Miracle-dz/UniFAR-FTUs huggingface dataset:
Multilevel Polar Coded-Modulation for Wireless Communications

In wireless channels, the signal quality degrades mainly due to the additive noise and the random variation of attenuation of the signal, known as fading. The additive noise can be compensated to some extent using forward error correction (FEC) coding and automatic repeat request (ARQ). The fading can be compensated not only with FEC codes and ARQ schemes but also using spatial diversity and multiplexing achieved by employing multiple antenna systems, known as multiple-input multiple-output (MIMO) systems. MIMO schemes fall into different categories based on system requirements, e.g., space-time block codes (STBCs) and limited feedback schemes. FEC codes, as a method of substantial performance improvement, are employed in most modern communication systems. However, the optimal design of the concatenation of FEC codes and modulation schemes for different applications is an open problem. Polar codes are a new class of FEC codes that benefit from simple rate matching and a variety of low-complexity decoders which facilitate the design of efficient systems. Multilevel coding with multistage decoding (MLC/MSD) is a low-complexity capacity achieving coded-modulation technique that can be designed efficiently for polar codes due to the conceptual similarity. In this thesis, in order to achieve low-arithmetic-complexity/high-performance coded-modulation schemes for wireless channels, multilevel polar coded-modulation (MLPCM) schemes are designed and analyzed. To this end, new methods are proposed to decrease the MSD log-likelihood ratio estimation complexity and to improve the set-partitioning based bit-to-symbol mapping (SPM) design. Furthermore, some novel methods are proposed for the low-memory-space/low-arithmetic-complexity design of polar codes in additive white Gaussian noise and slow fading channels. In addition, a set of algorithms are proposed to design MLPCM based on the throughput for hybrid ARQ and channel-adaptive schemes. Moreover, to design the signal for MLC/MSD, a variety of multidimensional constellations are optimized using union bounds on the error rate of uncoded MIMO schemes, and their performance in the presence of polar codes is evaluated. Finally, MLPCM is designed in slow fading channels by optimizing STBCs based on the outage probability, generating SPM based on a bound on the outage, and the joint optimization of polar codes and STBCs.
A Novel Real-Time Multi-Phase BCI Speller Based on Sliding Control Paradigm of SSVEP

Speller had been proved that it’s a kind of well interactive manners for brain computer interface (BCI) system. In this study, we proposed a novel steady-state visual evoked potential (SSVEP) BCI speller developed for numerical input. Based on a previous off-line method of SSVEP recognition, a sliding control protocol was used for our real-time spelling task. For ten subjects, on-line experiments of 10 consecutive number inputs were conducted for two different control conditions. In contrast to traditional static protocol of multi-phase SSVEP signal extraction, the average information transmission rate (ITR) of sliding control protocol reached 23.45 bits/min, higher than that of traditional static protocol (19.85 bits/min). The results showed the validity and high-efficiency of sliding control paradigm for a real-time multi-phase SSVEP speller.
Cloud-Based Adjustable and Section Led Pattern Controlled Street Light

In this study, both the amount of light and the pattern control are focused on the street lamp, which can be managed over the cloud, which reduces energy consumption costs and can be applied according to the location. The proposed lighting unit is designed to be controlled and monitored remotely. The proposed street lighting provides specific lighting according to the lighting area. The lighting amount, position and fault conditions of the lamp can be monitored. Different control strategies have been proposed for various lighting scenarios. It is foreseen that this proposed system will be an innovative solution to existing lighting problems due to its practicality and efficiency.
The importance of interaction mechanisms in blended learning courses involving problem solving e-tivities

Blended learning is widely adopted by education agencies and organizations, as it is a flexible model in which face-to-face classroom practices are combined with computer-mediated activities. To overcome the limits of the loss of interaction between teacher and students and among students in distance learning, researchers proposed several solutions, conducting experiments in several teaching areas. Our interest is aimed at studying blended learning with a specific focus on those courses involving problem solving activities, through collaboration among students.Modern Learning Management Systems (LMS) allow to define virtual classrooms and offer various functionalities to support the class. At the same time, they are not designed to fully support all type of activities. Thus, they provide the possibility of integrating other more useful systems for more specific activities. A standard LMS has to be integrated using specific tools when problem solving activities are planned, to ensure effective collaboration among students. In this regard, there is no convergence towards a specific tool that can be used to carry out problem solving activities in collaboration.This paper aims to propose a minimal set of requirements for interaction mechanisms to support problem solving activities in a collaborative environment, in order to obtain better quality artifacts. We also report the results of a three-month experimental course (12 weeks) entitled ”Project Management: a look ahead”, based on blended learning and problem solving activities. The minimal set of requirements for interaction mechanisms was implemented using GitHub, that is not a teaching software, but it is a global software development tool which has powerful communication mechanisms. The results show that the aid of the proposed minimal set of requirements for interaction mechanisms significantly improves the quality of artifacts when problem solving activities are carried out.
A Centralized Building Energy Management System for Residential Energy Hubs

This paper proposes a framework for energy management in modern smart buildings under the context of integrated energy systems. The added value of this work is using the rolling time window framework for decision-making, along with the inclusion of the peak load tariffs. The rolling time window is used to send updated control commands near to real-time. A Swedish multi-family residential building is used in the case study. The results of the case study verify the effectiveness and the validity of the proposed model. The results show that by integrating the electricity and the district heating network with a 11 kW heat pump, the total energy cost reduces around 27%.
A Data Distribution Service in a Hierarchical SDN Architecture: Implementation and Evaluation

Software-defined networks (SDNs) have caused a paradigm shift in communication networks as they enable network programmability using either centralized or distributed controllers. With the development of the industry and society, new verticals have emerged, such as Industry 4.0, cooperative sensing and augmented reality. These verticals require network robustness and availability, which forces the use of distributed domains to improve network scalability and resilience. To this aim, this paper proposes a new solution to distribute SDN domains by using Data Distribution Services (DDS). The DDS allows the exchange of network information, synchronization among controllers and auto-discovery. Moreover, it increases the control plane robustness, an important characteristic in 5G networks (e.g., if a controller fails, its resources and devices can be managed by other controllers in a short amount of time as they already know this information). To verify the effectiveness of the DDS, we design a testbed by integrating the DDS in SDN controllers and deploying these controllers in different regions of Spain. The communication among the controllers was evaluated in terms of latency and overhead.
Development, implementation and evaluation of a wireless sensor network and a web-based platform for the monitoring and management of a microgrid with renewable energy sources

This paper describes the design, development and experimental validation of a wireless sensor network and a web-based platform for the monitoring and management of the INTA's microgrid, and shows the main results and conclusions of this integration. The work demonstrates how the management of renewable energy microgrids can be optimized through the deployment and implementation of low-power wireless monitoring networks, based on LoRaWan technology, integrated into an IoT platform with high data processing and storage capacity.
Dynamic Operation of a Storage Power Plant (SPP) with Voltage Angle Control as Ancillary Service

It is expected that in the near future, the electrical power supply networks will be significantly revolutionized. Today's conventional power plant structures will give way to a novel, inertia independent (free from rotating masses) power plant system. Such power stations, called storage power plants, will possess storages for different generation speed together with power electronic converters. They will be able to integrate and store energy from renewable sources. Since such a system will not possess any flywheels or rotating masses, thus frequency control as utilized in conventional power plants will be redundant. All the control principles necessary involving spinning reserve, primary and secondary control depending on frequency will be substituted by a comprehensive angle control of the nodal voltages in the transmission and distribution network. However, to be deemed truly feasible, these storage power plants must be able to function efficiently when they are integrated with conventional power plants and renewable energy sources. Thus, in this paper, these power plants are connected with conventional thermal and hydroelectric power stations as well as wind power plants, in a single network, and their dynamic behavior is studied under nodal voltage angle control as the ancillary service.
Pass in Human Style: Learning Soccer Game Patterns from Spatiotemporal Data

Passing patterns in soccer are one of the key characteristics of tactical team behavior. Thus, in the course of development of believable AI soccer teams, it is necessary to ensure that human-like passes are properly simulated. We propose learning passing behavior from real-life soccer teams and share experimental results, indicating that our approach indeed allows to obtain passing patterns similar to the ones present in human tracking data. We also show that a typical rule-based soccer AI team exhibits notable differences in passing behavior in comparison with real teams.
On D2D Caching with Uncoded Cache Placement

We consider a cache-aided wireless device-to-device (D2D) network under the constraint of one-shot delivery, where the placement phase is orchestrated by a central server. We assume that the devices’ caches are filled with uncoded data, and the whole file database at the server is made available in the collection of caches. Following this phase, the files requested by the users are serviced by inter-device multicast communication. For such a system setting, we provide the exact characterization of load-memory trade-off, by deriving both the minimum average and the minimum peak sum-loads of links between devices, for a given individual memory size at disposal of each user.
Cache-Aided K-User Broadcast Channels With State Information at Receivers

We study a <inline-formula> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula>-user coded-caching broadcast problem in a joint source-channel coding framework. The transmitter observes a database of files that are being generated at a certain rate per channel use, and each user has a cache, which can store a fixed fraction of the generated symbols. In the delivery phase, the transmitter broadcasts a message so that the users can decode their desired files using the received signal and their cache content. The communication between the transmitter and the receivers happens over a (deterministic) time-varying erasure broadcast channel, and the channel state information is only available to the users. We characterize the maximum achievable source rate for the 2-user and the degraded <inline-formula> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula>-user problems. We provide an upper bound for any caching strategy’s achievable source rates. Finally, we present a linear programming formulation to show that the upper bound is not a sharp characterization. Closing the gap between the achievable rate and the optimum rate remains open.
The Research Reviewed of Edge Network Active Safety Defense Technology

Edge computing network refers to a new paradigm of big data computing network on the edge side near the user or Internet of things, data source side, fusion network, computing, storage, and business core capabilities. The edge computing network is driven by the development of cloud computing and the Internet of things, its core is to face the massive uplink monitoring and acquisition produced by the intelligent sensing equipment, and the downlink decision control big data. This paper solves the problem of low performance of data computing in a centralized cloud computing model through edge side big data storage and computing. Compared with the traditional cloud computing network, the edge computing network has more terminal types, more frequent real-time data exchange, more complex transmission network technology system, and a higher degree of intelligent interconnection of business systems. However, the edge computing network is ubiquitous, and the open characteristics transmit the network security risk to every business link of the system, which faces severe security protection challenges. This paper focuses on the requirements of high real-time and high continuity of edge computing networks, and faces the dual constraints of the hybrid characteristics of edge computing networks and the uncertainty of new network attack characteristics, the present situation of active defense technologies such as detection, circumvention, deception, control and so on for edge computing network is summarized before serious damage is caused by edge computing network. This paper analyzes the security challenges faced by the existing technologies from four levels of terminal domain, data domain, network domain and system domain, and puts forward the urgent research trend
A Literature Analysis for the Identification of Machine Learning and Feature Extraction Methods for Sentiment Analysis

The increase in daily emails sent to the customer service of companies is creating new challenges. Sentiment analysis, i.e. the automated recognition of mood and polarity in texts, is a solution to this problem, but the sentiment analysis of German emails is still an open research problem. With the help of a literature analysis we identify and analyze the most relevant machine learning methods and the corresponding feature extraction methods.
Unsupervised Manifold Alignment for Cross-Domain Classification of Remote Sensing Images

The original manifold alignment (MA) approach is for semisupervised domain adaptation. Since the target prior information is difficult to obtain, we conduct it in an unsupervised manner, resulting in an unsupervised MA (UMA) method. This approach utilizes the probabilistic prediction results of target data to construct the cross-domain similarity matrix, which characterizes the relationships between domains and is used for alignment. Due to the spectral drift, the prediction results may not be accurate, and thus affect the alignment. We employed spatial filtering and overall centroid alignment method as two preprocessing strategies to improve the prediction results. Furthermore, per-class maximum mean discrepancy (MMD) constraint is introduced to the UMA to further improve the alignment performance. The proposed UMA_MMD algorithm is applied for the classification of remote sensing images, and the experimental results using hyperion multitemporal remote sensing images demonstrated the effectiveness of the proposed approach.
Two Contributions to Error Exponents for Asynchronous Multiple Access Channel

The following conjectures from previous work of the authors are proven, enhancing the relevance of results there on the subject in the title: (i) The error exponents previously derived assuming that consecutive messages could be encoded using different codebooks, are also achievable with each sender using only one codebook. (ii) In case the senders could be synchronized, controlled asynchronism (a deliberate shift of codewords) may admit to achieve error exponents unachievable by synchronous transmission.
Integrity of novel high-performance nanostructured insulation for high torque density propulsions

The All Electric Ship platform requires higher torque density and payload efficiency for marine propulsion and power generation. Nanostructured material for the ground wall insulation of high torque density propulsion has been successfully developed by dispersing 2D platelet clay in epoxy resin to achieve highly enhanced electrical, thermal, and mechanical properties. The integrity of the nanostructured material was validated over a wide range of temperatures and frequencies as well as under high electrical stress. Our studies show that the nanostructured insulation will impart 2X combined improvement in electrical and thermal performance over the state-of-the-art micaceous insulation. Machine uprating studies based on a 3.3 MW propulsion motor suggest an enhancement of torque density of ~15%. In this paper, the aging and voltage endurance characteristics of the nanostructured insulation was extensively investigated. Excellent discharge resistance, as a result of suppressing discharge intensity, of the nanostructured material promises an entirely contained nanostructured insulation system and game-changing insulation integrity.
Update Bandwidth for Distributed Storage

In this paper, we consider the update bandwidth in distributed storage systems. The update bandwidth is defined as the bandwidth when the data storage in a node is updated. The minimum update bandwidth for irregular array codes is provided. Further, we minimize the code redundancy when the update bandwidth is minimal. Finally, we introduce a class of vertical MDS codes that minimizes both update bandwidth and code redundancy.
Location-Aware Targeted Influence Blocking Maximization in Social Networks

In this issue, we consider the location-aware targeted influence blocking maximization (LTIBM) problem, which plays a very important role in viral marketing and rumor control. LTIBM aims to find a set of positive seeds in a given social network to block the influence propagation of negative seeds over the targeted nodes located in a given region and having a preference on a given topic set as much as possible. We devise a simulation-based greedy algorithm based on monotone and submodular characteristics of influence function under the homogeneous independent cascade model. To improve the efficiency of the greedy algorithm, we propose LTIBM-H, a heuristic algorithm based on QT-tree and maximum influence arborescence (MIA). Experimental results show that the proposed LTIBM-H algorithm can achieve matching the blocking effect to the greedy algorithm and often performs better in terms of effectiveness than other baseline algorithms, while LTIBM-H is four orders of magnitude faster than the greedy algorithm.
SDN/Cloud Solutions for Intent-Based Networking

The approach of SDN and NFV integration in cloud environment for Intent-Based Networking has been proposed. The method to provide the required QoS level is developed. For this purpose in the hours of the largest load, in case when all physical resources of the network are used, proposed to deploy additional network resources in the cloud. And vice versa, when the network load is lower-undeploy not used resources. This will allow us to unload the physical network and maintain the required QoS level. Also, since this process will occur automatically– we can minimize the human factor for setting up equipment and reduce network elements deploying time to a minimum. This approach can be used for both SDN switches and SDN controllers. Proposed to serve in cloud traffic that is not sensitive to sending time and delays. It will unload the physical network for sensitive services.In this paper we present the QoS balance formula for the hybrid network (physical and in cloud) and the scheme of such network is presented. The advantages and disadvantages are analyzed.
Turning Sensor Networks into Distributed Antenna Arrays for Improved Communication Performance

We study the potential of using sensor networks as distributed antenna arrays for improved packet reception performance. In many sensor network applications, nodes can be distinguished according to their roles. Backbone (or ground) nodes establish a core network used to deliver data to a (possibly central) sink, whereas mobile nodes transmit sensor readings to this backbone. In the case of errors, the transmitted information is either lost or must be repeated. Considering very energy constrained nodes, such retransmission is often prohibitive. Making use of the spatial distribution of such a ground network means that macrodiversity can be exploited. By combining received signal samples from multiple ground stations, the chance of successful decoding can be substantially improved. Using a specific wildlife monitoring application, we demonstrate the advantages of this concept. To the best of our knowledge, this is the first work to make use of a sensor network as a distributed antenna array, which offers many possibilities in upcoming Internet of Things applications.
A Tester of the MEMS Accelerometers Operation Modes

The work deals with the issues of analyzing the operation modes of integrated circuits of MEMS accelerometers using built-in self-test functions and motion detectors. Test measurement techniques are intended for compensation for the time instability of the measurement track of an accelerometer. Test measurement techniques consist in formation of periodical deflection of a preset magnitude inside inertial parts of MEMS structures. Motion detectors are implemented using an integrated memory management system with a 32-level first in first out buffer. The work is aimed at developing a tester of operation modes and searching patterns in the characteristics of MEMS accelerometers inside IMU modules. The subject of study is the accelerometer ADXL345 inside the IMU module GY-SO. We have formulated basic requirements for procedures of investigation into the parameters of accelerometers and other components of IMUs. Upon the formulated requirements we have developed a hardware-software tool IMUTester. The work presents examples of investigation into the operation modes of MEMS accelerometers ADXL345 including the test measurement and detection modes.
Approach to Estimate the Level of Influence of Motivation on the Effectiveness of Employees9 Depending on Their Needs

This article deals with the approach to the estimate of the influence of motivational factors of the personnel at work. The analysis of the impact of the motivation of staff performance is proposed on the basis of the developed scale of estimation of the level of influence of the motivational factors of different groups of needs for labor productivity. To determine the impact of each motivational unit on a specific performance indicator, an approach to the calculation of performance indicators based on the weighting factors of the influence of these groups is proposed.