Online Pose Estimation and Tracking Approach with Siamese Region Proposal Network
Human pose estimation and tracking are to accurately identify and locate the positions of human joints in the video. It is a computer vision task which is of great significance for human motion recognition, behavior understanding and scene analysis. There has been remarkable progress on human pose estimation in recent years. However, more researches are needed for human pose tracking especially for online tracking. In this paper, a framework, called PoseSRPN, is proposed for online single-person pose estimation and tracking. We use Siamese network attaching a pose estimation branch to incorporate Single-person Pose Tracking (SPT) and Visual Object Tracking (VOT) into one framework. The pose estimation branch has a simple network structure that replaces the complex upsampling and convolution network structure with deconvolution. By augmenting the loss of fully convolutional Siamese network with the pose estimation task, pose estimation and tracking can be trained in one stage. Once trained, PoseSRPN only relies on a single bounding box initialization and producing human joints location. The experimental results show that while maintaining the good accuracy of pose estimation on COCO and PoseTrack datasets, the proposed method achieves a speed of 59 frame/s, which is superior to other pose tracking frameworks.
Vision Based People Tracking System
In this paper we present the design and the implementation of a target tracking system where the target is set to be a moving person in a video sequence. The system can be applied easily as a vision system for mobile robot. The system is composed of two major parts the first is the detection of the person in the video frame using the SVM learning machine based on the “HOG” descriptors. The second part is the tracking of a moving person it’s done by using a combination of the Kalman filter and a modified version of the Camshift tracking algorithm by adding the target motion feature to the color feature, the experimental results had shown that the new algorithm had overcame the traditional Camshift algorithm in robustness and in case of occlusion.
Dependability Tools in Multi-Agent Support for Failures Analysis of Computer Networks
During their activity, all systems must be operational without failures and in this context, the dependability concept is essential avoiding disruption of their function. As computer networks are systems with the same requirements of dependability, this article deals with an analysis of failures for a computer network. The proposed approach integrates specific tools of the plat-form KB3, usually applied in dependability studies of industrial systems. The methodology is supported by a multi-agent system formed by six agents grouped in three meta agents, dealing with two levels. The first level concerns a modeling step through a conceptual agent and a generating agent. The conceptual agent is dedicated to the building of the knowledge base from the system specifications written in the FIGARO language. The generating agent allows producing automatically both the structural model and a dependability model of the system. The second level, the simulation, shows the effects of the failures of the system through a simulation agent. The approach validation is obtained by its application on a specific computer network, giving an analysis of failures through their effects for the considered network.
Single Ion Transport with a Single-Layer Graphene Nanopore
Graphene material has found tremendous applications
in water desalination, DNA sequencing and energy storage. Multiple
nanopores are etched to create opening for water desalination and
energy storage applications. The nanopores created are of the order
of 3-5 nm allowing multiple ions to transport through the pore. In
this paper, we present for the first time, molecular dynamics study of
single ion transport, where only one ion passes through the graphene
nanopore. The diameter of the graphene nanopore is of the same
order as the hydration layers formed around each ion. Analogous to
single electron transport resulting from ionic transport is observed
for the first time. The current-voltage characteristics of such a device
are similar to single electron transport in quantum dots. The current
is blocked until a critical voltage, as the ions are trapped inside a
hydration shell. The trapped ions have a high energy barrier compared
to the applied input electrical voltage, preventing the ion to break free
from the hydration shell. This region is called “Coulomb blockade
region”. In this region, we observe zero transport of ions inside the
nanopore. However, when the electrical voltage is beyond the critical
voltage, the ion has sufficient energy to break free from the energy
barrier created by the hydration shell to enter into the pore. Thus, the
input voltage can control the transport of the ion inside the nanopore.
The device therefore acts as a binary storage unit, storing 0 when
no ion passes through the pore and storing 1 when a single ion
passes through the pore. We therefore postulate that the device can
be used for fluidic computing applications in chemistry and biology,
mimicking a computer. Furthermore, the trapped ion stores a finite
charge in the Coulomb blockade region; hence the device also acts
a super capacitor.
Time-Domain Simulations of the Coupled Dynamics of Surface Riding Wave Energy Converter
A surface riding (SR) wave energy converter (WEC) is designed and its feasibility and performance are numerically simulated by the author-developed floater-mooring-magnet-electromagnetics fully-coupled dynamic analysis computer program. The biggest advantage of the SR-WEC is that the performance is equally effective even in low sea states and its structural robustness is greatly improved by simply riding along the wave surface compared to other existing WECs. By the numerical simulations and actuator testing, it is clearly demonstrated that the concept works and through the optimization process, its efficiency can be improved.
A Brain Controlled Robotic Gait Trainer for Neurorehabilitation
This paper discusses a brain controlled robotic gait
trainer for neurorehabilitation of Spinal Cord Injury (SCI) patients.
Patients suffering from Spinal Cord Injuries (SCI) become unable to
execute motion control of their lower proximities due to degeneration
of spinal cord neurons. The presented approach can help SCI patients
in neuro-rehabilitation training by directly translating patient motor
imagery into walkers motion commands and thus bypassing spinal
cord neurons completely. A non-invasive EEG based brain-computer
interface is used for capturing patient neural activity. For signal
processing and classification, an open source software (OpenVibe)
is used. Classifiers categorize the patient motor imagery (MI) into
a specific set of commands that are further translated into walker
motion commands. The robotic walker also employs fall detection
for ensuring safety of patient during gait training and can act as a
support for SCI patients. The gait trainer is tested with subjects, and
satisfactory results were achieved.
The Paralinguistic Function of Emojis in Twitter Communication
In response to the dearth of information about emoji use for different purposes in different settings, this paper investigates the paralinguistic function of emojis within Twitter communication in the United States. To conduct this investigation, the Twitter feeds from 16 population centers spread throughout the United States were collected from the Twitter public API. One hundred tweets were collected from each population center, totaling to 1,600 tweets. Tweets containing emojis were next extracted using the “emot” Python package; these were then analyzed via the IBM Watson API Natural Language Understanding module to identify the topics discussed. A manual content analysis was then conducted to ascertain the paralinguistic and emotional features of the emojis used in these tweets. We present our characterization of emoji usage in Twitter and discuss implications for the design of Twitter and other text-based communication tools.
The Use of Different Methodological Approaches to Teaching Mathematics at Secondary Level
The article describes methods of preparation of future teachers that includes the entire diversity of traditional and computer-oriented methodological approaches. The authors reveal how, in the specific educational environment, a teacher can choose the most effective combination of educational technologies based on the nature of the learning task. The key conditions that determine such a choice are that the methodological approach corresponds to the specificity of the problem being solved and that it is also responsive to the individual characteristics of the students. The article refers to the training of students in the proper use of mathematical electronic tools for educational purposes. The preparation of future mathematics teachers should be a step-by-step process, building on specific examples. At the first stage, students optimally solve problems aided by electronic means of teaching. At the second stage, the main emphasis is on modeling lessons. At the third stage, students develop and implement strategies in the study of one of the topics within a school mathematics curriculum. The article also recommended the implementation of this strategy in preparation of future teachers and stated the possible benefits.
A Topology for High Voltage Gain Half-Bridge Z-Source Inverter with Low Voltage Stress on Capacitors
In this paper, a topology for high voltage gain half-bridge z-source inverter with low voltage stress on capacitors is proposed. The proposed inverter has only one impedance network. It can generate symmetric and asymmetric voltages with different magnitudes during both half-cycles. By selecting the duty cycle it can also produce conventional half-bridge inverter characteristics. It is used in special applications like, electrochemical and electro plating applications. Calculations of voltage ripple of capacitors, capacitors voltage stress inductors current ripple are presented. The proposed topology is simulated using PSCAD software and the simulated values are compared with the theoretical values.
Cybersecurity Protection Structures: The Case of Lesotho
The Internet brings increasing use of Information and Communications Technology (ICT) services and facilities. Consequently, new computing paradigms emerge to provide services over the Internet. Although there are several benefits stemming from these services, they pose several risks inherited from the Internet. For example, cybercrime, identity theft, malware etc. To thwart these risks, this paper proposes a holistic approach. This approach involves multidisciplinary interactions. The paper proposes a top-down and bottom-up approach to deal with cyber security concerns in developing countries. These concerns range from regulatory and legislative areas, cyber awareness, research and development, technical dimensions etc. The main focus areas are highlighted and a cybersecurity model solution is proposed. The paper concludes by combining all relevant solutions into a proposed cybersecurity model to assist developing countries in enhancing a cyber-safe environment to instill and promote a culture of cybersecurity.
Analysis of Image Segmentation Techniques for Diagnosis of Dental Caries in X-ray Images
Early diagnosis of dental caries is essential for maintaining dental health. In this paper, method for diagnosis of dental caries is proposed using Laplacian filter, adaptive thresholding, texture analysis and Support Vector Machine (SVM) classifier. Analysis of the proposed method is compared with Otsu thresholding, watershed segmentation and active contouring method. Adaptive thresholding has comparatively better performance with 96.9% accuracy and 96.1% precision. The results are validated using statistical method, two-way ANOVA, at significant level of 5%, that shows the interaction of proposed method on performance parameter measures are significant. Hence the proposed technique could be used for detection of dental caries in automated computer assisted diagnosis system.
A Motion Dictionary to Real-Time Recognition of Sign Language Alphabet Using Dynamic Time Warping and Artificial Neural Network
Computacional recognition of sign languages aims to
allow a greater social and digital inclusion of deaf people through
interpretation of their language by computer. This article presents
a model of recognition of two of global parameters from sign
languages; hand configurations and hand movements. Hand motion
is captured through an infrared technology and its joints are built
into a virtual three-dimensional space. A Multilayer Perceptron
Neural Network (MLP) was used to classify hand configurations and
Dynamic Time Warping (DWT) recognizes hand motion. Beyond
of the method of sign recognition, we provide a dataset of
hand configurations and motion capture built with help of fluent
professionals in sign languages. Despite this technology can be
used to translate any sign from any signs dictionary, Brazilian
Sign Language (Libras) was used as case study. Finally, the model
presented in this paper achieved a recognition rate of 80.4%.
Monitoring Co-Creation: A Survey of Lithuanian Urban Communities
In this paper, we conduct a systematic survey of urban communities in Lithuania to evaluate their potential to co-create collective intelligence or “civic intelligence” applying Digital Co-creation Index methodology that includes different socio-technological indicators. Civic intelligence is a form of collective intelligence that refers to the group’s capacity to perceive societal problems and to address them effectively. The research focuses on evaluation of diverse organizational designs that increase efficient collective performance. The current scientific project advanced the state of the art by evaluating the basic preconditions in the urban communities through which the collective intelligence is being co-created under the systemic manner. The research subject is the “bottom up” digital enabled urban platforms, initiated by Lithuanian public organizations, civic movements or business entities. The web-based monitoring results obtained by applying a social indices calculation methodology and Pearson correlation analysis provided the information about the potential and limits of the urban communities and what possible changes need to be implemented to overcome the limitations.
Classification of Computer Generated Images from Photographic Images Using Convolutional Neural Networks
This paper presents a deep-learning mechanism for classifying computer generated images and photographic images. The proposed method accounts for a convolutional layer capable of automatically learning correlation between neighbouring pixels. In the current form, Convolutional Neural Network (CNN) will learn features based on an image's content instead of the structural features of the image. The layer is particularly designed to subdue an image's content and robustly learn the sensor pattern noise features (usually inherited from image processing in a camera) as well as the statistical properties of images. The paper was assessed on latest natural and computer generated images, and it was concluded that it performs better than the current state of the art methods.
Optimized Brain Computer Interface System for Unspoken Speech Recognition: Role of Wernicke Area
In this paper, we propose an optimized brain computer
interface (BCI) system for unspoken speech recognition, based on
the fact that the constructions of unspoken words rely strongly on the
Wernicke area, situated in the temporal lobe. Our BCI system has four
modules: (i) the EEG Acquisition module based on a non-invasive
headset with 14 electrodes; (ii) the Preprocessing module to remove
noise and artifacts, using the Common Average Reference method;
(iii) the Features Extraction module, using Wavelet Packet Transform
(WPT); (iv) the Classification module based on a one-hidden layer
artificial neural network. The present study consists of comparing
the recognition accuracy of 5 Arabic words, when using all the
headset electrodes or only the 4 electrodes situated near the Wernicke
area, as well as the selection effect of the subbands produced by
the WPT module. After applying the articial neural network on the
produced database, we obtain, on the test dataset, an accuracy of
83.4% with all the electrodes and all the subbands of 8 levels of the
WPT decomposition. However, by using only the 4 electrodes near
Wernicke Area and the 6 middle subbands of the WPT, we obtain
a high reduction of the dataset size, equal to approximately 19% of
the total dataset, with 67.5% of accuracy rate. This reduction appears
particularly important to improve the design of a low cost and simple
to use BCI, trained for several words.
Digital Image Forensics: Discovering the History of Digital Images
Digital multimedia contents such as image, video, and audio can be tampered easily due to the availability of powerful editing softwares. Multimedia forensics is devoted to analyze these contents by using various digital forensic techniques in order to validate their authenticity. Digital image forensics is dedicated to investigate the reliability of digital images by analyzing the integrity of data and by reconstructing the historical information of an image related to its acquisition phase. In this paper, a survey is carried out on the forgery detection by considering the most recent and promising digital image forensic techniques.
Teaching Computer Programming to Diverse Students: A Comparative, Mixed-Methods, Classroom Research Study
Lack of motivation and interest is a serious obstacle to students’ learning computing skills. A need exists for a knowledge base on effective pedagogy and curricula to teach computer programming. This paper presents results from research evaluating a six-year project designed to teach complex concepts in computer programming collaboratively, while supporting students to continue developing their computer thinking and related coding skills individually. Utilizing a quasi-experimental, mixed methods design, the pedagogical approaches and methods were assessed in two contrasting groups of students with different socioeconomic status, gender, and age composition. Analyses of quantitative data from Likert-scale surveys and an evaluation rubric, combined with qualitative data from reflective writing exercises and semi-structured interviews yielded convincing evidence of the project’s success at both teaching and inspiring students.
A Holographic Infotainment System for Connected and Driverless Cars: An Exploratory Study of Gesture Based Interaction
In this paper, an interactive in-car interface called HoloDash is presented. It is intended to provide information and infotainment in both autonomous vehicles and ‘connected cars’, vehicles equipped with Internet access via cellular services. The research focuses on the development of interactive avatars for this system and its gesture-based control system. This is a case study for the development of a possible human-centred means of presenting a connected or autonomous vehicle’s On-Board Diagnostics through a projected ‘holographic’ infotainment system. This system is termed a Holographic Human Vehicle Interface (HHIV), as it utilises a dashboard projection unit and gesture detection. The research also examines the suitability for gestures in an automotive environment, given that it might be used in both driver-controlled and driverless vehicles. Using Human Centred Design methods, questions were posed to test subjects and preferences discovered in terms of the gesture interface and the user experience for passengers within the vehicle. These affirm the benefits of this mode of visual communication for both connected and driverless cars.
MITOS-RCNN: Mitotic Figure Detection in Breast Cancer Histopathology Images Using Region Based Convolutional Neural Networks
Studies estimate that there will be 266,120 new cases
of invasive breast cancer and 40,920 breast cancer induced deaths
in the year of 2018 alone. Despite the pervasiveness of this
affliction, the current process to obtain an accurate breast cancer
prognosis is tedious and time consuming. It usually requires a
trained pathologist to manually examine histopathological images and
identify the features that characterize various cancer severity levels.
We propose MITOS-RCNN: a region based convolutional neural
network (RCNN) geared for small object detection to accurately
grade one of the three factors that characterize tumor belligerence
described by the Nottingham Grading System: mitotic count. Other
computational approaches to mitotic figure counting and detection
do not demonstrate ample recall or precision to be clinically viable.
Our models outperformed all previous participants in the ICPR 2012
challenge, the AMIDA 2013 challenge and the MITOS-ATYPIA-14
challenge along with recently published works. Our model achieved
an F- measure score of 0.955, a 6.11% improvement in accuracy from
the most accurate of the previously proposed models.
Automotive Emotions: An Investigation of Their Natures, Frequencies of Occurrence and Causes
Technological and sociological developments in the automotive sector are shifting the focus of design towards developing a better understanding of driver needs, desires and emotions. Human centred design methods are being more frequently applied to automotive research, including the use of systems to detect human emotions in real-time. One method for a non-contact measurement of emotion with low intrusiveness is Facial-Expression Analysis (FEA). This paper describes a research study investigating emotional responses of 22 participants in a naturalistic driving environment by applying a multi-method approach. The research explored the possibility to investigate emotional responses and their frequencies during naturalistic driving through real-time FEA. Observational analysis was conducted to assign causes to the collected emotional responses. In total, 730 emotional responses were measured in the collective study time of 440 minutes. Causes were assigned to 92% of the measured emotional responses. This research establishes and validates a methodology for the study of emotions and their causes in the driving environment through which systems and factors causing positive and negative emotional effects can be identified.
Automated Heart Sound Classification from Unsegmented Phonocardiogram Signals Using Time Frequency Features
Cardiologists perform cardiac auscultation to detect
abnormalities in heart sounds. Since accurate auscultation is
a crucial first step in screening patients with heart diseases,
there is a need to develop computer-aided detection/diagnosis
(CAD) systems to assist cardiologists in interpreting heart sounds
and provide second opinions. In this paper different algorithms
are implemented for automated heart sound classification using
unsegmented phonocardiogram (PCG) signals. Support vector
machine (SVM), artificial neural network (ANN) and cartesian
genetic programming evolved artificial neural network (CGPANN)
without the application of any segmentation algorithm has been
explored in this study. The signals are first pre-processed to remove
any unwanted frequencies. Both time and frequency domain features
are then extracted for training the different models. The different
algorithms are tested in multiple scenarios and their strengths and
weaknesses are discussed. Results indicate that SVM outperforms
the rest with an accuracy of 73.64%.
The Effect of Computer-Mediated vs. Face-to-Face Instruction on L2 Pragmatics: A Meta-Analysis
This paper reports the results of a meta-analysis of studies on the effects of instruction mode on learning second language pragmatics during the last decade (from 2006 to 2016). After establishing related inclusion/ exclusion criteria, 39 published studies were retrieved and included in the present meta-analysis. Studies were later coded for face-to-face and computer-assisted mode of instruction. Statistical procedures were applied to obtain effect sizes. It was found that Computer-Assisted-Language-Learning studies generated larger effects than Face-to-Face instruction.
Attempt to Reuse Used-PCs as Distributed Storage
Storage for storing data is indispensable. If a storage
capacity becomes insufficient, we can increase its capacity by adding
new disks. It is, however, difficult to add a new disk when a
budget is not enough. On the other hand, there are many unused
idle resources such as used personal computers despite those use
value. In order to solve those problems, used personal computers can
be reused as storage. In this paper, we attempt to reuse used-PCs
as a distributed storage. First, we list up the characteristics of
used-PCs and design a storage system that utilizes its characteristics.
Next, we experimentally implement an auto-construction system
that automatically constructs a distributed storage environment in
Animation of Objects on the Website by Application of CSS3 Language
Scientific work analytically explores and demonstrates techniques that can animate objects and geometric characters using CSS3 language by applying proper formatting and positioning of elements. This paper presents examples of optimum application of the CSS3 descriptive language when generating general web animations (e.g., billiards and movement of geometric characters, etc.). The paper presents analytically, the optimal development and animation design with the frames within which the animated objects are. The originally developed content is based on the upgrading of existing CSS3 descriptive language animations with more complex syntax and project-oriented work. The purpose of the developed animations is to provide an overview of the interactive features of CSS3 descriptive language design for computer games and the animation of important analytical data based on the web view. It has been analytically demonstrated that CSS3 as a descriptive language allows inserting of various multimedia elements into websites for public and internal sites.
Impact of Ownership Structure on Provision of Staff and Infrastructure for Implementing Computer Aided Design Curriculum in Universities in South-East Nigeria
Instruction towards acquiring skills in the use of Computer Aided Design technologies has become a vital part of architectural education curriculum in the digital era. Its implementation, however, requires deployment of extra resources to build new infrastructure, acquisition and maintenance of new equipment, retraining of staff and recruitment of new ones who are knowledgeable in this area. This study sought to examine the impact that ownership structure of Nigerian universities had on provision of staff and infrastructure for implementing computer aided design curriculum with a view to developing a framework for the evaluation for appropriate implementation by the institutions. Survey research design was employed. The focus was on departments of architecture in universities in south-east Nigeria accredited by the National Universities Commission. Data were obtained in the areas of infrastructure and personnel for CAD implementation. A multi-stage stratified random sampling method was adopted. The first stage of stratification involved the accredited departments. Random sampling by balloting was then carried out. At the second stage, sampling size formulae was applied to obtain respondents’ number. For data analysis, analysis of variance tool for testing differences of means was used. With ρ < 0.5, the study found that there was significant difference between private-funded, state-funded and federal-funded departments of architecture in the provision of personnel and infrastructure. The implications of these findings were that for successful implementation leading to attainment of CAD proficiency to occur in every institution regardless of ownership structure, minimum evaluation guidelines needed to be set. A regular comparison of implementation in institutions was recommended as a means of rating performance. This will inform better interaction with those who consistently show weakness to challenge them towards improvement.
Hand Motion and Gesture Control of Laboratory Test Equipment Using the Leap Motion Controller
In this paper, the design and development of a system to provide hand motion and gesture control of laboratory test equipment is considered and discussed. The Leap Motion controller is used to provide an input to control a laboratory power supply as part of an electronic circuit experiment. By suitable hand motions and gestures, control of the power supply is provided remotely and without the need to physically touch the equipment used. As such, it provides an alternative manner in which to control electronic equipment via a PC and is considered here within the field of human computer interaction (HCI).
The Use of Computer-Aided Design in Small Contractors in a Local Area of Korea
A survey of small-size contractors in Jeju was conducted to investigate college graduate's computer-aided design (CAD) competence. Most of small-size contractors use CAD software to review and update drawings submitted from an architect. This research analyzed the curriculum of the architectural engineering in several national universities. The CAD classes have 4 or 6 hours per week and use AutoCAD primarily. This paper proposes that a CAD class needs 6 hours per week, 2D drawing is the main theme in the curriculum, and exercises to make 3D models are also included in the CAD class. An improved method, for example Internet cafe and real time feedbacks using smartphones, to evaluate the reports and exercise results is necessary.
The Design Process of an Interactive Seat for Improving Workplace Productivity
Creative industries’ workers are becoming more prominent as countries move towards intellectual-based economies. Consequently, the nature and essence of the workplace needs to be reconfigured so that creativity and productivity can be better promoted at these spaces. Using a multidisciplinary approach and a user-centered methodology, combining product design, electronic engineering, software and human-computer interaction, we have designed and developed a new seat that uses embedded sensors and actuators to increase the overall well-being of its users, their productivity and their creativity. Our contribution focuses on the parameters that most affect the user’s work on these kinds of spaces, which are, according to our study, noise and temperature. We describe the design process for a new interactive seat targeted at improving workspace productivity.
SENSE-SEAT: Improving Creativity and Productivity through the Redesign of a Multisensory Technological Office Chair
The current trend of organizations offering their workers open-office spaces and co-working offices has been primed for stimulating teamwork and collaboration. However, this is not always valid as these kinds of spaces bring other types of challenges that compromise workers productivity and creativity. We present an approach for improving creativity and productivity at the workspace by redesigning an office chair that incorporates subtle technological elements that help users focus, relax and being more productive and creative. This sheds light on how we can better design interactive furniture for such popular contexts, as we develop this new chair through a multidisciplinary approach using ergonomics, interior design, interaction design, hardware and software engineering and psychology.
A Design-Based Approach to Developing a Mobile Learning System
This paper presents technologically innovative and scalable mobile learning solution within the SCOLLAm project (“Opening up education through Seamless and COLLAborative mobile learning on tablet computers”). The main research method applied during the development of the SCOLLAm mobile learning system is design-based research. It assumes iterative refinement of the system guided by collaboration between researches and practitioners. Following the identification of requirements, a multiplatform mobile learning system SCOLLAm [in]Form was developed. Several experiments were designed and conducted in the first and second grade of elementary school. SCOLLAm [in]Form system was used to design learning activities for math classes during which students practice calculation. System refinements were based on experience and interaction data gathered during class observations. In addition to implemented improvements, the data were used to outline possible improvements and deficiencies of the system that should be addressed in the next phase of the SCOLLAm [in]Form development.