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Da più di quarant’anni il tema dell’intelligenza artificiale è studiato da diverse prospettive nel suo rapporto con il diritto e con i sistemi giudiziari. L’articolo propone alcune riflessioni sullo stato attuale di questo rapporto e sulla infondatezza della paura ancestrale che la macchina possa sopraffare l’uomo o comunque possa sostituirlo in tutte le attività nelle quali è necessaria la ragionevolezza e non solo la razionalità.

In uno scenario sempre più connotato dall’impatto delle tecnologie su nozioni e processi giuridici, lo spazio virtuale non rappresenta certo una garanzia per la promozione dell’eguaglianza tra i generi. A questo proposito, il contributo si sofferma sulle nuove forme e articolazioni che la violenza contro le donne assume sul web, per giungere a delineare possibili strategie di contrasto nel solco della normativa vigente

This paper examines the application of Information Communication Technology (ICT) tools by lawyers to simplify the task of legislative drafting of Bills and legislation. Using case studies in Nigeria and Canada some examples of the application of ICT to legislative drafting are examined. The idea of use and application of ICT tools for legislative drafting in Nigeria was first mooted in Nigeria in 1992 by the late Professor Keith Patchett during the Nigerian course in Legislative Drafting held in London. The lawyers that participated in the said course returned to Nigeria and trained other lawyers including Dr. Tonye Clinton Jaja, who led a team of computer experts to design a simple software for legislative drafting. Regarding Canada, Chantal Lamarre explains how the application of ICT for legislative drafting can improve the overall legislative process.

This study proposes a robust second-order terminal sliding mode control with perturbation estimation (2OTSMCPE) strategy with application to trajectory tracking control of the flexure-based nanopositioning system. The proposed controller advantages not only lie on its finite-time convergence but also can provide a high tracking precision with a chattering alleviation which is attend by employing a second-order sliding surface with the switching function. The model of the piezo-driven nanopositioning system is presented first. Second, the sliding variable is designed such as proportional–integral–derivative form to enhance the dynamic response of the control system. Then, a non-singular terminal sliding function (NTSM) is used to achieve the finite-time convergence of the linear sliding variable. Next, a perturbation estimation technique is integrated with the control structure for online estimation of the system uncertainties, thus the prior knowledge of the bounds of system uncertainties are not needed in the proposed control design. Afterwards, the theoretical analysis of the 2OTSMCPE with stability proof is investigated herein. Finally, the system performance with the proposed controller is experimentally verified. The results reveal that the 2OTSMCPE has stronger robustness and also has smoother control signals in comparison with both conventional sliding mode control and the NTSM controller.

This research was conducted in order to get an overview from the teaching staff on pirated software. The results acquired were an overview about pirated software, the use of pirated software, the price and willingness to switch to original software. In general, the perception of respondents stated that they knew about pirated software (66.67%), those who did not know (28.07%) and a small proportion were still in doubt (5.26%) regarding this matter. However, almost half of the respondents said that they did not know that the laptop used pirated software (49.12%) and those who knew about it are 21.05%. Small proportion of respondents (19.82%) are still in doubt whether their laptop uses pirated software or not. Respondents who agree (62.28%) original software is expensive, are willing to buy (72.81%) do not want to buy and are hesitant (20.18%). Respondents who disagreed (17.54%) original software was expensive, hesitant to obtain it legally (7.02%). The use of pirated software takes other people's rights (77.19%) and also violates the Copyright Law (79.82%) and disagrees (12.28%) on this. Respondents who were still in doubt were 10.53% and 7.89%. Respondents want to switch (72.81%), not willing (7.02%). The hesitation to move is 20.18%. Only a small proportion (27.19%) of respondents who do not know where to buy it, those who know (41.23%). Not sure where to get it (31.58%).

The rapid development of the covid-19 virus requires learning and teaching to be carried out online or remotely, the online learning process is carried out to break the chain of spreading the covid-19 virus. In the application of online learning STAIN Tengku Dirundeng Meulaboh uses an e-learning application developed with a codeigniter framework. The use of the existing MVC method in the Codeigniter framework can facilitate the development of e-learning applications that must adapt to user needs, therefore a study was conducted to determine the effectiveness of STAIN Tengku Dirundeng Meulaboh e-learning users during the Covid-19 pandemic. Measuring the effectiveness of this is done through a questionnaire by asking several questions to measure user satisfaction based on the End User Computing Satisfaction (EUCS) method. Based on the research results, it was found that 94% of e-learning users were greatly helped in the learning process and the level of user satisfaction was 85%.

Allineare le misure di sicurezza informatica ai requisiti previsti dall’articolo 32 del GDPR costituisce una delle difficoltà principali che le organizzazioni devono affrontare nei loro processi di conformità complessiva al GDPR. Tale difficoltà è certamente giustificata da alcune criticità proprie del tema specifico delle misure di sicurezza, come ad esempio il vastissimo ambito in cui esse sono implementate, la grande diversità di misure implementabili e il necessario coinvolgimento di diverse figure professionali. L’articolo 32, inoltre, non precisa quali misure debbano essere implementate, né tantomeno quali misure possano considerarsi adeguate, ma si limita a fornire un elenco non esaustivo di possibili misure. Pertanto, un’analisi della giurisprudenza delle autorità di controllo europee può rappresentare un utile contributo sia per individuare con precisione le misure informatiche ritenute inadeguate (anche al fine di verificare l’applicazione uniforme dei criteri di sicurezza) che per accompagnare gli operatori di settore nei loro processi di conformità. Per raggiungere tale obiettivo, sono state analizzate diverse decisioni emesse da autorità di cinque paesi (Italia, Regno Unito, Spagna, Francia e Danimarca), e le vulnerabilità rilevate sono state raggruppate in macrocategorie: accountability, gestione degli accessi, utilizzo di applicazioni obsolete e protezione dei dati. Il quadro che emerge dall’analisi è un approccio sostanzialmente uniforme da parte delle autorità di controllo, le quali sembrano concordare sia sul carattere inadeguato di alcune misure rilevate sia sul carattere adeguato di misure alternative discusse nei provvedimenti. L’interesse sul tema potrebbe d’altronde essere esteso in un futuro lavoro all’analisi delle politiche sanzionatorie e correttive adottate dalle autorità.

Processing data in an institution or organization has become an activity or routine for each meeting. In processing data, of course there are various kinds of problems, ranging from missing data, either because of an error in entering data or the result of a system failure. To overcome these problems, in an agency or company must have data backup, so as to create problems that occur in the data, the institution still has data backup. To call, another method of database replication is used. From the test results obtained data on the value of RTA (Round Trip Average) that is the time required for one time sending and receiving data from the replication database is 5426.22 ms and for compilation service diagrams a query attack occurs with a percentage of 29% in the database applications that produce 1774.45 ms results and for service diagrams at a query attack percentage of 29% a single database estimates the server down .

The purpose of this research is to produce a valid web-based learning media, practical, and effective in basic computer and networking subjects. This web-based learning media is designed to improve student’s understanding so that it can improve to learn the outcomes. The method in this study uses Research and Development (R and D) with 4-D development procedures (Define, Design, Develop, Desseminate). The data of analysis technique uses descriptive analysis techniques to describe the validity, practicality, and effectiveness of web-based learning media. The results obtained of this development research: The validity of web-based learning media is declared valid on the media and material aspects. The practicality of web-based learning media from teacher and student responses is stated to be very practical. The effectiveness of web-based learning media is stated to be effective in improve to learn the outcomes. Based on the findings of this study it is concluded that the web-based learning media is valid, practical, and effective to be used as a learning aid in basic computer and network subjects.

Computer vision is an important cornerstone for the foundation of many modern technologies. The development of modern computer-aided-surgery, especially in the context of surgical navigation for minimally invasive surgery, is one example. Surgical navigation provides the necessary spatial information in computer-aided-surgery. Amongst the various forms of perception, vision-based sensing has been proposed as a promising candidate for tracking and localisation application largely due to its ability to provide timely intra-operative feedback and contactless sensing. The motivation for vision-based sensing in surgical navigation stems from many factors, including the challenges faced by other forms of navigation systems. A common surgical navigation system performs tracking of surgical tools with external tracking systems, which may suffer from both technical and usability issues. Vision-based tracking offers a relatively streamlined framework compared to those approaches implemented with external tracking systems. This review study aims to discuss contemporary research and development in vision-based sensing for surgical navigation. The selected review materials are expected to provide a comprehensive appreciation of state-of-the-art technology and technical issues enabling holistic discussions of the challenges and knowledge gaps in contemporary development. Original views on the significance and development prospect of vision-based sensing in surgical navigation are presented.

To solve the problem of uncertain parameters in dynamic modelling of upper-limb rehabilitation robots, a dynamic parameter identification method based on variable parameters particle swarm optimisation (PSO) is developed. Based on the dynamic model of the system, the algorithm changes the inertia parameter and learning law of the basic PSO algorithm from the fixed-parameter to the function that changes with the number of iterations. It solves the problems of small search space in the early stage and slow convergence speed in the later stage of the basic PSO algorithm, which greatly improves its identification accuracy. Finally, through the comparison and analysis of the simulation results, compared with those of the least square (LS) and unmodified PSO identification algorithms, a great improvement in the identification accuracy of the algorithm is achieved. The control effect in the actual control system is also much better than those of the LS and PSO algorithms.

In this study, a robust controller is proposed for rollover risk suppression in automatically-driven vehicles by reducing the lateral acceleration through a steer-by-wire system equipped on the vehicles. First, since the slip angle is difficult to measure directly, a sliding mode observer combining an add-on switching term with a linear observer is developed to provide more robust estimation of slip angle in the presence of system uncertainties. Second, an adaptive sliding mode control method is proposed, in which the control gain is adaptively tuned to compensate for the system uncertainties. Lastly, simulation is conducted and the results verify that the proposed estimator and controller can reduce the vehicle rollover risk efficiently and robustly.

A key challenge associated with myoelectric prosthesis limbs is the acquisition of a good quality gesture intent signal from the residual anatomy of an amputee. In this study, the authors aim to overcome this limitation by observing the classification accuracy of the fusion of wearable electromyography (EMG) and near-infrared (NIR) to classify eight hand gesture motions across 12 able-bodied participants. As part of the study, they investigate the classification accuracy across a multi-layer perceptron neural network, linear discriminant analysis and quadratic discriminant analysis for different sensing configurations, i.e. EMG-only, NIR-only and EMG-NIR. A separate offline ultrasound scan was conducted as part of the study and served as a ground truth and contrastive basis for the results picked up from the wearable sensors, and allowed for a closer study of the anatomy along the humerus during gesture motion. Results and findings from the work suggest that it could be possible to further develop transhumeral prosthesis using affordable, ergonomic and wearable EMG and NIR sensing, without the need for invasive neuromuscular sensors or further hardware complexity.

Academic achievement is determined by two factors, namely internal factors originating from within the individual in this case students and external factors that come from outside the individual or things that are influenced by the environment. There are many ways to find an academic achievement, one of which uses data mining which aims to predict or classify data using a classification algorithm. This study aims to 1) find out how to apply the Naive Bayes algorithm to student achievement, and 2) see the accuracy of the Naive Bayes algorithm to student achievement. This type of research is secondary data in the form of student data obtained from the information technology center and the Ar-Raniry UIN database. This research uses Naive Bayes algorithm and random forest algorithm. The results obtained from this study indicate the highest correlation value in the initial IP variable of r = 0.783 and the leave variable has a very weak correlation level of r = 0.054. The accuracy value of Naive Bayes algorithm after cleaning is 78.0% and Random Forest algorithm variable is 76.7%.

An archive is an important document that is saved with a purpose when it is needed again it is easy to find it. The archive plays an important role in Dayah Tuha Village's Lurah office, so it is highly hoped that the process of managing the archives is good, fast, and easy. If the files that are owned are not well managed it will impact the difficulty of finding the information and it can impede the next stage of work. Therefore, the archive must be managed with a good and correct management system. In this research, discusses the analysis and design of a web-based document, which is suitable for the needs of the office of Tuha Village. The design of this information system based on the design of systems that have been compiled include use case diagram, activity and sequence Diaram. Dayah Tuha Village's office is still using the manual way of managing the archives. So that by the existence of this system is expected to help the work in the head office of Dayah Tuha in terms of the management of archives.

Cloud computing is the transformation of information and communication technology from client or server-based computers. Cloud computing technology benefits users no longer need to invest heavily in software or maintenance software applications. So by developing the Cloud, there is a Cloud gaming which is a process to install a remote interactive game in the cloud and issued in the form of video to the user's device via the internet. In this journal, we need a cloud gaming application called Skyegrid. This study aims to implement cloud-based mobile gaming cloud implementation using an open-source server (Skyegrid) to find out Resources, Service Quality and Experience Quality in this study. In this study Skyegrid is used to discuss some popular games, namely games called Rainbow Six Siege and Monster Hunter World. The result of this study is that Skyegrid's cloud gaming mobile system is able to implement PC games that can be run on Android smartphones and reduce the use of CPU and RAM resources, and use low cost using skyegrid cloud gaming using personal computers that require greater costs.

The development of technology is currently developing very quickly, this is directly proportional to releasing cyber crime. One crime that often occurs is the case of Pornography. This application is done using one of the very popular Instant Messenger (IM) applications, the WhatsApp application. But after the crime is committed next or sending evidence in the form of conversations, video recordings, images and others committed by the suspect using the WhatsApp application. Therefore, this study proposes to find evidence related to digital pornography. This research produced a forensic procedure in conducting an investigation of the WhatsApp application to obtain previously published evidence containing a conversation session, a list of contact numbers, a profile photo of the victim and others. This research was conducted by reading a backup file of the encrypted WhatsApp application database that stores the conversation session that has been released. This research uses the method (National Institute of Standards and Technology (NIST). This digital evidence can be obtained using one of the forensic tools namely WhtasApp Viewer. The results obtained in this study contain WhatsApp contents that have been available which can be found digitally in uncovering the crime of pornography that is happen.

Jumlah data akademik yang terus meningkat pada institusi perguruan tinggi perlu dikelola dengan efektif sehingga pengaksesan data melalui sistem informasi akademik menjadi lebih mudah dan cepat. Salah satu teknologi Database Management System (DBMS) yang masih sering digunakan pada institusi perguruan tinggi adalah MySQL. Umumnya, aplikasi MySQL yang digunakan untuk memproses query dari pengguna masih bersifat tunggal pada sebuah server sehingga overload akses pada waktu tertentu dapat menyebabkan sistem informasi menjadi tidak stabil bahkan sering mengalami timeout. Penelitian ini bertujuan untuk menganalisa proses migrasi MySQL non-cluster ke MySQL cluster dalam menangani fail-over sistem akademik. Hasil penelitian yang diperoleh yaitu berupa dokumen konfigurasi yang tepat pada MySQL cluster sehingga dapat digunakan secara umum pada berbagai MySQL server. Selain itu, load-balancing juga diuji dalam penelitian ini untuk mendistribusikan request antara MySQL server.

Owing to the non-collocation of actuators and sensors in a flexible-link manipulator (FLM) it becomes difficult to achieve accurate tip position tracking. To resolve this issue, a vision sensor is used for direct measurement of the tip position instead of employing the traditional mechanical sensors. Among the different visual servoing (VS) control schemes, image-based VS (IBVS) is more effective. However, there are many challenges in the IBVS scheme such as singularities in the interaction matrix and local minima in trajectories that affect the system performance in real-time applications. In this study, the moment-based new visual feature is selected to address the aforesaid issues that arise in the IBVS scheme. Furthermore, a new two-time scale IBVS controller is developed for addressing the tip-tracking control problem of the two-link flexible manipulator (TLFM). In the proposed control scheme, the dynamics of the FLM is decomposed into two-time scale models, namely a slow subsystem and a fast subsystem. The performance and robustness of the proposed new two-time scale IBVS controller for TLFM are verified by pursuing simulation studies. It is observed from the obtained results that the proposed controller effectively stabilises the oscillatory dynamics and tracks the reference trajectory accurately.

A non-linear optimal (H-infinity) control approach is proposed for the dynamic model of multi-degree-of-freedom (DOF) electro-hydraulic robotic manipulators. Control of electro-hydraulic manipulators is a non-trivial problem because of their non-linear and multi-variable dynamics. In this study, the considered robotic system consists of a multi-link robotic manipulator that receives actuation from rotary electro-hydraulic drives. The article's approach relies first on approximate linearisation of the state-space model of the electro-hydraulic manipulator, according to first-order Taylor series expansion and the computation of the related Jacobian matrices. For the approximately linearised model of the manipulator, a stabilising H-infinity feedback controller is designed. To compute the controller's gains, an algebraic Riccati equation is solved at each time-step of the control algorithm. The global stability properties of the control scheme are proven through Lyapunov analysis. The proposed control method retains the advantages of typical optimal control, i.e. fast and accurate tracking of the reference setpoints under moderate variations of the control inputs.

The authors solve the problem of estimating the best rotation aligning two sets of corresponding vectors (also known as Wahba's problem or point cloud registration). The proposed method is among the fastest methods reported in recent literatures, moreover it is robust to noise, accurate and simpler than most other methods. It is based on solving the linear equations derived from the formulation of the problem in Euclidean Geometric Algebra. The authors show its efficiency in two applications: the as-rigid-as-possible (ARAP) surface modelling and the more smooth rotation enhanced ARAP mesh animation which is the only method capable of deforming surface modes with quality of tetrahedral models. Mesh deformation is a key technique in games, automated construction and robotics. The ARAP technique along with its improved variants, although have been extensively studied, can still not be achieved efficiently. Linear geometric algebra based rotor solution proposed in this study gives another perspective of the kernel problem. This, however, not only improves the real performance of the three-dimensional mesh deformation, but also provides a brand new computationally efficient solution to the Wahba's problem and point cloud registration, which has been closely related to the automation science and engineering.

Motion planning is a vital module for unmanned aerial vehicles (UAVs), especially in scenarios of autonomous navigation and operation. This survey delivers some recent state-of-the-art UAV motion planning algorithms and related applications. The logic flow of this survey is divided as the path finding, which is the front-end of most motion planning systems, and the trajectory optimisation, which usually serves as the back-end. Motivation, methodology, problem formulation and derivation are given in this survey, in detail. Finally, a section about real-world applications is given, where roles and effectiveness of most popular motion planning methods are revealed.

The performance of a formation control algorithm for a group of autonomous underwater vehicles (AUVs) may be degraded due to communication constraints between the leader and the follower AUVs. Moreover, as the distance between the AUVs change due to ocean waves, the delay in communication also varies. In this study, a modified constrained adaptive controller (CAC) is proposed to resolve the issue of variable-delay as well as actuator saturation. Due to the on-line reduction of the cost function, the gains of the CAC are updated at each sampling time taking into account the effects of communication delay. This improves the path-following accuracy of the leader AUV as well as follower AUVs. The effectiveness of the proposed control algorithm is demonstrated by implementing it on a prototype AUV (ODRA-I) model. The obtained simulation and experimental results show that the follower AUVs maintain a desired distance from the leader AUV to avoid a collision. For the proposed algorithm, the desired path-following performance of the follower AUV is maintained even when the delay is changed from 0 to 5 s. Moreover, the proposed control algorithm is efficient in avoiding actuator saturation.

In order to handle undesirable failures of a multicopter which occur in either the pre-flight process or the in-flight process, a failsafe mechanism design method based on supervisory control theory is proposed for the semi-autonomous control mode. Failsafe mechanism is a control logic that guides what subsequent actions the multicopter should take, by taking account of real-time information from guidance, attitude control, diagnosis, and other low-level subsystems. In order to design a failsafe mechanism for multicopters, safety issues of multicopters are introduced. Then, user requirements including functional requirements and safety requirements are textually described, where function requirements determine a general multicopter plant, and safety requirements cover the failsafe measures dealing with the presented safety issues. In order to model the user requirements by discrete-event systems, several multicopter modes and events are defined. On this basis, the multicopter plant and control specifications are modeled by automata. Then, a supervisor is synthesized by monolithic supervisory control theory. In addition, we present three examples to demonstrate the potential blocking phenomenon due to inappropriate design of control specifications. Also, we discuss the meaning of correctness and the properties of the obtained supervisor. This makes the failsafe mechanism convincingly correct and effective. Finally, based on the obtained supervisory controller generated by TCT software, an implementation method suitable for multicopters is presented, in which the supervisory controller is transformed into decision-making codes., 33 pages, 15 figures

Tomographic particle image velocimetry (Tomo-PIV) has been successfully applied in measuring three-dimensional (3D) flow field in recent years. Such technology highly relies on the reconstruction technique which provides the spatial particle distribution by using images from multiple cameras at different viewing angles. As the most popular reconstruction method, the multiplicative algebraic reconstruction technique (MART) has advantages in high computational speed and high accuracy for low particle seeding reconstruction. However, the accuracy is not satisfactory in the case of dense particle distributions to be reconstructed. To overcome this problem, a symmetric encode–decoder fully convolutional network is proposed in this paper to improve the reconstruction quality of MART. The input of the neural network is the particle field reconstructed by the MART approach, while the output is the regenerated image with the same resolution. Numerical evaluations indicate that those blurred or irregular particles can be significantly refined by the trained neural network. Most of the ghost particles can also be removed by this filtering method. The reconstruction accuracy can be improved by more than 10% without increasing the computational cost. Experimental evaluations indicate that the trained neural network can also provide similar satisfactory reconstruction and improved velocity fields.

Affidabilità, autenticità, integrità e leggibilità dei documenti nel tempo sono principi essenziali su cui misurare l’efficienza delle strutture sanitarie. La conservazione digitale, realizzata nel pieno rispetto delle normative, è estremamente importante, specialmente in un settore sensibile come quello sanitario, soprattutto considerando tale processo nel contesto del Fascicolo Sanitario Elettronico (FSE). In questo lavoro, sono analizzate le principali problematiche legate alla realizzazione di un sistema di conservazione a norma efficace ed efficiente e di idonee metodologie di interazione con il FSE. È evidenziata, infine, l’importanza di definire e migliorare un insieme adeguato di metadati, essenziali per la descrizione e il recupero dei documenti digitali.

Negli anni recenti, il progresso tecnologico delle infrastrutture ed applicazioni informatiche ha permesso lo sviluppo di nuovi sistemi capaci di fornire analisi ed informazioni con precisione e dettagli inediti. Tali sistemi sono alimentati tramite dati raccolti dalle più diverse fonti interconnesse tra loro. Le informazioni che si posso trarre da questi database hanno un valore molto grande per la loro capacità di restituire la descrizione di un fenomeno, di una persona o di una comunità. In questo lavoro si pone l’attenzione sui dati non personali ovvero quelli generati nell’ambito dell’Internet of Things - IoT nel settore pubblico e privato. Si tratta di aspetti che solo di recente sembrano aver avuto la giusta attenzione e che recano con sé nuove problematiche di natura giuridica, economica e tecnologica. Per poter correttamente porre le basi della discussione, si deve procedere all’indagine della natura di tali dati e delle ragioni giuridiche della loro tutela nonché all’esame di modelli economici e di mercato di valorizzazione degli stessi.

Perché scrivere chiaro? E in che contesti? L’articolo distingue la scrittura letteraria da quella dei testi giuridici sottolineando, per questi, la necessità che siano chiari e concisi per permettere ai cittadini di comprenderli con facilità esercitando così il loro diritto e dovere di conoscere le leggi, gli atti amministrativi e gli atti giudiziari che li riguardano. Una scrittura non chiara produce infatti effetti molto negativi sui cittadini e sulle imprese alterando il principio della divisione dei poteri e scaricando sugli interpreti i dubbi che derivano da una cattiva scrittura. Sono poi indicate le ragioni dello scrivere oscuro da parte dei tecnici e dei politici. Urge allora il cambiamento di una cultura e una formazione permanente dei redattori degli atti. A tal fine si auspica la costituzione di comunità professionali (un esempio è quello dell’Osservatorio legislativo interregionale - OLI). Occorrono anche la formazione di una classe politica di alto profilo ed un sistema giudiziario non tradizionalista che si adoperino realmente ai fini di formulare atti chiari e concisi.

Autorecensione

Along with the increasing development of Information and Communication Technology (ICT), there has been a change in the learning approach method. Methods of face-to-face learning (conventional) and classrooms as implementation have now changed. The ilearning method approach has turned into the direction of future learning or as a learning age of knowledge. In the world of education, information becomes a vital need to support teaching and learning activities. In the online learning system that applied to iLearning+ information needs become critical needs therein. But in reality, the delivery of information is not done online, but with current information such as the delivery of information is done in an intermediary between lecturers and students, which must be done face to face so get a piece of information. So in that event, a system is needed to be able to convey information with a Web-based system so that delivery can be done online and can be accessed anytime and anywhere without being limited by time and space. In this study, using the literature review research method as a comparison material on existing research.

Support Vector Machine (SVM) is one of the most popular methods of classification problems due to its global optima solution. However, the selection of appropriate parameters and kernel values remains an obstacle in the process. The problem can be solved by adding the best value of parameter during optimization process in SVM. Gravitational Search Algorithm (GSA) will be used to optimize parameters of SVM. GSA is an optimization algorithm that is inspired by mass interaction and Newton's law of gravity. This research hybridizes the GSA and SVM to increase system accuracy. The proposed approach had been implemented to improve the classification performance of Thyroid Nodule. The data used in this research are ultrasonography image of Thyroid Nodule obtained from RSUP Dr. Sardjito, Yogyakarta. This research had been evaluated by comparing the default SVM parameters with the proposed method in term of accuracy. The experiment results showed that the use of GSA on SVM is capable to increase system accuracy. In the polynomial kernel the accuracy rose up from 58.5366 % to 89.4309 %, and 41.4634 % to 98.374 % in Polynomial kernel

The volume density of vehicles is a problem that often occurs in every city, as for the impact of vehicle density is congestion. Classification of vehicle density levels on certain roads is required because there are at least 7 vehicle density level conditions. Monitoring conducted by the police, the Department of Transportation and the organizers of the road currently using video-based surveillance such as CCTV that is still monitored by people manually. Deep Learning is an approach of synthetic neural network-based learning machines that are actively developed and researched lately because it has succeeded in delivering good results in solving various soft-computing problems, This research uses the convolutional neural network architecture. This research tries to change the supporting parameters on the convolutional neural network to further calibrate the maximum accuracy. After the experiment changed the parameters, the classification model was tested using K-fold cross-validation, confusion matrix and model exam with data testing. On the K-fold cross-validation test with an average yield of 92.83% with a value of K (fold) = 5, model testing is done by entering data testing amounting to 100 data, the model can predict or classify correctly i.e. 81 data.

FAQs are mostly provided on the company's website to inform their service and product. It's just that the FAQ is usually less interactive and presents too much information that is less practical. Chatbot can be used as an alternative in providing FAQ. In this study, chatbots were developed for BTPN in providing information about their products, namely Jenius. Chatbot developed utilizes natural language processing so that the system can understand user queries in the form of natural language. The cosine similarity algorithm is used to find similarities between queries and patterns in the knowledge base. Patterns with the highest cosine values are considered to be most similar to user queries. It's just that, this algorithm does not pay attention to the structure of the sentence so that it adds checking the structure of the sentence with the parse tree to give weight to the pattern. This chatbot application has been tested by 10 users and it was found that the suitability of the answers with user input was 84%. Therefore the chatbot developed can be used by BTPN to provide Jenius product information to consumers more interactively and practically.

The performance appraisal of Sunday school teacher in the Imanuel Lurang congregation aims to measure and distinguish the quality of performance achieved by Sunday school teacher and decide various policies such as giving rewards to every Sunday school teacher with the best performance, and for Sunday school teacher who have poor performance scores will be given a guiding, approach, etc. The number of criteria in determining the quality of Sunday school teacher is not an easy thing to do by manual. Then it is essential that a computerized performance appraisal-based performance app can speed up the process of progressing to be more effective and efficient. This research develops decision support systems (DSS) that is dynamic using the PHP programming language, by combining the AHP method that has been refined by the VIKOR method. The AHP method is used in determining the weight of each criterion, and the VIKOR method is used for the ranking process. Test results indicate that the system can provide a sequence of alternative Sunday school teacher that will be used as recommendations for decision makers to determine which Sunday school teachers are quality and not qualified.

This study using the Weighted Fair Queue scheduling algorithm when the weights can change and calculated based on changes in the average queue size in the buffer. This algorithm divides the priorities of each sensor into three priorities, namely high, medium and low priority. Each queue is given a weight that is adjusted to the resource requirements of each traffic. High priority data will take precedence, but medium and low priority data will remain underserved and guaranteed by network resources.The results of this study show packet loss ratio when the ratio of the number of buffers and the amount of data is 1: 3 with variations in the number of high, medium and low priority buffers 75: 75: 150 and 50: 50: 200 is 0%. The delay time in the high priority and the medium priority buffer has almost the same delay time when data is transmitted, whereas for the low priority buffer increased in the delay time.

Congestion in the seaports area is a common issue in many parts of the world. Fluctuating truck arrival has been identified as one of the significant determinants of congestion. In response, a truck appointment system (TAS) is introduced to manage truck arrival, particularly at peak times. In the existing TAS mechanism, the scheduling decision is centralized and disregards the concerns of trucking companies. Moreover, TAS may complicate the business operation of trucking companies that already have a constrained truck schedule. This study proposes a decentralized negotiation mechanism in TAS that allows trucking companies to adjust arrival times by utilizing the waiting time estimation provided by the terminal operator. We develop an agent-based model of a TAS in the container terminal pick-up procedure. The simulation results indicate that compared to the existing TAS mechanism, the negotiation TAS mechanism generates a shorter average truck turnaround time regardless of truck arrival rates. In terms of average net time cost, the negotiation TAS mechanism provides better value under high truck arrival rate conditions. The incentive for trucking companies to participate in the negotiations is even higher at peak times.

The class imbalance is a condition when one class has a higher percentage than the other then it can affect the accuracy. One method in data mining that can be used to classification is logistic regression method. The method used in this research is RWO-sampling method using random replicate approach for synthetic data generation on descrete attribute. The result of the research can handle the problem of class imbalance, RWO-sampling method with random replicate approach shows better accuracy than RWO-sampling method with roulette and ROS approach. The accuracy value for RWO-Sampling method with roulette and RWO-Sampling approach with random replicate approach has increased to an average of 15.55% of each dataset. As for comparithem with the ROS method has increased an average of 3.7% of each dataset. Furthermore, for testing the underfitting problem in logistic regression, the oversampling method is better than non-oversampling with an increase in accuracy value reaching an average of 2.3% of each dataset.

The current technology is changing rapidly, with the significant growth of the internet technology, cyber threats are becoming challenging for IT professionals in the companies and organisations to guard their system. Especially when all the hacking tools and instructions are freely available on the Internet for beginners to learn how to hack such as stealing data and information. Tic Timor IP is one of the organisations involved and engaged in the data center operation. It often gets attacks from the outside networks. A network traffic monitoring system is fundamental to detect any unknown activities happening within a network. Port scanning is one of the first methods commonly used to attack a network by utilizing several free applications such as Angry IP Scan, Nmap and Low Orbit Ion Cannon (LOIC). On the other hand, the snort-based Intrusion Detection System (IDS) can be used to detect such attacks that occur within the network perimeter including on the web server. Based on the research result, snort has the ability to detect various types of attack including port scanning attacks and multiple snort rules can be accurately set to protect the network from any unknown threats.

Instagram is a social media that has the potential to be used to increase awareness of a product. Approximately 70% of users spend their time searching for a product on Instagram. Many people promote their products with a lack of attention to the target. So that not infrequently the information distributed is inaccurate information and not following user characteristics. This study aims to cluster the characteristics of Instagram users based on hashtag compatibility. The method used in this study is the K-Means Clustering method. Based on the results of the experiment, this research succeeded in clustering Instagram users based on the hashtag match on the text caption. Besides, TF-IDF can be used as a feature suitable for the K-Means Klastering method. The results of the hashtag "#kopi" analysis resulted in hashtag suggestions that can be used for the promotion of a product related to coffee, including the hashtag #coffeeshop and #coffee with total usage of 14968 captions.

Dental panoramic radiographs heavily depend on the performance of the segmentation method due to the presence of unevenly illumination and low contrast of the images. Conditional Spatial Fuzzy C-mean (csFCM) Clustering have been proposed to achieve through the incorporation of the component and added in the FCM to cluster grouping. This algorithm directs with consideration conditioning variables that consider membership value. However, csFCM does not consider Intuitionistic Fuzzy Set to take final membership and final non-membership value into account, the effect does not wipe off the deviation by illumination and low contrast of the images completely for improvement to skip some scope. In this current paper, we introduced a new image segmentation method namely Conditional Spatial in Intuitionistic Fuzzy C-Means Clustering for Segmentation of Teeth in Dental Panoramic Radiographs. Our proposed method adds hesitation function aiming to settle the indication of the knowledge lack that belongs to the final membership function to get a better segmentation result. The experiment result shows this method achieves better segmentation performance with misclassification error (ME) and relative foreground area error (RAE) values are 4.77 and 4.27 respectively.

Il confronto fra il panorama italiano e quello francese degli strumenti di accesso all’informazione giuridica si presenta fortemente connotato nazionalmente. Non tanto per il quadro legislativo o l’organizzazione del mercato editoriale, i due sono per altro simili, ma per le rispettive tradizioni di informatica giuridica e le loro applicazioni pratiche. Di fatto, una consolidata tradizione nello studio e applicazione dell’informatica giuridica in Italia, risalente a più di cinquant’anni fa, ha permesso l’evoluzione di alcuni strumenti che ne contraddistinguono l’offerta, come ad esempio la banca dati bibliografica DoGi - Dottrina Giuridica. Tuttavia, il confronto con il panorama francese resta valido, per evidenziare suggerimenti utili per un ulteriore miglioramento del quadro italiano, la cui evoluzione è sempre perfettibile.

Stenography and security are one of the techniques to develop art in securing data. Stenography has the most important aspect is the level of security in data hiding, which makes the third party unable to detect some information that has been secured. Usually used to hide textinformationThe (LSB) algorithm is one of the basic algorithms proposed by Arawak and Giant in 1994 to determine the frequent item set for Boolean association rules. A priory algorithm includes the type of association rules in data mining. The rule that states associations between attributes are often called affinity analysis or market basket analysis. OTP can be widely used in business. With the knowledge of text message, concealment techniques will make it easier for companies to know the number of frequencies of sales data, making it easier for companies to take an appropriate transaction action. The results of this study, hide the text message on the image (image) by using a combination of LSB and Otp methods.

Il presente lavoro si occupa del c.d. Sistema Informativo Integrato (SII), un sistema informatico centralizzato, previsto dall’art. 1-bis del decreto-legge 105/2010, per la gestione dei flussi informativi nei mercati dell’energia, basato su una banca dati dei punti di prelievo e dei dati identificativi dei clienti finali. L’analisi si concentra sulla disciplina dei suddetti flussi definita dall’autorità di regolamentazione settoriale, al fine di mostrare, in primo luogo, e con particolare riferimento al c.d. diritto dell’energia, il ruolo fondamentale che il SII assume, incidendo in modo notevole (e per certi versi analogo alle infrastrutture di rete che connotano tali settori) sulla stessa morfologia delle relazioni contrattuali che concorrono a costituire i relativi mercati (in particolare, quello retail ). In secondo luogo, ci si sofferma anche sui risvolti che il SII ha per la teoria generale del diritto, divenendo un caso quasi emblematico di come le tecniche documentarie (specie se realizzate mediante sistemi informatici) impiegate per la realizzazione di istituti giuridici e pratiche di governo condizionano la disciplina (e la sua evoluzione) di quegli istituti e di quelle pratiche.

Il contributo prende in considerazione le implicazioni economico-giuridiche relative all’utilizzo degli algoritmi automatici per le decisioni. Gli algoritmi automatizzati possono sostituirsi ai decisori creando dei contratti, modellando il negozio giuridico, disponendo delle obbligazioni per le parti. Chiaramente si pone la questione degli effetti giuridici di tali decisioni sulle parti e i terzi, e, fatto ancora più grave, si manifestano dei rischi di sostenibilità sistemica. Infatti, la crescita del numero delle decisioni pone delle questioni assai rilevanti in termini di crescita della probabilità di crisi e di manifestazione di avvenimenti avversi. Occorre allora essere attenti alla modellistica metrica utilizzata per analizzare l’impatto delle decisioni automatizzate sia a livello sistemico che nelle posizioni giuridiche dei singoli che possano venire coinvolti ed evitare effetti discriminatori o distorsivi. In questo senso vengono proposti in modo dialettico il metodo gaussiano e il metodo black swan. Il metodo gaussiano impedisce di considerare eventi altamente improbabili eppure distruttivi. Il metodo black swan consente di avere degli strumenti per valutare l’altamente improbabile. Gli algoritmi decisionali possono annullare la stabilità dei sistemi giuridici ed economici e minarne le basi introducendo nuovi paradigmi di funzionamento. Occorre allora accompagnare l’applicazione degli algoritmi automatici con modelli di governance e regolazioni di diritto che siano in grado di ridurre il rischio di eventi avversi distruttivi, di tutelare i contraenti e garantire la sostenibilità del sistema anche alla luce dei diritti individuali e sociali di ciascuno.

Nell’articolo si descrive un’attività di ricerca condotta in materia di procedure amministrative nell’ambito dell’immigrazione allo scopo di favorire il diritto di accesso alle informazioni normative e amministrative per tutti i cittadini. La ricerca ha avuto l’obiettivo di ricavare raccomandazioni e linee guida per facilitare la comunicazione online delle informazioni sulle procedure e renderla più idonea alle odierne società interculturali. Il lavoro ha portato anche a ipotizzare l’uso di piattaforme collaborative che possano supportare gli operatori della pubblica amministrazione nella comunicazione amministrativa tramite i portali pubblici. L’attività operativa della ricerca, che è stata condotta tramite una sperimentazione sul portale PAeSI della Regione Toscana – portale tematico in materia di procedure e norme sull’immigrazione –, è contestualizzata attraverso una riflessione sul rapporto tra inclusione, e-government e modalità comunicative della pubblica amministrazione e ha utilizzato una metodologia collaborativa che ha previsto il coinvolgimento degli stakeholder del dominio.

Il progetto #IOPARTECIPO ha sviluppato il tema della promozione della partecipazione attiva dei migranti orientandosi sul target group dei giovani di “seconda generazione” (2G), in attuazione delle proposte contenute nel Manifesto delle 2G promosso dal Ministero del Lavoro e delle politiche sociali. In particolare il progetto ha usato strumenti formativi e partecipativi per valorizzare i giovani 2G residenti in Toscana al fine di incentivare la loro partecipazione nel contesto economico e sociale in cui vivono. A tal fine sono stati usati innovativi sistemi di formazione e partecipazione che hanno usufruito anche delle nuove tecnologie ed in particolar modo delle potenzialità della piattaforma OPENTOSCANA.

Natural Language Processing is part of Artificial Intelegence that focus on language processing. One of stage in Natural Language Processing is Preprocessing. Preprocessing is the stage to prepare data before it is processed. There are many types of proccess in preprocessing, one of them is stemming. Stemming is process to find the root word from regular word. Errors when determining root words can cause misinformation. In addition, stemming process does not always produce one root word because there are several words in Indonesian that have two possibilities as root word or affixes word, e.g.the word “beruang”.To handle these problems, this study proposes a stemmer with more accurate word results by employing a non deterministic algorithm which gives more than one word candidate result. All rules are checked and the word results are kept in a candidate list. In case there are several word candidates were found, then one result will be chosen.This stemmer has been tested to 15.934 word and results in an accurate level of 93%. Therefore the stemmer can be used to detect words with more than one root word.

This study presents a combination of the robust passivity-based controller (RPBC) and an extended state observer (ESO) for the tracking control of a three degree-of-freedom PUMA 500 robot manipulator under parameter variations and external disturbances. The dynamic model of the PUMA robot and its structural properties are analysed. The extra state in the ESO estimates the parameter variations and external disturbances in the control system. Then the RPBC cancels them in the control law. The stability of the proposed control system and the convergence of the observation errors are analysed. Simulations prove that the proposed controller is robust and tracks well under parameter variations, and external disturbances, validating the proposed control scheme.

While both international and European law-makers are currently in the process of introducing new laws re-gulating the fight against cybercrime and the exchange of digital evidence amongst competent authorities,this paper elaborates on a series of investigative challenges deriving from the application of current cyber-crime norms in a number of jurisdictions, unveiling a tension between the current legal system and its in-terpretation by the law enforcement and judicial community. This study analyzes the research undertakenon the legal and regulatory uncertainties observed in the Italian framework, as well as in other Europeanand non-European jurisdictions, by ways of comparative analysis. The main international legal instrumenton cybercrime is the Council of Europe’s Convention on Cybercrime (‘Cybercrime Convention’), signed in2001 and then ratified by almost 60 countries worldwide over the last 17 years. Aimed at raising awarenessto national and international policy and law makers, this paper intends to critically demonstrate how theimplementation of such a treaty into domestic laws has not always been smooth. It often presents interpre-tative issues, which add up to the growing difficulties for both law enforcement and judicial bodies to copewith the challenges arising by countering new and innovative forms of criminal activities in the cyberspace ispartof: Rivista italiana di informatica e diritto issue:2 pages:1-19 status: Published online

In this study, an extreme learning-based non-linear model predictive controller (NMPC) is proposed for path following planning of an autonomous underwater vehicle (AUV) using horizontal way-points. The proposed controller comprises a kinematic controller and a dynamic controller. The kinematic controller is designed by using back-stepping approach whilst the dynamic controller is designed by employing the NMPC approach. The dynamics of the AUV is identified in real-time by employing an extreme learning machine (ELM) structure. In view of achieving improved performance of the ELM structure, its hidden layer parameters are optimally determined by applying Jaya optimisation algorithm. The resulting ELM model is then used to design a NMPC considering the constraint on rudder planes. The tracking performance of the proposed controller is compared with that of two recently reported control algorithms namely, $H_\infty $ H ∞ state feedback controller and inverse optimal self-tuning proportional–integral–derivative (PID) controller. The proposed controller is implemented using MATLAB and then in real-time on a prototype AUV developed in the authors’ laboratory. From both the simulation and experimental results obtained, it is observed that the proposed controller exhibits superior tracking performance compared to both $H_\infty $ H ∞ state feedback controller and inverse optimal self-tuning PID controller.