Miracle-dz/UniFAR-FTUs huggingface dataset:
Perforance evaluation of vehicle radiofrequency communication systems : contribution to the modelling approach

The general framework of this Ph.D. thesis deals with Vehicle to Vehicle (V2V) communications. This communication is principally dedicated to reinforce security through exchange of information between vehicles in case of unexpected events. The development of V2V solutions requires the understanding and merging of a number of techniques from several communication technology areas. Indeed, the performance of these systems are related to three main blocks: the implementation of the modems, the antenna configuration and the fast varying electromagnetic environment surrounding the transmitter and the receiver. The purpose of this PhD thesis is precisely to elaborate a design strategy to investigate all the different blocks constituting the communication chain. The ultimate goal is to optimize antenna selection and location on board the vehicle. In the first place, we proposed a geometry-based stochastic channel modelling approach to develop virtual dynamic scenarios. It was shown that the most common propagation environments such as rural, highway or urban-like propagation channels are reached through adjustment or numbers and location of simple metallic plates. Using this method, we are able to emulate the characteristics, such as the delay spread, angles of arrival distribution and the Doppler spectrum, of these typical driving scenarios. Moreover, we dealt with antenna integration problems in the second part of this work. A study on the simplification of numerical models of vehicles was carried out. Furthermore in this section, we investigated the limit of validity of representing the integrated antenna on board vehicle solely by its radiation pattern. We deduced from this study that the interactions with the elements present in the near-field is no longer valid. Thus, a strategy to alleviate the degree of error was found upon consideration of the near-field scatter in the a-priori simulation of the antenna integrated on the vehicle. In the third part of this thesis, we evaluated the performance of different antenna configurations in terms of packet error rate after the embodiment of the PHY layer of the LEEE 802.11p standard. Simulation results, for each antenna configurations, was given for several combinations of PHY layer parameters such as data rate and packet length. The last part of this manuscript is dedicated to the presentation of a measurement campaign that was carried out in a rural driving environment. Results obtained from these functional tests were confronted with simulation results to demonstrate the strength of the latter. We found that the expected trends in communication performance in terms of PER are globally predictable from our model though we obtained surprising results in some cases, needing further investigation.
Risk Terrain Modeling: Seasonality and Predictive Validity

Abstract This study focuses on crimes involving firearms in Baltimore, Maryland to answer three research questions concerning the effect of seasonality: (1) Do changes in the seasons affect which spatial factors are significantly related to crime? ; (2) Does risk terrain modeling have predictive validity on a short-term basis? ; and (3) Are the same areas high-risk throughout the year? To accomplish this, the authors ran twelve monthly risk terrain models and one yearly risk terrain model. The study found that risk factors vary by month and that monthly and yearly spatial risk factors do not necessarily overlap. The study also found that risk terrain models retain their predictive validity on a short-term basis. The results are further discussed in relation to whether the same areas are high-risk throughout the course of the year.
Reliable Low Latency Wireless Communication Enabling Industrial Mobile Control and Safety Applications

Advanced industrial applications for human-machine interaction such as augmented reality support for maintenance works or mobile control panels for operating production facility set high demands on underlying wireless connectivity so- lution. Based on 802.11 standard, this paper proposes a concept of a new system, which is capable of those requirements. For increasing reliability, an agile triple-band (2.4 GHz, 5 GHz and 60 GHz) communication system can be used. In order to deal with latency and deterministic channel access, PHY and MAC techniques such as new waveforms or hybrid MAC schemes are investigated. Integration of precise localization introduces new possibilities for safety-critical applications.
Fast-Field Cycling Nuclear Magnetic Resonance relaxometer's electromagnet with optimized homogeneity and reduced volume

In this article a Fast Field Cycling (FFC) Nuclear Magnetic Resonance (NMR) electromagnet with low power consumption (less than 200 W), high field homogeneity and reduced volume is projected and described. The electromagnet is iron and copper based, possessing a high permeability and allowing for good magnetic field homogeneity in the operating range of 0 to 0.33 T. With this solution, it is possible to increase 65% the maximum magnetic field keeping the magnetic field homogeneity in comparison with former similar FFC relaxometers. Electromagnet's experimental and simulation results evaluating the generated magnetic field, field homogeneity, heating effects and cooling requirements are also presented. In addition, some technical aspects of the required coupled systems such as the cooling, sample heating are assessed.
Sub-policy pruning in Meta Learning Shared Hierarchies

MLSH (Meta Learning Shared Hierarchies) is a meta learning method that divide a policy into multiple sub-policies and a master-policy that picks one of the sub-policies to be actually used. By training sub-policies in advance, master policy can rapidly adjust to given environments. However, MLSH is not suitable for complicated environments. In complicated environments, a number of sub-policies are required, and it is very difficult to train them properly. We propose a method to effectively prune excessive sub-policies to give better chance the other sub-policies to be trained. We demonstrate that we can prune 40 % of sub-policies while preserving the performance.
Surgical-prosthetic rehabilitation of patients with aggressive periodontitis and immediately loaded implants: a report of two cases

Background Treatment with dental implants is demonstrated to be a predictable procedure to replace lost or defective teeth in patients with a history of chronic and aggressive periodontitis. Although the dental implants are less successful in compromised patients compared to uncompromised patients. Case report In this report, two cases are described of Generalized Aggressive Periodontitis (GAgP) treated with multidisciplinary management and a two-year follow-up. The two patients received periodontal and prosthetic treatment with immediately loaded implants using a supported surgical computer-planned guide. Dental implants were inserted by means of a flapless procedure, and immediate provisionalizations were put into place. The survival of the implants was evaluated by clinical and radiographic means after two years. Minimal pain and edema on the surgical site were observed. Conclusion The 2 case reports support the benefits of immediate loading with provisional implant-retained fixed prostheses in patients with GAgP.
Volumetric visualization techniques of rigid and deformable models for surgery simulation.

Virtual reality computer simulation is nowadays widely used in various fields, such as aviation, military or medicine. However, the current simulators do not completely fulfil the necessary requirements for some fields. For example, in medicine many requirements have to be met in order to allow a really meaningful simulation. However most current medical simulators do not adequately meet them, reducing the usability of these simulators for certain aspects. One of these requirements is the visualization, which in the case of medicine has to deal with unusual data sets, i.e. volume datasets. Additionally, training simulation for medicine needs to calculate and visualize the physical deformations of tissue which adds an additional challenge to the visualization in these type of simulators. In order to overcome this limitations, a prototype of a patient specific neurosurgery simulator has been developed. This simulator features a fully volumetric visualization of patient data, physical interaction with the models through the use of haptic devices and realistic physical simulation for the tissues. This thesis presents a study about the visualization methods necessary to achieve high quality visualization in such simulator. The different possibilities for rigid volumetric visualization have been studied. As a result, improvements on the current volumetric visualization frameworks have been done. Additionally, the use of direct volumetric isosurfaces for certain cases have been studied. The resulting visualization scheme has been demonstrated by an intermediate craniotomy simulator. Furthermore, the use of deformable volumetric models has been studied. The necessary algorithms for this type of visualization have been developed and the different rendering options have been experimentally studied. This study gives the necessary information to make informed decisions about the visualization in the neurosurgery simulator prototype
User Customization for Music Emotion Classification using Online Sequential Extreme Learning Machine

USER CUSTOMIZATION FOR MUSIC EMOTION CLASSIFICATION USING ONLINE SEQUENTIAL EXTREME LEARNING MACHINE By Chi-Man Wong Thesis Supervisor: Dr. Chi-Man Vong Department of Computer and Information Science Machine learning techniques have been widely applied to handle complicated and advanced classification problem including classification of music emotion. In this work, traditional machine learning algorithms such as k-nearest neighbor, and state-of-the-art neural network methods such as support vector machine, and extreme learning machine are applied and compared with different combinations of feature sets extracted from a benchmark music set using MIRtoolbox for music emotion classification. The best classifier with the best feature sets combination is chosen for user customization. Because music emotion perception is subjective and can vary individual to individual, the model may not fit all users. To overcome this problem, we propose using online sequential extreme learning machine to update the model based on user’s preference because it is fast and accurate with good generalization ability. The result showed that with respect to user’s preference, the model can be updated immediately and remained a similar accuracy. Further more, it is also important to learn a good feature representation for music emotion classification task, so that we also investigate on the deep network such as Multi layer extreme learning machines (MLELM). MLELM inherits the fastness property of ELM while it can learn higher level of feature representation for classification. However, there are three problems for MLELM: 1) To determine the number of hidden neurons for each layer; 2) When the number of hidden neurons of i hidden layer is different than the number of hidden neurons of (i+1) hidden layer, the output from i hidden needed to be scaled in order to fit in the (i+1) hidden layer; 3) It assumes that the feature space for each hidden layer is the same. To solve these problems, we propose using a new kernel-based MLELM, to analytically determine the hidden neurons number for each layer. The result showed that the proposed kernel MLELM obtained a better performance than MLELM, SVM, and ELM.
KEMAMPUAN PEMAHAMAN MATEMATIS PESERTA DIDIK MELALUI COOPERATIVE LEARNING TIPE PAIR CHECKS VS PROBLEM BASED LEARNING

Penggunaan model pembelajaran bisa digunakan sebagai perangsang minat dan motivasi belajar peserta didik agar bisa terlibat secara aktif dalam pembelajaran. Adapun tujuan penelitian ini untuk menganalisis perbedaan dan kualitas peningkatan kemampuan pemahaman matematis serta respon peserta didik antara yang menggunakan model pembelajaan kooperatif tipe Pair Checks dan model Problem Based Learning . Metode penelitian yang digunakan adalah metode kuasi eksperimen dengan menggunakan dua kelas sebagai sampel. Penelitian dilakukan di SMP Negeri 2 Cilawu tahun ajaran 2016/2017, kelas eksperimen I adalah kelas VII-G yang mendapatkan model pembelajaran kooperatif tipe Pair Checks dengan jumlah peserta didik sebanyak 32 orang dan kelas eksperimen II adalah kelas VII-H yang mendapatkan model Problem Based Learning dengan jumlah peserta didik sebanyak 32 orang. Materi yang digunakan dalam penelitian ini adalah Segiempat. Berdasarkan hasil analisis statistik yang dilakukan diperoleh kesimpulan: "Tidak terdapat perbedaan peningkatan kemampuan akhir yang signifikan antara peserta didik yang mendapatkan model pembelajaran kooperatif tipe Pair Check dan model Problem Based Learning ”. sedangkan peningkatan kemampuan pemahaman matematis peserta didik dari kedua kelas dikategorikan tinggi. Respon peserta didik terhadap model pembelajaran kooperatif tipe Pair Check menghasilkan respon baik dan respon peserta didik terhadap model Problem Based Learning menghasilkan respon sangat baik
Intelligent Ontology CBR System for Fault Diagnosis and Repair

Previous research in decision making has proposed the use of a case based reasoning approach to accumulate, organize, preserve, link and share diverse knowledge coming from past experiences. However, existing CBR systems lack semantic understanding, which is important for intelligent knowledge retrieval in decision support system. To develop an intelligent CBR system which can not only carry out data matching retrieval, but also perform semantic associated data access, and improve the traditional keyword-based search. An effective case representation method as well as an appropriate case retrieval approach must be found. Ontology technology is an ideal selection for realizing our system because owing to the good semantic understanding offered by ontology. Thus, we adopt ontology approach as a means to acquire domain knowledge and construct a case-base and use ontological semantic retrieval as the case retrieval method. The resulting ontology based CBR tool is experimented in fault diagnosis and repairing domain, a semi-structured decision-making environment involving multiple attributes. The results showed the feasibility and the applicability of our approach, and the benefit of the ontology support.
PEMASARAN MUSIK PADA ERA DIGITAL DIGITALISASI INDUSTRI MUSIK DALAM INDUSTRI 4.0 DI INDONESIA

Penelitian ini akan membahas bagaimana digitalisasi dalam industri musik mempunyai dampak pada pemasaran musik. Hal tersebut berdampak besar bagi para pelaku industri dalam hal pemasaran musik maupun konsumen dalam hal menikmati musik. Layanan streaming menjadi sesuatu yang sangat berpengaruh dalam era digital yang kita kenal industri 4.0. Industri musik tidak lagi dapat bergantung pada produk fisik dan konsumen pun kini lebih selektif dalam menikmati musik. Metode yang digunakan pada penelitian ini adalah metode kualitatif dengan strategi penelitian fenomenologi tentang apa yang dialami oleh subjek penelitian, seperti; perilaku, persepsi,motivasi, tindakan, dan lain-lain secara holistik dan dengan cara deskripsi dalam bentuk kata-kata dan bahasa. Hasil penelitian ini adalah bagi konsumen adalah mudahnya pencarian musikdan pelaku industri sangat mendukung adanya digitalisasi dalam industri musik karena mempermudah dalam memasarkan musik mereka dan membantu melindungi kekayaan intelektual mereka karena mengurangi pembajakan.
Basic key exchange protocols for secret key cryptosystems under CRYMPIX library

ACKNOWLEDGEMENTS I would like to express my sincere gratitude to my advisor, Assoc. Prof. Dr. Ahmet Koltuksuz, for his guidance, patience and encouragement. He was the one who supported me when I was in trouble with critical decisions. His valuable support and confidence have been the driving force of this thesis work. Furthermore, I had the pleasure of working with Dr. Serap Atay who helped me in understanding the elliptic curve arithmetic and documentation of the thesis. and Selma Tekir who cooperated with me in many studies. Finally, I should thank to my parents who always supported me throughout my education as well as in my graduate study. Key exchange protocols are developed in order to overcome the key distribution problem of symmetrical cryptosystems. These protocols which are based on various algebraic domains are different implementations of public-key cryptography. In this thesis, the basic key exchange protocols are reviewed and CRYMPIX 1 implementations of them are provided. CRYMPIX has a portable structure that provides platform independence for generated code. Hence, the implemented key exchange mechanisms are suitable to be used on different hardware and software platforms.
Heave and Pitch Motions of a Towed Ship in Waves Incorporated with an Asymmetrical Bridle Towline Model

Investigation of a ship towing system performance in waves incorporated with an asymmetrical towline configuration is necessarily to be studied to ensure a towing safety of navigation. To achieve the objective, this paper presents the ship towing motion performance in waves using Computational Fluid Dynamic (CFD) approach. Here, the heave and pitch motions of the towed ship so-called barge has been analysed, where several effects of the towing angle and towing speeds have been taken into account. In the calm water condition, the results revealed that the increase of tow angle was proportional with the sufficient reduction of the sway amplitude motion and inversely proportional to her yaw motion. The increase of the asymmetrical tow angle, however, has led to increase her sway motion amplitude in wave condition and conversely reduced the tow speed increased. In addition to the pitch motion characteristic, it subsequently increased by 12.1% as the tow angle raised from 25° to 35°; meanwhile the pitch motion of barge has by 10.2% as the tow speed increased from 0.655 m/s to 0.728 m/s. This CFD simulation is very useful as the preliminary prediction on the heave and pitch motion characteristics ensure a safety navigation of a towed ship in waves.
A Generative Grammar Approach for Action-AdventureMap Generation in The Legend of Zelda

In this paper we present an approach towards procedural generation of maps for 2D action-adventure games akin to those found within the classic Nintendo series The Legend of Zelda. Maps are generated through courtesy of a two-phase constructive approach, expanding upon existing research in the composition of missions and spaces for the action-adventure genre. Having completed the‘mission graph’ in the first phase, we are reliant upon a constraint-based approach to build geometry that faithfully represents the original mission structure. We investigate the effectiveness of this approach and the playable levels it can generate by creating dungeons within the open source game The Legend of Zelda: The Mystery of the Solarus.
An improved geometric algorithm for indoor localization

Indoor localization system using receive signal strength indicator from wireless access point has attracted lots of attention recently. Geometric method is one of the most widely used spatial graph algorithms to locate object in an indoor environment, but it does not achieve good results when it is applied to a limited amount of valid data, especially when using the trilateration method. On the other hand, localization based on fingerprint can achieve high accuracy but need to pay heavy manual labor for fingerprint database establishment. In this article, we propose a bilateral greed iteration localization method based on greedy algorithm in order to use all of the effective anchor points. Comparing to trilateration, fingerprint, and maximum-likelihood method, the bilateral greed iteration method improves the localization accuracy and reduces complexity of localization process. The method proposed, coupled with measurements in a real indoor environment, demonstrates its feasibility and suitability, since it outperforms trilateration and maximum-likelihood receive signal strength indicator–based indoor location methods without using any radio map information nor a complicated algorithm. Extensive experiment results in a Wi-Fi coverage office environment indicate that the proposed bilateral greed iteration method reduces the localization error, 63.55%, 9.93%, and 47.85%, compared to trilateration, fingerprint, and maximum-likelihood method, respectively.
Testing and Calibration of Phasor Measurement Units

Abstract: In the evolving Smart Grid, time-variant sources and loads introduce disturbances that can threaten the stability of the grid. Sophisticated protection and control systems are required to preserve reliability. These systems rely on accurate, synchronous measurements of voltage, current and frequency made by Phasor Measurement Units (PMUs). Although PMUs first appeared in 1988, their recent deployment has exposed inconsistent measurements and poor interoperability across brands and models. However, several recent developments promise to enhance the accuracy and consistency of PMU measurements. IEEE C37.118. 1:2011, “Standard for Synchrophasor Measurements for Power Systems”, established new performance limits for PMU test and calibration. The revised standard more clearly defines existing concepts, and enhanced and added material to the sections on steady state and dynamic tests. The emergence of automated systems supports the consistent execution of standard tests during PMU calibrations, and the observance of sound traceability practices for PMU ensures the accuracy of those calibrations. This paper describes the fundamentals of phasor measurements, the recent revisions to the IEEE C37.118. 1 standard, a new automated PMU calibration system developed at Fluke, and the establishment of traceability for PMU calibrations.
Navigating Black Identity: Self-Identification Strategies of Refugees in Post-Apartheid South Africa

ABSTRACT Scholars studying race in post-apartheid South Africa have largely focused on South African nationals. Little is known about the ways in which non-South African migrants and refugees navigate the South African racial classification system. In the context of continued immigration to South Africa, it is important to examine how refugees negotiate South African racial categories. This paper addresses this gap by interviewing Eritrean refugees and asylum seekers, who originate from an ethnicity-based classification system, to examine how they racially self-identify in everyday life as a result of their exposure to a race-conscious host society. Convenience and snowball sampling were used to select participants. The research sites were Johannesburg, Durban and Cape Town. A qualitative interpretative phenomenological analysis approach was employed to analyse data. The results presented here (patterns of Black self-identification) form only part of a larger project involving 46 Eritrean asylum seekers. Only 16 or one-third of the participants appropriated South African Black identity for a variety of reasons. Five themes were identified within Black self-identification: (1) “my phenotype makes me Black”; (2) “I feel Black when around Black South African friends”; (3) “living in Black neighbourhoods makes me feel black”; (4) “I am Black as I identify with the black experience”; and (5) “I check Black on forms to benefit from affirmative action”. Participants appropriated Black identity for various reasons depending on different circumstantial factors. For some participants, their physical appearance did not inform their Black self-identification, but other social factors. Through their various tactics and strategies of Black self-identification, participants redefined and re-casted what it means to be Black in post-apartheid South Africa. Their reasons for Black self-identification violate traditional understandings of Blackness in South Africa.