Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification of cryptographic algorithms in binary programs

This thesis is about the design of automatic or semi-automatic methods to detect and identify cryptographic algorithms inside programs compiled into machine code. Two methods are presented. The objective of the first method is to identify cryptographic primitives. A machine code implementation of a cryptographic primitive, regarded as a sequence of instructions, is represented by a graph structure. During a normalization phase, a set of rewrite rules is used to modify this graph representation while preserving a specific notion of semantics. The goal is to converge towards expressions which are shared across several implementations of the same primitive. We use these expressions as a basis to create efficient signatures. A subgraph isomorphism enumeration algorithm is used to search for signatures. The second method is built on top of the first one. It produces a synthetic representation designed to help in the identification of modes of operation. This synthetic representation is defined as the smallest subgraph which preserve distances between sets of vertices previously identified as the input and output parameters of the primitives involved within the mode of operation.
Empirical Analysis of Military Expenditure and Industrialisation Nexus: A Regional Approach for Africa

This study investigates the impact of military expenditure on industrialisation at regional economic communities of African countries for a balanced panel of 35 African countries between 1990 and 2015. We applied a more recently developed panel causality and Generalised Method of Moments (GMM) estimation techniques. The findings suggest a feedback causality between military expenditure and industrialisation, but with significant differences between military expenditure and other determining variables of industrialisation. The causality results justified the use of System-GMM. The System-GMM results show that military expenditure has: (1) significant positive impact on industrialisation in AMU, CEN-SAD, IGAD, and SADC; (2) insignificant impact in COMESA, ECCAS and ECOWAS regions. The positive impact of military expenditure on industrialisation in the four regions suggests that the military expenditure needed to create a conducive environment for industrialisation process has been relatively effective. While in regions where the impact is insignificant suggests the need for a greater coordinated military spending needed to promote industrialisation process.
Non-linear inductor modelling for a DC/DC Buck converter

The paper is focused on the modelling of an inductor to exploit its non-linear behaviour in the roll-off region when it is employed in a DC/DC converter. The model is set up on the basis of experimental data measured in operating conditions, which are fitted to a polynomial curve describing the inductance variations. The analysis of the buck converter, performed by including the proposed model, is validated by experimental tests.
Net neutrality regulation and the participatory condition

: Across the globe, net neutrality policy consultations have sought the input of an engaged networked public by recursively mobilising the very technology of the internet itself as a kind of policy participation. This paper examines such cases, where regulators in the United States, Canada, India, and the European Union intended to more accurately represent public interest perspectives. However, as I argue, appeals to the participatory culture of the internet risk reifying participation itself while ignoring systemic inequalities that structure the concept of networked publics according to the exclusionary norms of internet discourse.
The Effect of ESG on a Global Fund Market - Integrating Environmental, Social and Governance (ESG) in the investment strategy: A Global Market Research

This paper investigates the different performances of global funds when implementing an ESG-strategy during the period 2013 to 2018. Using the from Morningstar Direct, consisting of return, Morningstar Sustainability Rating, Morningstar Portfolio Sustainability Score, Portfolio Controversy level and Environmental-, Social-, and GovernanceScore, we conduct the regression analysis using the Fama French Carhart model. This paper finds evidence that the performances of the global funds are negatively affected by ESG-strategies in the short run, which are consistent with some previous studies. However, a substantial amount of literature suggest that long term benefits of implementing ESG-strategy exceeds the costs. There is also literature suggesting ESG is a profitable investment since it is less risky, thus a risk-adjusted return would imply similar or higher returns. In the long run, ESG investments are profitable. Bachelors thesis (15hp) Department of Economics School of Business, Economics and Law University of Gothenburg Supervisor: Jian Hua Zhang Keywords​: ESG, global funds, environmental responsibility, social responsibility, corporate governance, responsible investments, impact investments, Morningstar Acknowledgments​: We are grateful to Aineas Mallios who has supported us throughout the econometric process and our supervisor Jian Hua Zhang for his insight and support during the entirety of the research process. Also, we must acknowledge Camilla Evertsson at LF Halland for sharing her experience in the field of finance. Thank you to our friends and family, that we now can finally spend time with. Thank you.
Effect of halal awareness, halal logo and attitude on foreign consumers’ purchase intention

Purpose The purpose of this paper is to determine the factors that affect foreign consumers’ purchase intention towards purchasing halal food products in South Africa. These factors are halal awareness, halal logo and attitude, which are important factors in affecting the intention of consumers. Design/methodology/approach Data were collected via a self-questionnaire with a sample of 230 foreign consumers. For analysing these data, a structural equation modelling technique was used in this study. Findings Based on the study’s results, all factors significantly influence foreign consumers’ intention towards purchasing halal food products and, subsequently, their buying behaviour. Interestingly, the study found that attitudes and halal awareness of non-Muslim consumers are very high compared with those of the Muslim consumers. Although the study addressed halal food consumers, most of the respondents participated in the study were non-Muslims and the majority of them were Christians. Research limitations/implications The respondents were only limited to the Cape Town city in South Africa, and the focus was only on five variables related to halal food consumers, namely, halal awareness halal logo, attitude, purchase intention and buying behaviour. Social implications This study can be used to develop halal food products to attract both Muslim and non-Muslim consumers, who are foreigners to a particular country. Originality/value This study is one of the first studies seeking to determine the factors that affect foreign consumers with regard to the purchase of halal food products in South Africa. It is regarded one of the first attempts to determine halal awareness, halal logo and attitude and how purchase intention and buying behaviour can be influenced.
Vision Based Lidar Segmentation for Accelerated Scan Matching

 — A vision-based algorithm brings a fast segmentation process to a 2D lidar point cloud. Extracted features allow us to set up a segment-based scan matcher. This matching is one of the steps for the localization. Features also give semantic information about the environment. The detection of a corner or a door indicates a potential encounter with human beings. Aware of this ―danger‖ area, the robot will be able to adapt its speed and define areas of focus to the vision algorithms. Indeed, vision is known for its high computation load. The focus provided by the lidar diminishes the area in the image to be analyzed and reduces the load.
The Protective Influence of Relationship Commitment on the Effects of Facebook Addiction on Marital Disaffection

Abstract Previous research has suggested that Facebook use can lead to adverse romantic relationship outcomes due to interpersonal conflicts, interactions with potential romantic alternatives, and jealousy. However, these associations have been explored mainly with undergraduates, focusing primarily on conflict rather than emotional disengagement. The current study examined the associations between Facebook addiction and marital disaffection (e.g., loss of love, emotional disengagement) amongst 138 (95 females and 43 males) cohabiting married Facebook users residing in the United States. The results revealed that Facebook addiction and marital disaffection were positively related, even after controlling for relationship commitment. Additionally, greater relationship commitment weakened the association between Facebook addiction and marital disaffection. There are likely multiple explanations for the current findings; however, results suggest that higher levels of relationship commitment may protect spouses against the negative relationship outcomes associated with Facebook addiction. Future longitudinal work with couples is needed to clarify the directionality of the relationship between Facebook addiction and marital disaffection.
Geomagnetism: From Alexander von Humboldt to Current Challenges

The Earth's magnetic field shields our habitat against potentially harmful charged particles from outer space. Moreover, it is an important source of information about Earth's deep interior and geological history, both inaccessible to direct observations. Geomagnetism, the study of all aspects of the Earth's magneticfield, formed as a field of natural sciences in the early nineteenth century, largely under the influence of two prominent polymaths, Alexander von Humboldt and Carl Friedrich Gauss. On the occasion of the AGU 2019 centennial and Alexander von Humboldt's 250th anniversary, we link Humboldt's activities in geomagnetism with modern research in this domain and its challenges. Based on magnetic field observations during his scientific journeys, Alexander von Humboldt determined the increase of magnetic intensity with distance from the equator. He initiated coordinated observations across the globe and thus laid the foundation for international data exchange and collaboration. Observation is a prerequisite to a better understanding of the Earth's magnetic field with its various sources from the Earth's core, lithosphere, and electrical current systems outside the Earth, with a multitude of applications from navigation, exploration, natural hazard assessment, and study of Earth's evolution. A full understanding of the physical processes underlying the various geomagnetic field sources is mandatory to tackle the challenge of forecasting the future geomagnetic field evolution and to take advantage of the information that the geomagnetic field can provide about the Earth's history, geological and tectonic conditions and processes, and the near‐Earth's space environment.
An Analytics Prediction Model of Monthly Rainfall Time Series: Case of Thailand

Rainfall prediction is regarded as a challenging task in an agricultural country like Thailand. A time series data especially rainfall and temperature needs analytics technologies to return a valuable knowledge. It has been recognized that a high accuracy of rainfall prediction model will be helpful for agriculturist and water management. The study area of this research is located in Thailand, which the daily rainfall and temperature time series data collected from five regions of Thailand were taken by Meteorological Department of Thailand from years 2000 to 2015. In this research, analytics method is proposed in the preprocessing steps, which are composed of data cleansing and data transform. Principal component analysis in feature selection step and weighted moving average are applied. In the prediction modeling, support vector regression (SVR) and artificial neural network (ANN) are employed. The results of the experiment showed the comparison of overall accuracy between ANN and SVR in five data sets over the area of study. The results of the experiment showed that the two prediction models gave a high overall accuracy, although SVR plays an important advantage in less computational time than ANN. This experiment is extremely useful not only as the most effective way to manage the amount of rainfall in water management for Thai agriculturist, but the proposed model can also become a representative in the monthly rainfall prediction model used in Thailand.
Software Cost Estimation using Particle Swarm Optimization and Neural Network

– In today’s time, cost estimation of the project is the major part. Whenever a project is required by any company or organization, then the second major thing along with project requirements comes the cost they can spent on the project. In project management, planning and resources are allocated according to the cost it takes. Only then resources are described and assigned which includes the effort in allocating the resources and time in allocation of resources. In our research we are going to minimize the effort estimation non-linearity using clustering technique called K-means clustering. Then parameters of each cluster are tuned using PSO. These clusters and tuned parameters are further trained using back propagation .
The organisational impact of open educational resources

The open educational resource (OER) movement has been growing rapidly since 2001, stimulated by funding from benefactors such as the Hewlett Foundation and UNESCO, and providing educational content freely to institutions and learners across the World. Individuals and organisations are motivated by a variety of drivers to produce OERs, both altruistic and self-interested. There are parallels with the open source movement where authors and others combine their efforts to provide a product which they and others can use freely and adapt to their own purposes. There are many different ways in which OER initiatives are organised and an infinite range of possibilities for how the OERs themselves are constituted. If institutions are to develop sustainable OER initiatives they need to build successful change management initiatives, developing models for the production and quality assurance of OERs, licensing them through appropriate mechanisms such as the Creative Commons, and considering how the resources will be discovered and used by learners.
ENERGY EFFICIENCY AS A WAY TO ECOLOGICAL SAFETY: EVIDENCE FROM RUSSIA

The paper proposes the link between effective use of energy and reduction of carbon emissions at the case of Russia. A number of energy efficiency indicators are reviewed and calculated. Deterministic analysis is conducted to identify what factors influence carbon intensity the most. The analysis has shown that increasing energy intensity causes a much greater increase in carbon intensity. This paper adopts the method of chain substitutions to calculate the contribution of each factor to the changes in the carbon intensity over a period of time. Therefore, it must be the ultimate goal to achieve a sustainable economy by consuming less energy which in its turn will lead to less CO2 emission.
Mixed convection heat transfer

This book presents the papers given at a conference on heat transfer and fluid flow. Topics considered at the conference included flow visualization experiments of secondary flow patterns in an isothermally heated curved pipe, flow models, evaporation, thermodynamics, heat transfer fluids, and the analysis of combined buoyancy effects of thermal and mass diffusion on laminar forced convection heat transfer in a vertical tube.
The follow-up of alumni as a strategic action in Brazilian universities

In Brazilian universities, considered as the complex organization because of its multiple objectives, high specialization and low degree of coordination, the follow-up of alumni presents itself as a strategic action. The purpose of following-up alumni consists in obtaining information that enables evaluating the impact of graduate programs on the professional and academic practice of alumni, as well as enhance the qualification of regular students. Taking these aspects into consideration, in this theoretical work we discuss aspects related to Brazilian universities and the follow-up of alumni as a strategic action in this context.
A Transcranial Stimulation Intervention to Support Flow State Induction

Background: Flow states are considered a positive, subjective experience during an optimal balance between skills and task demands. Previously, experimentally induced flow experiences have relied solely on adaptive tasks. Objective: To investigate whether cathodal transcranial direct current stimulation (tDCS) over the left dorsolateral prefrontal cortex (DLPFC) area and anodal tDCS over the right parietal cortex area during video game play will promote an increased experience of flow states. Methods: Two studies had participants play Tetris or first-person shooter (FPS) video games while receiving either real tDCS or sham stimulation. Tetris recruited 21 untrained players who infrequently played video games while the 11 FPS participants played FPS frequently. Flow experience was assessed before and after stimulation. Results: Compared to sham stimulation, real stimulation increased flow experience for both untrained Tetris and trained FPS players. Improved performance effects were only seen with untrained groups. Conclusion: Cathodal and anodal tDCS over the left DLPFC and right parietal areas, respectively may encourage flow experiences in complex real-life motor tasks that occur during sports, games, and everyday life.
CULTURE SHOCK AMONG FOREIGN STUDENTS: A CASE-STUDY OF THAI STUDENTS STUDYING AT UNIVERSITAS MUHAMMADIYAH PALEMBANG

The phenomenon of culture shock has some impacts on foreigners (i.e. psychological impact and intellectual impact), especially for foreign students studying in a new country. This research is aimed at figuring out the dominant aspects of culture shocks faced by the three Thai students studying at Universitas Muhammadiyah Palembang and how they cope with it. Descriptive-qualitative method was used in this research.To collect the data, the researchers used interview and questionnaire. Coding technique was used in analyzing the data. The results showed two dominant aspects of culture shocks found, namely: academic shocks (i.e teacher’s role and attitude, poorly organized program and classroom organization, and local students’ attitude). and social shocks (i.e.women-men relationship, community bonding, habits in social gathering). Generally, the three Thai students coped with the shock by preparing mental and psychology, as well as learning academic destination.
Proposal of a method to identify recall ability and brand associations

The purpose of this research is to develop a method to identify the ability to recall brand association and clarify which brand association is able to discriminate the recall ability. To achieve this purpose, in this research, the reaction and reaction time data to the presented brand association were collected via smartphone, and the data were analyzed by a hierarchy Bayesian model based on the idea of two-parameter model of item response theory (IRT). The result of description data showed that it was the significance to utilized reaction time. The analysis result by a hierarchy Bayesian model indicated that this method enables to efficient brand communication as the proposed model can estimate both the recall ability and the parameter to utilize in brand communication. This research contributes to both academic and business areas by proposing a convenience and effective method to identify consumers’ brand recalling ability.
Viewpoint Invariant Convolutional Networks for Identifying Risky Hand Hygiene Scenarios

Hand hygiene is essential in preventing costly and potentially lethal hospitalacquired infections. Proposed by the World Health Organization, the Five Moments of Hand Hygiene is an evidence-based and field-tested categorization designed to measure and improve clinical hand hygiene. In this paper, we show the effectiveness of a viewpoint invariant convolutional network for automatically identifying the five moments of hand hygiene. Using de-identified images from privacy-safe depth sensors inside patient rooms, we demonstrate the viability of our deep learning method and provide interpretable visualizations. Our results show that computer vision can offer high-fidelity monitoring of this paramount clinician behavior.
DETERMINANTS OF MOBILE PAYMENT USAGE AND THE MODERATING EFFECT OF GENDER: EXTENDING THE UTAUT MODEL WITH PRIVACY RISK

This study investigates the factors that influence the intention to use mobile payment services (MPS) and the extent to which these relationships are moderated by gender. A web-based survey was conducted using South Korean consumers (n=528). The results showed that performance expectancy and social influence had a positive effect on intention to use MPS, whereas privacy risk had a negative effect on intention to use MPS. Gender was found to moderate two paths in the model, such that a high level of facilitating conditions increased intention to use MPS for males but not for females, whereas privacy risk decreased intention to use MPS for females but not for males. Theoretical and managerial implications for researchers and marketing practitioners are then discussed. To cite this document: Jin-Myong Lee, Bohan Lee, and Jong-Youn Rha, " DETERMINANTS OF MOBILE PAYMENT USAGE AND THE MODERATING EFFECT OF GENDER: EXTENDING THE UTAUT MODEL WITH PRIVACY RISK ", International Journal of Electronic Commerce Studies, Vol.10, No.1, pp.43-64, 2019. Permanent link to this document: http://dx.doi. org/10.7903/ijecs.1644
Clasificación de células cervicales mediante el algoritmo KNN usando rasgos del núcleo Cervical cell classification by means of the KNN algorithm using nucleus' features

The Pap test is a test of gynecological screening that allows appreciating changes in the morphology of the cells of the cervix. This study can alert on such frequent pathologies in women as cancer of the cervix. The analysis of these kinds of images is important in the generation of diagnostic and the investigations that carried out, so that developing new techniques that made a practical analysis of the samples is necessary. Similarity search is one of the most common procedures in problems involving processing of data, an alternative to solve this problem is the kNN search (k-Nearest Neighbors). In this paper, the kNN classifier was used together with a specific distance function, to provide a solution to the real problem associated with the classification of cervical cells in normal and abnormal classes, the features used for classification were in this case based solely on information extracted from the nuclei region. From the study, among the manhattan distance, Euclidean and Mahalanobis and considering measures for evaluating F, AUC, negative predictivity and H-mean was found that manhattan performed well holding 97.1% values of AUC. The results indicate a reduction compared to the rate of false negative Pap test. H-mean with the purpose of comparing the results of other investigations regarding kNN, obtaining 92.33% with regard thereto.