OpenRaiser/Intern-Atlas huggingface dataset:
$Laoco\ddot{o}n$: Scalable and Portable Receipt-free E-voting Protocol without Untappable Channels
Venue: arXiv cs.CR 2019
Year: 2019

Vote-buying and voter-coercion are the impending threats when deploying remote online voting into large scale elections. With a policy of carrot and stick, it will encourage voters to deviate from honest voting strategy and spoil the democratic election. To deal with this problem, many voting protocols proposed their solutions with the notion of receipt-freeness. However, existing receipt-free voting protocols either rely on some impractical assumptions as untappable communication channel, or are burden with heavy voter-side computation and quadratic tallying complexity. In this paper, we present $Laoco\ddot{o}n$, a brand new cryptographic voting protocol which is practical and light-weight to be deployed in large scale online elections. By taking advantage of proxy re-encryption, our protocol can defend vote-buying attacks. Furthermore, we introduce a new property, candidate-adaptiveness, in electronic voting which refers to as every candidate knows the real-time vote number towards himself, while he knows nothing about others, nor he buys votes. We prove the correctness of our protocol and evaluate the performance with experimental results. Finally we advance some open problems which will be coped in our future work.
Parallel and Memory-limited Algorithms for Optimal Task Scheduling Using a Duplicate-Free State-Space
Venue: arXiv cs.DC 2019
Year: 2019

The problem of task scheduling with communication delays is strongly NP-hard. State-space search algorithms such as A* have been shown to be a promising approach to solving small to medium sized instances optimally. A recently proposed state-space model for task scheduling, known as Allocation-Ordering (AO), allows state-space search methods to be applied without the need for previously necessary duplicate avoidance mechanisms, and resulted in significantly improved A* performance. The property of a duplicate-free state space also holds particular promise for memory limited search algorithms, such as depth-first branch-and-bound (DFBnB), and parallel search algorithms. This paper investigates and proposes such algorithms for the AO model and, for comparison, the older Exhaustive List Scheduling (ELS) state-space model. Our extensive evaluation shows that AO gives a clear advantage to DFBnB and allows greater scalability for parallel search algorithms.
Coded Distributed Tracking
Venue: arXiv cs.IT 2019
Year: 2019

We consider the problem of tracking the state of a process that evolves over time in a distributed setting, with multiple observers each observing parts of the state, which is a fundamental information processing problem with a wide range of applications. We propose a cloud-assisted scheme where the tracking is performed over the cloud. In particular, to provide timely and accurate updates, and alleviate the straggler problem of cloud computing, we propose a coded distributed computing approach where coded observations are distributed over multiple workers. The proposed scheme is based on a coded version of the Kalman filter that operates on data encoded with an erasure correcting code, such that the state can be estimated from partial updates computed by a subset of the workers. We apply the proposed scheme to the problem of tracking multiple vehicles. We show that replication achieves significantly higher accuracy than the corresponding uncoded scheme. The use of maximum distance separable (MDS) codes further improves accuracy for larger update intervals. In both cases, the proposed scheme approaches the accuracy of an ideal centralized scheme when the update interval is large enough. Finally, we observe a trade-off between age-of-information and estimation accuracy for MDS codes.
Selection Combining Scheme over Non-identically Distributed Fisher-Snedecor $\mathcal{F}$ Fading Channels
Venue: arXiv cs.IT 2019
Year: 2019

In this paper, the performance of the selection combining (SC) scheme over Fisher-Snedecor $\mathcal{F}$ fading channels with independent and non-identically distributed (i.n.i.d.) branches is analysed. The probability density function (PDF) and the moment generating function (MGF) of the maximum i.n.i.d. Fisher-Snedecor $\mathcal{F}$ variates are derived first in terms of the multivariate Fox's $H$-function that has been efficiently implemented in the technical literature by various software codes. Based on this, the average bit error probability (ABEP) and the average channel capacity (ACC) of SC diversity with i.n.i.d. receivers are investigated. Moreover, we analyse the performance of the energy detection that is widely employed to perform the spectrum sensing in cognitive radio networks via deriving the average detection probability (ADP) and the average area under the receiver operating characteristics curve (AUC). To validate our analysis, the numerical results are affirmed by the Monte Carlo simulations.
Saliency difference based objective evaluation method for a superimposed screen of the HUD with various background
Venue: arXiv cs.HC 2019
Year: 2019

The head-up display (HUD) is an emerging device which can project information on a transparent screen. The HUD has been used in airplanes and vehicles, and it is usually placed in front of the operator's view. In the case of the vehicle, the driver can see not only various information on the HUD but also the backgrounds (driving environment) through the HUD. However, the projected information on the HUD may interfere with the colors in the background because the HUD is transparent. For example, a red message on the HUD will be less noticeable when there is an overlap between it and the red brake light from the front vehicle. As the first step to solve this issue, how to evaluate the mutual interference between the information on the HUD and backgrounds is important. Therefore, this paper proposes a method to evaluate the mutual interference based on saliency. It can be evaluated by comparing the HUD part cut from a saliency map of a measured image with the HUD image.
Monocular 3D Object Detection via Geometric Reasoning on Keypoints
Venue: arXiv cs.CV 2019
Year: 2019

Monocular 3D object detection is well-known to be a challenging vision task due to the loss of depth information; attempts to recover depth using separate image-only approaches lead to unstable and noisy depth estimates, harming 3D detections. In this paper, we propose a novel keypoint-based approach for 3D object detection and localization from a single RGB image. We build our multi-branch model around 2D keypoint detection in images and complement it with a conceptually simple geometric reasoning method. Our network performs in an end-to-end manner, simultaneously and interdependently estimating 2D characteristics, such as 2D bounding boxes, keypoints, and orientation, along with full 3D pose in the scene. We fuse the outputs of distinct branches, applying a reprojection consistency loss during training. The experimental evaluation on the challenging KITTI dataset benchmark demonstrates that our network achieves state-of-the-art results among other monocular 3D detectors.
Scratchy: A Lightweight Modular Autonomous Robot for Robotic Competitions
Venue: arXiv cs.RO 2019
Year: 2019

We present Scratchy---a modular, lightweight robot built for low budget competition attendances. Its base is mainly built with standard 4040 aluminium profiles and the robot is driven by four mecanum wheels on brushless DC motors. In combination with a laser range finder we use estimated odometry -- which is calculated by encoders -- for creating maps using a particle filter. A RGB-D camera is utilized for object detection and pose estimation. Additionally, there is the option to use a 6-DOF arm to grip objects from an estimated pose or generally for manipulation tasks. The robot can be assembled in less than one hour and fits into two pieces of hand luggage or one bigger suitcase. Therefore, it provides a huge advantage for student teams that participate in robot competitions like the European Robotics League or RoboCup. Thus, this keeps the funding required for participation, which is often a big hurdle for student teams to overcome, low. The software and additional hardware descriptions are available under: https://github.com/homer-robotics/scratchy.
Efficient Ladder-style DenseNets for Semantic Segmentation of Large Images
Venue: arXiv cs.CV 2019
Year: 2019

Recent progress of deep image classification models has provided great potential to improve state-of-the-art performance in related computer vision tasks. However, the transition to semantic segmentation is hampered by strict memory limitations of contemporary GPUs. The extent of feature map caching required by convolutional backprop poses significant challenges even for moderately sized Pascal images, while requiring careful architectural considerations when the source resolution is in the megapixel range. To address these concerns, we propose a novel DenseNet-based ladder-style architecture which features high modelling power and a very lean upsampling datapath. We also propose to substantially reduce the extent of feature map caching by exploiting inherent spatial efficiency of the DenseNet feature extractor. The resulting models deliver high performance with fewer parameters than competitive approaches, and allow training at megapixel resolution on commodity hardware. The presented experimental results outperform the state-of-the-art in terms of prediction accuracy and execution speed on Cityscapes, Pascal VOC 2012, CamVid and ROB 2018 datasets. Source code will be released upon publication.
Evaluation Metrics for Unsupervised Learning Algorithms
Venue: arXiv cs.LG 2019
Year: 2019

Determining the quality of the results obtained by clustering techniques is a key issue in unsupervised machine learning. Many authors have discussed the desirable features of good clustering algorithms. However, Jon Kleinberg established an impossibility theorem for clustering. As a consequence, a wealth of studies have proposed techniques to evaluate the quality of clustering results depending on the characteristics of the clustering problem and the algorithmic technique employed to cluster data.
The Algonauts Project: A Platform for Communication between the Sciences of Biological and Artificial Intelligence
Venue: arXiv cs.CV 2019
Year: 2019

In the last decade, artificial intelligence (AI) models inspired by the brain have made unprecedented progress in performing real-world perceptual tasks like object classification and speech recognition. Recently, researchers of natural intelligence have begun using those AI models to explore how the brain performs such tasks. These developments suggest that future progress will benefit from increased interaction between disciplines. Here we introduce the Algonauts Project as a structured and quantitative communication channel for interdisciplinary interaction between natural and artificial intelligence researchers. The project's core is an open challenge with a quantitative benchmark whose goal is to account for brain data through computational models. This project has the potential to provide better models of natural intelligence and to gather findings that advance AI. The 2019 Algonauts Project focuses on benchmarking computational models predicting human brain activity when people look at pictures of objects. The 2019 edition of the Algonauts Project is available online: http://algonauts.csail.mit.edu/.
SuperChat: Dialogue Generation by Transfer Learning from Vision to Language using Two-dimensional Word Embedding and Pretrained ImageNet CNN Models
Venue: arXiv cs.CL 2019
Year: 2019

The recent work of Super Characters method using two-dimensional word embedding achieved state-of-the-art results in text classification tasks, showcasing the promise of this new approach. This paper borrows the idea of Super Characters method and two-dimensional embedding, and proposes a method of generating conversational response for open domain dialogues. The experimental results on a public dataset shows that the proposed SuperChat method generates high quality responses. An interactive demo is ready to show at the workshop.
Simulation Typology and Termination Risks
Venue: arXiv cs.OH 2019
Year: 2019

The goal of the article is to explore what is the most probable type of simulation in which humanity lives (if any) and how this affects simulation termination risks. We firstly explore the question of what kind of simulation in which humanity is most likely located based on pure theoretical reasoning. We suggest a new patch to the classical simulation argument, showing that we are likely simulated not by our own descendants, but by alien civilizations. Based on this, we provide classification of different possible simulations and we find that simpler, less expensive and one-person-centered simulations, resurrectional simulations, or simulations of the first artificial general intelligence's (AGI's) origin (singularity simulations) should dominate. Also, simulations which simulate the 21st century and global catastrophic risks are probable. We then explore whether the simulation could collapse or be terminated. Most simulations must be terminated after they model the singularity or after they model a global catastrophe before the singularity. Undeniably observed glitches, but not philosophical speculations could result in simulation termination. The simulation could collapse if it is overwhelmed by glitches. The Doomsday Argument in simulations implies termination soon. We conclude that all types of the most probable simulations except resurrectional simulations are prone to termination risks in a relatively short time frame of hundreds of years or less from now.
Pointing task on smart glasses: Comparison of four interaction techniques
Venue: arXiv cs.HC 2019
Year: 2019

Mobile devices such as smartphones, smartwatches or smart glasses have revolutionized how we interact. We are interested in smart glasses because they have the advantage of providing a simultaneous view of both physical and digital worlds. Despite this potential, pointing task on smart glasses is not really widespread. In this paper, we compared four interaction techniques for selecting targets : (a) the Absolute Head Movement and (b) the Relative Head Movement, where head movement controls the cursor on smart glasses in absolute or relative way, (c) the Absolute Free Hand interaction, where the forefinger control the cursor and (d) the Tactile Surface interaction, where the user controls the cursor via a small touchpad connected to smart glasses. We conducted an experiment with 18 participants. The Tactile Surface and Absolute Head Movement were the most efficient. The Relative Head Movement and Absolute Free Hand interactions were promising and require more exploration for other tasks.
Extraction and Analysis of Clinically Important Follow-up Recommendations in a Large Radiology Dataset
Venue: arXiv cs.CL 2019
Year: 2019

Communication of follow-up recommendations when abnormalities are identified on imaging studies is prone to error. In this paper, we present a natural language processing approach based on deep learning to automatically identify clinically important recommendations in radiology reports. Our approach first identifies the recommendation sentences and then extracts reason, test, and time frame of the identified recommendations. To train our extraction models, we created a corpus of 567 radiology reports annotated for recommendation information. Our extraction models achieved 0.92 f-score for recommendation sentence, 0.65 f-score for reason, 0.73 f-score for test, and 0.84 f-score for time frame. We applied the extraction models to a set of over 3.3 million radiology reports and analyzed the adherence of follow-up recommendations.
Indicating Asynchronous Array Multipliers
Venue: arXiv cs.AR 2019
Year: 2019

Multiplication is an important arithmetic operation that is frequently encountered in microprocessing and digital signal processing applications, and multiplication is physically realized using a multiplier. This paper discusses the physical implementation of many indicating asynchronous array multipliers, which are inherently elastic and modular and are robust to timing, process and parametric variations. We consider the physical realization of many indicating asynchronous array multipliers using a 32/28nm CMOS technology. The weak-indication array multipliers comprise strong-indication or weak-indication full adders, and strong-indication 2-input AND functions to realize the partial products. The multipliers were synthesized in a semi-custom ASIC design style using standard library cells including a custom-designed 2-input C-element. 4x4 and 8x8 multiplication operations were considered for the physical implementations. The 4-phase return-to-zero (RTZ) and the 4-phase return-to-one (RTO) handshake protocols were utilized for data communication, and the delay-insensitive dual-rail code was used for data encoding. Among several weak-indication array multipliers, a weak-indication array multiplier utilizing a biased weak-indication full adder and the strong-indication 2-input AND function is found to have reduced cycle time and power-cycle time product with respect to RTZ and RTO handshaking for 4x4 and 8x8 multiplications. Further, the 4-phase RTO handshaking is found to be preferable to the 4-phase RTZ handshaking for achieving enhanced optimizations of the design metrics.
Modern Problems Require Modern Solutions: Hybrid Concepts for Industrial Intrusion Detection
Venue: arXiv cs.CR 2019
Year: 2019

The concept of Industry 4.0 brings a disruption into the processing industry. It is characterised by a high degree of intercommunication, embedded computation, resulting in a decentralised and distributed handling of data. Additionally, cloud-storage and Software-as-a-Service (SaaS) approaches enhance a centralised storage and handling of data. This often takes place in third-party networks. Furthermore, Industry 4.0 is driven by novel business cases. Lot sizes of one, customer individual production, observation of process state and progress in real-time and remote maintenance, just to name a few. All of these new business cases make use of the novel technologies. However, cyber security has not been an issue in industry. Industrial networks have been considered physically separated from public networks. Additionally, the high level of uniqueness of any industrial network was said to prevent attackers from exploiting flaws. Those assumptions are inherently broken by the concept of Industry 4.0. As a result, an abundance of attack vectors is created. In the past, attackers have used those attack vectors in spectacular fashions. Especially Small and Mediumsized Enterprises (SMEs) in Germany struggle to adapt to these challenges. Reasons are the cost required for technical solutions and security professionals. In order to enable SMEs to cope with the growing threat in the cyberspace, the research project IUNO Insec aims at providing and improving security solutions that can be used without specialised security knowledge. The project IUNO Insec is briefly introduced in this work. Furthermore, contributions in the field of intrusion detection, especially machine learning-based solutions, for industrial environments provided by the authors are presented and set into context.
A Preliminary Theory for Open Source Ecosystem Micro-economics
Venue: arXiv cs.CY 2019
Year: 2019

While there has been substantial empirical work identifying factors that influence the contribution to, and use of open source software, we have as yet little theory that identifies the key constructs and relationships that would allow us to explain and predict how open source ecosystems function. What is needed is a clearly articulated and empirically validated theory of open source ecosystems. Such a theory should: $\bullet$ Explain why, how, and when key resources---primarily the work of developers---are attracted to or depart from a project or an ecosystem. $\bullet$ Explain why, how, and when projects and ecosystems move through a life cycle, from initiation, growth, maturity, and decline and death. $\bullet$ Explain how decisions about use are made, and how the cumulatively influence the socio-technical position of a project within an ecosystem, and the relations of ecosystems to each other.The remainder of this chapter provides a sketch of such a theory in the form of a set of propositions, which may form the foundation for future empirical work
Survival of the Fittest in PlayerUnknown BattleGround
Venue: arXiv cs.LG 2019
Year: 2019

The goal of this paper was to predict the placement in the multiplayer game PUBG (playerunknown battleground). In the game, up to one hundred players parachutes onto an island and scavenge for weapons and equipment to kill others, while avoiding getting killed themselves. The available safe area of the game map decreases in size over time, directing surviving players into tighter areas to force encounters. The last player or team standing wins the round. In this paper specifically, we have tried to predict the placement of the player in the ultimate survival test. The data set has been taken from Kaggle. Entire dataset has 29 attributes which are categories to 1 label(winPlacePerc), training set has 4.5 million instances and testing set has 1.9 million. winPlacePerc is continuous category, which makes it harder to predict the survival of the fittest. To overcome this problem, we have applied multiple machine learning models to find the optimum prediction. Model consists of LightGBM Regression (Light Gradient Boosting Machine Regression), MultiLayer Perceptron, M5P (improvement on C4.5) and Random Forest. To measure the error rate, Mean Absolute Error has been used. With the final prediction we have achieved MAE of 0.02047, 0.065, 0.0592 and 0634 respectively.
On the Cost of Security Compliance in Information Systems
Venue: arXiv cs.CR 2019
Year: 2019

The onward development of information and communication technology has led to a new industrial revolution called Industry 4.0. This revolution involves Cyber-Physical Production Systems (CPPS), which consist of intelligent Cyber-Physical Systems that may be able to adapt themselves autonomously in a production environment. At the moment, machines in industrial environments are often not connected to the internet, which thus needs a point-to-point connection to access the device if necessary. Through Industry 4.0, these devices should enable remote access for smart maintenance through a connection to the outside world. However, this connection opens the gate for possible cyber-attacks and thus raises the question about providing security for these environments. Therefore, this paper used an adapted approach based on SixSigma to solve this security problem by investigating security standards. Security requirements were gathered and mapped to controls from well known security standards, formed into a catalog. This catalog includes assessment information to check how secure a solution for a use case is and also includes a link to an estimation method for implementation cost. Thus this papers outcome shows how to make Industry 4.0 use cases secure by fulfilling security standard controls and how to estimate the resulting implementation costs.
DeXTT: Deterministic Cross-Blockchain Token Transfers
Venue: arXiv cs.DC 2019
Year: 2019

Current blockchain technologies provide very limited interoperability. Restrictions with regards to asset transfers and data exchange between different blockchains reduce usability and comfort for users, and hinder novel developments within the blockchain space. As a first step towards cross-blockchain interoperability, we propose the DeXTT cross-blockchain transfer protocol, which can be used to transfer a token on any number of blockchains simultaneously in a decentralized manner. We provide a reference implementation using Solidity, and evaluate its performance. We show logarithmic scalability of DeXTT with respect to the number of participating nodes, and analyze cost requirements of the transferred tokens.