Miracle-dz/UniFAR-FTUs huggingface dataset:
A New Design of a Compact Metamaterial Antenna for RFID Handheld Applications

The development of miniature antennas is the key requirement for radio frequency identification applications in various fields. In this paper, a new design of a compact metamaterial microstrip antenna based CSRR resonators is proposed. The proposed metamaterial antenna has a simple structure. It is formed by a rectangular patch embedded a T-shaped slot in one side, and a two metamaterial unit cells formed by CSRR etched from the ground plane in the other side. The designed antenna is printed on an epoxy Frame Resistant 4 substrate by using CST Microwave Studio. It operates at two RFID bands around 5.8GHz and 2.45GHz. The designed antenna is fabricated by using an LPKF machine. The simulation results have been justified by measuring the parameters, respectively.
Survey on Intrusion Detection System Types

Intrusion detection system (IDS) is one of amongst the most essential consideration of cyber-security that can discover intrusion before and/or after attack occur. An Intrusion detection system is software or hardware designed to detect any malicious activity or attack against the system or network. The main contribution in this paper is to present an overall review of IDS types that are deployed in various environments. So many IDS researches have mostly described the types of IDS. However, their description has addressed a specific area and there is a lack of researches that present an overall review of IDS types. This paper conducts a review of different types of IDSs related to different environments and platforms through a comparative approach. Also, it presents a classification of IDS types based on criteria such as platform and input data. It introduces their significant features, advantages and disadvantages of each type. The finding out of this survey have been coming from our analysis of the current research and trends of the field. In this paper has addressed the lack of IDS types research and many points of research have been figured out as a future work.
IMPROVING VOLTAGE STABILITY ON SINGLE PHASE GRID CONNECTED PHOTOVOLTAIC SYSTEM BY USING STATIC VAR GENERATOR.

This paper investigate to solve the issues in the system using a shunt controller ,in order to improve the voltage quality in case of small voltage drops and in unbalanced load conditions. The maximum power is obtained from the PV panel by using the incremental conductance algorithm (MPPT) technique . In this paper a repetitive controller is used to reduce the selected harmonics. This paper consists of single phase PV system which is connected to the grid which reduces the harmonic distortions and provides voltage support in the system . The designed PV system provides grid voltage support at fundamental frequency and compensation of harmonic distortion at the point of common coupling. An inductance is added on the grid side in order to make the grid mainly inductive. In this paper ,the PV converter not only supplies the power produced by the panel but also improves the voltage stability. IndexTerms Maximum Power Point Tracking(MPPT),Distributed power generation system(DPGS),phase-locked loops(PLL).
A Novel Technique Using Multiple K-Shingling Based Weighted Dissimilarity Score for Web Content Outlier Mining

: The technological evolution of Internet and Web along with several applications leads to the problem of redundancy as the documents are unanimously forwarded and are stored in several servers and platforms. Recently, not only duplicate documents but also near-duplicate documents affect the performance of the search results. The main objective of this paper is to provide significant documents by eliminating the redundancy and near redundancy documents present in the web search results. The proposed model comprises of two phases such as pre-processing phase and dissimilarity computation phase. For dissimilarity computation, the proposed model employs multiple k-shingling based dissimilarity score to identify the duplicate and near-duplicate documents which are considered as the outliers present in the set of input web documents. The proposed model has been evaluated using several experimental analysis. As there are no real datasets available for duplicate detection, datasets have been created and the performance evaluation is carried out with the created datasets. Several statistical analysis has been made wherein the average specificity, sensitivity, precision, and accuracy are 87%, 93%, 80%, and 92% respectively. The comparative analysis has also been made with various existing methods, in which the proposed model provides better results than existing methods in removing near-duplicates. The proposed multiple k-shingling based weighted dissimilarity model effectively detects the duplicates and near-duplicates when the number of outliers is minimum.
Communicability of traditional interfaces VS chatbots in healthcare and smart home domains

ABSTRACT This paper presents a study about communicability of conversational interfaces (namely chatbots) under a semiotic perspective. A chatbot is a software system that allows you to simulate real conversations between devices and users by means of a conversational interface (CI). After introducing the chatbot concept, focusing on its advantages and issues, we will present two domains of use in which chatbot interfaces can be effective: healthcare and smart home. For carrying out simple tasks such as finding information or triggering operations, users need an easy-to-use and to an easy-to-learn system to communicate with. To face this, conversational interfaces represent the latest trend in the field of digital design. For studying the communicability aspects of a CI, we carried out a user test to compare traditional and chatbot interfaces. This paper aims at evaluating the benefits at the communicability level of a chatbot in comparison to traditional GUI for incrementing the effectiveness and efficacy of communication between users and the system specifically for users with poor attitude in using technologies. In details, we evaluated the communicability of two prototypes that can be used to solve simple tasks in order to favour user inclusion, including everyone with very little exposure to technologies.
Data Mining Technique as Majors Support System Management with Classification Approach

Majors systems in an educational institution both at the primary level and higher education are the main thing. The academic potential of students becomes one of the main factors in supporting the success of learning. Even in an admission system, entrance test cannot be separated from the potential academic test. The academic potential test is only used as a standard of acceptance, and very rarely even never used to be information that can classify students into a specialization. Analysis of potential academic data with various variables will be very much so that required Data Mining techniques to mining of the larger data. The purpose of this research is to implement of Data Mining technique with classification approach to analyze academic potency in the major supports system management. The classification technique is applied as the object of research and measured its performance to obtain information according to the needs and objectives of the study. The results showed that the implementation of classification techniques could provide information that indicates the academic potential in major support system management, so this research can be a reference to create a system of potential academic search in general and can be implemented as an applicable tool in major support system management.
Recent advances in video coding beyond the HEVC standard

The standardization process for Versatile Video Coding (VVC), the next generation video coding standard, was launched in 2018, after several recent advances in video coding technologies had been investigated under the Joint Video Experts Team (JVET) of ITU-T VCEG and ISO/IEC MPEG experts. The recent standard development status (up to VVC working draft 2) shows that the VTM software, the test model for this VVC standard, can achieve over 23% average coding gain under random access configuration when compared to the HM software, the test model of HEVC standard. This paper gives a review of recently developed video coding technologies that have been either adopted into the VVC working draft as part of the standard or under further evaluation for potential inclusions.
Research on Genetic Algorithm for Optimization of File Transmission

An edge coloring model for this problem is given. Genetic algorithm is a high paxallel, random and self-adaption search algorithm developed in reference to natural slection and the system of evolution in biology cycle. To solve the file transmission problem, a new genetic algorithm for file transmission problems is developed by introducing a new method with self adaptive commute and mutate probability. The structure of the genetic algorithms is provided and its genetic algorithm operators are discussed. This paper gives an example to illustrate the convergence property and the convergence efficiency of the algorithm. Simulation shows that this method is effective.
Experimental investigation into the volatilities of highly oxygenated organic molecules (HOM)

Abstract. Secondary organic aerosol (SOA) forms a major part of the tropospheric submicron aerosol. Still, the exact formation mechanisms of SOA have remained elusive. Recently, a newly discovered group of oxidation products of volatile organic compounds (VOC), highly oxygenated organic molecules (HOM), have been proposed to be responsible for a large fraction of SOA formation. To assess the potential of HOM to form SOA, and to even take part in new particle formation, knowledge of their exact volatilities would be essential. However, due to their exotic, and partially unknown, structures, estimating their volatility is challenging. In this study, we performed a set of continuous flow chamber experiments, supported by box modelling, to study the volatilities of HOM, along with some less oxygenated compounds, formed in the ozonolysis of alpha-pinene, an abundant VOC emitted by the boreal forests. Along with gaseous precursors, we periodically injected inorganic seed aerosol into the chamber to vary the condensation sink (CS) of low volatility vapours. We monitored the decrease of oxidation products in the gas phase in response to increasing CS, and were able to relate the responses to the volatilities of the compounds. We found that HOM monomers are mainly of low volatility, with a small fraction being semi-volatile. HOM dimers were all of at least low volatility, but probably of extremely low volatility: however, our method is not directly able to distinguish between the two. We were able to explain the volatility of the oxidation products in terms of their carbon, hydrogen, oxygen and nitrogen numbers. We found that increasing levels of oxygenation correspond to lower volatilities, as expected, but that the decrease is less steep than would be expected based on many existing models for volatility, such as SIMPOL. The hydrogen number of a compound also explained its volatility, independently of the carbon number, with higher hydrogen numbers corresponding to lower volatilities. This can be explained in terms of the functional groups making up a molecule: high hydrogen numbers are associated with e.g. hyrdoxy groups, which lower the volatility more than e.g. carbonyls, that are associated with a lower hydrogen number. The method presented should be applicable to systems other than α-pinene ozonolysis, and with different organic loadings in order to study different volatility ranges.
Accessing Big Data in the Cloud Using Mobile Devices

The amount of data acquired, stored, and processed annually over the Internet has exceeded the processing capabilities of modern computer systems, including supercomputers with multiple-Petaflop processing power, giving rise to the term Big Data. Continuous research efforts to implement systems to cope with this insurmountable amount of data are underway. The authors introduce the ongoing research in three different facets: 1) in the Acquisition front, they introduce a concept that has come to the forefront in the past few years: Internet-of-Things (IoT), which will be one of the major sources for Big Data generation in the following decades. The authors provide a brief survey of IoT to understand the concept and the ongoing research in this field. 2) In the Cloud Storage and Processing front, they provide a survey of techniques to efficiently store the acquired Big Data in the cloud, index it, and get it ready for processing. While IoT relates primarily to sensor nodes and thin devices, the authors study this storage and processing aspect of Big Data within the framework of Cloud Computing. 3) In the Mobile Access front, they perform a survey of existing infrastructures to access the Big Data efficiently via mobile devices. This survey also includes intermediate devices, such as a Cloudlet, to accelerate the Big Data collection from IoT and access to Big Data for applications that require response times that are close to real-time.
Multi-Agent Traffic Signal Control System Using Deep Q-Network

In urban areas, temporal and economic losses due to traffic congestion are getting worse. It has a great influence on our lives. As a cause of traffic congestion, on ordinary road, inappropriate signal switching may be cited. Parameter manipulation in the general signal control is set based on experiences by human hands, and it is never optimal. Therefore, controlling traffic lights to improve traffic behavior is possible way to solve traffic congestion. In this study, we combine multi agent system with Deep Q-Network method. We used an intersection as an agent and conducted experiment in road environment with multiple intersections. As a result, it was shown that agents can perform appropriate parameter manipulation by mutual exchange of information among agents.
A Building-Block Approach to State-Space Modeling of DC-DC Converter Systems

Small-signal models of DC-DC converters are often based on a state-space averaging approach, from which both control-oriented and other frequency-domain characteristics, such as input or output impedance, can be derived. Updating these models when extending the converter by filters or non-trivial loads, or adding control loops, can become a tedious task, however. To simplify this potentially error-prone process, a modular modeling approach is being proposed in this article. It consists of small state-space models for certain building blocks of a converter system on the one hand, and standardized operations for connecting these subsystem models to an overall converter system model on the other hand. The resulting state-space system model builds upon a two-port converter description and allows the extraction of control-oriented and impedance characteristics at any modeling stage, be it open loop or closed loop, single converter or series connections of converters. The ease of creating more complex models enabled by the proposed approach is also demonstrated with examples comprising multiple control loops or cascaded converters.
A Power and Latency Aware Cloudlet Selection Strategy for Multi-Cloudlet Environment

Fast interactive response in mobile cloud computing is an emerging area of interest. Execution of applications inside the remote cloud increases the delay and affects the service quality. To avoid this difficulty cloudlet is introduced. Cloudlet provides the same service to the device as cloud at low latency but at high bandwidth. But selection of a cloudlet for offloading computation at low power is a major challenge if more than one cloudlet is available nearby. In this paper we have proposed a power and latency aware optimum cloudlet selection strategy for multi-cloudlet environment with the introduction of a proxy server. Theoretical analysis show that using the proposed approach the power and the latency consumption are reduced by approximately 29-32 and 33-36 percent respectively than offloading to the remote cloud. An experimental analysis of the proposed cloudlet selection scheme is performed using cloudlets and cloud servers located at our university laboratory. Theoretical and experimental results demonstrate that using the proposed strategy power and latency aware cloudlet selection can be performed. The proposed approach is compared with the existing methods on multi-cloudlet scenario to demonstrate that the proposed approach reduces the power consumption and the system response time.
Design and function analysis of permanent magnet-type bearingless motor

Aimed at the design specifics of the permanent magnettype bearingless motor including torque winding and suspension winding, a new approach was proposed for realizing the optimal design of rotor structure, suspension winding and the motors permanent magnet thickness. An analytical expression of levitation force for a permanent magnettype bearingless motor was suggested with the location of the eccentricity between stator and rotor taken into consideration, and the computation accuracy of the expression was verified by electromagnetic field analysis.The control system of the permanent magnettype bearingless motor was obtained by applying the force model. The simulation results show that the proposed design approach improves the torque and suspension performance, and that the motor has excellent static and dynamic performance.
Improved adaptive stereo matching algorithm with double dynamic programming with row and column

Among various stereo matching algorithms,the one with dynamic programming can effectively improve speed and precision with good real-time performance and easy realization.This paper,based on advantages of dynamic programming algorithm,presents a self-adaptive stereo matching algorithm using dynamic programming with row and column,which uses improved adaptive support-weight approach and energy minimization model to solve the optimization problem,during which gives the corresponding data items different reward values to reduce apparent defective stripes,rested on the change of the initial disparity on the direction of column derived with dynamic programming algorithm with row,and finally acquires the final solution using dynamic programming algorithm with column.Experimental results show that the proposed algorithm can reduce the overall matching error rates and apparent defective stripes and get a better stereo matching effect.
Nested Monte Carlo Tree Search as Applied to Samurai Sudoku

As Sudoku has come into prominence as a favorite logic puzzle, mathematicians and computer scientists alike have analyzed the game for interesting properties. The large search space presents a challenge for both generating and solving Sudoku puzzles without relying on techniques that simply permute a valid puzzle. These permutations result in puzzles that are essentially the same since they follow the same solution path. Many Sudoku generating or solving programs rely on brute-force methods to avoid this pitfall, but this is inefficient since there is no heuristic to navigate the huge search space. A nested Monte Carlo tree search has some basis in brute-force methods, but guides the search in order to achieve better results by using random games within nested search stages. In this paper, we show that when the nested Monte Carlo search algorithm is implemented for solving Samurai Sudoku, a version of Sudoku in which a standard Sudoku puzzle is placed with four other standard Sudoku puzzles overlapping on each of the corners, it performs better than a completely random brute-force algorithm. Additionally, an improvement to the nested Monte Carlo search is made by implementing a heuristic that is used at each level of search.
Sampling Methods for Multiresource Forest Inventory

Focus, Fundamental Concepts, and Theory. Probabilistic Sampling Strategies. Forest Sampling--Single Level. Multi-Information Sources for Sampling. Model-Based Inference. Mensurational Aspects of Forest Inventory. Related Sampling Topics. Related Estimation Topics. Future Directions in Multiresource Sampling in Forestry. References. Answers to the Problems. Index.
Research on Digital Sound Spreading-Frequency Modulation Based on Hyperchaos Sequence

Compared with ordinary chaos systems, hyperchaos systems have excellent security in communication because hyperchaos sequence has better complexity and randomicity. The thought of applying dimension-lowered hyperchaos sequence to spreading-frequency communication is proposed. A dimension-lowered model is designed to generate hyperchaos sequence with well-proportioned stochastic diffusion, then the capability of hyperchaos sequence is analyzed in defail. The sound spreading-frequency modulation model based on hyperchaos random sequence is tested by practical circuit experiments. Measuring results verify the validity of designing thought. Another idea is briefly introduced for the deep research into spreading-frequency secrecy communication technique.
Deep learning methods towards infotainment systems

Automotive vehicles are sophisticated systems embedding with many subsystems such as infotainment, power-train, exterior light, etc. CEVT has been developing automated testing using auto-generated python scripts to execute various functions on expensive equipment to investigate these systems’ behavior. It is time-consuming to execute test scripts. In this thesis we investigate and develop an RNN based log-ﬁle prediction method in order to improve the automated testing eﬃciency. Further-more, a generative adversarial model for data augmentation has been investigated to verify whether the prediction performance can be further improved. The results show that the LSTM detection system can achieve around 86% accuracy on a small data-set and it can save up to 60% of execution time to improve the test eﬃciency.
Coloured Petri Nets as a formalism to represent alternative models for a discrete event system

Coloured Petri nets (CPN) constitute a formalism that belongs to the paradigm of the Petri nets, used to model discrete event systems (DES). This formalism has been extensively used to represent complex systems and shows its full potential when arise a large number of subnets with the same static structure thanks to the folding process. In this paper a completely new application of the Coloured Petri nets is presented. It implies a conceptual variation in the traditional scope of use of the CPN. The coloured Petri nets will be used to represent sets of alternative Petri nets. In other words, they will represent a set of exclusive models for a single DES by means if a unique CPN. The main advantage in this application of the coloured Petri nets is that they can be used to develop efficient algorithms to solve optimization problems based on Petri net models.