Miracle-dz/UniFAR-FTUs huggingface dataset:
Coordinated wind power dispatch model for an integrated heat and power system by a novel scenario-dependent algorithm

Combined heat and power (CHP) units required to meet high heat demands over heating periods in North China have high power injections into electrical grids, greatly aggravating the wind generation curtailment. To deal with this issue, this paper develops a coordinated wind power dispatch model for the CHP units which are integrated with a thermal energy storage (TES) and an electric boiler (EB) placed at the CHP thermal output side and power demand side respectively. The dispatch model optimises the operation of all the components integrated within the system by minimising the total dispatch cost associated with electricity and heat generation and wind curtailment. The CHP thermoelectric coupling constraint is decoupled based on a scenario decomposing strategy where the feasible operation region of CHP units is converted into inequality constratins, permitting to solve the economic dispatch problem by the use of a scenario-dependent elitist genetic algorithm combind with an interior point method. The coordinated dispatch model is tested on a modified IEEE 30-bus system with different combinations of TES and EB. The dispatch results show that the proposed model can optimise the schedules of TES and EB to maximise the use of wind generation and lower the overall dispatch cost across the plan time horizon. In addition, the relationship between the EB heat-supply propotion and the dispatch cost is discussed.
Radial basis function artificial neural network model to estimate higher heating value of solid wastes

ABSTRACT Waste combustion is considered as a promising method of energy production due to their proper higher heating value (HHV) to be used as fuels. In this study, HHV values are estimated using a radial basis function artificial neural network (RBFANN) combined with Levenberg Marquardt algorithm as the optimization method. HHV values are predicted using mass percentages of water, carbon, oxygen, hydrogen, nitrogen, sulfur, and ash in the solid waste. The proposed RBFANN is then compared with other available correlations, revealing a great accuracy in prediction of HHV values with mean squared error (MSE) and R2 values of 0.248 and 0.997, respectively. Therefore, the proposed RBFANN is considered a reliable predictive tool to estimate the wastes’ HHV values.
Energy-Efficient Uplink Power Control in NOMA Enhanced Cell-Free Massive MIMO Networks

The ever-increasing communication requirement of the next generation network imposes great challenges in the existing cellular architecture and requires energy-efficient resource allocation. In this paper, we consider a cell-free (CF) massive multiple-input multiple-output (MIMO) network, where a large number of distributed access points with multiple antennas simultaneously serve a smaller number of users in a geographic coverage without cell boundary. To alleviate the limitation of orthogonal resource and further enhance network capacity, non-orthogonal multiple access is applied to the CF massive MIMO network in both channel training and uplink transmission phases. First, we derive the closed-form expression of uplink transmission rate by taking into account the imperfect channel state information (CSI) caused by pilot contamination and channel statistics. Second, based on the obtained uplink rate expression, an energy efficiency (EE) maximization problem is formulated by optimizing power control scheme, and we propose a low-complexity algorithm to address the non-convex optimization. Finally, simulation results validate that the designed algorithm can improve EE significantly compared to benchmarks in different CSI cases and network setups.
An Improved Bit-Flipping Based Decoding Algorithm for Polar Codes

In this paper, we propose three improved bit flipping algorithms in successive cancellation (SC) decoding and successive cancellation list (SCL) decoding. Weighted single-bit flipping successive cancellation (WSFSC) decoding first performs SC decoding on the output sequence, T bits with the smallest product of channel capacity and absolute value of LLR are regarded as unreliable bits. In multi-bit flipping successive cancellation (MFSC) algorithm, the unreliable bits are respectively corrected according to the single-bit flipping and multi-bit flipping rules. In single flipping successive cancellation list (SFSCL) algorithm, by subtracting a large penalty value from the path metric (PM) value of the unreliable bit, the decoding path corresponding to this bit is more likely to be pruned during path screening, so as to realize bit flipping indirectly. Simulation results show that the proposed WSFSC and MFSC algorithm has a gain of 0.3dB compared with the traditional SC algorithm, SFSCL algorithm has a gain of 0.3dB compared with the traditional SCL algorithm.
Review on Leaf diseases detection using Deep learning

Agriculture is the most critical part of the Indian economy so to prevent production loss, disease attacks must be predicted and treated early. In plants with differing climatic conditions, disease is very normal and natural which decreases the crop productivity. Study into the use of image processing techniques for plant disease identification has become a hot subject in order to address these issues. Deep learning (DL) is the golden age of machine learning (ML), and it is now helping to identify and classify plant diseases early. This review investigates and analyzed recent methods on Deep learning, Transfer learning and convolution neural network for crop disease detection. First, a look at the deep learning architectures, data sources and various image processing techniques that were used to process the imaging data. Many DL architectures have recently been adopted, along with visualization tools, which are critical for identifying signs and classifying plant diseases. We also go through some of the unsolved issues that must be tackled in order to create functional automated plant disease recognition systems that can be used in the field.
Bit Error Rate Performance of Hybrid Interleaver in Turbo Codes

An Interleaver is a component or a system tool that is useful for saving processing time by rearranging the input bitstreams. The approach to design a hybrid interleaver is to cascade different interleavers such as the 3rd generation partnership project interleaver and block interleaver et cetera. As the number of bits increasing, the memory and time required for coding and decoding increases due to which some applications completely avoid using interleavers to save time resulting in high Bit error rates. This paper proposes a method to design a cascaded, two-stage, hybrid interleaver and also analyzes its bit error rate performance. The hybrid interleaver reduces coding and decoding times of turbo codes and maintains good bit error rate levels that are achieved in other interleavers such as the 3rd generation partnership project interleaver and block interleaver.
Bringing BPM to the Workers: Towards Worker-Centric Management of Business Processes

Workﬂow management systems, as originally conceived, tried to impose structure to work, in a way similar to the assembly line. While imposing constraints may be needed because of regulations and compliance, it is important to recognize that much of knowledge work is done in an ad-hoc fashion. Case management is an admission that ad-hoc work exists, and an attempt to adjust to the ﬂexibility of work. Unfortunately, it still requires some explicit steps. With recent changes in the nature of knowledge work, enterprises have increased the adoption of online communication tools such as chat and collaborative documents. Ad-hoc work has become the new norm, and knowledge workers are increasingly utilizing these communication tools to resolve and complete cases. In this work, we argue that business process management solutions need to engage workers in the channels where they already work and outline the challenges of bringing the tools to these environments.
Hardware Chip Performance of CORDIC Based OFDM Transceiver for Wireless Communication

The fourth-generation (4G) and fifth-generation (5G) wireless communication systems use the orthogonal frequency division multiplexing (OFDM) modulation techniques and subcarrier allocations. The OFDM modulator and demodulator have inverse fast Fourier transform (IFFT) and fast Fourier transform (FFT) respectively. The biggest challenge in IFFT/FFT processor is the computation of imaginary and real values. CORDIC has been proved one of the best rotation algorithms for logarithmic, trigonometric, and complex calculations. The proposed work focuses on the OFDM transceiver hardware chip implementation, in which 8-point to 1024-point IFFT and FFT are used to compute the operations in transmitter and receiver respectively. The coordinate rotation digital computer (CORDIC) algorithm has read-only memory (ROM)-based architecture to store FFT twiddle factors and their angle generators. The address generation unit is required to fetch the data and write the results into the memory in the appropriate sequence. CORDIC provides low memory, delay, and optimized hardware on the field-programmable gate array (FPGA) in comparison to normal FFT architecture for the OFDM system. The comparative performance of the FFT and CORDICFFT based OFDM transceiver chip is estimated using FPGA parameters: slices, flip-flops, lookup table (LUTs), frequency, power, and delay. The design is developed using integrated synthesis environment (ISE) Xilinx version 14.7 software, synthesized using very-high-speed integrated circuit hardware description language (VHDL), and tested on Virtex-5 FPGA.
Intrusion Detection Systems Using Blockchain Technology: A Review, Issues and Challenges

Intrusion detection systems that have emerged in recent decades can identify a variety of malicious attacks that target networks by employing several detection approaches. However, the current approaches have challenges in detecting intrusions, which may affect the performance of the overall detection system as well as network performance. For the time being, one of the most important creative technological advancements that plays a significant role in the professional world today is blockchain technology. Blockchain technology moves in the direction of persistent revolution and change. It is a chain of blocks that covers information and maintains trust between individuals no matter how far apart they are. Recently, blockchain was integrated into intrusion detection systems to enhance their overall performance. Blockchain has also been adopted in healthcare, supply chain management, and the Internet of Things. Blockchain uses robust cryptography with private and public keys, and it has numerous properties that have leveraged security’s performance over peer-to-peer networks without the need for a third party. To explore and highlight the importance of integrating blockchain with intrusion detection systems, this paper provides a comprehensive background of intrusion detection systems and blockchain technology. Furthermore, a comprehensive review of emerging intrusion detection systems based on blockchain technology is presented. Finally, this paper suggests important future research directions and trending topics in intrusion detection systems based on blockchain technology.
Process Mining with Common Sense

We argue that, with the growth of process mining in breadth (variety of covered tasks) and depth (sophistication of the considered process models), event logs need to be augmented by commonsense knowledge to provide a better input for process mining algorithms. This is crucial to infer key facts that are not explicitly recorded in the logs, but are necessary in a variety of tasks, such as understanding the event data, assessing their compliance and quality, identifying outliers and clusters, computing statistics, and discovering decisions, ultimately empowering process mining as a whole.
Holistic Summarization of Recommender Systems Results

Item-centric summaries of recommender systems results fail to provide an overall perspective on consumer satisfaction because they focus on features and aspects of suggestions. However, the appreciation of items is not only a matter of liking their properties. The whole process of their fruition, which might involve interacting with services and other actors, should be taken into account to enhance user awareness and decision-making. To address this issue, we present a visual summarization model that supports a holistic overview of search results by exploiting an explicit representation of the service underlying item fruition as a basis to measure multiple user experience evaluation dimensions. We instantiated our model on the home-booking domain. A preliminary user study has shown its usefulness as an information filtering tool to screen recommendation lists down to a small set of promising options.
A Physical Layer Experimentation Framework for Automotive WLAN

Future cars will be equipped with communication modules that allow them to exchange information directly with each other and potentially infrastructure nodes, forming a Vehicular Ad Hoc Network (VANET). Through communication, cars will be able to coordinate and drive cooperatively, which will make transportation safer, more efficient, and more comfortable than ever before. One of the considered technologies for vehicular networks is IEEE 802.11p, a slightly modified version of consumer Wireless LAN (WLAN) that was adapted to better fit the characteristics of vehicular environments. While the decision to rely on readily available technology might ease market introduction, it also raises the question whether a physical layer that was designed for relatively static indoor environments can provide reasonable performance in highly dynamic VANETs. Using Software Defined Radios (SDRs), i.e., fully programmable radios, we are able to address this question, as they allow us to closely examine and modify the physical waveform. We made SDRs accessible for research on VANETs by implementing the first IEEE 802.11p transceiver for GNU Radio, a popular real-time signal processing framework for use in SDRs. Performing all signal processing on a PC, our transceiver is well-suited for rapid prototyping and can be used for simulations as well as real-world experiments, offering a seamless switch from theory to practice. In the first part of the thesis, we detail the design of our IEEE 802.11p transceiver, study its computational complexity, and present results from thorough validations through simulations and interoperability tests. We furthermore show that it is possible to support time-critical functionalities like channel access and automatic gain control without giving up the advantages of a PC implementation. In the second part, we use our transceiver to address selected research questions in VANETs. Here, we conduct field tests to compare the performance of different devices and algorithms in realistic environments and study the impact of noise and intra-technology interference on IEEE 802.11p. Finally, we show a use-case for our transceiver that goes beyond signal processing: With full access to all information down to the physical layer, we develop a novel, robust attack on the location privacy of vehicles and study its impact through network simulations.
Vibration-Based Pattern Password Approach for Visually Impaired People

The pattern password method is amongst the most attractive authentication methods and involves drawing a pattern; this is seen as easier than typing a password. However, since people with visual impairments have been increasing their usage of smart devices, this method is inaccessible for them as it requires them to select points on the touch screen. Therefore, this paper exploits the haptic technology by introducing a vibration-based pattern password approach in which the vibration feedback plays an important role. This approach allows visually impaired people to use a pattern password through two developed vibration feedback: pulses, which are counted by the user, and duration, which has to be estimated by the user. In order to make the proposed approach capable to prevent shoulder-surfing attacks, a camouflage pattern approach is applied. An experimental study is conducted to evaluate the proposed approach, the results of which show that the vibration pulses feedback is usable and resistant to shoulder-surfing attacks.
The Discrete Median and Center Line Segment Problems in the Plane

Let P be a set of n points in the plane. The discrete median line segment of P is the line segment with both its endpoints in P such that the sum of the distances from P to the line segment is minimized. Similarly, the discrete center line segment of P is the line segment bounded by two points of P such that the maximum of the distances from P to the line segment is minimized. We present exact algorithms for computing the discrete median and center line segments of P . Our algorithms run in O ( n 2 ) time and use O ( n 2 ) space.
Performance Analysis and Throughput Enhancement of the STET Technique for WLAN IEEE 802.11ad

The IEEE 802.11ad innovation has enabled the impact of remote devices in unauthorized 60 GHz unlicensed frequency band at Giga bits per second information transfer rate in speed concentrated 5G applications. We have presented an innovative work that deals with the upgradation of the ability of IEEE 802.11ad wireless LAN to make it suitable for wireless applications. An exact examination on the IEEE 802.11ad analysis has been carried out in this work to achieve the greatest throughput. This has pulled attraction in broad consideration for accomplishing the pinnacle transmission rate of 8 Gbit/s. IEEE 802.11ad is a convention utilized for extremely high information rates (around 8 Gbit/s) and for short range remote correspondence of around 1 to 10 meters. The Multi-layer with Multi-User Multiple Input Multiple-Output (MLMU-MIMO) innovation has enabled transmission of multiple information packets all the while from the WLAN IEEE 802.11 ad Access Point (AP) to various receivers by means of different wireless applications. To help the MLMU-MIMO innovation at Medium Access Control (MAC), a new method called Simultaneous Transmission for Enhanced Throughput (STET) has been presented for enhancement of the transmission rate of the wireless standard. A mathematical model has been used for the evaluation of the performance of an IEEE 802.11ad AP empowering the STET allocation technique. This STET model can help determination of the throughput improvement of a STET technique, for example, audio information, images, good quality and foundation impact. The main goal of this work is to analyze the improvement of the STET allocation technique in regard to the usage of rare frequency band, when obtaining spectrum access between the various access points. The theoretical and simulation outcomes are also confirmed by Riverbed modeler 17.5 simulation tool.
User compliance and remediation success after IoT malware notifications

Internet Service Providers (ISPs) are getting involved in remediating Internet of Things (IoT) infections of end users. This endeavor runs into serious usability problems. Given that it is usually unknown what kind of device is infected, they can only provide users with very generic cleanup advice, trying to cover all device types and remediation paths. Does this advice work? To what extent do users comply with the instructions? And does more compliance lead to higher cleanup rates? This study is the first to shed light on these questions. In partnership with an ISP, we designed a randomized control experiment followed up by a user survey. We randomly assigned 177 consumers affected by malware from the Mirai family to three different groups: (i) notified via a walled garden (quarantine network), (ii) notified via email, and (iii) no immediate notification, i.e. a control group. The notification asks the user to take five steps to remediate the infection. We conducted a phone survey with 95 of these customers based on communication–human information processing theory. We model the impact of the treatment, comprehension, and motivation on the compliance rate of each customer, while controlling for differences in demographics and infected device types. We also estimate the extent to which compliance leads to successful cleanup of the infected IoT devices. While only 24% of notified users perform all five remediation steps, 92% of notified users perform at least one action. Compliance increases the probability of successful cleanup by 32%, while the presence of competing malware reduces it by 54%. We provide an empirical basis to shape ISP best practices in the fight against IoT malware.
User-friendly Query Interfaces for the HOPE Project

The paper introduces the current state of an ongoing research project devoted to the study and development of a user-friendly query interface to access open data. More specifically, the interface has been conceived so to enable simplified queries over heterogeneous data from different sources, such as public governmental sources or private structured repositories. This has been done by expanding the functionalities of an already existing interface for querying knowledge bases. The aim of this paper is showing the main interface features, highlighting the research questions they respond to and the open issues we intend
Dense Matrix Multiplication Algorithms and Performance Evaluation of HPCC in 81 Nodes IBM Power 8 Architecture

Optimizing HPC systems based on performance factors and bottlenecks is essential for designing an HPC infrastructure with the best characteristics and at a reasonable cost. Such insight can only be achieved through a detailed analysis of existing HPC systems and the execution of their workloads. The “Quinde I” is the only and most powerful supercomputer in Ecuador and is currently listed third on the South America. It was built with the IBM Power 8 servers. In this work, we measured its performance using different parameters from High-Performance Computing (HPC) to compare it with theoretical values and values obtained from tests on similar models. To measure its performance, we compiled and ran different benchmarks with the specific optimization flags for Power 8 to get the maximum performance with the current configuration in the hardware installed by the vendor. The inputs of the benchmarks were varied to analyze their impact on the system performance. In addition, we compile and compare the performance of two algorithms for dense matrix multiplication SRUMMA and DGEMM.