Reviewerly/exHarmony huggingface dataset:
Multi-robot Cooperative Exploration Based on Geometric-topological Scene Map

In view of the advantages and disadvantages of node geometry information and characteristic scene information, this paper proposes multi-robot cooperative exploration based on geometric-topological scene map. Our algorithm adds the geometric information of nodes to the feature scene map, so as to detect and recognize the node loop. Considering the spatial relationship between a single node and different nodes, we use the Hidden Markov Model (HMM) to locate nodes accurately, and use the geometrical-topological feature scene matching method to perform map fusion. The local map fusion of each robot is turned into a problem of geometrical-characteristic scene matching. Finally, the multitask assignment method of market method is used to realize the multi-robot cooperative exploration task on the simulation platform.
Single photon detector on avalanche photodiode

The technology of quantum cryptography, based on the quantum properties of light, allows a random sequence of bits to be transmitted over an unprotected communication channel in such a way that an intruder's interference in the transmission process generates additional noise in the channel and is detected by legitimate users. One of the important elements of the quantum key distribution system is a single photon detector. In this work proposed quantum cryptographic system that generates only an orthogonal basis (vertical and horizontal) has one semiconductor diode laser used to generate information and synchronization photons and functional diagram of the device for registration of single photons. The developed device allows increasing the quantum efficiency of registration up to 45%.
Systemic NPC-Side Branching in Linear AAA Video Game Stories

Much has been made of games that include the subcategory of play labelled “choice and consequence” (Taylor-Giles, Toward a Deeper Understanding of Branching Dialogue Systems. Queensland University of Technology, 2014). However, previous discussions focussed exclusively on video games that already include a choice-based dialogue interface, such as Mass Effect (BioWare, Mass Effect [Computer Software]. Electronic Arts, Redwood City, CA, 2007), Dragon Age: Origins (BioWare, Dragon Age: Origins [Computer Software]. Electronic Arts, Redwood City, CA, 2009), Deus Ex: Human Revolution (Eidos Montreal, Deus ex: Human Revolution [Computer Software]. Square Enix, El Segundo, CA, 2011), and The Elder Scrolls V: Skyrim (Bethesda Game Studios, The Elder Scrolls V: Skyrim [Computer Software]. Bethesda Softworks, LLC, Rockville, MD, 2011) (Taylor-Giles, Game User Experience and Player-Centered Design. Springer, Cham, 2020). This chapter explores the key learnings of branching dialogue systems and how they can be applied to linear, large-scale video game stories in a way that is efficient, cost-effective, and which does not require the inclusion of a choice-based dialogue interface.
The Computer Intelligent Selection of Scientific Research Subjects Through Ensemble Learning for Large-Scale Data Sources and Deep Neural Network

Abstract Selecting a proper scientific research subject is critical for scientific researchers and managers. Scientific researching data are from massive sources and have various attributes. For the problem of subject selection, feature extraction and prediction model play important role in performance optimization. In the paper we introduce ensemble learning method to help find the best fit attributes describing data. Our ensemble learning models include random forests, support vector machine, Boltzmann machine and decision tree. Since the data are from many data sources, we adopt multiple models of deep neural network. An acceleration method is used to reduce the training time as well. Experiments shows that the proposed approach performs better than RNN algorithm both in accuracy ratio and recall ratio. The model selection module and acceleration method help optimize the time cost largely.
IOT device identification solution based on unsupervised to semi-supervised

With the development of 5G, the types and numbers of IoT terminals will become more abundant. Different types of IoT terminals have large differences in behavior and network requirements. The refined operation and maintenance based on IoT application scenarios is an important for operators. The identification of the IoT terminal type is the first step to achieve refined operation and maintenance. In order to address difficulties of identifying IOT terminal type and lack of labeled data, this paper proposes a solution to fulfill the IoT terminal type based on network data using AI algorithm. This solution is to extract the behavioral patterns of IoT terminals based on network data, use a combination of semi-supervised and unsupervised methods to fulfill the labeling of training data, and use AI algorithms to identify IoT terminal type. The verification results show that the accuracy in identifying bus IoT from the APN of the IoT terminal hybrid access reaches 97.87%, which proved the effectiveness of the solution.
Study of the Efficiency Coefficient of the Steganographic Embedding in Text Containers Using the Letter Replacement Method

The embedding efficiency is one of the important indicators for the steganographic methods. This article presents a study of this indicator when embedding hidden information in text containers using the letter replacement method. Containers in four different languages were studied and a comparison of the embedding efficiency in each of these languages was made.
Recognition Of Fingertip Movement Using Optical Flow For Human Machine Interface

Optical flow contains motion information of an object in a captured image, so it is often used as an image processing method for motion recognition. Today, optical flow precision and robustness have improved dramatically over the last few years and optical flow is widely used in many areas. The purpose of this research is to apply this technology and develop a new interface that uses optical flow to input human hand motion information. PCs have the physical limitation of needing a flat surface on which to place the keyboard and mouse. To overcome this difficulty, we aim to develop a new interface that can move the cursor and input characters by moving the hand in the air. We expect to function as an interface that allows cursor movement and character input in response to the operation, when a specific operation is performed.
Image Coding Based on Efficient Representation of Trivial Regions in Quantization

The article deals with an algorithm for coding trivial regions of quantized prediction errors for compressing digital images. The algorithm uses a special multilevel representation of these trivial regions. The multilevel representation improves the compression ratio of quantized prediction errors. The proposed algorithm for coding trivial regions of quantized prediction errors is considered for digital image compression based on pyramidal representation of images. Computational experiments are carried out to study the proposed coding algorithm for trivial regions of quantized prediction errors in natural images. The computational experiments confirm that the proposed algorithm for coding trivial regions of quantized prediction errors can provide a significant advantage during digital image compression. In addition, computational experiments also estimate the levels number of image pyramid that provide the best results
Balancing interests of authors and broad public

The authors investigate into the rules contained in the international treaties, Russian existing laws and judicial routine related to exclusiveness of authors’ rights. The character of social changes in the digital era were specified. Several types of legal relations remain traditional, however in today’s information society has to revise existing laws in which authors rights dominate over information user interests. At the same time, the authors re underprotected from piracy. Legislators have to prioritize in the first place who and from whom must be protected in the information society: the authros from pirates, intellectual property from plagiarism, or the users from actualaccessible information. Secondly, the rights of new knowledge have to be managed and efficient ways to righ t-ful transfer of accumulated knowledge to users have to be found. Implementation of information technologies into libraries and access to digital information resources change radically the quality of library services. The authors challenged themselves with attracting attention to the problems of information society in Russia.
“Yakety yak: Don’t talk back”: An autopsy of anonymity gone awry

This article compares the socio-legal factors and challenges contributing to the failure of the deceased anonymous, hyperlocal platform, Yik Yak, with a living anonymous, hyperlocal platform, Jodel. By analysing each platform’s Terms of Service (ToS) statements alongside their guidelines and values, the article traces how anonymous, hyperlocal applications both diverge from and mirror communication law in fashioning their approaches to content moderation and responses to the dark side of communication. The article concludes that in contrast with Yik Yak, which attempted to rely on its ToS and limited community monitoring system to curb cyberbullying and harassment, the case of Jodel—and by extension, the German approach to regulating hate speech and bullying—suggests that surviving hyperlocal, anonymous platforms of U.S. origin should not solely hide behind Section 230 of the Communications Decency Act (CDA). Instead, they should aim to combine (1) robust ToS statements with (2) specific community values or guidelines that are fortified by (3) a comprehensive monitoring system in order to curb abusive behaviour on their platforms.
The Design of Mini CNC Assembly Simulator Based on Virtual Reality Toolkit (VRTK)

Abstract Information and communication technology development today has provided the latest innovation in didactic world. One of such innovation is the usage of virtual reality (VR) as learning media. The application of virtual reality in learning environment started to be adopted because VR is considered more capable to explain learning material when compared with other learning material. Moreover, learning with VR has the capability for student to learn independently anytime and anywhere. One of VR utilization in learning environment is to use it in a Mini CNC machine assembly simulator. The learning media is meant to be used to improve student skill in assembling a Mini CNC machine independently. This research uses Research and Development method with waterfall model which has several stages which are communication, planning, modelling, construction, and deployment. However, this research only aims up to construction stage, because this research focuses on media functionality test. The media black box research has shown that the media is capable to function as expected.
Cell Image Stitching Algorithm Based on Retinex And Improved ORB

Due to the limited shooting range of microscopic imaging equipment, as well as the complicated factors such as the shooting environment and the cell tissue itself, the microscopic cell image is not clear in detail and the brightness is not equal. An algorithm based on Retinex and improved ORB for microscopic cell image registration and stitching is proposed. Firstly, the multi-scale Retinex algorithm is improved by homomorphic high-low-pass filtering to enhance the image, and the image feature extraction area is specified to improve the efficiency of algorithm execution. Then the improved ORB algorithm can be used to extract feature points, which can reduce feature point redundancy while reducing feature extraction time. Finally, the Laplacian multi-resolution fusion algorithm based on the optimal seam algorithm was used to eliminate the large color difference and ghosting on both sides of the stitch. The experimental results show that the algorithm has achieved better results in the quality and clarity of microscopic cell image stitching, and the efficiency of the algorithm has been improved.
Research on the Impact of Data Driven on the Cultivation of Innovative Talents in Economics Majors in China

With the application of Internet big data in the economic field, the requirements for the cultivation of innovative and entrepreneurial talents have been put forward for the current economic universities. Based on the current situation of my country's economic professional talents innovation training under the data-driven background, this article analyzes the impact of data-driven on the training of economic professional innovative talents in my country, and points out the problems in the training of economic professional innovative talents driven by data. And put forward targeted suggestions and opinions.
ARMixer: Live Stage Monitor Mixing through Gestural Interaction in Augmented Reality

Existing stage monitor mixing systems are inefficient and cannot accommodate the communication between the musicians and sound engineers. We introduce ARMixer, which allows musicians to perform self-stage monitor mixing through gestures in augmented reality to provide an intuitive mixing experience. We performed two usability tests and found that ARMixer is acceptable to the user and has excellent psychoacoustic intuitiveness in terms of mixing parameter controls by gestures and identifying mixing target.
Benchmarking Virtual Machine and Container-based Services for DNN Training

Containerized infrastructure is becoming the leading strategy for deployment and operation of software components including trending neural networks. Training neural networks requires computational resources and complex software environments with a lot of dependencies. In this regard, containers can solve some of the software related challenges. We perform benchmarks to compare the performances of containers inside a virtual machine and a bare metal model for training three artificial neural networks on two leading cloud providers. The results show negligible performance drawback for using containers in the stack tested on Google Cloud and clear performance advantages in Amazon Web Services.
The Feasible Study to Use The IP Camera for Doing The Online Physics Experiment

This pandemic time, the face to face learning has many constraints. Several online applications possibly do the lecture course. It can give the benefit as well as in-class learning. However, it is impossible to provide hands-on experiments, which is a significant objective of the laboratory. This paper proposes the feasibility study to apply the IP camera for doing online physics experiments of first-year engineering students. The simple harmonic motion experiment was an example for this study in order to recover the laboratory objective. The IP camera's pan and tilt functions are employed to do the experiment as a student's hand. Free mobile and computer applications, such as EYE4, are used as the student's eyes to observe the experiment's object movement. These are similar to hands-on interaction. This study found that this method is low cost and easy to modify and maintain the experiment by physics teachers. In addition, using the IP camera with physics experiments turns general online learning into hands-on interaction physics experiments to continuously train students' practical skills. The most beneficial of using an IP camera with a physics experiment is that the students can do the physics experiment from their homes in this global pandemic. However, this method depended on the internet speed, the smartphone performance, and the quality of the IP camera.
Identity Theft and Older Adults: How Minorities and the Poor Suffer the Worst Consequences

Abstract Society’s growing reliance on technology to transfer and store private information has created more opportunities for identity thieves to access personal data. Prior work using data from the National Crime Victimization Survey (NCVS) Identity Theft Supplement (ITS) showed that baby boomers were significantly more likely than Millennials to be victims of identity theft and that older people and minorities experience more severe economic and psychological consequences. This study examines how socioeconomic status, demographic characteristics, and incident-specific factors relate to how much money is stolen during identity theft, the likelihood of experiencing out-of-pocket costs, and emotional distress among identity theft victims age 65 and older. Using combined data from the 2014 and 2016 NCVS-ITS, this study examines the correlates of financial and psychological consequences of identity theft among 2,307 victims age 65 and older. Older Black victims are more likely to have greater amounts of money stolen and are more likely feel distressed than older non-Latino white identity theft victims. The most disadvantaged older adults living at or below the federal poverty level are nearly five times as likely to suffer out-of-pocket costs. The length of time information is misused and the hours spent resolving identity theft are significantly associated with emotional distress. More than one-third of older victims experience moderate to severe emotional distress following identity theft, and those who can least afford it suffer out-of-pocket costs. Greater advocacy and psychological support are needed to help older adults recover, in addition to tools to protect their personal information from misuse.
ALResNet: Attention-Driven Lightweight Residual Network for Fast and Accurate Image Recognition

research-article Share on ALResNet: Attention-Driven Lightweight Residual Network for Fast and Accurate Image Recognition Authors: Chang Lu College of Information Science and Technology, Jinan University, China College of Information Science and Technology, Jinan University, ChinaView Profile , Rui Wang College of Information Science and Technology, Jinan University, China College of Information Science and Technology, Jinan University, ChinaView Profile , Beibei Huang College of Information Science and Technology, Jinan University, China College of Information Science and Technology, Jinan University, ChinaView Profile , Yuan Li College of Information Science and Technology, Jinan University, China College of Information Science and Technology, Jinan University, ChinaView Profile , Zunkai Huang Shanghai Advanced Research Institute, Chinese Academy of Sciences, China Shanghai Advanced Research Institute, Chinese Academy of Sciences, ChinaView Profile , Yicong Zhou Department of Computer and Information Science, University of Macau, China Department of Computer and Information Science, University of Macau, ChinaView Profile , Aiwen Luo College of Information Science and Technology, Jinan University, China and Department of Computer and Information Science, University of Macau, China College of Information Science and Technology, Jinan University, China and Department of Computer and Information Science, University of Macau, ChinaView Profile Authors Info & Claims MLMI'21: 2021 The 4th International Conference on Machine Learning and Machine IntelligenceSeptember 2021 Pages 21–29https://doi.org/10.1145/3490725.3490729Online:29 December 2021Publication History 0citation59DownloadsMetricsTotal Citations0Total Downloads59Last 12 Months59Last 6 weeks3 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Blockchain Technology in Ecosystems

The complex human society needs a robust technological ecosystem that may interoperate cordially among the systems. As the systems are components, these components offer a variety of services for humankind. Services evolve and interact in a different manner and cater to numerous capabilities. These activities have many issues that need to be taken care of with the most advanced and secure technology. Blockchain is one such approach among the many approaches available. This study of blockchain technology will discuss its categorization. Also, it will address how and where all this recent technology has contributed to the ecosystem.
Index Matrix Representation of MapReduce Algorithm

In the current investigation the MapReduce algorithm is discussed. The idea for MapReduce is introduced initially in the field of functional programming languages. Thereafter various implementations of MapReduce are provided and it is successfully applied in many different data platforms for fast processing of large amount of data in parallel and distributed environments. The popular open source implementations are Apache Hadoop and Apache Spark. The MapReduce algorithm consists of two main functions: map and reduce. In the current investigation the authors present the MapReduce algorithm in the field of index matrices theory. The map and reduce functions are presented using index matrix operations. A numerical example is presented. Apache Spark implementation is visualized.
Mobile Smartphone as a Security and Surveillance Device

A general problem that comes with setting up a security system is the price of the hardware that is used for surveillance, the ease of setting up the hardware required for the system that is in use and the accessibility of the application controlling the system from the user’s perspective. This paper presents two different methods of solving this problem. Each method was done as a separate app. The main idea is to find a device that can run these apps without costing too much and that doesn’t require much knowledge from the end user. When implementing our security system we also have to look at two different possibilities of conducting the system. The first possibility is to use an external server for analyzing the video stream that was captured from our device, while the second possibility is to implement the entire process on the same device as the surveillance system. There are also two different methods in creating our automated security system. The first method is to implement it using conventional computer vision techniques, while the second method relies on neural networks for detecting and tracking our intruder. The first app was created using the Java programming language with the help of the OpenCV library and the SMTP library. While the second app uses both Java and Python programming languages with the help of the YOLO library.
DHQN: a Stable Approach to Remove Target Network from Deep Q-learning Network

As the first successful attempt to combine deep neural network and reinforcement learning, Deep Q-learning Network (DQN) draws a lot of attention from reinforcement learning researchers. One of the most important components of DQN is target network, which is used to stabilize learning process. When confront complex network structure, the existence of target network means extra memory resource to preserve the neural network weights and high computing cost to calculate target. Thus, we propose a Deep Hybrid Q-learning Network (DHQN) algorithm, which introduces an alternative approach, Random Hybrid Optimization (RHO), that can simplify DQN and attain a more stable and faster learning without a target network. We illustrate that RHO can decelerate divergence in the classical off-policy counterexample θ → 2θ problem. We also testify the effectiveness of DHQN in several control and Atari domains, which shows DHQN outperforms DQN without a target network and original DQN.