nils-herrmann/clean_scirepeval huggingface dataset:
THE COMPONENTS OF SPEECH EVENTS AND THE USAGE OF LANGUAGE VARIATIONS ON THE CENTRAL CHARACTER IN THE FILM THE GREATEST SHOWMAN
Year: 2019

This study discusses the components of events and the use of language variations of the central figure in The Greatest Showman movie (2017) The purpose of this research is to explain how to use speech and the use of language variations of central figures. This study discusses the emergence of speech events and variations in usage on central character. The method used is descriptive qualitative research method with proficient free listening techniques. The results of data analysis show that the speech component always appears for each variety language and there are four languages variations from five different languages. The variety of languages that are often used by central figures is a consultative style, and the variety that is very little used is the formal style and casual style. For the results, it can be concluded that there are 41 variations in the variety of languages found in Michael Gracey's The Greatest Showman movie (7) Official variations or variations (Formal) (17) Variations or types of business (Consultative) (7 Casual variation or variety, and (8) Intimate variation or variety (Intimate) Of the 41 data found in the film there are 7 formal types with a percentage of 17% 17 different types of businesses with a percentage of 42% 7 types of casualties with a percentage of 17% and 10 intimate varieties with a percentage of 20% Keywords Sosiolinguistic, c omponents of speech events, language variations, central figure.
Audiovisual perception of gemination and pharyngealization in Arabic
Venue: Speech Commun.
Year: 2018

This paper addresses a gap in the literature on audiovisual speech perception. Existing literature has largely examined the degree to which the audiovisual perception of primary place of articulation is influenced by visual information. Visual influences on the audiovisual categorization of a consonant as long (geminate) or short (singleton) have not, however, previously been examined. Furthermore, no experiment, to the authors' knowledge, has examined audiovisual perception of the presence or absence of the secondary articulation of pharyngealization. The experiments reported in this article fill this gap by demonstrating that the audiovisual perception, by Arabic speakers, of both singleton versus geminate and pharyngealized versus non pharyngealized is susceptible to visual influence. These experiments also serve to address the general lack of research on audiovisual speech processing in Arabic. Finally, these experiments provide a methodological advance in dealing with temporal asynchrony when investigating audiovisual speech perception.
Educational Robot Using Lego Mindstorms and Mobile Device
Venue: Advances and Applications in Computer Science, Electronics and Industrial Engineering
Year: 2019

Modern education at different levels has integrated the use of technology as a teaching learning assistant, especially in the initial stage of training because it motivates curiosity and helps the abstraction of knowledge. This paper presents the development of an educational robot using components of the Lego Mindstorms EV3 kit and a mobile app to interact with the student; the robot is build using two motors and two sensors, one to differentiate colours and the other one to measure proximity. The objective is to teach the different colours and explain the spatial position to children under five years old, while the screen of the mobile device interacts with the user. The results show the finished product, the data generated by a learning test, and a usability test, concluding that the robot fulfils its purpose, but requires certain improvements.
Generalizing Fingerprint Spoof Detector: Learning a One Class Classifier
Venue: 2019 International Conference on Biometrics (ICB)
Year: 2019

Prevailing fingerprint recognition systems are vulnerable to spoof attacks. To mitigate these attacks, automated spoof detectors are trained to distinguish a set of live or bona fide fingerprints from a set of known spoof fingerprints. Despite their success, spoof detectors remain vulnerable when exposed to attacks from spoofs made with materials not seen during training of the detector. To alleviate this shortcoming, we approach spoof detection as a one class classification problem. The goal is to train a spoof detector on only the live fingerprints such that once the concept of "live" has been learned, spoofs of any material can be rejected. We accomplish this through training multiple generative adversarial networks (GANS) on live fingerprint images acquired with the open source, dual camera, 1900 ppi RaspiReader fingerprint reader. Our experimental results, conducted on 5.5K spoof images (from 12 materials) and 11.8K live images show that the proposed approach improves the cross material spoof detection performance over state of the art one class and binary class spoof detectors on 11 of 12 testing materials and 7 of 12 testing materials, respectively.
The Role of Economics and Democracy in Institutional Change for Sustainability
Year: 2014

Institutional change for sustainable development does not happen by itself. Individuals and organizations function as actors to influence development processes. Reference is made to a "political economic person" (PEP) guided by her/his "ideological orientation" and "political economic organization" (PEO) guided by its "mission" Leaving present unsustainable trends behind is a matter of politics and ideology and even power positions, where democracy plays a crucial role. The perspectives of influential (and other) actors are essential in facilitating (or hindering) change. I will discuss ideas of the role of science in society, mainstream neoclassical economics in relation to institutional economics in the spirit of K. William Kapp and Gunnar Myrdal as well as neo liberalism as ideology (where neoclassical economics has contributed to strengthen the legitimacy of neo liberalism) Various aspects of inertia and flexibility in institutional change processes, such as path dependence, are discussed. Emphasis is on the role of economics and how a strengthened democracy can open the door for a degree of pluralism.
Is Pokemon GO Watching You? A Survey on the Privacy Awareness of Location Based Apps' Users
Venue: 2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC)
Year: 2017

After the NSA surveillance revelations in 2013, people became aware of the lack of privacy with respect to the US government. But are users aware that also apps may spy them, collect and even sell their personal data? From their common behavior during their always connected every day life, it does not seem so: many people use apps that collect and send their browsing habits to third parties. An example is the Pokemon GO app, a game that in a few months became a worldwide phenomenon, that in its Privacy policy clearly states that the user allows the app to access his emails, address book, location and other very private personal info. In this work, we examined consumers' attitudes and perceptions regarding their privacy by conducting a survey on 208 participants diverse in age, gender and education. Findings suggest that consumers have very low awareness on privacy issues, and that, when downloading apps, they often fail to read the privacy policy, where it is stated who will gather access to their data and which data will be collected by the app.
Removing Confounding Factors Associated Weights in Deep Neural Networks Improves the Prediction Accuracy for Healthcare Applications
Venue: PSB
Year: 2019

The proliferation of healthcare data has brought the opportunities of applying data driven approaches, such as machine learning methods, to assist diagnosis. Recently, many deep learning methods have been shown with impressive successes in predicting disease status with raw input data. However, the "black box" nature of deep learning and the high reliability requirement of biomedical applications have created new challenges regarding the existence of confounding factors. In this paper, with a brief argument that inappropriate handling of confounding factors will lead to models' sub optimal performance in real world applications, we present an efficient method that can remove the influences of confounding factors such as age or gender to improve the across cohort prediction accuracy of neural networks. One distinct advantage of our method is that it only requires minimal changes of the baseline model's architecture so that it can be plugged into most of the existing neural networks. We conduct experiments across CT scan, MRA, and EEG brain wave with convolutional neural networks and LSTM to verify the efficiency of our method.
A Graph Based Decision Support Model for Vulnerability Analysis in IoT Networks
Venue: SSCC
Year: 2018

The Internet of Things (IoT) refers to the technological phenomenon that envisages reliable connection and secure exchange of data between the real world devices and applications. However, the vulnerabilities residing in the IoT devices are identified as the potential entry points for the attackers, thereby causing a huge security threat to the IoT network. The attackers can further advance deep into the network by exploiting the relations among these vulnerabilities. In this work, we address the security issues in the IoT network due to the existence of vulnerabilities in the network devices. We propose a multi attacker multi target graphical model referred to as IoT Security Graph, representing the potential attackers, targets, and the vulnerability relations in the IoT network. As the graph is derived from the network, its analysis can reveal many security relevant parameters of the network. Security analysts are keen in evaluating threats to critical resources in the network due to the presence of inherent vulnerabilities in the devices and in analyzing cost effective security hardening options. To aid this, we introduce the Terminator Oriented Directed Acyclic Graph (TODAG) for each terminal node representing a potential target in the network. The TODAG for a given terminal node is a sub graph of the IoT Security Graph of the underlying network and represents all the potential attack paths in the network that orient toward it. The proposal also includes the likelihood estimation of the dominant attack paths in the TODAG. The removal of such paths can significantly reduce the threat at the targets.
The review of migration decisions a story of borders and orders
Year: 2009

In the last decade in Australia and the United Kingdom, the review of immigration decisions in tribunals and courts has been marked by constitutional conflict between the executive and the judiciary; a crisis of confidence; and continual change. This thesis explores what this tumultuous story of immigration review tells us about the law as a social practice, as an institution, and as a linguistic genre in these jurisdictions, in these times. This thesis argues that the story of immigration review is explained best not through the conventional story of a battle between the executive and the judiciary, but rather as a story of the fundamental challenges immigration poses to the social, institutional, ideological and linguistic dimensions of law, and of the attempt by judges and the legal community to defend their different conceptions of the legitimacy of the law from those challenges, in different ways. Four fundamental challenges are identified. First, immigration challenges the coherence of the legal framework, as it exposes tensions within and between the different legal regimes. Second, the more reductive language used in legal contexts competes badly with more complex, and more socially powerful, discourses about immigration. Third, immigration challenges the capacity of law to perform the functions of resolving disputes and regulating behaviour. Fourth, immigration challenges our deepest concepts of legality. The thesis examines these challenges, and the responses they provoke, by drawing on the insights of migration studies, contemporary political philosophy, language and the law, and regulatory theory, as well as examining important case law in detail. In doing so, it aims both to capture the story of immigration review more fully, and to illuminate some of the complexities of, and limits to, the contemporary social practice of law.
Design and implementation of hybrid integration of cognitive learning and chaotic countermeasures for side channel attacks
Venue: J. Ambient Intell. Humaniz. Comput.
Year: 2021

Security in embedded systems is considered to be more important and needs to be a diagnosis for every minute. Also with the advent of the Internet of Things (IoT) security in the embedded system has reached its new peak of dimension. A Mathematically secure algorithm was formulated and runs on the cryptographic chips which are embedded in the systems, but secret keys can be at risk and even information can be retrieved by the prominent side channel attacks. Fixed encryption keys, non intelligent detection of side channel attacks are some of the real time challenges in an existing system of encryption. Following the limitations of existing systems, this research article focuses on the integration of powerful machine learning algorithms by retrieving the secret key information with countermeasures methodology using the chaotic logistic maps and includes the following contributions: (a) Preparation of Data Sets from the Power consumption traces captured from ARTIX 7 FPGA boards while running the Elliptical Curve Cryptography(ECC) on it (b) Implementation of High Speed and High Accurate Single feed forward learning machines for the detection and classification of side channel attacks (c) Design of Chaotic Countermeasures using 3 Dlogistic maps for attacked bits. The test_bed has been developed using the integration of FPGA along with Cortex A57 architectures for experimentation of the proposed work and various evaluation parameters such as Accuracy, F calls, Precision rates, sensitivity, and correlation co efficient, entropy were calculated and analyzed. Moreover, the parameters of the proposed system which has been analyzed prove to outperform the other existing algorithms in terms of performance and detection.
Mottainai! A Practice Theoretical Analysis of Japanese Consumers' Food Waste Reduction
Year: 2019

This study focuses on food waste and its reduction by describing and analyzing the food waste related everyday life of Japanese consumers through a practice theoretical lens. The research enables paying attention to the role of culture in sustainable consumer behavior, which is a largely unexplored area in previous food waste research. The methodological approach is qualitative and the empirical data of the study were generated through mobile ethnography. It combines elements from diary methods, multi sited ethnography, and digital ethnography, producing visual and textual data of the practices that the participants of the study considered meaningful. The analysis identifies materials, meanings, and competences of the practices related to food waste reduction. These practices were interlinked with five broader food related practices: planning, grocery shopping, cooking, eating, and handling surplus food. The findings reveal specific elements related to Japanese culture such as mottainai a concept used to express the regret of wasting something valuable. The study contributes to the literature on sustainable consumption by emphasizing the importance of identifying and understanding how culturally linked practices may support sustainable (or unsustainable) consumption.
Community Detection in Dynamic Social Networks Based on Multiobjective Immune Algorithm
Year: 2012

Community structure is one of the most important properties in social networks,and community detection has received an enormous amount of attention in recent years.In dynamic networks,the communities may evolve over time so that pose more challenging tasks than in static ones.Community detection in dynamic networks is a problem which can naturally be formulated with two contradictory objectives and consequently be solved by multiobjective optimization algorithms.In this paper,a novel multiobjective immune algorithm is proposed to solve the community detection problem in dynamic networks.It employs the framework of nondominated neighbor immune algorithm to simultaneously optimize the modularity and normalized mutual information,which quantitatively measure the quality of the community partitions and temporal cost,respectively.The problem specific knowledge is incorporated in genetic operators and local search to improve the effectiveness and efficiency of our method.Experimental studies based on four synthetic datasets and two real world social networks demonstrate that our algorithm can not only find community structure and capture community evolution more accurately but also be more steadily than the state of the art algorithms.
Memristor Theory and Concepts
Year: 2020

Although the concept of the memristor (an amalgamation of the words: memory and resistor) was introduced 50 years ago, only recently research community has started seriously investigating various properties and potential applications of this nonlinear two terminal electrical component. The absence of any reliable and practical physical device that can demonstrate the perceived behaviors of the memristor has been hindering the experimental work and the implementation of memristor based applications. Therefore, most of the research works are still at the analytical stage and depend on mathematical models or emulator circuits of the memristor. In this chapter, the fundamental concepts and the theoretical background of memristor are briefly illustrated to provide a background for the memristor models and emulator circuits to be presented in this book.
Review of Indications of FDA Approved Immune Checkpoint Inhibitors per NCCN Guidelines with the Level of Evidence
Venue: Cancers
Year: 2020

Cancer is associated with higher morbidity and mortality and is the second leading cause of death in the US. Further, in some nations, cancer has overtaken heart disease as the leading cause of mortality. Identification of molecular mechanisms by which cancerous cells evade T cell mediated cytotoxic damage has led to the modern era of immunotherapy in cancer treatment. Agents that release these immune brakes have shown activity to recover dysfunctional T cells and regress various cancer. Both cytotoxic T lymphocyte associated protein 4 (CTLA 4) and Programmed Death 1 (PD 1) play their role as physiologic brakes on unrestrained cytotoxic T effector function. CTLA 4 (CD 152) is a B7/CD28 family; it mediates immunosuppression by indirectly diminishing signaling through the co stimulatory receptor CD28. Ipilimumab is the first and only FDA approved CTLA 4 inhibitor; PD 1 is an inhibitory transmembrane protein expressed on T cells, B cells, Natural Killer cells (NKs) and Myeloid Derived Suppressor Cells (MDSCs) Programmed Death Ligand 1 (PD L1) is expressed on the surface of multiple tissue types, including many tumor cells and hematopoietic cells. PD L2 is more restricted to hematopoietic cells. Blockade of the PD 1 /PDL 1 pathway can enhance anti tumor T cell reactivity and promotes immune control over the cancerous cells. Since the FDA approval of ipilimumab (human IgG1 k anti CTLA 4 monoclonal antibody) in 2011, six more immune checkpoint inhibitors (ICIs) have been approved for cancer therapy. PD 1 inhibitors nivolumab, pembrolizumab, cemiplimab and PD L1 inhibitors atezolizumab, avelumab, and durvalumab are in the current list of the approved agents in addition to ipilimumab. In this review paper, we discuss the role of each immune checkpoint inhibitor (ICI) the landmark trials which led to their FDA approval, and the strength of the evidence per National Comprehensive Cancer Network (NCCN) which is broadly utilized by medical oncologists and hematologists in their daily practice.
Reproductive, maternal, newborn and child health service delivery during conflict in Yemen: a case study
Venue: Conflict and Health
Year: 2020

Armed conflict, food insecurity, epidemic cholera, economic decline and deterioration of essential public services present overwhelming challenges to population health and well being in Yemen. Although the majority of the population is in need of humanitarian assistance and civil servants in many areas have not received salaries since 2016, many healthcare providers continue to work, and families continue to need and seek care.  This case study examines how reproductive, maternal, newborn, child and adolescent health and nutrition (RMNCAH+N) services have been delivered since 2015, and identifies factors influencing implementation of these services in three governorates of Yemen. Content analysis methods were used to analyze publicly available documents and datasets published since 2000 as well as 94 semi structured individual and group interviews conducted with government officials, humanitarian agency staff and facility based healthcare providers and six focus group discussions conducted with community health midwives and volunteers in September October 2018.  Humanitarian response efforts focus on maintaining basic services at functioning facilities, and deploying mobile clinics, outreach teams and community health volunteer networks to address urgent needs where access is possible. Attention to specific aspects of RMNCAH+N varies slightly by location, with differences driven by priorities of government authorities, levels of violence, humanitarian access and availability of qualified human resources. Health services for women and children are generally considered to be a priority; however, cholera control and treatment of acute malnutrition are given precedence over other services along the continuum of care. Although health workers display notable resilience working in difficult conditions, challenges resulting from insecurity, limited functionality of health facilities, and challenges in importation and distribution of supplies limit the availability and quality of services.  Challenges to providing quality RMNCAH+N services in Yemen are formidable, given the nature and scale of humanitarian needs, lack of access due to insecurity, politicization of aid, weak health system capacity, costs of care seeking, and an ongoing cholera epidemic. Greater attention to availability, quality and coordination of RMNCAH services, coupled with investments in health workforce development and supply management are needed to maintain access to life saving services and mitigate longer term impacts on maternal and child health and development. Lessons learned from Yemen on how to address ongoing primary health care needs during massive epidemics in conflict settings, particularly for women and children, will be important to support other countries faced with similar crises in the future.