Reviewerly/exHarmony huggingface dataset:
7<sup>th</sup> International Workshop on Safety and Security of Intelligent Vehicles – SSIV 2021

Mobile robot systems, like aerial and ground vehicles, have been receiving an increased number of electronic components, connected through wireless networks, and running embedded software. This strong integration between the physical environment, dedicated computing devices, and networking, composes a Cyber-Physical System (CPS). CPS have thus become part of common vehicles, accessible to everyone, such as automobiles or unmanned aerial vehicles (UAVs). Furthermore, as processing power increases and software becomes more sophisticated, these vehicles gain the ability to perform complex operations, becoming more autonomous, efficient, adaptable, comfortable, safe, and usable. These are known as Intelligent Vehicles (IV).
Freedom of Expression &amp;amp; Hate Speech in the EU’s Digital Age: ‘To What Extent Have the Approaches to 'Online Freedom of Expression' of both the Council of Europe and the European Union Demonstrated that Eu Law Is Fit for Purpose in the Digital Age? Following from This, What Lessons Can the EU Legislature Learn from the Aforementioned Approaches in Drafting Legislation on the Specific Issue of Online Hate Speech and How It Impacts upon Freedom of Expression?’

This thesis explores the European Commission's unenviable task of regulating the digital space to curb the prevalence of online hate speech whilst ensuring major platforms remain open forums for public debate. Considering the significant impact which new EU-wide rules tackling online hate speech would have on fundamental rights, particularly freedom of expression, the paper firstly explores the Council of Europe's approach to freedom of expression online. This opening chapter ensures human rights are at the foreground of upcoming critical analysis as the thesis progresses on to discuss both the EU legislature and the CJEU's approach to free speech online. The remainder of the thesis focuses solely on online hate speech, looking to diverging regulatory approaches of national legislatures and social media platforms. Within this, it becomes evident that constitutional values and the ethos of private companies impact how different players assess hate speech regulation. The concluding chapter compiles all the lessons learned in previous chapters to tease out how and why the EU must regulate online hate speech, putting forth the specific technological solution of ‘quarantining' hate speech as an appropriate means of protecting users’ against hate speech whilst not overly infringing upon freedom of expression.
Perspectives on the Development of Intelligent Control Technology in the Field of Artificial Intelligence

This paper mainly focuses on the development of artificial intelligence and intelligent control in each stage. Artificial intelligence and intelligent control need coexist and influence each other. The problems faced by artificial intelligence in intelligent control methods are analyzed. The development of intelligent control in artificial intelligence method is used in theory research and practical applications. The paper gives the future development direction of artificial intelligence in intelligent control.
A Method for Identifying Fatigue State of Driver's Face Based on Improved AAM Algorithm

The change of lighting conditions and facial pose often affects the driver's face's video registration greatly, which affects the recognition accuracy of the driver's fatigue state. In this paper, the authors first analyze the reasons for the failure of the driver's face registration in the light conditions and the changes of facial gestures, and propose an adaptive AAM (Active Appearance Model) algorithm of adaptive illumination and attitude change. Then, the SURF (speeded up robust feature) feature extraction is performed on the registered driver's face video images, and finally the authors input the extracted SURF feature into the designed artificial neural network to realize the recognition of driver's fatigue state. The experimental results show that the improved AAM method can better adapt to the driver's face under the illumination and attitude changes, and the driver's facial image's SURF feature is more obvious. The average correct recognition rate of the driver's fatigue states is 92.43%.
Quality assurance

Digital evidence concerns the evidence, or digital traces, produced as a result of digital technologies, most commonly computer processing and involves a range of devices. Technology is related to engineering with a basis in science and mathematics. Technology involves the manipulation of matter and the application of defined things such as devices, systems, methods and proceduresto perform a practical function. As digital evidence is applied to legal processes, it then follows that it should be subject to the same admissibility requirements as other scientific evidence.
An Intelligent Multi-Objective Framework of Pervasive Information Computing

This article describes how electronic healthcare has been the key application of pervasive computing innovations to enhance healthcare quality and protect human lives. Specific patients of constant sicknesses and elderly individuals, by and large, may oblige continuous observing of their wellbeing status wherever they are. In this regard, remote patient monitoring technology plays the various important role through wearable devices to monitor patient's physiological figures. But, this must ensure some broad issues like, wearability, adaptability, interoperability, integration, security, and network efficiency. This article proposes a data-driven multi-layer architecture for pervasively remote patient monitoring that incorporates aforesaid issues. It enables the patient's care at the real time and supports anywhere and anytime requirement with using network infrastructure efficiently.
THE ANALYSIS OF STUDENTS’ READING COMPREHENSION ABILITY AT INDONESIAN MARITIME ACADEMY, MEDAN

This study is about the analysis of students’ reading comprehension ability, it is done to find out how students’ reading comprehension ability. This study was done at Indonesian Maritime Academy, Medan. The method of the study was quantitative with survey design. The instrument of the study used was a set of reading comprehension test which were constructed based on the taxonomic level. The respondent of this study were 83 respondents who were randomly selected, consisting of two students who studied English for almost two years at Indonesian Maritime Academy, Medan. The result is that the level of students’ reading comprehension among students is at the moderate level and there is a significant relationship between reading comprehension and English language achievement. In conclusion, one way to improve student achievement in English language subjects is by increasing the level of students ’reading comprehension.
A preliminary classification of different tasks that make use of uncertainty visualizations

Individuals often struggle with tasks that involve uncertainty. Uncertainty visualizations are a type of cognitive aid that provides uncertainty information to help people with performing these tasks. However, the literature has shown that uncertainty visualizations differ in the extent they improve individuals’ task performance. We hypothesize that differences in the tasks can account for some of this variability. In this study, we aimed to create an initial classification of task types based on studies on uncertainty visualizations by reviewing a diverse set of recent research involving uncertainty visualizations. We classified the experimental tasks found in these papers into four groups: uncertainty assessment, forecasting, decision making, and metacognition. Then, we reviewed the result of the experiments in terms of the similarities and differences in the use of uncertainty visualizations within and between tasks. This classification serves as a starting point for further research into the effective design of visualizations of uncertainty.
Methodology for the Research Conducted

This chapter describes and discusses a combination of research methodologies (e.g., experimental, theoretical, and systems design) used in this research, allowing us to eliminate as much as possible every limitation that can be encountered with the individual methods themselves. For example, experimental research methodology has a limitation because the experiments are performed mainly in a controlled environment and might not reflect properly some practices performed ‘in the wild'. But combining this with some survey and prototype (system's) design reduced such limitations. The knowledge gained from carrying out preliminary experimentation is used in the next chapter to design and model the Hybrid-AutoML system.
Optimization Methods

The machine learning models aim to construct a prediction function which minimizes the loss function. There are many algorithms which aim to minimize the loss function. Most of them are iterative and operate by decreasing the loss function following a descent direction. These methods solve the problem when the loss function is supposed to be convex. The main idea can be expressed simply as follows: starting from initial arbitrary (or randomly) chosen point in the parameter space, they allow the “descent” to the minimum of the loss function accordingly to the chosen set of directions. Here we discuss some of the most known and used optimization algorithms in this field.
Linked Ocean Data 2.0

Within the theme of sustainable development, it is not desirable to either have data siloed in one location where it cannot be reused for purposes beyond which it was originally collected, or in a state where it cannot be integrated into a holistic view of the marine environment. As such, the links between datasets should be formally documented and exploited as best as possible. Given this, the use of Semantic Web technology and information modelling patterns are explored in this chapter with reference to the marine domain. Further, new strategies for adding semantic annotation to data in real-time are discussed and prototyped.
Can Blockchain Really Help the Poor?

It is the firm belief of the authors that Blockchain and other frontier technologies will be an important tool for social impact globally. It is now possible, with technology, to envision a world where everyone has an identity, where everyone can be connected to the economic system, where farmers get fair deals for their crops, and land registration is incorruptible. Advances in solar, battery, and digital commerce make it possible to imagine even the smallest village in Africa being able to produce and trade small amounts of energy. The Sustainable Development Goals (SDGs) were a visionary leap to a future state where the world can be a better place for humankind. However, they will not be achieved without harnessing the potential of technology. Nor will they be reached alone. In this chapter, the authors profile innovative case studies in Blockchain, which, if brought to scale, may realise the technology's potential. It is through this learning and experimentation that we will learn how to deploy this technology globally for social impact.
Business and Social Media

During the 21st century, businesses benefit from two key components of effective innovation: social media and collaboration. This chapter provides an in-depth analysis to study the interrelatedness of these components. Featured in this chapter are classroom exercises to deepen the learning of students. By providing multiple recent social media examples, the reality of the integral ways in which social media permeates our lives is delivered. Introduced in the chapter is a sixth discipline, an extension of Senge's five disciplines of collaboration. Through the presentation of a new leadership model based upon the six disciplines, the impact of social media is examined. The conclusion of the chapter contains definitions of the concepts introduced. The use of social media has been and still remains a strategically keen tool in business effectiveness.*
Educational Ontology Development

Ontology use in education environments can be explained in three groups: content access and/or retrieval, content creation, and personalization. Use of ontologies helps content creators to design and develop online courses, provide smart searches and content suggestions, and design personalized learning environments for learners. But it is not always possible for educators to find the best ontology for their needs in their learning management system. Since the ontology creation is a complex process, it might not be always easy or even possible to create an ontology for a selected domain and use accordingly. In this chapter, a review of state-of-the art literature regarding the ontologies in educational domain will be reviewed. Second, the challenges and difficulties in ontology development process for educational domain will be addressed and explained in detail. Finally, design suggestions to the difficulties expressed in the literature and further opportunities in ontology design and development will be presented, taking the existing ontology evaluation frameworks into account.
Research on Accurate Reading Recommendation of University Library Based on Student Portraits

[Purpose/Significance] Based on the concept of student portraits, this paper proposes a strategy for recommending accurate reading in academic libraries in order to provide useful reference and reference for the reading promotion work of academic libraries in my country. [Method/Process] Aiming at the design conception and data analysis of student portraits, a set of accurate reading recommendation strategies based on student portraits is proposed. [Results/Conclusions] It will be a beneficial attempt to use the strategy of student portraits to promote accurate reading recommendation work. However, the introduction of student portraits in the field of university libraries is in its infancy, and most universities do not have mature platforms to implement them. Step by step is required. Persistent practice and application process.
Electronic Theses and Dissertations (ETDs)

Electronic theses and dissertations (ETDs) have been a recent addition to the library's online access system, or digital project. This chapter traces the history of dissertations, from their printed form and issuance in microform by various agencies. It examines the changes in textual content and its presentation from the pre-digital to digitized documents, and the relation to software developed for music and other fields. It then examines the evolution of audio and video formats for the accompanying materials, particularly in the performing arts, and the content of these materials. It concludes with issues in ETDs management and ensuring long-term access and preservation, such as digital quality and copyright.
A Digital Currency System with Transaction Amount Privacy Protection

Blockchain has the characteristics of decentralization, tamper proof, and untraceability and has been used in various areas. Nowadays, users are increasingly concerned about their privacy. However, anonymity poses a huge challenge on anti-crime, such as anti-money laundering, counter-terrorism financing and tax evasion. In order to achieve a broader use of blockchain, a trade-off between privacy and regulation must be achieved. We study the contradiction between privacy-preserving payment mechanisms including controllable anonymity, and penetrating regulation on digital currency. We then propose a solution based on homomorphic encryption and federated learning. Finally, a digital currency prototype is implemented with corda framework to verify our strategies.
Lossless compression methods

This chapter describes methods for coding images without loss; this means that, after compression, the input signal can be exactly reconstructed. These have two primary uses. Firstly, they are useful when it is a requirement of the application that loss of any kind is unacceptable. Examples include some medical applications, where compression artifacts could be considered to impact upon diagnoses, or perhaps in legal cases where documents are used as evidence. Secondly, and more commonly, they are used as a component in a lossy compression technique, in combination with transformation and quantization, to provide entropy-efficient representations of the resulting coefficients. We first review the motivations and requirements for lossless compression and then focus our attention on the two primary methods, Huffman coding and arithmetic coding. Huffman coding is used widely, for example in most JPEG codecs, and we show it can be combined with the discrete cosine transform (DCT) to yield a compressed bitstream with minimum average codeword length. We explore the properties and limitations of Huffman coding in Section 7.3 and then introduce an alternative method – arithmetic coding – in Section 7.6. This elegant and flexible, yet simple, method supports encoding strings of symbols rather than single symbols as in Huffman coding. Arithmetic coding has now been universally adopted as the entropy coder of choice in all modern compression standards. Finally, Section 7.7 presents some performance comparisons between Huffman and arithmetic coding.
Applications

This chapter presents real-world applications of previously discussed modern optimization methods: traveling salesman problem, time series forecasting, and wine quality classification.
The application and prospect of educational technology innovation in adolescent cognitive development

Traditional educational technology is mechanically repetitive and boring, and ignores the cultivation of non-intellectual factors, which limits the ability of multi-angle thinking. With the innovation of science and technology and the development of society, adolescent education technology is constantly updated. VR, AR and MR technologies, for example, not only revolutionize education and teaching technologies, but also promote the cognitive development of teenagers. The integration of VR, AR and MR technologies into the education of teenagers not only expands the tools and space of education and teaching, but also plays a positive role in the cognitive development of teenagers, the cultivation of thinking and the formation of children’s personality and psychology. At present, there are many researches on the application of virtual reality and augmented reality to adolescent cognitive development in primary and secondary schools. However, there are still few researches on the construction of a new teaching method of "multi-mode + human-computer collaboration" by carrying out cognitive development teaching based on MR and focusing on multi-mode data representation such as vision, hearing and touch. Based on this, this paper will focus on VR and cognitive development teaching based on MR technology.
Explore a Novel Knowledge Distillation Framework for Network Learning and Low-Bit Quantization

Knowledge distillation is a kind of model compression methods. It improves the performance of "student" networks by transferring the knowledge of "teacher" to "student". However, due to the huge gap between "teacher" and "student" in knowledge representation capabilities, directly minimizing the difference between them to transfer the knowledge will lead to the convergence issue. To this end, this paper proposes a novel framework of knowledge distillation. By sharing the weights of "teacher" and "student" in fully connected layers, we reduce the challenge of knowledge transfer. Furthermore, we propose a novel training strategy to improve the performance of low-bit quantization networks based on our distillation framework called distillation for low-bit quantization (DLBQ). The experimental results show that our methods can achieve significant improvement across different tasks. For instance, ResNet-20 gains 1.81% improvement on Cifar10 dataset. ResNet-56 shows 3.36% improvement on Cifar100 dataset and even exhibits 1.72% performance improvement than "teacher" network. Additionally, as for the improvements of quantization performance, ResNet-20 gain 1.25% improvement with ternary weights on Cifar10, and ResNet-110 manifects 3.22% improvement with binary weights on Cifar100 dataset.
SiamTD: Siamese twin delayed deep deterministic policy gradient for rubust Object Tracking

In the last decades, many different algorithms have been proposed to visual tracking. New trends showed that demonstrations of an agent trained by reinforcement learning can be efficiently used in visual tracking. Inspired by those achievements, we propose a novel tracking net SiameseTD(Twin delayed deep deterministic policy gradient) which combines the advantages of Siamese framework and reinforcement learning. Different from previous trackers based on Reinforcement learning, the TD algorithm we used builds on a double Q-learning net, by taking the minimum value between a pair of critics to limit over estimation problem of Q-value in the actor-critic methods. The novelty of our method is that we introduce the reinforcement learning algorithm TD into visual tracking and combine the advantages of Siamese framework. Experiments on most benchmarks show that the our tracker performs favorably better than many state-of-arts trackers.
Achieving Cloud Security Using a Third Party Auditor and Preserving Privacy for Shared Data Over a Public Cloud

Correctness of data and efficient mechanisms for data security, while transferring the file to and from Cloud, are of paramount importance in today's cloud-centric processing. A mechanism for correctness and efficient transfer of data is proposed in this article. While processing users request data, a set of attributes are defined and checked. States with attributes at different levels are defined to prevent unauthorized access. Security is provided while storing the data using a chunk generation algorithm and verification of chunks using lightweight Third-Party Auditor (TPA). TPA uses digital signatures to verify user's data that are generated by RSA with MD5 algorithms. The metadata file of generated chunks is encrypted using a modified AES algorithm. The proposed method prevents unauthorized users from accessing the data in the cloud environment, in addition to maintaining data integrity. Results of the proposed cloud security model implementation are discussed.
Uniform Random Number Generation With Jumping Facilities

A facility for generating sequences of pseudorandom numbers is a fundamental part of computer simulation systems. Furthermore, multiple independent streams of random numbers are often required in simulation studies, for instance, to facilitate synchronization for variance-reduction purposes, and for making independent replications. A portable set of software utilities is described for uniform random-number generation. It provides for multiple generators (streams) running simultaneously, and each generator (stream) has its sequence of numbers partitioned into many long disjoint contiguous substreams. Simple procedure calls allow the user to make any generator “jump” ahead/back v steps (random numbers). Implementation issues are discussed. An efficient and portable code is also provided to implement the package. The basic underlying generator CMRG (combined multiple recursive generator) combines two multiple recursive random number generators with a period length of approximately 2191 (≈ 3.1× 1057), good speed, and excellent theoretical properties.