Human-centric Computing and Information Sciences

http://link.springer.com/journal/13673

List of Papers (Total 213)

Enhanced ground segmentation method for Lidar point clouds in human-centric autonomous robot systems

Ground segmentation is an important step for any autonomous and remote-controlled systems. After separating ground and nonground parts, many works such as object tracking and 3D reconstruction can be performed. In this paper, we propose an efficient method for segmenting the ground data of point clouds acquired from multi-channel Lidar sensors. The goal of this study is to...

Reducing the effects of DoS attacks in software defined networks using parallel flow installation

Software defined networking (SDN) is becoming more and more popular due to its key features, such as monitoring, fine-grained control, flexibility and scalability. The centralized control of SDN makes it vulnerable to various types of attacks, e.g., flooding, spoofing, and denial of service (DoS). Among these attacks, DoS attack has the most severe impact because it degrades the...

Attack detection in water distribution systems using machine learning

The threat to critical water system infrastructure has increased in recent years as is evident from the increasing number of reported attacks against these systems. Preventative security mechanisms are often not enough to keep attackers out so a second layer of security in the form of intrusion detection is paramount in order to limit the damage of successful attacks. In this...

On construction of a cloud storage system with heterogeneous software-defined storage technologies

With the rapid development of networks and Information technologies, cloud computing is not only becoming popular, the types of cloud services available are also increasing. Through cloud services, users can upload their requirements via the Internet to the cloud environment and receive responses following post-processing, for example, with cloud storage services. Software...

Hybrid case-base maintenance approach for modeling large scale case-based reasoning systems

Case-based reasoning (CBR) is a nature inspired paradigm of machine learning capable to continuously learn from the past experience. Each newly solved problem and its corresponding solution is retained in its central knowledge repository called case-base. Withρ the regular use of the CBR system, the case-base cardinality keeps on growing. It results into performance bottleneck as...

Compatibility enhancement and performance measurement for socket interface with PCIe interconnections

Today the key technology of high-performance computing systems is the emergence of interconnect technology that makes multiple computers into one computer cluster. This technique is a general method in which each constituent node processes its own operation and communicates with different nodes. Therefore, a high-performance network has been required. InfiniBand and Gigabit...

Infrared bundle adjusting and clustering method for head-mounted display and Leap Motion calibration

Leap Motion has become widely used due to its ability to recognize intuitive hand gestures or accurate finger positions. Attaching a Leap Motion to a virtual reality head-mounted display (VR HMD) is highly interoperable with virtual objects in virtual reality. However, it is difficult for a virtual reality application to identify the accurate position where the Leap Motion is...

An audio attention computational model based on information entropy of two channels and exponential moving average

The main down-top attention model usually uses some characteristics of audio signal to extract the auditory saliency map at present. But existing audio attention computational model based image saliency mostly doesn’t consider the continuity and attenuation mechanism of the human brain on paying attention to some occurred events in our real environment. To address these issues...

Random forest and WiFi fingerprint-based indoor location recognition system using smart watch

Various technologies such as WiFi, Bluetooth, and RFID are being used to provide indoor location-based services (LBS). In particular, a WiFi base using a WiFi AP already installed in an indoor space is widely applied, and the importance of indoor location recognition using deep running has emerged. In this study, we propose a WiFi-based indoor location recognition system using a...

Visual analytics for collaborative human-machine confidence in human-centric active learning tasks

Active machine learning is a human-centric paradigm that leverages a small labelled dataset to build an initial weak classifier, that can then be improved over time through human-machine collaboration. As new unlabelled samples are observed, the machine can either provide a prediction, or query a human ‘oracle’ when the machine is not confident in its prediction. Of course, just...

A symbolic model checking approach in formal verification of distributed systems

Model checking is an influential method to verify complex interactions, concurrent and distributed systems. Model checking constructs a behavioral model of the system using formal concepts such as operations, states, events and actions. The model checkers suffer some weaknesses such as state space explosion problem that has high memory consumption and time complexity. Also...

Performance prediction of data streams on high-performance architecture

Worldwide sensor streams are expanding continuously with unbounded velocity in volume, and for this acceleration, there is an adaptation of large stream data processing system from the homogeneous to rack-scale architecture which makes serious concern in the domain of workload optimization, scheduling, and resource management algorithms. Our proposed framework is based on...

IoT + AR: pervasive and augmented environments for “Digi-log” shopping experience

The current bare Internet of Things (IoT) infrastructure has recently been extended to include smarter and more effective user interactions. Individual or meaningful sets and groups of IoT objects can be imbued with data and/or content in a distributed manner and efficiently utilized by the client. This distribution makes it possible to scale and customize interaction techniques...

An Efficient movie recommendation algorithm based on improved k-clique

The amount of movie has increased to become more congested; therefore, to find a movie what users are looking for through the existing technologies are very hard. For this reason, the users want a system that can suggest the movie requirement to them and the best technology about these is the recommendation system. However, the most recommendation system is using collaborative...

Improved user similarity computation for finding friends in your location

Recommender systems are most often used to predict possible ratings that a user would assign to items, in order to find and propose items of possible interest to each user. In our work, we are interested in a system that will analyze user preferences in order to find and connect people with common interests that happen to be in the same geographical area, i.e., a “friend...

Investigating the influence of online interpersonal interaction on purchase intention based on stimulus-organism-reaction model

Based on the stimulus-organism-reaction model, we study the direct effects of the three interpersonal attraction factors (perceived similarity, perceived familiarity, and perceived expertise) on purchase intention in the social commerce era, as well as the mediating roles of the normative and informational influence of reference groups in the above relationship. We apply...

A multi-hop graph-based approach for an energy-efficient routing protocol in wireless sensor networks

Emerging technological advances in wireless communication and networking have led to the design of large scale networks and small sensor units with minimal power requirements and multifunctional processing. Though energy harvesting technologies are improving, the energy of sensors remains a scarce resource when designing routing protocols between sensor nodes and base station...

Classifying 3D objects in LiDAR point clouds with a back-propagation neural network

Due to object recognition accuracy limitations, unmanned ground vehicles (UGVs) must perceive their environments for local path planning and object avoidance. To gather high-precision information about the UGV’s surroundings, Light Detection and Ranging (LiDAR) is frequently used to collect large-scale point clouds. However, the complex spatial features of these clouds, such as...

The design of an indirect method for the human presence monitoring in the intelligent building

This article describes the design and verification of the indirect method of predicting the course of CO2 concentration (ppm) from the measured temperature variables Tindoor (°C) and the relative humidity rHindoor (%) and the temperature Toutdoor (°C) using the Artificial Neural Network (ANN) with the Bayesian Regulation Method (BRM) for monitoring the presence of people in the...

A survey of simulation provenance systems: modeling, capturing, querying, visualization, and advanced utilization

Research and education through computer simulation has been actively conducted in various scientific and engineering fields including computational science engineering. Accordingly, there have been a lot of attentions paid to actively utilize provenance information regarding such computer simulations, particularly conducted on high-performance computing and storage resources. In...

AMACE: agent based multi-criterions adaptation in cloud environment

Efficient resource management in dynamic cloud computing is receiving more and more attentions. Many works are still ongoing, since federated cloud computing is an open environment. We present in this paper a flexible model, new cloud operators can join the federation or leave it. The model integrates interactions between broker agents organization, permitting a multi-criterion...

Improving clustering performance using independent component analysis and unsupervised feature learning

ObjectiveTo provide a parsimonious clustering pipeline that provides comparable performance to deep learning-based clustering methods, but without using deep learning algorithms, such as autoencoders.Materials and methodsClustering was performed on six benchmark datasets, consisting of five image datasets used in object, face, digit recognition tasks (COIL20, COIL100, CMU-PIE...

Personality classification based on profiles of social networks’ users and the five-factor model of personality

Online social networks have become demanded ways for users to show themselves and connect and share information with each other among these social networks. Facebook is the most popular social network. Personality recognition is one of the new challenges between investigators in social networks. This paper presents a hypothesis that users by similar personality are expected to...

Li-Fi based on security cloud framework for future IT environment

In the new era of the Internet of Things (IoT), all information related to the environment, things and humans is connected to networks. Humans, too, can be considered an integral part of the IoT ecosystem. The growing human-centricity of IoT applications raises the need greater dynamicity, heterogeneity, and scalability in future IoT systems. Recently, the IoT and cloud computing...