituted with distance to parking space as the former is believed to affect driving habits among motorist, whom may require the inference to as well cover other important locations such as nearest or cheapest gas station, hotels, hospitals etc.

The dynamic of professional knowledge utilized in software applications for process controlling

Main objective of the presented paper is the examination of the professional knowledge used in intelligent software applications for process controlling. It concerns in particular the user instruction and the realization of corresponding interaction as well as the interface design. Regular approach for service of the different user groups is evaluated and extended in means of flexibility in the time. The rules decisive for the user interaction with the application are outlined. They represent the interdependency between quality of professional knowledge to be utilized and user group characteristics alter in time. An application scenario for knowledge visualization is presented to show the practicability of the concept developed.

Guest Editorial: Special Section on Learning Systems for Science and Technology Education

Computer-based technology can significantly enhance science education and training, as well as shape both what and how people learn. With this special issue of the IEEE Transactions on Learning Technologies (TLT), we present contributions that address education and training in science and technology disciplines using computer-based technology innovations, with a particular emphasis on the development and application of intelligent software that supports conceptual understanding and high-order learning approaches. This special section includes six contributions. The first four papers focus on specific systems for learning topics in science and technology. Each contribution highlights a unique educational need and describes and argues for technology that has been developed to enable that learning. The systems have all been used and tested in real-world educational settings.

Architectural Pattern of Health Care System Using GSM Networks

Large-scale networked environments, such as the Internet, possess the characteristics of centralised data, centralised access and centralised control; this gives the user a powerful mechanism for building and integrating large repositories of centralised information from diverse resources set. However, a centralised network system with GSM Networks development for a hospital information systems or a health care information portal is still in its infancy. The shortcomings of the currently available tools have made the use of mobile devices more appealing. In mobile computing, the issues such as low bandwidth, high latency wireless Networks, loss or degradation of wireless connections, and network errors or failures need to be dealt with. Other issues to be addressed include system adaptability, reliability, robustness, extensibility, flexibility, and maintainability. GSM approach has emerged as the most viable approach for development of intelligent software applications for wireless mobile devices in a centralized environment, which gives higher band width of 900 MHz for transmission. The e-healthcare system that we have developed provides support for physicians, nurses, pharmacists and other healthcare professionals, as well as for patients and medical devices used to monitor patients. In this paper, we present the architecture and the demonstration prototype.

The development and clinical application of intelligent hypertension management software

The development and clinical application of intelligent hypertension management software

Formal driven prototyping approach for multiagent systems

Even if Multiagent Systems (MASs) are recognised as an appealing paradigm for designing many computer systems ranging from complex distributed systems to intelligent software applications, they are still difficult to engineer. A common point of MAS engineering methodologies is the production of different work products or models during the different phases. Each work product or model helps to progress towards an implementation of the system under development. Nevertheless, there are very few ways to ensure that the work products and models produced are validated against the requirements. The aim of this paper is to present a formal driven prototyping approach for MAS. This process provides a support for incremental specification leading to an executable model of the system being built. Indeed, this process is based upon a formal organisational framework which uses a formal notation, namely OZS. The process is illustrated through the specification of a multiagent architecture.

Commentary on: Simon, B., Dolog., P., Miklós, Z., Olmedilla, D. and Sintek, M. (2004). Conceptualising Smart Spaces for Learning

Abstract: A Smart Space for Learning (SSL) is a proposed software application system supporting access to individualized learning materials and experiences using Personal Learning Assistants (PLAs). PLAs are intelligent agent software applications that aid the learner in searching for relevant content across a distributed network. They hold the promise of harnessing the power of the network to break the cost barriers that have restricted learning environments to time- and location-dependent cohort groups. Using SSL, individual learners should be able to navigate their way through the large mass of materials available on the World Wide Web and build themselves a coherent and cohesive learning plan that is independent of time and place. Paper: Simon, B. et al, (2004) Conceptualising Smart Spaces for Learning. . Editors: Terry Anderson and Denise Whitelock.

Integrated Display for Supervisory Control of Space Operations

In recent years, intelligent software has been applied for monitoring and controlling space systems to reduce the workload of the crew and ground support personnel. The application of intelligent software to system control changes the human role in space operations. Instead of directly performing control tasks, humans now often supervise automated software performing control tasks. We have designed an integrated overview display supporting supervisory monitoring and control tasks. This design provides a view of control information integrated over time, supporting a supervisor in following a thread of operational information extending from the past into the future. It associates control activities with the resulting consequences of control on the environment and system configuration. And it provides a uniform way to access and display a heterogeneous set of archived information characterizing system control.