Miracle-dz/UniFAR-FTUs huggingface dataset:
Secure Full Duplex Communications in the Presence of Malicious Adversary

In this paper, we study the physical layer security in the presence of an adversary which is able to switch its mode from jamming mode (when transmits jamming signals) to eavesdropping mode (when adversary eavesdrops legitimate link) and vice versa. To combat with this type of adversary and establish security in this communication, we propose two approaches: 1) probabilistic approach (PA), 2) worst case approach (WCA). The system model consists of a source, an adversary and full-duplex destination. A full-duplex destination can receive the private message and transmit jamming signal to deceive the adversary, simultaneously. The simulation results show that the average rate PA, is 50% more than the WCA.
Trustworthiness Evaluation-Based Routing Protocol for Incompletely Predictable Vehicular Ad Hoc Networks

Incompletely predictable vehicular ad hoc networks is a type of networks where vehicles move in a certain range or just in a particular tendency, which is very similar to some circumstances in reality. However, how to route in such type of networks more efficiently according to the node motion characteristics and related historical big data is still an open issue. In this paper, we propose a novel routing protocol named trustworthiness evaluation-based routing protocol (TERP). In our protocol, trustworthiness of each individual is calculated by the cloud depending on the attribute parameters uploaded by the corresponding vehicle. In addition, according to the trustworthiness provided by the cloud, vehicles in the network choose reliable forward nodes and complete the entire route. The analysis shows that our protocol can effectively improve the fairness of the trustworthiness judgement. In the simulation, our protocol has a good performance in terms of the packet delivery ratio, normalized routing overhead and average end-to-end delay.
Spectrally efficient turbo reception technologies for single-carrier broadband wireless communications

Future broadband wireless communication systems are expected to increase both their transmission (TX) rate and their spectrum efficiency under the constraints of low TX power and a low computational complexity. In general, a data sequence is transmitted together with overheads such as training sequence (TS) required to perform energyand computationally-efficient reception techniques. We hence have a trade-off between the spectral efficiency and the receiver performance. The objective of this thesis is to enhance robustness of the receiving algorithms with reasonable complexity, aiming to improve the trade-off. For this purpose, l1 regularized channel estimation techniques are studied under an assumption that broadband wireless channels observed at a receiver does not fully exhibit dense nature in a low to moderate signal-to-noise ratio (SNR) regime. This thesis proposes a novel conditional l1 regularized minimum mean square error (MMSE) channel estimation and chained turbo estimation (CHATES) algorithms to solve the inter-block-interference (IBI) problem incurred as the result of pursuing spectral efficiency. A new l1 least squares (LS) and l2 MMSE-based hybrid channel estimation algorithm is also proposed to solve the tracking error problem often observed with intermittent transmission. Moreover, performance analysis shows that an l1 regularized MMSE channel estimation algorithm can achieve the Cramér-Rao bound (CRB) asymptotically even when random TSs are used. This thesis further studies frequency domain turbo equalization techniques without cyclic prefix (CP) transmission to improve the spectral efficiency. The previously-proposed chained turbo equalization, referred to as CHATUE1, allows us to use a lower rate code. However, it can suffer from the noise enhancement problem at the equalizer output. As a solution to the problem, this thesis proposes a new algorithm, CHATUE2. The theoretical analysis supported with simulation results shows that the proposed CHATUE2 can solve the problem after performing enough turbo iterations by utilizing a new composite replica constructed with the conventional soft replica and received signals.
ÖĞRETMEN YETERLİĞİ VE NİTELİKLERİ ÜZERİNE YAPILMIŞ LİSANSÜSTÜ ÇALIŞMALARIN İNCELENMESİ: BİR İÇERİK ANALİZİ ÇALIŞMASI

Bu calismanin amaci ogretmen yeterligi, niteligi, oz-yeterligi ve ozelligi alanlarinda yayinlanmis yuksek lisans ve doktora tezlerini belirlenen olcutlere gore incelemektir. Tarama modelindeki bu calisma, icerik analizine dayali olarak gerceklestirilmistir. Arastirma kapsaminda YOK Ulusal Tez Merkezinde 2000-2017 yillari arasinda yayinlanan, belirlenen konu alanlarinda, erisime acik olan lisansustu tezleri incelenmistir. Calismada amacli ornekleme yontemi ile ulasilan 54 adet lisansustu tezi arastirmaci tarafindan olusturulan tez inceleme formu ile analiz edilmistir. Bu temel amac dogrultusunda, tezler yayinlandigi yil, konu alanlari, hazirlandigi universite, enstitu, alani, yontemi, veri toplama araclari, orneklem turu ve orneklem buyuklugu acisindan degerlendirilmistir. Calismanin guvenirligini saglamak amaciyla tekrar kodlama guvenirligi hesaplanmistir. Elde edilen veriler, yuzde ve frekansa dayali bir sekilde yorumlanmistir. Arastirma sonucuna gore en fazla sayida calismanin 2010 yilinda yapildigi, calismalarin daha cok ogretmen yeterligi alaninda yogunlastigi, sayisal olarak en fazla tezin Gazi Universitesi’nde ve bunlarin buyuk cogunlugunun egitim bilimleri enstitusunde hazirlandigi belirlenmistir. Ayrica calismalarin egitim programlari ve ogretim alaninda yogunlastigi, veri toplama araclari olarak genellikle anket ve olceklerin kullanildigi ve bunlarin analizinde cogunlukla nicel analiz yontemlerine basvuruldugu ve ayrica orneklem turunde tesadufi orneklem kullanildigi gorulmustur. Arastirma, lisansustu calismalarin yonelimlerini ortaya koyarak arastirmacilara yol gosterici olmasi bakimindan onem tasimaktadir.
Plongements lexicaux spécifiques à la langue arabe : application à l’analyse d’opinions (Arabic-specific embedddings : application in Sentiment Analysis)

Nous nous intéressons, dans cet article, à la tâche d’analyse d’opinions en arabe. Nous étudions la spécificité de la langue arabe pour la détection de polarité. Nous nous focalisons ici sur les caractéristiques d’agglutination et de richesse morphologique de cette langue. Nous avons particulièrement étudié différentes représentations d’unité lexicale : token, lemme et light stemme. Nous avons construit et testé des espaces continus de ces différentes représentations lexicales. Nous avons mesuré l’apport de tels types de representations vectorielles dans notre cadre spécifique. Les performances du réseau CNN montrent un gain significatif de 2% par rapport à l’état de l’art.
Factors Inﬂuencing Teacher Professionalism Development on Secondary School

Development is a permanent issue in school worldwide which teacher demand in enhance their competence, especially in professionalism competence. The main purpose of this article is to investigate whether three factors were inﬂuence teacher professionalism development, those are (1) leadership of principal, (2) organizational commitment, (3) school culture. This research is survey research. The population was 182 teachers of Muhammadiyah Secondary School of Yogyakarta. A sample of 162 teacherswasestablishedusingthesimplerandomsamplingtechnique.Thedatawere collected through questionnaire that had been tested for validity and reliability. The data analysis technique used double regression. The research ﬁnding shows that there was a positive and signiﬁcant effect of: (1) leadership of principal on teacher professionalism development, as much 15,7%, (2) organizational commitment on teacher professionalism development, as much 15,7%, (3) school culture on teacher professionalism development, as much 21,1%.
Subgraph Methods for Comparing Complex Networks

xi List of Abbreviations and Symbols Used . xii Acknowledgements . xiii Chapter
Endoscopic Management of Supratentorial Ventricular Tumors

Background: Intraventricular tumors are ideal indications for neuroendoscopic surgery. Because intraventricular tumors often cause cerebrospinal fluid (CSF) pathway obstruction, resulting in ventricular dilation and sufficient space for maneuvering with the endoscopes is available. Objective: The aim of this study was retrospectively and antrospectively evaluation of the role and outcome of use of endoscope in intraventricular tumors in term of: 1-Diagnostic of the deep lesions. 2- Management of increased intra-cranial pressure (ICP). 3-Excision of tumor depends on the type. Patients and Methods: This prospective and retrospective study was carried on 30 patients who sought medical advice for intra ventricular tumor from 2015 to 2019 in Al-Hussein University Hospital. Tumors are removed or biopsied with or without ETV and septum pellucidostomy. Results: According to our study, we found that endoscopic removal of intraventricular tumors has low rate of complications. There were 25 cases with no complications (83.3%) and better outcome. There were 15 cases (50%) very good outcome and 10 cases (33.3%) were good outcome, as there was minimal dissection and brain retraction. Conclusion: Regarding endoscopic treatment of intra ventricular tumors, there are many advantages of the endoscopic approach as low rate of complications, minimal dissection, better outcome, brain retraction, rapid access to the target and excellent visualization of the lesion and surrounding structures. Endoscopic approach also has the ability of treatment of the associated hydrocephalus at the same session with low rate of failure or recurrence.
Multi Kernel Boosting Algorithm for Image Segmentation and Analysis

: The bootstrap learning algorithm for salient object detection in which both weak and strong models are exploited. First, a weak saliency map is constructed based on image priors to generate training samples for a strong model. Second, a strong classifier based on samples directly from an input image is learned to detect salient pixels. Results from multiscale saliency maps are integrated to further improve the detection performance. The proposes a novel framework to improve the saliency detection performance of an existing saliency model, which is used to generate the initial saliency map. First, a novel regional descriptor consisting of regional self-information, regional variance, and regional contrast on a number of features with local, global, and border context is proposed to describe the segmented regions at multiple scales. Then, regarding saliency computation as a regression problem, a multiple kernel boosting method based on support vector regression (MKB-SVR) is proposed to generate the complementary saliency map. Finally, an adaptive fusion method via learning a quality prediction model for saliency maps is proposed to effectively fuse the initial saliency map with the complementary saliency map and obtain the final saliency map with improvement on saliency detection performance. Experimental results on two public datasets with the state-of-the-art saliency models validate that the proposed method consistently improves the saliency detection performance of various saliency models.
Complex Event Processing Module in IOT Resource Access and Intelligent Processing Platform

The enormous number of sensors and smart objects being conveyed in the IOT (Internet of Things) represent the potential for IOT platform to identify and respond to live-circumstances. For utilizing this hidden potential, CEP (Complex Event Processing) intends to effectively distinguish event patterns (Complex Event) in the real time sensor stream and thusly help in understanding a ‘distributed intelligence’ in the Internet of Things. IOT Resource Access and Intelligent Processing Platform aims at providing a general platform to access different sensors and smart objects, distribute messages around heterogeneous systems and transform low-level data streams to high-level ones, which complex event processing module is responsible for. Therefore, apart from the basic demand to process real time event stream with low latency and high throughput, this module is also designed to access and create event streams dynamically, manage event streams and processing logistic at runtime and trigger business rule or work flow.
A Semantic Similarity Algorithm Based on the Nearest Common Ancestor Node

The word semantic similarity calculation is the basis of keyword search in the field of semantic web information retrieval. In view of the deficiency of semantic similarity computation in the existing algorithms, this paper discussed the influence of node depth on the semantic similarity, and presented an improved similarity calculation method based on the nearest common ancestor node, which can represent the depth of the two sememe nodes that need to compute the similarity. The simulation was carried out by using simple biological ontology and HowNet system architecture data, and the comparison with the original algorithm was done. The results prove the correctness and rationality of the improved method.
Undervisning og digitale medier - Distraktion, koncentration og engagement

Artiklen fremforer ud fra forskningsprojektet Socio Media Education en model, der gor det muligt at diskutere, hvordan laerere og elever kan reagere pa de nye digitale medier, herunder hvad de undervisningsmaessige konsekvenser kan blive. Modellen beskriver tre bolger, der rummer distinkte reaktioner og konsekvenser. Fokus er pa, hvordan laererne forholder sig didaktisk til de nye digitale/sociale medier. I den forste bolge bliver eleverne fristet af de muligheder for ikkeundervisningsrelevante aktiviteter, som internettet abner op for. Uanset om laererne forbyder eller ignorerer disse muligheder, far det negative konsekvenser for undervisningen. Internettet fremtraeder her som distraktion. Den anden bolge opstar, nar laerere og elever bruger de nye medier til at forbedre deltagelsesmulighederne i undervisningen og til at traekke opmaerksomheden tilbage til undervisningsfaellesskabet. Her fremtraeder internettet som en mulighed for at skabe bedre koncentration. Den tredje bolge bliver til, nar laerere og elever bruger internettet til at inkludere tredje parter i undervisningsinteraktionen. Her fremtraeder internettet som en ny made at skabe dannende engagement pa. Der argumenteres for, at de tre bolger giver hver sine didaktiske perspektiver og diskussioner, der bor adresseres hver for sig; samtisig udgor bevaegelsen fra bolge 1 til bolge 3 et samlet hele, der tillige bor forstas i sin helhed.
Development of Mobile Learning in Faculty of Economics, Bina Nusantara University

The research wanted to find the workflow and solution by developing m-learning object for Android and iOS-based smartphone and tablet that supported interactive multimedia. The research began with analysis, design, implementation, and evaluation. Currently, the learning objects were not compatible with mobile devices. To overcome this problem, the research focused on designing the instructional design for m-learning and the development of interactive multimedia. Instructional design was created by the collaboration of the subject matter expert and instructional designer. M-learning was designed using UML and developed using Adobe AIR technology. The implementation of this research was a prototype of m-learning for concept of cost in Faculty of Economics, Bina Nusantara University. Then, the evaluation was conducted by distributing m-learning object to 32 selected students by simple random sampling in their first week of lectures in February 2014. The observation was conducted during m-learning object installation and initial learning process. At the end of the second week of the experiment, summative assessment and questionnaire were given to students. The results show that m-learning object is compatible with mobile devices. The students also say that m-learning is easy to use and helpful for their learning.
Blue Brain : Bringing a Virtual brain to Life

The Blue Brain Project is the first complex project in which a human is been portrayed in such a way that it helps us to understand its function and dysfunction through detailed simulations. The main aim is to upload human brain into a machine. So that man can think, take decision without any effort. After the death of the body, the virtual brain will act as the man . So, even after the death of a person we can use it for the development of the human society.
Entrepreneurial attitudes of state program “Paraná improving business" participants, in the county of Francisco Beltrão – PR

This study aims to analyze the existence of differences in the attitudes of entrepreneurs in relation to the economic sectors in which they live their projects of participants of the State Program "Parana Improving Business" in the county of Francisco Beltrao - PR. The study took place between the months of March and August 2013. For the data collection was used a model developed by Lopez Jr. (2005) called Attitude Measurement Instrument Enterprising - IMAE. The questionnaire used is a Likert measurement scale of 10 points with a sample of 101 respondents. The study was carried out by a quantitative approach, in which the data were treated by descriptive statistics. In a comparative analysis of the dimensions, the implementation had higher overall averages of agreement, followed by innovation, power and finally the planning dimension. Comparing the industry sectors, trade and services, it was found that there were subtle differences between them. Thus the research proposed a different analytical perspective to the work of Bosma and Schutjens (2007), exploring the entrepreneurial attitudes with spatial differentiations in Europe, analyzing the attribute of economic sectors as distinction vectors.
QoS SUPPORT IN EDGE ROUTERS

many flows are short Web transfers and about 1% of the largest flows carry more than 50% of all bytes. Motivated by the high variability property of Internet traffic, we first analyze the performance of LAS under the M/G/1 queue, where G is a job size distribution with varying degree of variability. The analysis for LAS shows that the conditional mean response time highly depends on the variability of a job size distribution and that the percentage of large jobs that see penalty under LAS is negligible when a job size distribution shows the high variability property. While shortest remaining processing time (SRPT) is known to be the optimal policy in reducing the mean response time, we show that LAS offers a conditional mean response time close to SRPT. When compared to first-come first-serve (FCFS), LAS significantly outperforms FCFS for job size distributions with the high variability property. Moreover, as opposed to FCFS, we prove that LAS can service some jobs even at overload. We then use simulations to investigate the performance of LAS in packet networks for various network configurations. We also study the interaction of LAS with TCP. We find that LAS has quite interesting features that cause it to reduce the transfer time for short TCP flows without penalizing large flows a lot. In addition, we show through simulations that LAS allocates bandwidth equally among competing TCP connections in congested heterogeneous networks. The simulation results show that LAS penalizes long-lived TCP and UDP flows at high network load above 75%. To address this issue, we propose a family of new LAS-based scheduling policies that differentiate the service in order to improve the performance of priority flows. To evaluate these policies, we develop analytic models to compute the mean flow transfer time for TCP flows that share a single bottleneck link that uses LAS or one of new LAS-based policies . Over a wide range of settings , we show that the analytic models agree with the ns2 simulation of the policies in packet networks when loss rates are low. Evaluation of the proposed policies shows that they notably improve the performance of priority flows in terms of reducing their mean transfer time, average jitter, and loss rate while affecting ordinary flows in a minor way. Finally, we evaluate a hybrid policy called LAS-FCFS that services small jobs using LAS and large jobs using FCFS. This policy can be useful when the penalty for the largest jobs under LAS is not acceptable. Analytical results show that LAS-FCFS improves the performance of the largest jobs when a job size distribution exhibits the high variability property. We also analyze an evaluate variants of LAS-FCFS that offer service differentiation.
Design and Characterization of SRAMs for Ultra Dynamic Voltage Scalable (U-DVS) Systems

The ever expanding range of applications for embedded systems continues to offer new challenges (and opportunities) to chip manufacturers. Applications ranging from exciting high resolution gaming to routine tasks like temperature control need to be supported on increasingly small devices with shrinking dimensions and tighter energy budgets. These systems benefit greatly by having the capability to operate over a wide range of supply voltages, known as ultra dynamic voltage scaling (U-DVS). This refers to systems capable of operating from nominal voltages down to sub-threshold voltages. Memories play an important role in these systems with future chips estimated to have over 80% of chip area occupied by memories. This thesis presents the design and characterization of an ultra dynamic voltage scalable memory (SRAM) that functions from nominal voltages down to subthreshold voltages without the need for external support. The key contributions of the thesis are as follows: 1) A variation tolerant reference generation for single ended sensing: We present a reference generator, for U-DVS memories, that tracks the memory over a wide range of voltages and is tunable to allow functioning down to sub-threshold voltages. Replica columns are used togenerate the reference voltage which allows the technique to track slow changes such as temperature and aging. A few configurable cells in the replica column are found to be sufficient to cover the whole range of voltages of interest. The use of tunable delay line to generate timing is shown to help in overcoming the effects of process variations. 2) Random-sampling based tuning algorithm: Tuning is necessary to overcome the increased effects of variation at lower voltages. We present an random-sampling based BIST tuning algorithm that significantly speed-up the tuning ensuring that the time required to tune is comparable to a single MBIST algorithm. Further, the use of redundancy after delay tuning enables maximum utilization of redundancy infrastructure to reduce power consumption and enhance performance. 3) Testing and Characterization for U-DVS systems: Testing and characterization is an important challenge in U-DVS systems that has remained largely unexplored. We propose an iterative technique allows realization of on-chip oscilloscope with minimal area overhead. The all digital nature of the technique makes it simple to design and implement across technology nodes. Combining the proposed techniques allows the designed 4 Kb SRAM array to function from 1.2 V down to 310 mV with reads functioning down to 190 mV. This would contribute towards moving ultra wide voltage operation a step closer towards implementation in commercial designs.