The global agricultural sector confronts significant obstacles such as population growth, climate change, and natural disasters, which negatively impact food production pose a threat to security. In response these challenges, the integration of IoT AI technologies emerges promising solution, facilitating data-driven decision-making, optimizing resource allocation, enhancing monitoring control systems in operations address challenges promote sustainable farming practices. This study examines...

Data fusion is a prevalent technique for assembling imperfect raw data coming from multiple sources to capture reliable and accurate information. Dempster–Shafer evidence theory one of useful methodologies in the uncertain multisource The existing literature lacks thorough comprehensive review recent advances Dempster– Shafer fusion. Therefore, state art has be surveyed gain insight into how beneficial it evolved over time. In this paper, we first provide methods based on its extensions,...

To mitigate the effects of lack IoT standardization, including scalability, reusability, and interoperability, we propose a domain-agnostic monitoring control framework (MCF) for design implementation Internet Things (IoT) systems. We created building blocks layers five-layer architecture built MCF's subsystems (monitoring subsystem, computing subsystem). demonstrated utilization MCF in real-world use-case smart agriculture, using off-the-shelf sensors actuators an open-source code. As user...

Hyperparameter optimization is a fundamental part of Auto Machine Learning (AutoML) and it has been widely researched in recent years; however, still remains as one the main challenges this area. Motivated by need faster more accurate hyperparameter algorithms we developed HyperBRKGA, new population-based approach for optimization. HyperBRKGA combines Biased Random Key Genetic Algorithm with an Exploitation Method order to search space efficiently than other commonly used algorithms, such...

Intelligent applications in several areas increasingly rely on big data solutions to improve their efficiency, but the processing and management of incur high costs. Although cloud-computing-based offer a promising solution provide scalable abundant resources, current cloud-based platforms do not properly address latency, privacy, bandwidth consumption challenges that arise when sending large volumes user cloud. Computing edge fog layers is quickly emerging as an extension cloud computing...

Machine learning has recently become a popular algorithm in building reliable intrusion detection systems (IDSs). However, most of the models are static and trained using datasets containing all targeted intrusions. If new intrusions emerge, these must be retrained old to classify accurately. In real-world situations, threats continuously appear. Therefore, machine algorithms used for IDSs should have ability learn incrementally when emerge. To solve this issue, we propose T-DFNN. T-DFNN is...

As most of the Internet Things (IoT) applications are event-driven, emergence serverless computing paradigm, which is a natural fit for event-driven applications, promising to host multi-tenant IoT applications. Furthermore, increasing resource capability low-cost edge and fog devices provides an opportunity take advantage resources available leads edge-fog-cloud continuum, can conduct processing across entire continuum. To identify necessary adaptations we integrate paradigm in each layer...

In this paper, we try to reduce the amount of control traffic optimized link state routing protocol (OLSR). OLSR is a proactive for mobile ad-hoc networks (MANETs). known well as low protocol, since it adopts multipoint relays (MPRs). MPRs concept significantly reduces number broadcast messages during flooding process. Although MPR optimal each node transmit its all two hop neighbors, show there are still redundant which can be piggybacked with other in dense networks. This redundancy caused...

Social network services (SNS) are more and popular. People increasingly accustomed to express their opinions on SNS in two ways: (1) product reviews online shopping sites (2) posts, comments, tweets, chats social sites. text classification is challenging due various natural language phenomena, such as spelling mistakes variations, polysemy, contextual ambiguity semantic variations. In this paper, we propose a novel deep learning architecture called Hybrid Convolutional Neural Networks...

Incremental learning is a promising algorithm for creating an adaptive network intrusion detection system (IDS) model. In contrast with batch models, incremental models can be retrained easily when new data emerge. Moreover, some such as the Hoeffding Tree model, only using latest training data. This advantage appealing because computer networks produce enormous amounts of every day. Using detecting ever-growing intrusions save computational resources while preserving performance models....

Semantic text similarity (STS) uses specific test collections as its performance evaluation measurement. The consist of pairs with the same meaning even though in different form. existence is scarce compared information retrieval (IR) collections. This paper investigates possibility to reuse IR for STS tasks. Text are derived from relevant pair Latent semantic analysis (LSA) and explicit (ESA) evaluate Glasgow's collections, which provided by ACM SIGIR community. Jaccard index measures...

Vehicular ad hoc networks (VANETs) are the specific class of Mobile (MANETs). Since vehicles tend to move in a high speed, network topology is rapidly changed. Thus vehicle's connectivity problem one interesting issues VANETs. Ad on-demand multipath distance vector (AOMDV) extended version (AODV). AOMDV designed overcome due highly dynamic topology. It provides for data packets delivery from source destination. Although outperforms AODV packet ratio, AOMDV's establishment and maintenance...

This paper presents a strategy to improve positioning estimation from low-cost Inertia Measurement Unit (IMU) sensor and Global Positioning System (GPS) for apron vehicle localization. IMU provides raw acceleration values its attitude, while GPS geodetic position, velocity, heading course values. Fusion result both sensors believed could comply Advanced-Surface Movement Guidance Control (A-SMGCS) standard with less economical cost. Within this paper, we propose graded Kalman filter method...

The performance of a machine learning algorithm is highly dependent on its hyperparameters. However, hyperparameter optimization not trivial task as it problem-specific. difficulty rises when coupled with larger number hyperparameters resulting in high search space dimensions. common understanding seems to be that the only done limited Indeed, have been commonly utilized optimization. This study investigates role by using genetic (GA) main method for convolutional neural network (CNN)....

Hyperparameters and architecture greatly influence the performance of convolutional neural networks (CNNs); therefore, their optimization is important to obtain desired results. One state-of-the-art methods achieve this use neuroevolution that utilizes a genetic algorithm (GA) optimize CNN. However, GA often trapped into local optimum resulting in premature convergence. In study, we propose an approach called "diversity-guided algorithm-convolutional network (DGGA-CNN)" uses adaptive...

In semiconductor manufacturing, it is required to detect anomalies which cause expensive defects. recent years, Generative Adversarial Networks (GANs) have played a big role in anomaly detection. This study aims by analyzing sensor data using GAN when multivariate time series of are given. Our could cannot be detected visually. Experimental results indicated that an attention mechanism tell us important sensors detecting anomalies.

Fidelity plays an important role in quantum information processing, which provides a basic scale for comparing two states. At present, one of the most commonly used fidelities is Uhlmann-Jozsa (U-J) fidelity. However, U-J fidelity needs to calculate square root matrix, not trivial case large or infinite density matrices. Moreover, measure overlap, has limitations some cases and cannot reflect similarity between states well. Therefore, novel called Tanimoto coefficient (QTC) proposed this...

In vehicle dead reckoning or positioning systems, an inertial measurement unit (IMU) sensor has important role to provide acceleration and orientation of the vehicle. The from IMU accelerometer is used calculate velocity vehicle, then it estimates vehicle's distance traveled time. However, suffers external noises such as vibrations (generated engine, alternator, compressor, etc) road noises. This paper delivers deep analysis focuses on how handle error vibrations. A filter method proposed by...

It is useful if a bug tracking system can detect report duplication with unfinished reports. To investigate the feasibility, we study relations between accuracy of duplicate detection using features extracted from textual information in reports and number words this paper. The results show that increasing to be used over certain does not affect very much. also indicate had better use about 100 80 Eclipse OpenOffice, respectively, because may have many wrong candidates more than numbers. We...