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Topic Review
Reconstructing Superquadrics from Intensity and Color Images
The task of reconstructing 3D scenes based on visual data represents a longstanding problem in computer vision. Common reconstruction approaches rely on the use of multiple volumetric primitives to describe complex objects. Superquadrics (a class of volumetric primitives) have shown great promise due to their ability to describe various shapes with only a few parameters. Research has shown that deep learning methods can be used to accurately reconstruct random superquadrics from both 3D point cloud data and simple depth images. Researchers extend these reconstruction methods to intensity and color images. 
  • 422
  • 09 Aug 2022
Topic Review
Low Rate DDoS Detection Techniques in Software-Defined Networks
Software-defined networking (SDN) is a new networking paradigm that provides centralized control, programmability, and a global view of topology in the controller. SDN is becoming more popular due to its high audibility, which also raises security and privacy concerns. SDN must be outfitted with the best security scheme to counter the evolving security attacks. A Distributed Denial-of-Service (DDoS) attack is a network attack that floods network links with illegitimate data using high-rate packet transmission. Illegitimate data traffic can overload network links, causing legitimate data to be dropped and network services to be unavailable. Low-rate Distributed Denial-of-Service (LDDoS) is a recent evolution of DDoS attack that has been emerged as one of the most serious vulnerabilities for the Internet, cloud computing platforms, the Internet of Things (IoT), and large data centers. Moreover, LDDoS attacks are more challenging to detect because this attack sends a large amount of illegitimate data that are disguised as legitimate traffic. Thus, traditional security mechanisms such as symmetric/asymmetric detection schemes that have been proposed to protect SDN from DDoS attacks may not be suitable or inefficient for detecting LDDoS attacks. 
  • 719
  • 08 Aug 2022
Topic Review
User Story Quality in Practice
User stories are widely used in Agile development as requirements. User stories have their origins in extreme programming (XP). Kent Beck, the founder of XP, stated that user stories were created to address the specific needs of software development, conducted by small teams in the face of changing and vague requirements.
  • 390
  • 08 Aug 2022
Topic Review
SBGTool v2.0: An Empirical Study
SBGTool v2.0 differs from SBGTool due to design changes made in response to teacher suggestions, the addition of sorting options to the dashboard table, the addition of a dropdown component to group the students into classrooms, and improvement in some visualizations. By applying SBGTool v2.0, teachers may compare the outcomes of individual students inside a classroom, determine which subjects are the most and least difficult over the period of a week or an academic year, identify the numbers of correct and incorrect responses for the most difficult and easiest subjects, categorize students into various groups based on their learning outcomes, discover the week with the most interactions for examining students’ engagement, and find the relationship between students’ activity and study success. 
  • 419
  • 08 Aug 2022
Topic Review
Corpus Statistics Empowered Document Classification
In natural language processing (NLP), document classification is an important task that relies on the proper thematic representation of the documents. Gaussian mixture-based clustering is widespread for capturing rich thematic semantics but ignores emphasizing potential terms in the corpus. Moreover, the soft clustering approach causes long-tail noise by putting every word into every cluster, which affects the natural thematic representation of documents and their proper classification. It is more challenging to capture semantic insights when dealing with short-length documents where word co-occurrence information is limited.
  • 677
  • 05 Aug 2022
Topic Review
Efficient Task Offloading in Multi-User Edge Computing
Task offloading is one of the most important issues in edge computing and has attracted continuous research attention in recent years. With task offloading, end devices can offload the entire task or only subtasks to the edge servers to meet the delay and energy requirements.
  • 894
  • 05 Aug 2022
Topic Review
Internet of Things and Blockchain Integration
The Internet of things model enables a world in which all of our everyday devices can be integrated and communicate with each other and their surroundings to gather and share data and simplify task implementation.
  • 573
  • 05 Aug 2022
Topic Review
Human Detection in Heavy Smoke Scenarios
The most dangerous factor in a fire scene is smoke and heat, especially smoke. How to locate people and guide them out of a heavy smoke environment will be the key to surviving an evacuation process. A variety of instruments have been studied that can be used in fire and smoky situations, including visible camera, kinetic depth sensor, LIDAR, night vision, IR camera, radar, and sonar.
  • 1.5K
  • 04 Aug 2022
Topic Review
Human-Robot Interaction
As in human–human interaction, several modalities can be used at once in human-robot interaction in social contexts. Vision, eye gaze, verbal dialogue, touch, and gestures are examples of modalities that can be used herein. In a social context, the intelligence that a robot display depends on the modalities it uses and each modality can have specific importance and effect on the human side of the interaction which translates into the degree of trust that the robot has. Moreover, the acceptance of robots in social interaction depends on their ability to express emotions and they require a proper design of emotional expressions to improve their likability and believability as multimodal interaction can enhance the engagement
  • 740
  • 04 Aug 2022
Topic Review
Human Activity Recognition Methods
Human activity recognition (HAR) can effectively improve the safety of the elderly at home. Many researchers have studied HAR from different aspects, such as sensors and algorithms. HAR methods can be divided into three categories based on the types of sensors: wearable devices, cameras, and millimeter-wave radars.
  • 1.2K
  • 04 Aug 2022
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