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Topic Review
Commonsense-Guided Inductive Relation Prediction with Dual Attention Mechanism
Inductive relationship prediction for knowledge graphs, as an important research topic, aims to predict missing relationships between unknown entities and many practical applications. Most of the existing approaches to this problem use closed subgraphs to extract features of target nodes for prediction; however, there is a tendency to ignore neighboring relationships outside the closed subgraphs, which leads to inaccurate predictions. In addition, they ignore the rich commonsense information that can help filter out less compelling results.
  • 854
  • 07 Mar 2024
Topic Review
KinectGaitNet
Gait recognition had gained a lot of attention in various research and industrial domains. These include remote surveillance, border control, medical rehabilitation, emotion detection from posture, fall detection, and sports training. The main advantages of identifying a person by their gait include unobtrusiveness, acceptance, and low costs. Researchers proposes a convolutional neural network KinectGaitNet for Kinect-based gait recognition. The 3D coordinates of each of the body joints over the gait cycle are transformed to create a unique input representation. The proposed KinectGaitNet is trained directly using the 3D input representation without the necessity of the handcrafted features. The KinectGaitNet design allows avoiding gait cycle resampling, and the residual learning method ensures high accuracy without the degradation problem.
  • 853
  • 20 Apr 2022
Topic Review
Cards Against Calamity Learning Game: Civics, Negotiation, Sustainability
Learning games for instruction constitute a progressively important and mutually universal challenge for academics, researchers, and software engineers worldwide. Gaming offers immersive space for interaction and co-creation of successful negotiation and conflict management, civic learning and sustainable development attributes in higher education and workplace context. 
  • 853
  • 16 Nov 2022
Topic Review
Vision-Based Human Action Recognition Field
Artificial intelligence’s rapid advancement has enabled various applications, including intelligent video surveillance systems, assisted living, and human–computer interaction. These applications often require one core task: video-based human action recognition.
  • 851
  • 23 Apr 2023
Topic Review
HVAC Data-Driven Maintenance
Buildings’ heating, ventilation, and air-conditioning (HVAC) systems account for significant global energy use. Proper maintenance can minimize their environmental footprint and enhance the quality of the indoor environment. The adoption of Internet of Things (IoT) sensors integrated into HVAC systems has paved the way for data-driven predictive maintenance (PdM) grounded in real-time operational metrics.
  • 851
  • 27 Oct 2023
Topic Review
Deep Learning Frameworks and Tools
Deep learning (DL) has been applied successfully in medical imaging such as reconstruction, classification, segmentation, and detection.
  • 845
  • 07 Feb 2024
Topic Review
Deep Learning Using Explainable Artificial Intelligence and Clustering
Explainable artificial intelligence (XAI) is a field of Artificial Intelligence (AI) that seeks to offer insights into black-box models and their predictions. Trust, performance, legal (regulation), and ethical considerations are some reasons researchers advocate for XAI.
  • 842
  • 23 Nov 2023
Topic Review
Application Profiling System Architecture
Along with the rise of cloud and edge computing has come a plethora of solutions that regard the deployment and operation of different types of applications in such environments. Infrastructure as a service (IaaS) providers offer a number of different hardware solutions to facilitate the needs of the growing number of distributed applications. It is critical in this landscape to be able to navigate and discover the best-suited infrastructure solution for the applications, taking into account not only the cost of operation but also the quality of service (QoS) required for any given application. The proposed solution has two main research developments: (a) the creation and optimisation of multidimensional vectors that represent the hardware usage profiles of an application, and (b) the assimilation of a machine learning classification algorithm, in order to create a system that can create hardware-agnostic profiles of a vast variety of containerised applications in terms of nature and computational needs and classify them to known benchmarks. Given that benchmarks are widely used to evaluate a system’s hardware capabilities, having a system that can help select which benchmarks best correlate to a given application can help an IaaS provider make a more informed decision or recommendation on the hardware solution, not in a broad sense, but based on the needs of a specific application.
  • 839
  • 20 Dec 2022
Topic Review
Cancer Metastasis Detection via Effective Contrastive Learning
The metastasis detection in lymph nodes via microscopic examination of H&E stained histopathological images is one of the most crucial diagnostic procedures for breast cancer staging. The manual analysis is extremely labor-intensive and time-consuming because of complexities and diversities of histopathological images. Deep learning has been utilized in automatic cancer metastasis detection in recent years. The success of supervised deep learning is credited to a large labeled dataset, which is hard to obtain in medical image analysis. Contrastive learning, a branch of self-supervised learning, can help in this aspect through introducing an advanced strategy to learn discriminative feature representations from unlabeled images.
  • 837
  • 13 Sep 2022
Topic Review
Federated Learning-Based IoT Big Data Management Approach
Federated Learning (FL) is poised to play an essential role in extending the Internet of Things (IoT) and Big Data ecosystems by enabling entities to harness the computational power of private devices, thus safeguarding user data privacy. Despite its benefits, FL is vulnerable to multiple types of assaults, including label-flipping and covert attacks. The label-flipping attack specifically targets the central model by manipulating its decisions for a specific class, which can result in biased or incorrect results.
  • 837
  • 29 Dec 2023
Topic Review
Gallbladder Diseases
The gallbladder (GB) is a tiny pouch and a hollow organ located beneath the liver. Its primary role is to temporarily store bile. Bile is a fluid formed by the liver, which is used to aid digestion.  
  • 836
  • 25 May 2023
Topic Review
Healthcare Sustainability: Hospitalization Rate Forecasting
Monitoring and forecasting hospitalization rates are of essential significance to public health systems in understanding and managing overall healthcare deliveries and strategizing long-term sustainability. Early-stage prediction of hospitalization rates is crucial to meet the medical needs of numerous patients during emerging epidemic diseases such as COVID-19. Nevertheless, this is a challenging task due to insufficient data and experience. In addition, relevant existing work neglects or fails to exploit the extensive contribution of external factors such as news, policies, and geolocations. Herein, researchers demonstrate the significant relationship between hospitalization rates and COVID-19 infection cases. A transfer learning architecture with dynamic location-aware sentiment and semantic analysis (TLSS) is adapted to a new application scenario: hospitalization rate prediction during COVID-19. This architecture learns and transfers general transmission patterns of existing epidemic diseases to predict hospitalization rates during COVID-19. Researchers combine the learned knowledge with time series features and news sentiment and semantic features in a dynamic propagation process. Extensive experiments are conducted to compare the proposed approach with several state-of-the-art machine learning methods with different lead times of ground truth. The results show that TLSS exhibits outstanding predictive performance for hospitalization rates. Thus, it provides advanced artificial intelligence (AI) techniques for supporting decision-making in healthcare sustainability.
  • 836
  • 24 Nov 2023
Topic Review
Optimizing Straw Bale Retrieval Process
During a baling operation, the operator of the baler should decide when and where to drop the bales in the field to facilitate later retrieval of the bales for transport out of the field. Manually determining the time and place to drop a bale creates extra workload on the operator and may not result in the optimum drop location for the subsequent front loader and transport unit. Therefore, there is a need for a tool that can support operators during this decision process. The key objective of this study is to find the optimal traversal sequence of fieldwork tracks to be followed by the baler and bale retriever to minimize the non-working driving distance in the field. Two optimization processes are considered for this problem. Firstly, finding the optimal sequence of fieldwork tracks considering the constraints of the problem such as the capacity of the baler and the straw yield map of the field. Secondly, finding the optimal location and number of bales to drop in the field. A simulation model is developed to calculate all the non-productive traversal distances by baler and bale retrieval in the field. In a case study, the collected positional and temporal data from the baling process related to a sample field were considered. The output of the simulation model was compared with the conventional method applied by the operators. The results show that application of the proposed method can increase efficiency by 12.9% in comparison with the conventional method with edited data where the random movements (due to re-baling, turns in the middle of the swath, reversing, etc.) were removed from the data set. 
  • 834
  • 22 Jul 2021
Topic Review
Underwater Sensor Networks
The issue of limited energy resources is crucial for underwater wireless sensor networks (UWSNs) because these networks operate in remote and harsh environments where access to power sources is limited. Overcoming the energy constraints is necessary to ensure the long-term functionality and sustainability of UWSN, enabling continuous data collection and communication for various applications such as environmental monitoring and surveillance.
  • 834
  • 21 Aug 2023
Topic Review
Knowledge Reasoning
A knowledge graph (KG) organizes knowledge as a set of interlinked triples, and a triple ((head entity, relation, tail entity), simply represented as (h, r, t)) indicates the fact that two entities have a certain relation. The availability of formalized and rich structured knowledge has emerged as a valuable resource in facilitating various downstream tasks, such as question answering and recommender systems. Although KGs such as DBpedia, Freebase, and NELL contain large amounts of entities, relations, and triples, they are far from complete, which is an urgent issue for their broad application. To address this, researchers have introduced the concept of knowledge graph completion (KGC), which has garnered increasing interest. It utilizes knowledge reasoning techniques to automatically discover new facts based on existing ones in a KG.
  • 833
  • 12 Oct 2023
Topic Review
DetectFormer
Object detection plays a vital role in autonomous driving systems, and the accurate detection of surrounding objects can ensure the safe driving of vehicles. A category-assisted transformer object detector called DetectFormer for autonomous driving. The proposed object detector can achieve better accuracy compared with the baseline. Specifically, ClassDecoder is assisted by proposal categories and global information from the Global Extract Encoder (GEE) to improve the category sensitivity and detection performance. This fits the distribution of object categories in specific scene backgrounds and the connection between objects and the image context. Data augmentation is used to improve robustness and attention mechanism added in backbone network to extract channel-wise spatial features and direction information.
  • 832
  • 15 Jul 2022
Topic Review
Greylisting
Greylisting is a method of defending e-mail users against spam. A mail transfer agent (MTA) using greylisting will "temporarily reject" any email from a sender it does not recognize. If the mail is legitimate, the originating server will try again after a delay, and if sufficient time has elapsed, the email will be accepted.
  • 831
  • 14 Oct 2022
Topic Review
Small Object Detection and Traffic Signs Detection
The detection of traffic signs is easily affected by changes in the weather, partial occlusion, and light intensity, which increases the number of potential safety hazards in practical applications of autonomous driving.
  • 831
  • 14 Jun 2023
Topic Review
Global Trends in Cancer Nanotechnology
This study presents a new way to investigate comprehensive trends in cancer nanotechnology research in different countries, institutions, and journals providing critical insights to prevention, diagnosis, and therapy. This paper applies the qualitative method of bibliometric analysis on cancer nanotechnology using the PubMed database during the years 2000-2021. Inspired by hybrid medical models and content-based and bibliometric features for machine learning models, our results show cancer nanotechnology studies have expanded exponentially since 2010. The highest production of articles in cancer nanotechnology is mainly from US institutions, with several countries notably the USA, China, UK, India, and Iran as concentrated focal points as centers of cancer nanotechnology research, especially in the last five years. The analysis shows the greatest overlap between nanotechnology and DNA, RNA, iron oxide or mesoporous silica, breast cancer, and cancer diagnosis and cancer treatment. Moreover, more than 50% of information related to the keywords, authors, institutions, journals, and countries are considerably investigated in the form of publications from the top 100 journals. This study has the potentials to provide past and current lines of research that can unmask comprehensive trends in cancer nanotechnology, key research topics, or pmost productive countries and authors in the field.
  • 830
  • 10 Sep 2021
Topic Review
Deep Learning-Based Depression Detection from Social Media
Depression is a prevalent mental health condition that affects a substantial number of individuals worldwide [1]. It is characterized by persistent feelings of sadness, loss of interest, and impaired functioning, leading to a significant decline in overall well-being and quality of life.
  • 830
  • 17 Nov 2023
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