Miracle-dz/UniFAR-FTUs huggingface dataset:
Object registration for visual inspection operations

Describes the positioning module of a visual inspection system for dimensional verification. The system operates in two phases: learning and test. In the learning phase, the operator performs a set of inspection operations on the image of the prototype piece, while in the test phase the system processes the image of a piece that belongs to the class considered in the learning phase. For this purpose, the position of the test piece has to be determined. The authors represent the prototype and test pieces by attributed relational graphs (ARG) in which the nodes describe closed contours while the arcs represent their mutual relationships. Positioning is obtained by means of a graph matching technique based on a hypothesize and verify cycle. The authors use a hierarchical approach for graph matching; first they look for node correspondences (operating on a contour matching level), then they find the graph match by hypothesizing an arc correspondence and evaluating its consequences on the whole graph. <<ETX>>
A Study based on a bank of Kalman Filters design for Gas Turbine Accessory Fault Detection

This paper proposed a novel method integrating system identification of experimental data from hydraulic actuator rig with kalman filters for fault detection and isolation of a gas turbine accessory. Application of experimental data from hydraulic actuator rig for fault detection and isolation (FDI) of a gas turbine accessory which is of great interest to industry is proposed. The hydraulic actuator rig is designed to simulate different gas turbine accessory fault. The faults that typically occur in practice injected into real hardware subsystems to record the precise response. Through using this very realistic data the fault models are then established. Then these models are incorporated into the gas turbine engine simulation. In order to realize this, the transfer function based on the experimental data from the rig has been setup and integrated into the diagnostic algorithms for the aircraft gas turbine engine. Integration of actuator fault diagnostic algorithms was investigated and the injected faults can be detected successfully. The approach proposed in this paper can be used for online fault detection and isolation accurately, which is of practical significance for engine system.
Evaluation of IoT and videosurveillance applications in a 5G Smart City: the Italian 5G experimentation in Prato

The fifth generation (5G) cellular network is expected to bring disrupting services to the market, not only in terms of increased bandwidth, but also for mobile users, Internet of Things devices, and industrial control scenarios. Even though the standardization process is still ongoing, some field trials are already planned or starting. The aim of the field trials is to offer practical highlights to the telecom and service operators about the effective possibility to promptly use the new technology as soon as the first devices will hit the market. As a matter of fact, there are still a number of open issues about 5G, and it is expected that the field trials will offer good insights about any potential pitfall before an actual deployment. In this paper we will offer an overview of the 5G standardization status, and we will describe two of the field trials that will be conducted in Prato (Italy) in the 5G Italian experimental project.
Research on the Method of Multi-source Information Fusion Based on Bayesian Theory

Facing with the incompleteness and uncertainty of target damage information, the integrated method of multi-source information fusion and bayesian theory is put forward by using target damage rank from multi-source information fusion. Target damage information are fused by calculating maximum posterior probability of characteristic information through bayesian network information fusion model, and the feasibility of multi-source information fusion method is verified by example analysis.
Fast trajectory tracking based on flatness control for a high voltage AC-DC-AC power system

The main objective is to design a fast trajectory tracking control for a complete high voltage DC (HVDC) power system connecting wind generators to an AC grid which also incorporates conventional converters. For such nonlinear dynamics an original flatness-based feedback is derived which enables the controlled shifting from one to another steady state without inducing any appreciable transient. Simulation results are presented which well confirm the predicted behaviour.
Depression and antidepressants in Australia and beyond: A critical public health analysis

In Australia and most developed countries, depression has vaulted from an obscure affliction to a high-profile modern epidemic, accompanied by a significant escalation in antidepressant prescribing. A strong orthodoxy has developed that depression is common, serious, and treatable, and that the appropriate treatment is antidepressants. However, there are public health and social grounds for questioning this orthodox story. Vastly more people are being diagnosed with depression, and treated with antidepressants, now than several decades ago. Yet diagnosis of depression is subjective, and is based on highly criticised criteria. Furthermore, the evidence that underpins the orthodoxy is weak and biased, and this is compounded by biased interpretation and selective reporting, particularly in relation to clinical trials of antidepressants.Two analytical approaches are used in this thesis. The first is critical analysis of the objective validity of specific claims and assumptions about depression and antidepressants, using a mixture of epidemiological analysis and critical appraisal skills from the evidence-based medicine field. The second approach is a broad analysis of strategies used by advocates of the orthodoxy. This includes an analysis of how claims about depression and antidepressants and related issues such as suicide are deployed in the depression arena, focusing on what claims have been made, by which players, in which contexts, for which reasons, and with what impact. Also analysed are pharmaceutical industry marketing strategies, and strategies used by other players such as psychiatrists and consumer organisations, all of which often utilise claims about depression and so on.The orthodox story has been promoted by many players, including psychiatrists, pharmaceutical companies, marketing companies, health professional organisations, consumer organisations, governments and government agencies, and the media. These players interact in complex ways, based on overlapping and synergistic agendas.Key players have strongly promoted the orthodox story, despite contrary evidence, systematically exaggerating the prevalence and severity of depression and the effectiveness and safety of antidepressants for both depression and suicide prevention. Pharmaceutical companies have played a key role in the establishment and maintenance of the orthodoxy, skilfully recruiting other players to their cause.A detailed case-study analyses how key players, including prominent psychiatrists and consumer advocacy organisations and pharmaceutical companies, have succeeded in making depression a central focus of Australian mental health policy, fuelling the boom in antidepressant prescribing. Not only have antidepressants been remarkably successfully and profitably sold in Australia, but also depression has been reified and marketed as an all-purpose explanation for distress. As well as exposing many thousands of people to adverse effects of antidepressants, this has deflected attention from social determinants of well-being.
Review on Cost-Value Approach for Requirements Prioritization Techniques

The use of appropriate requirements prioritization techniques is crucial to the success of a software development project. There are many techniques offered with all the advantages and disadvantages of each. The question that come up frequently when doing requirements prioritization is “whether the priority list is generated based on customer’s required value? ” and “whether the value is generated comparable with the cost incurred for implementation? ”. This paper aims to conduct an empirical systematic review to identify and review the requirements prioritization studies based on the cost-value approach. This literature review generates many insights including: reduction of pairwise comparisons, factors and aspects of cost-value, features that support cost value and cost-value constraints.
The Study of Pedestrian Re-Identification with the Illumination Change

Pedestrian re-identification has caused the extensive concern of many scholars, but due to the problems such as illumination, pedestrian posture change and keep out, there is a lot of room for the study of pedestrian re-identification. Based on the influence of illumination change on pedestrian recognition, a new method of pedestrian re-identification which adapt to the change of light is proposed in this paper. Firstly, a candidate set of pedestrian features is established, and the local characteristics of pedestrian images are extracted based on the Bag-of-words model. Secondly, a number of sample subsets are obtained to simulate a variety of illumination scenarios. Based on the KISSME algorithm, the measurement matrix of single-illumination scene and cross-illumination scene was obtained. According to the scene, the corresponding measure matrix is selected to represent the similarity between pedestrians. Finally, a comprehensive decision scheme based on multi-feature recognition results is established to obtain the final result of pedestrian recognition. It is proved by experiment that the method of this paper can have a good recognition effect in the environment with the change of illumination.
Sentiment Analysis and Topic Modelling for Identification of Government Service Satisfaction

The era of information disclosure and social media tends to make people express their opinions on social media. Indonesia is one of the top five nations social media users in general, especially Twitter. This becomes an interesting thing when trying to see public opinion on a government service. Opinion mining can be used to get information from textual twitter to be processed into an information by classifying existing information into positive information classes and negative information classes. In this research, we try to do opinion mining on public opinion about Identification card (KTP) service in Surabaya city. We compare between supervised and unsupervised methods to see their performance for each classifier. In unsupervised the sentiwordnet approach is used to classify between negative and positive opinions. Supervised Support Vector Machine (SVM) method is used to create a classification model to define an opinion. Before the data is classified, preprocessing steps are used to make the data better. In addition, the Latent Dirichlet Allocation (LDA) approach is used to see for topics that tend to be strong which affects a negative or positive opinion. The result of the classification model by using SVM achieved accuracy rate of 75%.
Representation and Comparison of Uncertain Temporal Data Based on Duration

Although temporal data are often uncertain, especially in humanities, an appropriate standard method has not been established for operating them for retrievals and analysis. This study considered representing uncertainty of temporal data based on duration. Uncertain duration, which is a continuous range, was applied to represent duration of an uncertain time interval and temporal distance between two time intervals. Additionally, this study examined relation between two values of uncertain duration and observed that the relation portrayed three states, namely reliable, possible, and impossible. If these representations and relations are implemented using semantic Web technology and provided as Linked Data, uncertain temporal data are expected to be effectively used for retrieval, analysis, and other purposes.
Method for Comparative Analysis of Bullet Marks Based on the Multi-dimensional Feature Extraction

This paper presents the method for comparative analysis of 3D bullet mark data and proposes the technology of realizing accurate comparative analysis by extracting multidimensional features of bullet data. In our approach, the first step is to denoise the data, and then extract multidimensional feature, finally we make the comparison of coarse level to fine level. The experimental results demonstrate the effectiveness of the method.
Region growing for MRI brain tumor volume analysis

The tumor volume is a significant prognostic factor in the treatment of malignant tumors. Manual segmentation of brain tumors from MR images is a challenging and time consuming task. A semi-automated region growing segmentation method is proposed to segment brain tumor from MR images. The proposed method can successfully segment a tumor provided that the parameters are set properly. This method is applied to 8-tumor contained MRI slices from 2 brain tumor patients' and satisfactory segmentation results are achieved.
Genetic algorithm based control for unbalanced low voltage networks

There always exist unbalance in low voltage networks. It has adverse effects like current increase and voltage drops below regulatory limits in the most loaded phase, presence of current in the neutral conductor, over-voltage problems in the least loaded phase, and feeder tripping due to neutral overcurrent. Classic solutions involve grid reinforcements. In this paper a control methodology that may be applied to any unbalanced network is proposed. A real unbalanced low voltage network was modeled and simulated with OpenDSS and Matlab. The proposed control based on genetic algorithm found the least number of phase swaps required to restore voltage violations. It resulted in percentage voltage unbalance factor improvement and 18% losses reduction.
Dynamic Selection Method for Cooperative Decision-Making Center of Multi-UAV System based on Cloud Trust Model

This paper is devoted to designing a kind of dynamic selection method for cooperative decision-making center of multi-UAV system. In cooperative multi-UAV system with mixed and layered structure, the individual of cooperative decision-making can be called Decision-Making Center (DMC). The random fault of individual or interference, deception and malicious attack to the DMC will lead to the instability of the system. Traditional method based on formation leader selecting is feasible in normal environment, but not available when the cooperative system has been deceived or interfered. The existing methods will produce a certain deviation, even the system is deceived or intercepted. According to all of above problems, the ability of decision to provide the DMC has been modeled as its trust value, include trust degree (TD) and reputation degree (RD). Through the information which is interacting between UAVs and using of the Cloud Model to enhance the adaptability of the environmental uncertainty, a new method defined as Dynamic DMC Selection based on Cloud Trust Model (DDMCSCTM) has been built. It can adaptively select the best DMC in environment of deceived and interfered. Experimental results show that it can achieve better effect.
User Authentication Protocol Based On Chebyshev Polynomial For Wireless Sensor Networks

Aiming at the security problem of external users access to the wireless sensor networks, a new user authentication protocol with a key exchange function under the public-key system was proposed, the protocol based on the Chebyshev polynomials over finite fields have good chaos characteristic, semi-group property and the one-way trapped characteristic. This protocol can achieve the authentication process between user and network base station or sensor nodes, and completes the initialization of session key in the process of authentication. The analysis shows that the proposed protocol can meet the needs of the wireless sensor network for security authentication, and also has a good performance in authentication time, interaction, computational complexity, and security attacks.
Distributed Voltage Equalization Design for Supercapacitors Using State Observer

The switched shunting resistor circuit is a classical and practical passive equalization scheme that nevertheless suffers from the voltage imbalance after the charging process. It results from the discrepancy of the shunting resistor and the physical characteristics of supercapacitor (SC) cells. In this paper, the distributed voltage equalization control strategies with the proportional-integral (PI) observer for the switched shunting resistor circuit are analyzed and compared. First, the charging and equalizing system is modeled as the switched system and the system observability is proved. The decentralized control and consensus control are analyzed and their shortages are presented. Then, the leader–follower cooperative control is proposed to improve the charging time while keeping the equalization performance. Meanwhile, the PI observer is designed to estimate the internal capacitance voltage of an SC precisely to avoid the effect of equal series resistance. The control convergence is proved by using the Lyapunov stability and switched system theory. The experimental results show that the proposed method has much superiority and wide applicability than the existing methods for equalizing voltages of SCs.
Neutron Irradiation Impact on AlGaN/GaN HEMT Switching Transients

Current transient spectroscopy was used to measure the impact of neutron irradiation on output current-limiting charge traps in AlGaN/GaN high electron mobility transistors with time constants from 10 ms to 1800 s. We find that coupling between discrete traps was apparent, in contrast to the commonly employed assumption of independent trap (dis)charging, and increased after 14-MeV neutron irradiation of <inline-formula> <tex-math notation="LaTeX">$2 \times 10^{13}\,\,\text {n/cm}^{2}$ </tex-math></inline-formula> and above. Irradiation to a high dose of as much as <inline-formula> <tex-math notation="LaTeX">$7.8 \times 10^{14}\,\,\text {n/cm}^{2}$ </tex-math></inline-formula>, which is comparable to eight years exposure to a harsh radiation environment, such as the International Thermonuclear Experimental Reactor neutral-beam injector prototype, increased trapped charge density and reduced transient drain current to as little as 75% of its equilibrium value. These changes are consistent with displacement damage estimates based on the radiation transport calculations.
DEMAND Project: Bottom-Up Aggregation of Prosumers in Distribution Networks

The paper explains the concept of the DEMAND project, whose aim is to develop a technical framework for allowing a Bottom-Up aggregation of prosumers connected to the distribution grid. Load and generation aggregation is a very current issue given the great potential that the coordinated management of distributed resources has on power systems operation and design. The novelty in DEMAND is the absence of a physical aggregator and the recourse to a virtual aggregation environment (VAE) for allowing the exchange of information among the prosumers in order to provide a service to the DSO. After a general description of the research project, the paper presents the services that the aggregated community can offer to the grid, the components to be installed at the prosumer’s facility for the participation to the DEMAND community and the steps of the flexibility bidding and provision phases.
Defining of Lyapunov Functions for the Generalized Nonlinear Object

The paper d eals with the development of a method for defining of Lyapunov functions. This method is based on usage of coordinate transformations for both linear and nonlinear dynamical objects. One can use proposed method for definition of Lyapunov functions, which can be used as a basis for stability analysis. Positiveness and continuity of the above-mentioned functions are guaranteed by using the complete square technique while coefficients of Lyapunov functions are defined. Lyapunov functions which are defined into such way can be converted into various state spaces. Such transformation allows us to get non-quadratic Lyapunov functions for nonlinear dynamic objects and quadratic for linear ones. While one use Lie derivatives for performing coordinate transformation he can reduce the order of Lyapunov function, which is obtained for a controllable dynamical object.
A Common Base of Knowledge for Japanese Historical Materials and its Application

In the paper we describe the fundamental elements for handling and managing Japanese historical information such as catalogue, image, text, spatial, temporal, personal name, and introduce an application using the fundamental elements. Our Institution (The Historiographical Institute, the University of Tokyo) has been constructing and providing the information related to Japanese history and Japanese historical materials for more than 130 years. There is a diversity of data items for the materials, because data items added by some factors such as collections, eras and types are different. In order to make it easy to use the collected historical materials, we set fundamental items of them. We explain the features of each element. We will also describe the applications using that elements and their effects.
Analysis of Solar Rechargeable Airplane

In this paper, main goal focused on analysis for solar rechargeable airplane. This analysis has in configuration flow parameters that represent time and location of the starting point, solar cells performance and surface area, energy storage characteristics with initial state and power distribution for on-board systems. Simulation provides full continuous flight day performance for available power acquired from the Sun during the flight time, required power that unmanned aerial vehicle actually use and on-board battery bank’s state of charge.
A novel grid-based bidirectional local search algorithm for many-objective optimization

The balance between the convergence and diversity is the most important mission in evolutionary multiobjective optimization (EMO). Many studies pay attention to the convergence but neglect the diversity maintenance. In order to accomplish these two goals simultaneously, the proposed grid-based bidirectional local search algorithm (GrBLS) is capable of finding a set of solutions which have better convergence to the real Pareto optimal front as well as better distribution. The GrBLS uses grid-based framework to select the better individual in evolution generation. Through the different punishment degree in environmental selection process, the best solutions can be gotten from the previous population. Three state-of-the-art EMO algorithms are chosen to compare with GrBLS method by employing four classical performance indicators. The experimental results show that GrBLS method is able to obtain better spread of solutions and better convergence than the others algorithms. The results indicate that the excellent performance of the GrBLS method is suitable for handling multiobjective optimization problems.
Study of interactions among control, defense, and protection systems in small systems with HVDC links and large penetration of renewables

High Voltage Direct Current (HVDC) links help to integrate large amounts of power from Renewable Energy Sources (RES), however they may interact in complex ways with the control, defense, and protection systems of the power grid. The paper analyses some of the stability phenomena and interactions that may affect small systems weakly connected with the bulk power system via HVDC links, and characterized by low inertia, low short circuit power, and high production from RES. To this purpose, detailed time-domain simulations are performed, based on phasor models, to study severe disturbances such as short circuits close to the AC terminals of HVDC link. The stability outcome is significantly dependent on the control and defense system parameters. A sensitivity analysis is performed and the resulting changes in system performance indicators are discussed.