Reviewerly/exHarmony huggingface dataset:
Steuerung der Benutzeroberfläche

No AccessLabVIEW für EinsteigerFeb 2019Steuerung der BenutzeroberflächeNicolas KrauerNicolas KrauerSearch for more papers by this authorhttps://doi.org/10.3139/9783446459465.010SectionsAboutPDF ToolsAdd to FavoritesDownload CitationTrack CitationsCopy LTI LinkPDF key 'share (en)' returned an object instead of string.FacebookTwitterEmailLinkedIn previous chapternext chapter FiguresReferencesRelatedDetails 2019Pages: 167-183Print ISBN: 978-3-446-45906-9eISBN: 978-3-446-45946-5 Copyright & Permissions© 2019 Carl Hanser Verlag GmbH & Co. KGPDF downloadLoading ...
Economic Development in Mexico and the Role of Blockchain

This paper studies recent economic and political developments in Mexico and the potential role of blockchain technology in improving governance and fighting corruption in the country. Mexico badly needs innovative solutions to fight the persistent problems of corruption and inefficient governance. At the same time, blockchain, being a decentralized technology, promises to reduce administrative costs and ensure transparency in the public services. The paper takes stock of the current state of blockchain implementation in the economy and in the public administration of Mexico as well as studies the advantages and disadvantages related to the further outspread of the technology in the country. Moreover, the work aims at drawing policy recommendations as to the future role of blockchain in the public management and economic development in Mexico.
A Note with Computer Exploration on the Triangle Conjecture

The triangle conjecture states that codes formed by words of the form $$a^i b a^j$$ are either commutatively equivalent to a prefix code or not included in a finite maximal code. Thanks to computer exploration, we exhibit new examples of such non-commutatively prefix codes. In particular, we improve a lower bound in a bounding due to Shor and Hansel. We discuss in the rest of the article the possibility of those codes to be included in a finite maximal code.
Engaging K–12 Students in the Management of Educational Technology in Schools: A Strategy for Self-determination Development

AbstractInitiatives that have brought information and communication technologies into classrooms across the world often struggle to engage the school community to effectively use them. At the same time, involving students in extracurricular activities at school has been demonstrated to bring benefits in student motivation and academic achievement. This paper explores how Colombian K–12 students experience their participation in networks created—both at school and city level—to manage educational technologies in their schools through the lens of self-determination theory. The results suggest that student participation in these networks supports the development of the three psychological needs supporting intrinsic motivation: competence, autonomy, and relatedness. Students feel competent after participating in workshops and learning activities designed to support their responsibilities as members of the network; students feel the need to investigate and become more competent to be able to support teachers, other students, and their own families; students demonstrate autonomy by proposing activities within the network that may benefit their school and the school community; finally, students report changes in their relationship with teachers and other students as they become recognized as providers of technological support to their communities.
AVP: Physics-informed Data Generation for Small-data Learning.

Deep neural networks have achieved great success in multiple learning problems, and attracted increasing attention from the medicine community. In reality, however, the limited availability and high costs of medical data is a major challenge of applying deep neural networks to computer-aided diagnosis and treatment planning. We address this challenge with adaptive virtual patients (AVPs) and the associated physics-informed learning framework. Specifically, the original training dataset is fused with an additional dataset of AVPs, which are generated by a data-driven model and the associated supervision (e.g., labels) is obtained by a physics-based approach. A key novelty in the proposed framework is the bidirectional and uncoupled generative invertible networks (GIN), which can extract pathophysiological features from the training medical image and generate pathophysiologically meaningful virtual patients. In order to mitigate the possibly high labeling cost of physical experiments, a $\mu$-measure design is conducted: this allows the AVPs to not only further explore the uncertain regions, but also balance the label distribution. We then discuss the pathophysiological interpretability of GIN both theoretically and experimentally, and demonstrate the effectiveness of AVPs using a real medical image dataset, in which the proposed AVPs lower the labeling cost by 90% while achieving a 15% improvement in prediction accuracy.
PL.05.01 Paternal stress epigenetic germ cell programming of offspring neurodevelopment

Interacting multiple model (IMM) filter is a classical method to track targets in hybrid situations. However, it can exhibit divergence when the models are correlated or the system suffers from uncertainties. The generalized covariance intersection method based on the weighted Kullback–Leibler (K–L) divergence can solve the divergence problem of correlated estimates. A novel interacting multiple model (NIMM) filter is presented that combines two different algorithms, the adaptive fading Kalman filter and the maximum correntropy Kalman filter, based on the model interacting with the weighted K-L divergence to address the uncertainty problems of the system. The NIMM filter algorithm is designed and the stability and accuracy are analyzed. The simulation results demonstrate that the proposed filter can effectively improve the accuracy under different uncertainty conditions for classical examples and ballistic trajectory tracking scenarios.
Course Construction of Logistics Information Technology Based on OBE

In order to improve the cultivation quality of students in Logistics Engineering major of Beijing Union University, course construction of Logistics Information Technology based on Outcome-based Education (OBE) concept is explored in this paper. Three learning outcomes of this course are defined and their relationships with the teaching purposes of the major cultivation scheme are also presented. Then the teaching methods and assessment methods corresponding to the learning outcomes are designed. This study could present one example for the course construction of Logistics Engineering major based on the OBE concept.
A Study of the Effects of Computer-Assisted Packages on the Performance of Senior Secondary Students in Chemistry in Zaria Educational Zone, Kaduna State Nigeria

This study investigated the effect of computer-assisted instruction (CAI) package on the performance of Senior Secondary Students in Zaria, Kaduna state, Nigeria. The study also examined the significance difference of retention achievement scores of students taught using computer-assisted instruction and the conventional lecture method. The population for the study was made up of all the 1800 SSII senior secondary schools chemistry students in Zaria Educational zone, Nigeria The sample consisted of forty senior secondary school students and was drawn from two secondary schools. Stratified random sampling was used to select the 40 students (20 males and 20 females) four research questions and four hypotheses were formulated, and tested at 95% confidence level. Chemistry Achievement Test (CAT) and Chemical Retention Test (CRT) made of 50 items of multiple-choice questions each were developed and validated for data collection. The Chemistry achievement Test (CAT) was administered to students as pretest-posttest and the Chemistry Retention Test (CRT) as a post treatment-test. The results of students were analyzed using t-test statistics to test the hypotheses. The result indicated that there is a significant difference between the performances of students taught using (CAI) package, and those taught using the conventional lecture method of instruction(t cal=7.77>tcrit=2.093 at P t crit=2.093 at P< 0.05 The result also showed there was no significant difference in the post-test performance scores of male and female students taught using CAI of package. Based on the findings it was concluded that the use of computer assisted instructional packages significantly improved the performance of students in chemistry. It was recommended that Computer-Assistant instructional packages should be encouraged for teaching and learning of chemistry.
FSSPD: Fast Single Stage Pedestrian Detector for Autonomous Driving

For low accuracy of the anchor-based pedestrian detectors in the case of small and high-density pedestrian, a Fast Single Stage Pedestrian Detector (FSSPD) is presented, which has three merits. Firstly, a single stage anchor-based neural network is designed on the base of the modified Darknet-19 instead of the widely used VGG-16, largely reducing inference time during pedestrian detection. Secondly, Darknet-19 usually adapted in YOLOv2 is modified by using a scale invariant network structure with multi detection modules to detect small pedestrians. Thirdly, a dense anchor strategy is proposed to deal with high mistake rate and miss rate of high-density pedestrian. As a result, the proposed network structure and strategies are proved effective for small and highdensity pedestrian detection. On the evaluation set of KITTI dataset, dense anchor strategy improves the average precision by 1.5%, 1.5% and 1% in easy, moderate and hard level, respectively. And the multidetection- module strategy works well for small pedestrian with significantly improving the average precision by 15.8%, 16.5% and 17% in these three difficulty levels, respectively. On the test set of KITTI dataset, our approach get a comparative result compared to previous methods at the speed of 14.3fps in near real time. This indicates that FSSDP is suitable for pedestrian detection as a lightweight framework with a good tradeoff between precision and speed.
Styles, Themes, and CSS

User interface design challenges us to elegantly and functionally position layouts and controls while maintaining a coherent design and a consistent user experience across the entire application. This chapter is not about creating beautiful and visually appealing applications, which is an art in and of itself. This chapter explores beautiful and appealing ways to architect your UI code, separating the presentation from the content and structure using resources, styles, themes, and Cascading Style Sheets. Creating beautiful designs is a journey, and the purpose of this chapter is to take you on a journey from a simple but functional page to one that is also beautiful, dynamic, and maintainable. Reusability of UI code offers consistency of design, cleaner and more readable code, and the agility to change the look of the application over time.
Detecting Forged Scan of Educational Certificates Using a New Feature Set Matching Algorithm

Detection of forge scan certificates which are used during college admissions are done using scan copies from other genuine resources and materials and resources applying Photoshop and other image processing tools. This kind of certificates from different resources are used for creating scan certificate copies using Photoshop and giving that information to the name of other candidates. This situation leads to a point whereupon digital forgery can compromise the authenticity of the original documents. Using fake certificates to get jobs is worst as the eligibility of the candidate cannot be verified by administrative authorities in educational institutes. Nowadays many research oriented tools are used for detecting copied sections from different documents. In order to enhance trustworthiness and authenticate images, we have defined a feature point matching algorithm to identify forgery done in inaccurate manner. In our proposed study we have applied by an image processing algorithm to combine feature point matching tools and adaptive segmentation to identify suspected irregular patterns detected by the adaptive non-overlapping and irregular blocks and this process is carried out using the adaptive over-segmentation algorithm. The extraction of the feature points is performed by identification of the matching between each block and its features. The feature points are gradually replaced by using the super pixels in the proposed Forgery Region Extraction algorithm and then combine the adjacent blocks having similar color features to find out the merged regions for identification of the detected forgery regions.
Protecting Cloud-Based CIs: Covert Channel Vulnerabilities at the Resource Level

Critical Infrastructures (CIs) increasingly leverage Cloud computing given its benefits of on-demand scalability, high availability and cost efficiency. However, the Cloud is typically characterized by the co-location of users from varied security domains that also use shared computing resources. This introduces a number of resource/architecture-level vulnerabilities. For example, the usage of a basic shared storage component, such as a memory cache, can expose the entire Cloud system to security risks such as covert-channel attacks. The success of these exploits depends on various execution environment properties. Thus, providing means to assess the feasibility of these attacks in a specific execution environment and enabling postmortem analysis is needed. While attacks at the architectural level represent a potent vulnerability to exfiltrate information, the low-level often get neglected with techniques such as intrusion detection focused more on the high-level network/middleware threats. Interestingly, cache-based covert-channel attacks are typically not detectable by traditional intrusion detection systems as covert channels do not obey any access rights or other security policies. This paper focuses on the information provided at the low architectural level to cope with the cache-based covert-channel threat. We propose the usage of feasibility metrics collected at the low level to monitor the core-private cache covert channel and, infer information regarding the probability of a covert-channel exploit happening. We also illustrate the applicability of the proposed feasibility metrics in a use case.
An Integrative Approach for Tracking of Mobile Robot with Vision Sensor

Current work addresses an experimental approach which incorporates feature-based object detection, KLT algorithm-based tracking method and Kalman filter-based de-noising technique in a real-time environment. In the detection phase, the mobile robot is detected using Viola-Jones algorithm which extracts detectable features. Then the position of the mobile robot is computed with homography constraints and a region of interest window is set up to accommodate the mobile robot. In the tracking phase, the region of interest window is dealt with using KLT algorithm. The proposed method is of practical importance when the mobile robot is tracked while moving on a predetermined (specified) path as the size of the image of the mobile robot is small relative to the captured image of the environment. Thus the analysis of captured image of environment becomes unnecessary for tracking and thereby the approach reduces computational load. The proposed approach accurately detects and tracks the mobile robot with error percentage ranging from 0.5% to 10% in different parts of the specified path.
Facts and mysteries in elementary particle physics

The first edition of Martinus Veltman’s ‘Facts and Mysteries in Elementary Particle Physics’ appeared in 2003 and was an acclaimed success. Distinguished theoreticians have sometimes had difficulti...
Computer Networks (COMNET) Editorial for 2018

IOTA is a distributed ledger technology for the Internet-of-Things (IoT) industry. The protocol distinguishes itself from existing distributed ledgers by being formed on a directed acyclic graph. To enable micro-transactions for smart devices, it uses a scalable approach for network growth and transaction confirmations. Being a public distributed ledger, the transactions on the ledger are completely transparent hence opening up the possibilities for linking and identification attacks. Different promising privacy enhancing techniques have been proposed for improving anonymity in distributed ledgers. However, many of the proposed approaches provide security guarantees only against Elliptic Curve Digital Signature (ECDSA) schemes and thus become incompatible with the IOTA ledger because IOTA uses quantum resilient hash-based signatures. While centralized solutions can still work with IOTA ledger for enhancing privacy, they are still proprietary and prone to single point of failures. We propose a novel decentralized mixing protocol for the IOTA ledger that incorporates a combination of decryption mixnets and multi-signatures. Our technique does not require any (trusted or accountable) third party and it is completely compatible with the IOTA protocol. Analysis of our results for this technique shows that the security and privacy are guaranteed even in the presence of malicious entities in the system. Our technique provides strong privacy to the IOTA ledger and the degree of anonymity it adds, protects entities against identification and linking attacks.
From Memes To Technomemes and Digital Selves.

For thousands of years we have been around with a biological self and a psychological self. The biological self is based on genes, the psychological one is based on memes and memeplexes. Today the situation is slightly different: the many of us today have a biological self, a psychological self and a digital self and a phenomenon that characterize our times, and not only something that involves millennials, is the tendency to privilege the digital self over everything else.The digital self is so often perceived as even more relevant than the psychological self. The sense of identity and even psychological security is getting more and more digitalized: from cultural / ideological / family-based propagated and indoctrinated memes we entered the digital world of technological memes and the problem is that considering how the psychological self is in itself heavily conditioned by so many memetic factors that usually go unseen and unstudied, the digital self is actually even worse than that. Not because of the onset of social media, new technologies and AI development and its applications, but because of the dull and acritical relationship we have with such elements and with our own use of our thinking abilities; we are moving towards a society of entertainment and superficial thinking and this situation, which appears to be an actuality of our times, should show us what the urgency of implementing our thinking skills really is. Critical thinking should be combined with the understanding of memetics and the application of high order multilogical thinking skills.
30 anos do Arquivo Central da Universidade Federal de Santa Catarina

Commemoration of the 30th anniversary of the Central Archive of the Federal University of Santa Catarina
Sixth Sense Hand-Mouse Interface Using Gestures and Randomized Key

Automated teller machines in their modern form have been around for almost 50 years. And given that ATMs represent an apparently unattended box packed with cash, criminals have been keen on them for all that time. But attacks on cash machines – to steal not only money but customer data too – have been increasing significantly in recent years. How can they be stopped? ATM Security has always been one of the most prominent issues concerning the daily users and the not so frequent ones as well. While the ATM is used in large amount in the commercial banks and postal savings to deposit and draw conveniently and praised by the users, but dispute cases and financial crimes about it are increasing day by day. This paper emphasizes on the hypothetical, yet very possible scenario of an individual’s ATM machine Security with a low but Efficient cost hardware system. Our proposed model uses certain factors which would be monitored right from the initiation, to the end of the respective transaction. We have proposed a sixth sense ATM which uses No touching of any objects but by just using your gestural interface it lets us do the normal operations of ATM authentication system. Also it uses a High alert security system for reducing or eliminating ATM thefts.
Risk for antipsychotic-induced extrapyramidal symptoms: a focus on monoamine receptors on peripheral blood lymphocytes

Single image super-resolution (SR) aims to estimate a high-resolution (HR) image from only one observed low-resolution (LR) image. It is a severely ill-posed problem that needs image priors to ensure a reliable HR estimation. Since different priors usually emphasize different aspects of image characteristics, it’s a big challenge to impose a balanced-and-overall image property constraint on single image SR. In this paper, we cast single image SR into a maximum a posteriori optimization problem and combine two types of complementary priors to answer this challenge. One prior is a novel local gradient field prior derived from example-based gradient field estimation (EGFE) that focuses on recovering the sharpness of gradient profiles. It is good at enhancing the edge sharpness and restoring fine texture details. Whereas the other is a powerful non-local low rank prior implemented in a weighted adaptive p-norm model (WANM). By imposing lp penalties adaptive to regional saliency and weighted constraints, the WANM prior performs well in preserving edge smoothness and suppressing image noise and reconstruction artifacts. An improved Split Bregman Iteration method that adaptively attenuates the regularization strength is further developed to solve the proposed EGFE-WANM SR problem. Comprehensive experiments are conducted and the results show that the proposed EGFE-WANM SR method outperforms many state-of-the-art methods in both objective evaluations and subjective visual comparisons.
Research Guides: Copyright Clearance Center Guide: Content Covered by Copyright Clearance Center License

Best practices for the classroom and workplace. Does our license allow you to photocopy or electronically distribute copyrighted materials to your students, staff or co-workers? Carilion Clinic has a Copyright Clearance Center business license; Jefferson College and VTCSOM have Copyright Clearance Center academic licenses. Permission to use content varies--use the journal ISSN or the book ISBN to determine whether our license(s)
Relationship between women’s education and economic growth (case study selected Islamic countries)

Education and education are essential as one of the key pillars of economic development that boosts talent and improves the quality of manpower. Against gender discrimination in education and training can be a serious obstacle to the achievement of societies for economic growth and development. Accordingly, one can consider the study of women's education and its role in economic development from this point of view. This research analyzes the role of women's education in economic development in 13 selected Islamic countries including Iran, Turkey, Indonesia, Pakistan, Qatar, Algeria, Lebanon, Egypt, Morocco, Tajikistan, Bangladesh, Saudi Arabia and Kyrgyzstan between 2000 and 2014) Using the dynamic data panel model and modified least squares estimation methods (FMOLS) and dynamic least squares (DOLS) methods. Our criterion for choosing these countries is the availability of statistical data. According to the results, women's education has had a positive and significant effect on GDP growth in these countries. Therefore, in view of the theoretical and statistical descriptions of this study, it is necessary to adopt appropriate policies for the development of science in order to promote economic growth in these countries.