Reviewerly/exHarmony huggingface dataset:
Auction Based Secure Computation Offloading in Vehicular Networks

The cloud computing and edge computing technologies have provided new opportunities for vehicular task offloading in vehicular networks. However, the computing task of a vehicle can be offloaded to multiple edge servers. Therefore, how to select the optimal edge server to complete the offloading service is a challenge. In addition, some malicious edge servers may declare unreasonable prices to execute the offloading service. A market mechanism is thus required to constrain the bids of edge servers in the networks. Besides, the edge servers may provide the offloading services with low quality which will decrease the quality of experience (QoE) of the service requesters. In order to solve the above mentioned challenges, this chapter proposes an auction based task offloading framework to ensure that the computing tasks requested by vehicles can be safely offloaded and executed. First, to constrain the bids of the edge servers in the networks, a task offloading scheme based on the first price sealed auction is proposed for the edge servers which intend to join in the task offloading process. Then, considering the service quality of each edge server, the cloud server is used to evaluate the quality of the edge servers. By designing the security evaluation and prediction algorithm for edge servers based on transductive support vector machine (TSVM), the optimal edge server can be selected for the vehicle to execute the offloading task. With the edge-cloud networks, we evaluate the secure offloading strategy of the vehicle, where the simulation results show that the task offloading scheme proposed in this chapter has a higher efficiency than the conventional schemes.
Comparison of Different Information Display Modes for Smart Glasses Assisted Machine Operations

A pair of commercially available smart glasses, Epson BT-200, was evaluated with different information display modes for assisting machine operators. Two information display modes were selected, displaying animated images only, and displaying animated images with text illustrations. Direction prompts were added in the system. Whether the prompts are helpful or not was also discussed in this study. Task completion time and error rate were collected during the experiment. System Usability Scale (SUS) and NASA-Task Load Index (NASA-TLX) were used to collect subjective information after each experiment. Twenty participants (10 males and 10 females) were recruited. The results showed that the display mode of having smart glasses displaying animated images versus displaying animated images with text illustrations showed no significant difference in task completion time and error rate. But the significant difference was found in the result of SUS scores. Participants preferred the display mode of animate images with text illustrations according to the SUS scores. Moreover, the results indicated that the use of direction prompts had significant influences upon all the measures. Participants completed the tasks faster and had lower error rate by using the smart glasses with direction prompts. And the results of subjective ratings also showed higher SUS score and lower NASA-TLX score were associated with using smart glasses with direction prompts. Thus, the implementation of using smart glasses to guide machine operations should be considered the design of adding direction prompts to increase efficiency and effectiveness of the operations.
Morfeus+: Word parsing in Basque beyond morphological segmentation

This work describes the formalization of a word structure grammar that represents the complex morphological and morphosyntactic information embedded within the word forms of an agglutinative language (Basque), giving a comprehensive linguistic description of the main morphological phenomena, such as affixation, derivation, and composition, and also taking into account the modeling of both standard and non-standard words. We have identified the relevant issues to be addressed in the representation of such a grammar. We also present the development of Morfeus+, a tool for the analysis of unrestricted texts, testing its applicability and showing that its coverage is wide and robust, allowing the efficient processing of big volumes of data. This paper describes a mature system that has required several person/years and that tries to integrate a rigorous linguistic specification together with more practical implementation matters, such as the appropriate treatment of unknown words in unrestricted texts.
Formal verification of ontology transformation for distribution network information model based on meta‐model theory

This study presents a formal description and verification method of the ontology transformation process of the distribution network information model based on the meta-model theory. By defining the dynamic change structures and model mapping constraints of the ontology transformation process of distribution network, a formalised specification for describing the key attributes of model updating and model mapping processes was constructed. The model updating and model mapping instances were specified using model checking verification tool SPIN. The method fundamentally guarantees the standardisation and reliability of the model ontology transformation process achieved by the meta-model.
Efisiensi Saluran Drainase Eksisting pada Sistem Drainase Daerah Aliran Sungai Selumit Kota Tarakan Kalimantan Utara

In the City of Tarakan, there is a network of drainage systems that have different dimensions and water debit sizes. In the Selumit River Basin drainage system, runoff often runs on the road when it rains. This is caused by existing runoff. Yet according to planning calculations and based on dimensional calculation results, the channel can still accommodate existing runoff discharge. This is caused by some inefficient channels. Inefficient channels can cause runoff. Based on efficiency calculations, the Selumit River Basin drainage system in Tarakan City is an efficient channel, with an average percentage of efficiency of 97%. This means that only 3% of the percentage of water that escapes from the difference in water entering the channel with water coming out of the drainage channel. According to the Efficiency calculation, there are several very efficient drainage channels, namely channels with scheme numbers 3, 4, 6, 7, 10, 13 and 14 with each value of efficiency percentage is 100%. And there are some inefficient channels among which are channels with the number scheme 1, 2, 5, 8, 9, 11, 12, 15, 16, 17, 18, 19, and 20, with each percentage value of efficiency is 93% , 84%, 99%, 99%, 98%, 99%, 99%, 95%, 98%, 97%, 97%, 99%, and 92%. The channel with the lowest percentage of efficiency is 84% found in the channel with scheme number 2. It means that the runoff water in the drainage channel is as complicated as between 2% -16%. Based on the analysis, an alternative solution to the problem of an inefficient drainage system was formulated is to streamline an inefficient drainage channel.
Dickson Matrix Based Construction of Linear Maximum Rank Distance Codes

Maximum rank distance (MRD for short) codes lately attract more attention due to their various applications in storage systems, network coding, cryptography and space time coding. Similar to Reed-Solomon codes in classical coding theory, Gabidulin codes are the most prominent family of MRD codes. Due to their poor performance in list decoding or in constructing McEliece-type cryptosystems, the focus moves from Gabidulin codes to other non-Gabidulin codes. A natural following challenge is then to see if we can construct an infinite family of MRD codes that are not equivalent to Gabidulin codes. In this paper, we utilize Dickson matrices to construct an infinite family of Fq-linear MRD codes. Our codes are characterized by each of their codewords corresponding to a linearized polynomial with leading coefficient determined by one of any other coefficients. The family of codes corresponding to the set of linearized polynomials with leading coefficients dependent on the linear terms provides an extension to both Twisted Gabidulin codes and generalized Twisted Gabidulin codes for dimensions 1 and n-1. Lastly, we also provide some analysis on the equivalence between our proposed codes with some known families of MRD codes.
Progressive network delivery approach of rendered image

In this paper, we presents a novel image progressive deliver approach based on the continuous relationship, frame prediction and frame buffer between the drawn image sequences, which is a very simple and efficient method, especially when the network is unstable or the network bandwidth is not large. It makes use of the strong continuity between the action relativity in the user's actual operation and the continuous frames in the scene rendering, selects some key frames in a series of rendered high resolution images for progressive network transmission. The client of the network can use the received series of rendered images, then reconstruct the images of other viewpoints according to the images of these key frames, and set the image frame buffer to save the generated or transmitted images, so as to ensure a better user experience when the network is unstable. In the browsing process of 3D scene, it greatly reduces the number of images that need to be drawn by the background server, and also reduces the amount of image data actually transmitted by the network. In this way, under the same network bandwidth, it can smoothly browse the super large 3D scene by multiple people in real time, and improve the user's browsing experience. First of all, our algorithm divides and recognizes the action behavior of the browsing user, transforms the continuous interaction behavior of the browsing user into a series of standard behaviors, which can quantify the interaction behavior of the user, and provides a unified standardized standard for the subsequent prediction, image generation and image caching. Then select the image to be drawn or cached according to the interactive action of the browsing user, and select the image to be sent according to certain rules. Finally, the client program reconstructs the other time according to the received important frame sequence and a series of known constraints, and uses some strategies to cache some frames to prevent network jitter.
Object-Level Matching for Multi-source Image Using Improved Dictionary Learning Algorithm

Solving the problem of multi-source information matching is the foundation of multi-source information fusion. Aiming at the heterogeneity between different multi-source images, we propose a new method of object-level matching for multi-source image based on improved dictionary learning. Two main steps, unified representation and similarity measure, are contained. Firstly, we complete the unified representation of multi-source images by improved dictionary learning algorithm. On the basis of the representation ability of dictionary learning, we further make full use of the label information to boost the discriminative ability of dictionary, which is beneficial to the implementation of object matching. Then, we construct a neural network to learn the distance metric standard between matching and non-matching by supervised learning, which can replace the traditional distance metric method. In addition, we produce two sets of multi-source image object matching datasets based on the open datasets, which verifies the validity and accuracy of the algorithm, and shows the good performance of the algorithm in solving the zero-shot learning problems.
Establishment and Application of Big Data Processing Platform

With the advent of the era of big data, more and more enterprises begin to use big data technology to deal with related analysis work. Hadoop is the dominant processing platform in the field of big data, an ecosystem that integrates distributed computing, storage, and management. The Spark framework, on the other hand, is a faster, more versatile distributed computing platform. However, it is only a computing platform and does not provide distributed storage and management per se, and computing remains dependent on distributed file system HDFS and cluster Resource Manager Yarn in the Hadoop ecosystem. Therefore, the combination of Spark and Hadoop to build a big data processing platform can better improve the algorithm efficiency and processing scale. This article explains the setup process and running state of Hadoop and Spark in detail, and verifies its feasibility through several ways.
Insider Threat Dynamics; the dangerous triangle of pressure, rationalization and opportunity

Increasing dependency on information technology and an increasing number of cyber-attacks give rise to concerns about secure software development methods. Building system dynamics models we research and compare the structure underlying the behaviour relevant to security software developments for both agile and traditional software delivery methods. The difference between these models is related to the key characteristics of these methods, but not to the security aspects itself. Both dynamic models show similar structures to developing software and cybersecurity dynamics. Our study shows that network externalities may evoke the acceptance trap. The acceptance trap begins when insecure software is brought into production and is actively used, because if software is available, it can generate income, while further security development will cost more money. Insecure software means the software still contains vulnerabilities that can be exploited by cybercriminals in near future. In order to exploit these vulnerabilities cybercriminals will launch cyber attackers. In such situation there may be a contamination effect caused by successful attacks may evoke more cybercriminal activities. These ongoing cyber-attacks will have such an impact that more and more security improvements and incident responses are needed, which result in increasingly higher costs. As a result, less capacity will be available for future software development. The model structures suggest that more time and money spent on security testing and resolving vulnerabilities helps to avoid the acceptance trap. Similar conclusions have been formulated in the field of Internet of Things adaptation research. Further model quantification, validation, and policy evaluation should provide further insights and recommendations to resolve the acceptance trap.
Unsupervised Keyword Extraction for Full-Sentence VQA

In the majority of the existing Visual Question Answering (VQA) research, the answers consist of short, often single words, as per instructions given to the annotators during dataset construction.This study envisions a VQA task for natural situations, where the answers are more likely to be sentences rather than single words.To bridge the gap between this natural VQA and existing VQA approaches, a novel unsupervised keyword extraction method is proposed.The method is based on the principle that the full-sentence answers can be decomposed into two parts: one that contains new information answering the question (i.e., keywords), and one that contains information already included in the question.Discriminative decoders were designed to achieve such decomposition, and the method was experimentally implemented on VQA datasets containing full-sentence answers.The results show that the proposed model can accurately extract the keywords without being given explicit annotations describing them.
Can Refactorings Indicate Design Tradeoffs?

Refactoring does not always improve monotonically the quality of software. In this exploratory study, we analyze the revision history of JFreechart to see if fluctuations in internal quality metrics in commits containing refactoring can be used as indicators for the presence of design tradeoffs. We present qualitative and quantitative results suggesting that, in the context of refactoring, tradeoffs in internal quality metrics can be used to find design tradeoffs.
Future Work in Security Design of CPSs

The increasing reliance on computer and communication technologies exposes control systems to cybersecurity threats. The physical systems can now be attacked through cyberspace. Emerging sophisticated attacks can exploit zero-day vulnerabilities, persist in the system for long periods of time, and advance stealthily to achieve their attack goals. Protection and prevention against such attacks are not always possible, and a paradigm shift to emphasize the resilience of a control system is the overarching objective for safeguarding control systems to protect the nation’s critical infrastructures. This book has developed a set of powerful and versatile tools to establish scientific co-design principles for integrating cyber and physical systems in a holistic manner. The methodologies in this project provide a holistic and interdisciplinary approach to the secure and resilient CPS design, bridging the gap between multiple disciplines such as computer science, control, communications, and economics. In this chapter, we present several problems that could be addressed by applying or extending the proposed methodologies, and discuss future research directions of the secure and resilient CPSs. We first present two attack models for CPSs, including the man-in-the-middle (MITM) attack and the compromised-key attacks. The cross-layer co-design framework can potentially address these two attack models. Most of the existing works have focused on data confidentiality and integrity. We argue that data availability plays a critical role in time-critical CPSs. There is a need to use the cross-layer design framework to design safe-mode mechanisms and defense strategies to improve data availability.
Comparative analysis of background subtraction algorithms in the task of recognizing and identifying people in a video stream

Abstract The article is devoted to one of the most urgent tasks for today: preprocessing video material in the process of recognizing and identifying people in a video stream. The authors of this article conducted a study, which consists in comparing the results of several algorithms for subtracting the background on various input video materials (from the office and the minimum concentration of people, to the dining room in which there are up to ten or more people). The data obtained during the analysis of the algorithms is compared (such data are the number of frames processed per second, and the average load of the computer’s central processor). The most efficient algorithms that coped with the task most quickly, accurately and with the least expenditure of resources, were identified, as well as those that coped with the task the worst.
Towards Robust Localization Deep Feature Extraction by CNN

Robust localization is a fundamental capability to increase the autonomy levels of robotic platforms. A core processing step in vision based odometry methods is the extraction and tracking of distinctive features in the image frame. Nevertheless, when deploying robots in challenging environments like underground tunnels, the sensor measurements are noisy with lack of information due to low light conditions, introducing a bottleneck for feature detection methods. This paper proposes a deep classifier Convolutional Neural Network (CNN) architecture to retain detailed and noise tolerant feature maps from RBG images, establishing a novel feature tracking scheme in the context of localization. The proposed method is feeding the RGB image into the AlexNet or VGG-16 network and extracts a feature map at a specific layer. This feature map consists of feature points which are then paired between frames resulting in a discrete vector field of feature change. Finally, the proposed method is evaluated with RGB camera footage of the Micro Aerial Vehicle (MAV) flights in dark underground mines and the performance is compared with existing feature extraction methods, while the noise is added to the images.
A graphene-based synapse for photonic neural networks

We propose a graphene-based synapse model that consists of an electro-absorption modulator embedded in a microring resonator that has the potential to operate >100 GHz. We found that a maximum number of 55000 synaptic weights can be represented on our photonic device.
Parameter Evolution Self-Adaptive Strategy and Its Application for Cuckoo Search

Cuckoo Search (CS) is a simple yet efficient swarm intelligence algorithm based on Lévy Flight. However, its performance can depend heavily on the parameter settings. Though many studies have designed control strategies for scaling factor $$\alpha $$ , few have considered the adaption of the stability parameter $$\beta $$ (of Lévy Flight). In this paper, we propose the Parameter Evolution Self-Adaptive strategy (PESA) to control $$\beta $$ . PESA uses an evolutionary algorithm that runs in parallel to CS. We show that PESA can also be extended to control the parameters of other meta-heuristics, using Differential Evolution (DE) as a second example. We compare our strategy with the well-established self-adaptive strategy used in JADE, both in CS and DE, on classical benchmark functions. We discuss the increased flexibility of PESA and analyze the effect of changing the frequency of updating parameter values in CS.
Phenomenon of Reflection in the Context of Ontological Consideration

The peculiarity of the holistic-ontological approach is revealed in the article. Reflection is viewed as a modal object, as a process that takes place in the general dynamics of Being. The significance of the analysis of the diversity of the structural components of reflection as a whole, establishing the features of their interaction, as well as the influence of the modus-forming beginning of reflection on human being. The connection of the problem of reflection with the ontology of human life and the phenomenon of existential accomplishment is shown. The specificity of modes of reflection is considered as a transition from ontic to ontological levels of being. Moreover, the specificity of inauthentic and authentic manifestation of reflection is highlighted. It is concluded that the ontological status and nature of reflection changes depending on the specifics of its manifestation at the fundamental levels of human existence. Reflection actualizes the transcending mechanism, pushing the boundaries of the ontological implementation of the personality.