Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantum Key Management

Quantum key distribution (QKD), invented by Bennett & Brassard (1984) based on previous work of Wiesner (1983), has been recognized as a key-technology of the upcoming decades. With various (experimental) quantum networks existing (cf. the reports of Poppe et al. (2008) and Elliott (2004)), questions regarding the efficient construction and management of such networks arise. While much has been achieved in proving security of QKD under various assumptions (trusted devices as proposed by Salvail et al. (2009) vs. non-trustworthy devices as discussed by Elliott (2008b)), and many cryptographic primitives have been transferred to the quantum setting by Buchmann et al. (2004) and Damgard et al. (2004), some questions are still waiting to be answered. With the invention of public-key cryptography, key management has become an issue of major importance. Authentication is equally crucial for QKD-enhanced links, but authenticating keys here is inherently different to the public key setting. Nevertheless, why should quantum cryptography not benefit from the lessons learnt in classic, particularly public-key, cryptography (one of which is the strict principle not to use one key in two different applications)? Elegant ideas for key management and authentication have arisen in public-key cryptography (such as identity-based cryptography invented by Shamir (1985) or certificateless cryptography discussed in Al-Riyami & Paterson (2003)). Are similarly elegant solutions imaginable for the problem of entity authentication in the quantum setting? More importantly, with the one-time pad (OTP) as the encryption of choice, the key demand equals the data transmission demand in terms of size, so an effective management of keys is crucial for a reasonable quality of service of quantum networks. The whole security can be at stake if (quantum-)key generators cannot cope with the flood of information and run empty, thus logically (in terms of secrecy) cutting the link.
Prospective comparison of cytological specimen adequacy assessment by different rapid staining techniques for rapid on‐site evaluation in fine needle aspiration cytology and their cost‐effectiveness

Rapid on‐site evaluation (ROSE) is a technique beneficial in determining the adequacy of the samples, thereby increasing the diagnostic yield, useful in triage of specimens for ancillary studies and can also help determine a preliminary diagnosis in emergency cases. The different rapid stains for on‐site evaluation described in the literature are diff quik, toluidine blue (TB), brilliant cresyl blue (BCB), ultra‐fast Pap stains, and rapid hematoxylin and eosin (H&E). This study was undertaken as there is sparse literature regarding the best and the most cost‐effective rapid stain.
An Optimized Hidden Node Handling Approach For Improving The Coverage And Network Efficiency In Wireless Multimedia Sensor Networks

Wireless Multimedia Sensor Networks (WMSNs) are comprised of sensor nodes that form the momentary network and do not rely on the support of any orthodox centralized infrastructure or administration. Such a given situation mandates that every sensor node gets the support of the other sensor nodes in order to advance the packets to the desired destination node, and specifically to the sink node. Successful transmission of online multimedia streams in wireless multimedia sensor networks (WMSNs) is a challenge due to their limited bandwidth and power resources. The existing WMSN protocols are not completely appropriate for multimedia communication. The effectiveness of WMSNs vary as it depends on the correct location of the sensor nodes in the field. Thus, maximizing the multimedia coverage is the most important issue in the delivery of multimedia contents. The nodes in WMSNs are either static or mobile. Thus, the node connections change continuously due to the mobility in wireless multimedia
Model Predictive Control of Wheeled Mobile Robots

The control of nonholonomic wheeled mobile robots (WMRs) has gained a lot of attention in the field of robotics over the past few decades as WMRs provide an increased range of motion resulting in a larger workspace. This research focuses on the application of Model Predictive Control (MPC) for real-time trajectory tracking of a nonholonomic WMR. MPC is a control strategy in which the control law is designed based on optimizing a cost function. The input and output constraints that may arise in practical situations can be directly incorporated into the control system using MPC. Computation time is the biggest hurdle in adapting MPC strategies for trajectory tracking. This research applies a non-feasible active set MPC algorithm developed in [1] which is faster than the traditional active set methods (ASMs). A discrete-time linear model of a general WMR is used for the simulation. MATLAB simulations are performed for tracking circular as well as square trajectories using the discretized WMR model and the non-feasible ASM (NF-ASM). The performance of NF-ASM is compared to two other well-known traditional algorithms, i.e. Fletcher’s ASM and MATLAB’s Quadratic Programming algorithm. It is shown that, although all these algorithms are capable of providing satisfactory trajectory tracking performance, NF-ASM is a better choice in terms of the simulation time and required number of iterations for realtime trajectory tracking of any type as long as the constraints on the inputs stay active for a long period during the simulation.
Chapter 9. Bringing writers' voices to writing research: Talk around texts

This chapter explores how a key methodology developed by Roz Ivanič, “talk around texts”, constitutes a fundamental contribution to writing research in three ways; firstly by disrupting conventional researcherresearched positioning; secondly by keeping writers centre stage even whilst using text-linguistics; and thirdly by opening up opportunities for re-examining textual practices, by questioning what should (and could) be valued in formal institutions of learning. I locate this methodology within the particular values Ivanič espouses, as evidenced by both her pedagogic and her academic-theoretical work and illustrate how my own research has been influenced by this work in specific research decisions that I have made and in generating further questions that I am still struggling to address.
Implementation of Enhanced Graph Layout Algorithm for Visualizing Social Network Data using NetworkX Library

Networks are critical to modern society, and a thorough understanding of how they behave is crucial to their efficient operation. Fortunately, data on networks is plentiful; by visualizing this data, it is possible to greatly improve our understanding. Firstly, this paper discusses about social media and the use of Social Media Analytics by businesses. Second, how we plan to use available resources to analyze the sample case of a given social network. As a Case Study, this paper will demonstrate how by starting at a single twitter account we can build up a network graph of twitter followers and then visualize that network using the NetworkX library. In this seed account is used to collect twitter followers. After that, Process the collected twitter data to generate an output file of relationships between twitter accounts. At last, Visualize network data in a network graph using the NetworkX library. In this paper Snowball sampling algorithm is used. Keywords: Network visualization, Parameter focusing, social media Analysis, Network data analysis, Data manipulation
Prototype of Home Monitoring Device Using Internet of Things and River Formation Dynamics-Based Multi-Hop Routing Protocol (RFDHM)

Wireless sensor networks (WSNs) are an emerging technology to assist Internet of Things (IoT)-related applications. Applications, such as automated power control, monitoring of houses to prevent from theft, etc., can be implemented using IoT. In this paper, one such application is considered and WSN-based IoT system is proposed. The proposed system uses three passive infrared (PIR) motion sensors connected to a camera to capture the images of person entering or leaving the house. The captured images are communicated to the server for storing and further processing. This information is also used to switch OFF or ON power appliances, such as fan, lights, etc., thereby reducing power consumption. The forwarding of information, such as number of persons present in the room and the images of the persons entering or leaving the house is done using river formation dynamics-based multi-hop routing protocol (RFDMRP). A prototype of the proposed system is developed, installed, and tested.
A block-structured model for banking networks across multiple countries

A block-structured model for the reconstruction of directed and weighted financial networks, spanning multiple countries, is developed. In a first step, link-probability matrices are derived via a fitness model that is calibrated to reproduce a desired density and reciprocity for each block (i.e. country and cross-border sub-matrix). The resulting probability matrix allows for fast simulation through bivariate Bernoulli trials. In a second step, weights are allocated to a sampled adjacency matrix via an exponential random graph model (ERGM), which fulfills the row, column, and block weights. This model is analytically tractable, calibrated only on scarce publicly available data, and closely reconstructs known network characteristics of financial markets. In addition, an algorithm for the parameter estimation of the ERGM is presented. Furthermore, calibrating our model to the EU interbank market, we are able to assess the systemic risk within the European banking network by applying various contagion models.
SISTEM PENDUKUNG KEPUTUSAN UNTUK MEMPREDIKSI KELULUSAN MAHASISWA MENGGUNAKAN METODE NAÏVE BAYES

Abstrak Sistem Pendukung Keputusan untuk menentukan tingkat prediksi kelulusan mahasiswa digunakan untuk menentukan tingkat kelulusan mahasiswa di Progdi Sistem Informasi. Prediksi tersebut nantinya digunakan sebagai sumber informasi untuk menghasilkan sebuah keputusan. Penelitian ini menghasilkan sistem pendukung keputusan dengan menggunakan metode Naive Bayes dengan menggunakan beberapa parameter, yaitu jenis kelamin, alamat, umut, status pekerjaan mahasiswa, status pernikahan mahasiswa, rata-rata IPK, jumlah SKS dan status mahasiswa. Pengolahan data mining mahasiswa dengan menggunakan metode naive Bayes dimulai dari proses Data Gathering, Data Preprocessing, Proposed Model/Method, Method Test and Experiment, Result Evaluation and Validation. Dalam penelitian ini hasil yang dicapai memiliki akurasi untuk tepat waktu sebesar 93% dan akurasi untuk terlambat sebesar 71%. dengan menggunakan metode Naive Bayes yang semakin optimal dengan menentukan mahasiswa lulus tepat waktu atau terlambat Kata kunci: akurasi, data mining, naive bayes, tepat waktu, terlambat
Role of Magnetic Resonance Spectroscopy for Prognosis of Patients with Traumatic Brain Injury

Abstract Background Traumatic brain injury (TBI) is one of the leading causes of death worldwide. Long-term clinical outcome following TBI can be difficult to predict. Evaluation of the degree of severity of injury and prediction of outcome are important for the management of these patients. Objective To evaluate whether degree of severity of injury and outcome in moderate to severe TBI is possible by proton magnetic resonance spectroscopy (1H-MRS). Materials and Methods Patients with moderate (Glasgow coma scale [GCS] 9–13) and severe head injury (GCS: 5–8), within 1 week of trauma with their normal computed tomographic (CT) scan findings, their magnetic resonance imaging (MRI) finding, and neurologic status were investigated with single-voxel proton MRS (1H-MRS). The study included 51 patients and 24 controls. Result The MRS study revealed lower ratio of N-acetylaspartate (NAA)/choline (Cho) and NAA/creatine (Cr) and higher ratio of Cho/Cr and lactate level compared with the control group. The ratio of NAA/Cr, NAA/Cho, and Cho/Cr were statistically significant with initial GCS (p = < 0.00001, r = 0.7595; p = < 0.00001, r = 0.7506; and p < 0.00001, r = −0.5923, respectively), and these ratios were also statistically significant with Glasgow outcome scale (GOS) (p < 0.00001, r = 0.8498, p < 0.00001, r =0.9323, p < 0.00001, r = −0.9082, respectively). The ratio of NAA/Cr, NAA/Cho, and Cho/Cr were also statistically significant with severity of injury (p < 0.0001). Conclusion MRS can quantify damage after TBI and may be a method of assessing severity and outcome in TBI.
A process for software architecture evaluation using metrics

Software systems often undergo changes. Changes are necessary not only to fix defects but also to accommodate new features demanded by users. Most of the time, changes are made under schedule and budget constraints and developers lack time to study the software architecture and select the best way to implement the changes. As a result, the code degenerates, making it differ from the planned design. The time spent on the planned design to create architecture to satisfy certain properties is lost, and the systems may not satisfy those properties any more. We describe an approach to systematically detect and correct deviations from the planned design as soon as possible based on architectural guidelines. We also describe a case study, in which the process was applied.
Using Contextual Information to Improve Hidden Markov Model Recognition of Wrist Motions During Eating Activities

This dissertation considers the problem of recognizing wrist motions during eating. The wrist motion is tracked using accelerometer and gyroscope sensors worn in a watch-like device. The goal is to recognize a set of gestures that commonly occur during eating, such as taking a bite of food or consuming a drink of liquid. The wrist motion during a bite may consist of picking up a morsel of food, moving it the mouth for intake, and returning the hand to a rest position. Hidden Markov models (HMMs) are used to recognize these motions. An HMM is a doubly stochastic process where one set of stochastic processes generates the observables, in this case the sensor readings, and is controlled by another set of stochastic processes that is not observable, in this case the eating gestures. A benefit of an HMM is that it can encode the temporal structure of the signal, in this case the expected subsequence of motions comprising a gesture. The ideas pursued in this dissertation are motivated by methods used to improve the capability of HMMs to recognize speech. For example, it is challenging to build a generic HMM to capture all the varieties of accents and dialects of speakers. People in different regions may speak the same language with variations in pronunciation, vocabularies, and grammars. Building HMMs for each dialect group can improve the robustness of the system under speech variations. This dissertation attempts the similar analysis of wrist motion during eating activities. Similar to dialects and accents in speech, we propose that the demographics (gender, age, ethnicity), utensil being used, or types of foods being eaten, may cause variations in the wrist motions while eating. Several variations on this concept are explored and compared to baseline recognition accuracies. In Chapter 2, work is first described to establish a baseline accuracy of a non-HMM method. The method uses a simple pattern matching algorithm that only detects one type of gesture (called “bites” but includes any food or liquid intake). The method was tested on 276 people eating a meal in a cafeteria and was evaluated on 24,088 bites. It achieved 75% sensitivity and 89% positive
Détection hiérarchique multi-classes d'objets dans les images

Nous presentons une methode de detection multi-classes qui regroupe differentes classes d'objets dans une hierarchie pour ameliorer le score de detections. Pour parcourir l'arbre, nous proposons d'utiliser un algorithme de recherche efficace permettant de trouver le plus court chemin.
The Distal Impact of Two First-Grade Preventive Interventions on Conduct Problems and Disorder in Early Adolescence

In this article, we examine the impact of two universal, first-grade preventive interventions on the prevalence of conduct problems and disorder and mental health service need and use in early adolescence. The classroom-centered (CC) intervention was designed to reduce the risk for later conduct problems and disorder by enhancing teachers' behavior management in first grade, whereas the Family-School Partnership (FSP) intervention targeted improvement in parent-teacher communication and parents' child behavior management strategies. At Grade 6, or age 12, CC and FSP intervention children received significantly lower ratings from their teachers for conduct problems than control children. CC and FSP children were also significantly less likely than control children to meet diagnostic criteria for Conduct Disorder and to have been suspended from school in the last year. In addition, the CC intervention was associated with significantly lower rates of child mental health service need and utilization. Overall, the CC intervention appeared to be the more effective of the two in reducing the prevalence of conduct problems and disorder at age 12 and in reducing mental health service need and utilization. Nevertheless, future studies may show that the combination of CC and FSP interventions produces additive or even synergistic effects.
Kinematic, dynamic and workspace analysis of a novel 6-DOF parallel manipulator

To my parents and friends. You complete me. Acknowledgement I express my sincerest gratitude for my advisor, Dr. Krovi, for the constant guidance and support throughout the course of my MS degree, especially during the thesis. I also express my thanks to Dr. Roger Mayne and Dr. John Crassidis for being my committee members and critiquing my thesis report. I also thank the ARMLAB members for their support. Special thanks goes to LengFeng and Madu for helping to write the publications related to this thesis. I would also like to thank Sumit for being an excellent labmate, roommate and project partner and for his critique to my ideas and concepts throughout the duration of the thesis. I am also grateful to Xiaobo and Colin for being helpful and patient whenever I needed their help. productive. I also thank Dr. and Mrs. Dhiraj Shah for helping continually and graciously during my entire stay in Buffalo. In the end, but most importantly, I would like to thank my parents, who have always supported my dreams and motivated me to achieve them. I dedicate this work to their unending love and support, even when I was distant from home.
Design and Implementation of Bi-Directional DC-DC Converter for Wind Energy System

This paper proposes a design and implementation of the bi-directional DC-DC converter for Wind Energy Conversion System. The proposed project consists of boost DC/DC converter, bi-directional DC/DC converter (BDC), permanent magnet DC generator and batteries. A DC-DC boost converter is interface with proposed wind system to step up the initial generator voltage and maintain constant output voltage. The fluctuation nature of wind makes them unsuitable for standalone operation. To overcome the drawbacks an energy storage device is used in the proposed system to compensate the fluctuations and to maintain a smooth and continuous power flow in all operating modes to load. Bi-directional DC-DC converter (BDC) is capable of transforming energy between two DC buses. It can operate as a boost converter which supplies energy to the load when the wind generator output power is greater than the required load power. It also operates in buck mode which charges from DC bus when output power is less than the required load power. The proposed converter reduces the component losses and increases the performance of the overall system. The complete system is implemented in MATLAB/SIMULINK and verified with hardware.
DOES PROBLEM-BASED LEARNING IMPROVE CRITICAL THINKING SKILL?

Abstract: The study aims to understand the implementation of Problem-Based Learning and its impact on critical thinking skills for senior high school students. The study used the lesson study approach that was conducted in four cycles. Each learning activity consisted of identifying topic, presenting the report, and evaluating the Problem-Based Learning. The subject of the study was in a Senior High School in Malang, Indonesia. The level of critical thinking refers to Structure Observed Learning Outcome (SOLO) Taxonomy, consisting of Prestructural, Unistructural, Multistructural, Relational, and Extended Abstract thinking levels. The findings in the learning process show that the students’ critical thinking skills has increased. It is revealed by improving the ability to solve problems and making conclusions through critical thinking processes. The implementation of Problem-Based Learning also encourages students to think critically in the form of questioning, discussing problems and making solutions related to the employment issues, national income and economic growth in Indonesia. Keywords: Problem-Based Learning, Critical Thinking Skills, Lesson Study APAKAH PROBLEM-BASED LEARNING DAPAT MENINGKATKAN KEMAMPUAN BERPIKIR KRITIS? Abstrak: Penelitian ini bertujuan untuk mengetahui penerapan Problem-Based Learning dan pengaruhnya terhadap kemampuan berpikir kritis pada siswa sekolah menengah atas. Penelitian ini menggunakan pendekatan lesson study yang dilakukan melalui empat siklus. Setiap aktivitas pembelajaran terdiri dari mengindentifikasi permasalahan, mempresentasikan laporan kegiatan, dan mengevaluasi pelaksanaan Problem-Based Learning. Subject penelitian ini dilakukan pada sebuah Sekolah Menengah Atas di Malang, Indonesia. Tingkat kemampuan berpikir kritis siswa dalam penelitian ini mengacu pada taksonomi SOLO (Structure Observed Learning Outcome) yang meliputi prastruktural, Unistruktural, Multistruktural, Relasional, and Extended Abstract. Hasil penelitian ini menunjukkan bahwa selama proses pembelajaran, kemampuan siswa dalam berpikir kritis telah meningkat. Hal ini ditunjukkan dari peningkatan kemampuan menyelesaikan masalah dan membuat kesimpulan melalui proses berpikir kritis. Penerapan Problem-Based Learning juga mendorong siswa memiliki kemampuan berpikir kritis dalam berbagai aktivitas seperti mengajukan pertanyaan, mendiskusikan permasalahan, dan membuat solusi terkait permasalahan pengangguran, pendapatan nasional, pertumbuhan ekonomi di Indonesia. Kata Kunci: Problem-Based Learning, Kemampuan Berpikir Kritis, Lesson Study
Query Expansion and Noise Treatment for Information Retrieval

Most of the search engines available over the Web are based on mathematical approaches | classical techniques in the Information Retrieval area. Thereby, they are suitable for the retrieval of documents containing some or all the terms of a query, though not to retrieve the documents containing the meaning those terms were intended to express. This paper presents some advantages obtained from query expansion with WordNet and noise treatment with knowledge on top of Paraconsistent Logic. Both methods are semantically driven, allowing the retrieval of documents which do not contain any term of the original query. Noise treatment results from the combination of a smooth term comparison with knowledge about term authentication based on behaviors of features in the collection. Although query expansion recurs for every query, noise treatment is part of the indexing mechanism, causing no overhead in queries. The domain is retrieval of ontologies represented in Resource Description Framework.