Miracle-dz/UniFAR-FTUs huggingface dataset:
An efficient privacy protection mechanism for recommendation using hybrid transformation technique

The rapid evolution of the internet led to a development of an effective tool for coping with information overload. Recommendation system is one of the most widely adopted and perceptible technologies for solving information overload issue. Collaborative filtering is the most popular technique used in recommender system. But it has several limitation such as sparsity, scalability and most vital of all privacy. As proposed by the researchers, the sparsity issue can be alleviated by incorporating the trust measure in the recommendation system. Customers mostly provide false information because of privacy breaches which in turn affect the accuracy of the recommendations. In this paper, a hybrid transformation technique is proposed which fuses Principal Component Analysis and Rotation Transformation (PCART) to protect users' privacy with accurate recommendations based on trust. The performance of our method is evaluated experimentally using MovieLens Dataset. Our experimental results shows, the hybrid transformation techniques provides better recommendations with ensuring privacy compared to existing approaches.
Multiculturality and Interculturality in Tourism

Abstract There is a turmoil in Europe and the world as far as the terms multiculturality and interculturality are concerned and have been concerned in recent years. The overwhelming historical, political, cultural and economic changes that have shaken the whole world have brought about significant changes in otherwise relatively traditional societies and communities, as well, with a very important impact on people's lives not only in point of economy, but communication, attitude towards labour, personality traits, national security and others. All interpersonal relations have been tinted by the reaction towards some „buzz words” that are very popular nowadays; nevertheless, they are at the core of a tremendously huge process of changes in the mere life of European societies and communities. In this environment, all economic activities that involve huge movements of individuals and masses (like tourism and hospitality) have experienced huge transformations; and if the ability and skill of making international communication mingle with the feeling of security encountered in a certain environment- these would definitely lead to a potential and real growth in that economic sector, including the third one of services. We truly believe tourism is one of those, and good international relations, as well as strategic partnerships, contribute to its development. In order to achieve results in tourism you only have to provide the following: secure environment, a competitive product, and good value for price services. It also helps if you have skilled employees, though.
A private machine-cloud architecture and self-reliant controllers for operational technology systems

A private machine-cloud architecture and the associated Self-reliant Control System (SCS) for industrial applications are presented in this paper. The machine-to-machine (M2M) IP-based local area network creates a backbone for the proposed architecture, in which the traditional analogue input and output (I/O) or field-bus subsystems of a traditional process control system are not required. The proposed architecture is not only applicable to a large processing plant, but can also be deployed to the generic feedback control installations, including micro-grids in a power system. The quantitative reliability of the new system is achieved by the fault-tolerant structure of multiple processors via the M2M connectivity. Each processor is a computational platform for multiple feedback control algorithms, functioning in a self-reliant manner. As a result, the amount of data required to be exchanged between processors is kept to minimal. The congregation of these processors and the private M2M local area network form a ‘private machine cloud’ for the SCSs.
Time Effectiveness of Ultraviolet C Light (UVC) Emitted by Light Emitting Diodes (LEDs) in Reducing Stethoscope Contamination

Today it is well demonstrated that stethoscopes can be as contaminated as hands, which are a recognized source of Health-Care Associated Infections (HCAIs). Ultraviolet C (UVC) light has proven disinfection capacity and the innovative UVC technology of Light Emitting Diode (LED) shows several potential benefits. To verify whether the use of UVC LEDs is effective and reliable in stethoscope membrane disinfection after prolonged use, a pre-post intervention study was conducted. A total of 1668 five-minute cycles were performed on two UVC LEDs to simulate their use; thereafter, their disinfection capacity was tested on stethoscope membranes used on a previously auscultated volunteer. Then, a further 1249 cycles were run and finally the LEDs were tested to assess performance in reducing experimental contamination by Staphylococcus aureus, Pseudomonas aeruginosa and Escherichia coli on the stethoscope membrane. Baseline volunteer contamination identified 104 Colony Forming Units (CFUs) while treated Petri dishes had 12 and 15 CFUs (p < 0.001). Statistically significant differences (p < 0.001) were also found relating to the reduction of specific bacteria: in particular, after treatment no CFU were observed for S. aureus and E. coli. UVC LEDs demonstrated the capacity to maintain high levels of disinfection after more than 240 h of use and they were effective against common microorganisms that are causative agents of HCAIs.
Robust unsupervised detection of human screams in noisy acoustic environments

This study is focused on an unsupervised approach for detection of human scream vocalizations from continuous recordings in noisy acoustic environments. The proposed detection solution is based on compound segmentation, which employs weighted mean distance, T2-statistics and Bayesian Information Criteria for detection of screams. This solution also employs an unsupervised threshold optimized Combo-SAD for removal of non-vocal noisy segments in the preliminary stage. A total of five noisy environments were simulated for noise levels ranging from -20dB to +20dB for five different noisy environments. Performance of proposed system was compared using two alternative acoustic front-end features (i) Mel-frequency cepstral coefficients (MFCC) and (ii) perceptual minimum variance distortionless response (PMVDR). Evaluation results show that the new scream detection solution works well for clean, +20, +10 dB SNR levels, with performance declining as SNR decreases to -20dB across a number of the noise sources considered.
A practical system for harvesting and monitoring hot topics on the web

This poster briefly describes a practical system named FounderWISE for harvesting and monitoring hot topics on the Web. FounderWISE consists of five components: Web crawler, text classifier, topic detector, topic summarizer and topic analyzer. In this poster we present two key components of topic detector and topic analyzer. The system has been successfully deployed in a few Chinese major government departments.
A method for catheterization, harnessing and chronic infusion of undisturbed chickens

A system was designed to facilitate the chronic infusion and/or serial blood sampling of rapidly growing, meat-type chickens with little or no stress to the bird. Techniques for surgically preparing an indwelling catheter, fabricating a harness system to protect this catheter, utilizing a miniature fluid swivel to provide free movement and infusing solutions via a programmable pump are described.
Comparative and Functional Genomic Analysis of Prokaryotic Nickel and Cobalt Uptake Transporters: Evidence for a Novel Group of ATP-Binding Cassette Transporters

ABSTRACT The transition metals nickel and cobalt, essential components of many enzymes, are taken up by specific transport systems of several different types. We integrated in silico and in vivo methods for the analysis of various protein families containing both nickel and cobalt transport systems in prokaryotes. For functional annotation of genes, we used two comparative genomic approaches: identification of regulatory signals and analysis of the genomic positions of genes encoding candidate nickel/cobalt transporters. The nickel-responsive repressor NikR regulates many nickel uptake systems, though the NikR-binding signal is divergent in various taxonomic groups of bacteria and archaea. B12 riboswitches regulate most of the candidate cobalt transporters in bacteria. The nickel/cobalt transporter genes are often colocalized with genes for nickel-dependent or coenzyme B12 biosynthesis enzymes. Nickel/cobalt transporters of different families, including the previously known NiCoT, UreH, and HupE/UreJ families of secondary systems and the NikABCDE ABC-type transporters, showed a mosaic distribution in prokaryotic genomes. In silico analyses identified CbiMNQO and NikMNQO as the most widespread groups of microbial transporters for cobalt and nickel ions. These unusual uptake systems contain an ABC protein (CbiO or NikO) but lack an extracytoplasmic solute-binding protein. Experimental analysis confirmed metal transport activity for three members of this family and demonstrated significant activity for a basic module (CbiMN) of the Salmonella enterica serovar Typhimurium transporter.
RobinX : an XML driven classification for round-robin sports timetabling

Creating timetables for sports competitions is a complex matter due to conflicting interests of many stakeholders. Apart from some basic constraints, each competition has its own requirements and as a result, no generally applicable solution method exists [8]. For example, the minimization of consecutive home and away matches is key within most professional competitions (e.g. [1,4]), whereas respecting player availability is far more important in non-professional competitions (e.g. [6,14]). In a round-robin timetable, often called a schedule, every team plays against every other team a fixed number of times. Although a few contributions have been made to organize various constraints that occur in round-robin timetabling, they did not result in a generally applicable classification or file format for problem instances and solutions. Bartsch, Drexl, and Kröger [1] describe several sports competitions by means of organizational, attractiveness, and fairness constraints. Rasmussen and Trick [13] list eight common constraint types. Kendall, Knust, Ribeiro, and Urrutia [8] are the only authors to distinguish between different objective functions. Nurmi et al. [10] are the first to set up a (plain text-only) file format to store instances, and propose a set of artificial and real-world instances together with the best solutions found so far.
Stigma, decriminalisation, and violence against street-based sex workers: Changing the narrative

It is well documented that sex workers manage risks in their work – such as the potential for violence and the multiple risks associated with stigma. While sex workers are commonly understood to be a stigmatised population, few studies have considered in depth how stigma operates in different legislative contexts, how it relates to sex-worker safety, and how it may be reduced. Stigma is understood to be exacerbated by the criminalisation of sex work, which defines sex workers as deviant others and consequently renders them more vulnerable to violence. However, as full decriminalisation of sex work is still relatively rare, there has been little in-depth exploration into the relationship between this legislative approach, risks of violence, and stigma. Drawing on the findings of in-depth interviews with street-based sex workers and sex-worker rights advocates, in this article I explore the links between stigma and violence, and discuss the challenges of reducing stigma associated with sex work in New Zealand, post-decriminalisation. I argue that while decriminalisation has undoubtedly benefited sex workers in New Zealand, stigma continues to have a negative impact – particularly for street-based sex workers. Decriminalisation should therefore be considered an essential starting point. However, ongoing work must focus on countering stigmatising narratives, to enable a safer society for all sex workers.
Biomimetic electrical stimulation for cardiac tissue engineering

A major challenge of tissue engineering is directing cells to establish the physiological structure and function of the tissue being replaced. Electrical stimulation has been used to induce synchronous contractions of cultured cardiac constructs. The hypothesis adopted for this study is that functional cardiac constructs can be engineered by "mimicking" the conditions present during cardiac development, and in particular, electrical stimulation using suprathreshold signals. For this Master's Thesis research, I have compared the material properties and charge-transfer characteristics at the electrode-electrolyte interface of various biocompatible materials, including carbon, stainless steel, titanium and titanium nitride, for use as electrodes in a biomimetic system for cardiac tissue engineering. I have also designed and implemented an electrical stimulator which is capable of modulating several important parameters of electrical stimulation, including stimulus amplitude and frequency. In addition, I have built an experimental setup incorporating this electrical stimulator and used it for experiments with C2C12 mouse myoblast cells and neonatal rat cardiomyocytes. Lastly, I have analyzed cell morphology as well as functional performance of engineered tissue by assessing excitation thresholds and maximum capture rates. Thesis Supervisors: Joel Voldman Associate Professor of Electrical Engineering and Computer Science Massachusetts Institute of Technology Gordana Vunjak-Novakovic Professor of Biomedical Engineering Columbia University
Multi-Label Classification with Unlabeled Data: An Inductive Approach

The problem of multi-label classification has attracted great interests in the last decade. Multi-label classification refers to the problems where an example that is represented by a single instance can be assigned to more than one category. Until now, most of the researches on multi-label classification have focused on supervised settings whose assumption is that large amount of labeled training data is available. Unfortunately, labeling training example is expensive and time-consuming, especially when it has more than one label. However, in many cases abundant unlabeled data is easy to obtain. Current attempts toward exploiting unlabeled data for multi-label classification work under the transductive setting, which aim at making predictions on existing unlabeled data while can not generalize to new unseen data. In this paper, the problem of inductive semi-supervised multi-label classification is studied, where a new approach named iMLCU, i.e. inductive Multi-Label Classification with Unlabeled data, is proposed. We formulate the inductive semi-supervised multi-label learning as an optimization problem of learning linear models and ConCave Convex Procedure (CCCP) is applied to optimize the non-convex optimization problem. Empirical studies on twelve diversified real-word multi-label learning tasks clearly validate the superiority of iMLCU against the other well-established multi-label learning approaches.
Modeling Player Performance in Massively Multiplayer Online Role-Playing Games: The Effects of Diversity in Mentoring Network

This study investigates and reports preliminary findings on player performance prediction approaches which model player's past performance and social diversity in mentoring network in Ever Quest II, a popular massively multiplayer online role-playing game (MMORPG) developed by Sony Online Entertainment. Our contributions include a better understanding of performance metrics used in the game and a foundation of recommendation systems for mentors and apprentices. We examined three different game servers from the Ever Quest II game logs. In all three servers, the results from our analyses suggest that increase in social diversity in terms of characters and classes encountered moderately negatively correlates with player performance. Based on this finding, we built predictive models to predict player's future performance based on past performance and social diversity in terms of mentoring activities. Our results indicate that 1) models employing past performance and social diversity perform better and 2) prediction for mentors is generally better than that for apprentices.
Consensus ontologies in socially interacting MultiAgent systems

This paper presents approaches for building, managing, and evaluating consensus ontologies from the individual ontologies of a network of socially interacting agents. Each agent has its own conceptualization of the world within the multiagent system framework. The interactions between agents are modeled by sending queries and receiving responses and later assessing each other's performance based on the results. This model enables us to measure the quality of the societal beliefs in the resources which we represent as the expertise in each domain. The dynamic nature of our system allows us to model the emergence of consensus that mimics the evolution of language. We present an algorithm for generating the consensus ontologies which makes use of the authoritative agent's conceptualization in a given domain. As the expertise of agents changes after a number of interactions, the consensus ontology that we build based on the agents' individual views evolves. The resulting approach is concordant with the principles of emergent semantics. We provide formal definitions for the problem of finding a consensus ontology in a step by step manner. We evaluate the consensus ontologies by using different heuristic measures of similarity based on the component ontologies. Conceptual processing methods for generating, manipulating, and evaluating consensus ontologies are given and experimental results are presented. The presented approach looks promising and opens new directions for further research.
Dose-dependent inhibition of Gag cellular immunity by Env in SIV/HIV DNA vaccinated macaques

The induction of a balanced immune response targeting the major structural proteins, Gag and Env of HIV, is important for the development of an efficacious vaccine. The use of DNA plasmids expressing different antigens offers the opportunity to test in a controlled manner the influence of different vaccine components on the magnitude and distribution of the vaccine-induced cellular and humoral immune responses. Here, we show that increasing amounts of env DNA results in greatly enhanced Env antibody titers without significantly affecting the levels of anti-Env cellular immune responses. Co-immunization with Env protein further increased antibody levels, indicating that vaccination with DNA only is not sufficient for eliciting maximal humoral responses against Env. In contrast, under high env:gag DNA plasmid ratio, the development of Gag cellular responses was significantly reduced by either SIV or HIV Env, whereas Gag humoral responses were not affected. Our data indicate that a balanced ratio of the 2 key HIV/SIV vaccine components, Gag and Env, is important to avoid immunological interference and to achieve both maximal humoral responses against Env to prevent virus acquisition and maximal cytotoxic T cell responses against Gag to prevent virus spread.
Technology Growth and Expenditure Growth in Health Care

In the United States, health care technology has contributed to rising survival rates, yet health care spending relative to GDP has also grown more rapidly than in any other country. We develop a model of patient demand and supplier behavior to explain these parallel trends in technology growth and cost growth. We show that health care productivity depends on the heterogeneity of treatment effects across patients, the shape of the health production function, and the cost structure of procedures such as MRIs with high fixed costs and low marginal costs. The model implies a typology of medical technology productivity: (I) highly cost-effective "home run" innovations with little chance of overuse, such as anti-retroviral therapy for HIV, (II) treatments highly effective for some but not for all (e.g. stents), and (III) "gray area" treatments with uncertain clinical value such as ICU days among chronically ill patients. Not surprisingly, countries adopting Category I and effective Category II treatments gain the greatest health improvements, while countries adopting ineffective Category II and Category III treatments experience the most rapid cost growth. Ultimately, economic and political resistance in the U.S. to ever-rising tax rates will likely slow cost growth, with uncertain effects on technology growth.
Detection of task difficulty from intention level information in the EEG features

In this study, an approach which detects the level of intention in response to the difficulty of the task executed by the subjects in an electroencephalogram (EEG) based brain-computer interface (BCI), is proposed. For this purpose, event related synchronization and desynchronization patterns which occur in the process of lifting different weights by the right hand by executing elbow flexion and extension movements, are classified by the linear discriminant analysis (LDA). Our results show that the varying difficulty of the task can be classified based on the EEG signals. In addition, a correlation analysis between the intention levels detected from EEG and surface electromyogram (sEMG) signals is presented and the detected level of correlation between these two signals supports our previous inference. Determining the level of intention of the patients during the physical rehabilitation treatment, ensures the patients' active participation in their therapy task and increases the effectiveness of the robotic rehabilitation system. Accordingly, the type of intention level detection approach we propose here has the potential to be useful in such physical rehabilitation processes.
Impact of self orientations on the leadership need And psychological well being

Introduction Self-construal studies which draw much interest in psychology field, have recently started to take place in academic life. Self is basically defined as interdependent-independent self-types depending on the extent of relationship of individuals with others (Markus and Kitayama, 1991; Kağıtçıbaşı, 2013). Beliefs, attitudes, goals and behaviors are regulated by self-construal types. The aim of this study is to take Balanced Integration and Differentiation Model (Balanced Model) as a basis and accordingly to examine the impact of individuated and relational self-orientation on leadership need and psychological well-being in Turkey. BID model considers that individuation and relatedness are distinct, and complementary self-orientations for self-system (İmamoğlu, 2003). As a natural need, both of them is required for optimal psychological functioning Individuated self-orientation is related with exploration security, need for cognition, curiosity, tolerance for ambiguity and perceived autonomy. On