Miracle-dz/UniFAR-FTUs huggingface dataset:
The Detection of Pedestrian Crossing Behaviour

The pedestrian is regarded to be one of the most vulnerable road users. Non-verbal communication between drivers and pedestrians seems to play an important role in the mitigation of collisions. The emergence of autonomous vehicles in traffic in the near future presses the need to investigate objective measures related to pedestrian crossing behaviour and the efficacy of communication devices on autonomous vehicles that might replace the nonverbal signals of the human driver. In order to objectively investigate the efficacy of communication devices on autonomous vehicles, 24 participants in this study were immersed in a virtual reality environment, via the use of an Oculus Rift and an Xsens Link motion tracking device. In this virtual reality environment, participants were presented with 18 series of autonomous vehicles. Each series represented one unique combination of independent variables and contained a total of five vehicles. The vehicles were either equipped with a Text display or Frontal Braking Lights that indicated the yielding intentions of the vehicle, or were without any external interface. Furthermore, the inter-vehicular distance between the second and the third vehicle in the series varied between 20, 30 or 40 meters. The participants were instructed to cross the road onto the zebra crossing in the virtual environment when they deemed it was safe to do so. The experiment was designed in such a way that the only crossing opportunity for the participants was between the second and third vehicle when the third vehicles yielded. The road crossing decision of the participants, operationalized by the objective measure of their forward gait velocity, was earlier in time when there was either a Text display or Frontal Braking Lights present on the third vehicle in the series, when the inter-vehicular distance between the second and third vehicle was 20 meters and the third and subsequent vehicles yielded. Congruently, the self-reported ability of participants to predict the behaviour of the oncoming vehicles was significantly better when the third vehicle had a Text display compared to when there was no external interface. However, no significant difference in self-reported ability to predict the behaviour of the oncoming vehicles was found for the Frontal Braking Lights. Furthermore, the forward gait velocity was significantly greater in the presence of a Text display compared to when there was no external interface present for the condition in which the inter-vehicular distance between the second and third vehicle was 30 meters and the third and subsequent vehicles yielded. This work shows that besides the current standard of subjective validation by pedestrians of external human-machine interfaces on autonomous vehicles these interfaces can objectively be validated through the recording and differentiation of body motions.
Insect-Inspired Visual Navigation On-Board an Autonomous Robot: Real-World Routes Encoded in a Single Layer Network

Insect-Inspired models of visual navigation, that operate by scanning for familiar views of the world, have been shown to be capable of robust route navigation in simulation. These familiarity-based navigation algorithms operate by training an artificial neural network (ANN) with views from a training route, so that it can then output a familiarity score for any new view. In this paper we show that such an algorithm – with all computation performed on a small low-power robot – is capable of delivering reliable direction information along real-world outdoor routes, even when scenes contain few local landmarks and have high-levels of noise (from variable lighting and terrain). Indeed, routes can be precisely recapitulated and we show that the required computation and storage does not increase with the number of training views. Thus the ANN provides a compact representation of the knowledge needed to traverse a route. In fact, rather than losing information, there are instances where the use of an ANN ameliorates the problems of sub optimal paths caused by tortuous training routes. Our results suggest the feasibility of familiarity-based navigation for long-range autonomous visual homing.
Performance Limits Study of Stencil Codes on Modern GPGPUs

We study the performance limits of different algorithmic approaches to the implementation of a sample problem of wave equation solution with a cross stencil scheme. With this, we aim to find the highest limit of the achievable performance efficiency for stencil computing. To estimate the limits, we use a quantitative Roofline model to make a thorough analysis of the performance bottlenecks and develop the model further to account for the latency of different levels of GPU memory. These estimates provide an incentive to use spatial and temporal blocking algorithms. Thus, we study stepwise, domain decomposition, and domain decomposition with halo algorithms in that order. The knowledge of the limit incites the motivation to optimize the implementation. This led to the analysis of the block synchronization methods in CUDA, which is also provided in the text. After all optimizations, we have achieved 90% of the peak performance, which amounts to more than 1 trillion cell updates per second on one consumer level GPU device.
Without Oxygen no Burning Candle

Objective. Under certain circumstances, the results of multiple investigations – particularly, rigorously-designed trials, can be summarized by systematic reviews and meta-analyses. However, the results of properly conducted meta-analyses can but need not be stronger than single investigations, if (publication) bias is not considered to a necessary extent. Methods. In assessing the significance of publication bias due to study design simple to handle statistical measures for quantifying publication bias are developed and discussed which can be used as a characteristic of a meta-analysis. In addition, these measures may permit comparisons of publication biases between different meta-analyses. Results. Various properties and the performance of the new measures of publication bias are studied and illustrated using simulations and clearly described thought experiments. As a result, individual studies can be reviewed with a higher degree of certainty. Conclusions. Publication bias due to study design is a serious problem in scientific research, which can affect the validity and generalization of conclusions. The index of unfairness and the index of independence are of use to quantify publication bias and to improve the quality of systematic reviews and meta-analyses. Keywords: study design, study type, measuring technique, publication bias
BIM LOD for facility management tasks

Building information modeling (BIM) widely adopted in design and construction phase of the buildings, holds undeveloped possibilities for supporting Facility Management (FM) tasks in Operation & Maintenance (O&M) phase. The purpose of this paper is to define appropriate Level of Development (LOD) for different FM areas in order to enable FM-BIM for existing buildings during O&M phase. To do so, the customized LOD have been defined by existing literature review and facility experts. Then the required properties for each FM areas are implemented in two case studies. Conclusion demonstrated that more than 60 percent of properties defined as LOD500 are unnecessary to execute FM tasks. Besides, the elements which required more properties are related to the categories of Services including Mechanical, Electrical and Plumbing (MEP) and fire systems and they need specific LOD to leverage BIM in O&M phase.
Content Delivery Networks as a Service (CDNaaS)

The goal of this thesis is to study and evaluate the role a Virtual CDNs in improving the end-users QoE while saving on service providers’ costs and service availability. First, we present the design and implementation of an architecture for on-demand deployment of a vCDN infrastructure over a telco cloud. Second, we propose different algorithms for solving the Virtual Network Function (VNF) placement problem. We propose a polynomialtime heuristic algorithms to solve a relaxed version of the problem’s assumptions, we show experimentally that the derived solutions are close to the optimal. Finally, we study and evaluate solutions for the placement of VNF at the edge, by moving from the traditional central cloud to the edge one. We have also shown how our method can reduce delays and still provide a highly-available service.
A Study on Digital Watermarking Techniques

Digital watermarking was introduced as a result of rapid advancement of networked multimedia systems. It had been developed to enforce copyright technologies for cover of copyright possession. This technology is first used for still images however recently they need been developed for different multimedia objects like audio, video etc. Watermarking, that belong to the information hiding field, has seen plenty of research interest. There's a lot of work begin conducted in numerous branches in this field. The image watermarking techniques might divide on the idea of domain like spatial domain or transform domain or on the basis of wavelets. The copyright protection, capacity, security, strength etc are a number of the necessary factors that are taken in account whereas the watermarking system is intended. This paper aims to produce a detailed survey of all watermarking techniques specially focuses on image watermarking types and its applications in today’s world.
Planar Orientation Control and Torque Maximization Using a Swarm With Global Inputs

This paper studies the torque applied by a large number of particles on a long aspect-ratio rod. The particles are all pushed in the same direction by a global signal. We calculate the force and torque generated by three canonical position distributions of a swarm: uniform, triangular, and normal. The model shows that for a pivoted rod the uniform distribution produces the maximum torque for small swarm standard deviations, but the normal distribution maximizes torque for large standard deviations. In the simulation, we use these results to design proportional-derivative controllers to orient rigid objects. We conclude showing the experiments with up to 97 hardware robots to evaluate our theory in practice. Note to Practitioners—Workspace clutter can prevent large steered particles from being able to manipulate objects and maneuver, while smaller particles can pass through this clutter. A small particle produces less force than a big particle, so to produce the same force, more are needed. Their small size makes onboard sensing and computation hard. Therefore, they are often controlled by a shared control input. Manipulating objects with a swarm of particles actuated by a shared control input is a challenging task, but it is even more challenging when the object’s final orientation needs to be set. Many applications including assembly and delivery require a specific orientation of the object. Torque control with only one steered particle is easy: maximize torque by pushing on the object at a location as far from the pivot point as possible. However, a swarm of particles contributes force at different places on the object. This paper studies how to maximize torque using a swarm of particles shaped in three canonical position distributions. The work is limited by assuming each particle touching the object transmits equal force, but hardware experiments validate the necessity to consider swarm distribution when applying torque. In the future work, we will investigate how stochastic contacts between particles effects force and torque transmission, and examine control in 3-D space.
REARRANGE BASED ON IDENTITY AND APPLICATION IN EMAIL IN THE CLOUD

Within a CIBPRE system, a trusted key generation center initializes the CIBPRE machine parameters and generates private keys for users. To securely share files to multiple recipients, a sender can secure the files by using the recipients' identities and file discussion conditions. If the sender later wishes to talk about some files related to a similar condition together with other receivers, the sender can delegate a tagged re-encrypted encryption key using the condition for the proxy, as well as the parameters to create the encryption secret of re-archiving. It is beyond the original recipients of these files. Conditional PREs, based on identity and transmission PREs, are suggested for flexible applications. CIBPRE allows a sender to secure a note to multiple receivers by indicating the identities of those receivers, and can also delegate a re-encryption encryption response to a proxy to convert the first encrypted text into a substitute for a different group of recipients. Recipients by CPRE, IPRE and BPRE, this document proposes a flexible primitive known as conditional emission based on PRE identity and formalizes its semantic security. In addition, the re-encryption encryption key can be connected with a condition so that only the corresponding encryption texts can be encrypted again, allowing the initial sender to enforce access control of their remote encryption texts in a very detailed. Finally, we show a credit card application on our CIBPRE to protect the cloud email system that is beneficial to existing secure email systems according to very good privacy protocol or file-based encryption identity.
On Sexual Selection in the Presence of Multiple Costly Displays

Sexual selection is a powerful yet poorly understood evolutionary force. Research into sexual selection, whether biological, computational, or mathematical, has tended to take a top-down approach studying complex natural systems. Many simplifying assumptions must be made in order to make these systems tractable, but it is unclear if these simplifications result in a system which still represents natural ecological and evolutionary dynamics. Here, we take a bottom-up approach in which we construct simple computational systems from subsets of biologically plausible components and focus on examining the underlying dynamics resulting from the interactions of those components. We use this method to investigate sexual selection in general and the sexy sons theory in particular. The minimally necessary components are therefore genomes, genome-determined displays and preferences, and a process capable of overseeing parent selection and mating. We demonstrate the efficacy of our approach (i.e we observe the evolution of female preference) and provide support for sexy sons theory, including illustrating the oscillatory behavior that developed in the presence of multiple costly display traits.
SCIENTOMETRICS-BASED STUDY OF COMPUTER SCIENCE AND INFORMATION SYSTEMS RESEARCH COMMUNITY MACRO LEVEL PROFILES

This paper examines the current state and evolution of Computer Science (CS) and Information Systems (IS) research communities for the period of 2008 to 2019 by analysing Web of Science (WoS) core collection records. In order to compare and examine research outputs, the study period was divided into two time-periods. The first period included articles published between 2008 and 2013 and the second period included articles published between 2014 and 2019. Several analyses are presented in the scope of scientometrics regarding the (a) countries (b) historical occurrence-time (c) institutions (d) author collaboration (e) study topics-keywords (f) journals. This paper provides meta-analysis in different areas. We believe that our analysis results will shed a light for each area as well as interaction and intersection between both areas. As IS discipline and researchers we need to understand these intersections and interactions as well as understanding current trends in both disciplines.
Study on Observing the Evolution of Blockchain from the Perspective of Participatory Design

—There are many opinions that the credible exchange of data will be at the heart of many processes during the coming fourth industrial revolution. For this reason, in finance, insurance, and logistics, blockchain technology is regarded as the next huge disruptive force. Up close, the state of the entire blockchain domain is not as rosy as it seems. There are many problems with schema replication, with inferior or slightly modified schema replication versions emerging in an endless stream. Why technologists and managers with the best intentions cannot bring a better experience to the world? Few existing blockchain platforms have been successful, but what are the reasons for their success? The charm of blockchain attracts unlimited capital and technology investment and triggers a series of emotional reactions and public discussions. How do these events affect the world in turn? There are many developers and leaders who are trying to challenge the status quo and innovate. Some of them are committed to shaping the scene and designing the interfaces of blockchain applications, while others are bent on trying to influence the current social functioning system. They do this work for the purpose of rationalizing the foundations of trust in finance or other business, thereby improving people's quality of life. However, the results are often far from the original intentions. Regarding the blockchain events occurring between 2009 and 2019 as an experiment in participatory design, this paper analyzes the characteristics and trends of the times, the community's response, social discussions, and application examples. Finally, it is concluded that network applications based on the blockchain will be further developed, the corresponding legal system should be improved faster, and the human spirit of the contract needs to be updated and further improved so as to strive to become masters of the times.
Joint Transmitter-Receiver Spatial Modulation Design via Minimum Euclidean Distance Maximization

Joint transmitter–receiver spatial modulation (JSM) is an appealing transmission scheme in the spatial modulation family, where transmit diversity, receive diversity, and multiplexing gain are achieved simultaneously. However, the conventional JSM technique is neither spectrum efficient nor antenna efficient due to its limited candidates of bit-to-antenna mapping. In this paper, we propose a novel JSM approach that involves more mapping candidates to relax the implementation constraint and achieve better reliability. The proposed JSM scheme maximizes the minimum Euclidean distance (MED) between the received signals of different antenna mappings by optimizing the antenna selection and the power allocation over the transmit antennas, named MED-JSM. In particular, an optimal closed-form power allocation solution is derived when there are two receive antennas. For more receive antennas, a lower bound of the minimum Euclidean distance is derived, and a corresponding lower bound-approaching power allocation algorithm is proposed accordingly. Then, the proposed power allocation algorithm and antenna selection are used in a hybrid manner to further enhance the system reliability. Since the optimal MED-JSM requires an exhaustive search over all the received signals, we propose a suboptimal scheme with reduced computational complexity, which shrinks the search space via the Rayleigh–Ritz theorem. Numerical results show that the proposed MED-JSM outperforms the conventional JSM schemes in system’s reliability.
Development of Predictive Emissions Monitoring System Using Open Source Machine Learning Library – Keras: A Case Study on a Cogeneration Unit

The study provides an overview of Predictive Emissions Monitoring System’s (PEMS) research, application, installation, and regulatory framework as well as develops predictive models for NOx emissions from a natural gas fired cogeneration unit using an open source machine learning library, Keras, and open source programming languages, Python and R. Nine neural network based predictive models were trained with 12 086 examples and tested with 3020 examples. The neural network-based models use eight process parameters as inputs to predict NOx emissions. All models meet the regulatory requirements for precision. The best model (32-64-64-64) has four hidden layers and uses the Nadam method for optimization. The best model has a mean absolute error of 0.5982, r-value of 0.9451, and a difference of 0.14% between the measured and predicted emission values using the test dataset. The study demonstrated the feasibility of using open source machine learning library in PEMS development. It also provides guidance to facility operators to develop their own PEMS models for monitoring emissions.
Application health monitoring for extreme‐scale resiliency using cooperative fault management

Resiliency is and will be a critical factor in determining scientific productivity on current and exascale supercomputers, and beyond. Applications oblivious to and incapable of handling transient soft and hard errors could waste supercomputing resources or, worse, yield misleading scientific insights. We introduce a novel application‐driven silent error detection and recovery strategy based on application health monitoring. Our methodology uses application output that follows known patterns, as indicators of an application's health and knowledge that violation of these patterns could be indication of faults. Information from system monitors that report hardware and software health status is used to corroborate faults. Collectively, this information is used by a fault coordinator agent to take preventive and corrective measures by applying computational steering to an application between checkpoints. This cooperative fault management system uses the Fault Tolerance Backplane as a communication channel. The benefits of this framework are demonstrated with two real application case studies, molecular dynamics, and quantum chemistry simulations, on scalable clusters with simulated memory and I/O corruptions. The developed approach is general and can be easily applied to other applications.
AN ESTIMATING FLOOR REGION ALGORITHM BASED ON IMAGE SEGMENTATION USING FPGA FOR SMART ROVERS

By far most of the floor regions detection algorithms are still dependent on the depth or other additional sensors that consume more power relatively and increase the total weigh for smart land rovers. In this paper, a new framework that enable to estimate floor regions in single image for Unmanned Ground Vehicle (UGV) robots is presented. In general case, the cluttered indoor surroundings such as patterned floors, shadows and reflections, those surroundings are very difficult to differentiate floor regions. The proposed algorithm combines extracting surface texture characteristic with specific geometric area is able to find out from object boundary, and through SVM to distinguish between floor and non-floor regions. In experimental results, public MIT Scene dataset and indoor database were selected to verify the detection accuracy. The proposed algorithm accuracy can reach up to 94.72% in average without any other sensors for assistant.
Improving security and performance by implementing FS Algorithm in distributed cloud

The distributed file system is used to store a large number of files. The availability of the file is considered as the main factor for the availability of the system. The availability of the system is based on the retrieval time of the file. Metadata servers are separated from the data server and the replication of metadata is being implemented in the distributed file system to increase the availability. But there is a security issue in replication of metadata in a single server. When whole data is in sequential order if a single server gets hacked or failure occurs the entire data will be lost from the server. To overcome this problem, apply FS Algorithm. The scope of the paper is to Detach and reproduce methodology: divide a file into fragments, and replicate the fragmented data over the cloud node in a shuffling order.