Miracle-dz/UniFAR-FTUs huggingface dataset:
Aspects of Quality in Internet of Things (IoT) Solutions: A Systematic Mapping Study

Internet of Things (IoT) is an emerging technology that has the promising power to change our future. Due to the market pressure, IoT systems may be released without sufficient testing. However, it is no longer acceptable to release IoT systems to the market without assuring the quality. As in the case of new technologies, the quality assurance process is a challenging task. This paper shows the results of the first comprehensive and systematic mapping study to structure and categories the research evidence in the literature starting in 2009 when the early publication of IoT papers for IoT quality assurance appeared. The conducted research is based on the most recent guidelines on how to perform systematic mapping studies. A set of research questions is defined carefully regarding the quality aspects of the IoT. Based on these questions, a large number of evidence and research papers is considered in the study (478 papers). We have extracted and analyzed different levels of information from those considered papers. Also, we have classified the topics addressed in those papers into categories based on the quality aspects. The study results carry out different areas that require more work and investigation in the context of IoT quality assurance. The results of the study can help in a further understanding of the research gaps. Moreover, the results show a roadmap for future research directions.
Coordinating the Crowd: Inducing Desirable Equilibria in Non-Cooperative Systems

Many real-world systems such as taxi systems, traffic networks and smart grids involve self-interested actors that perform individual tasks in a shared environment. However, in such systems, the self-interested behaviour of agents produces welfare inefficient and globally suboptimal outcomes that are detrimental to all - common examples are congestion in traffic networks, demand spikes for resources in electricity grids and over-extraction of environmental resources such as fisheries. We propose an incentive-design method which modifies agents' rewards in non-cooperative multi-agent systems that results in independent, self-interested agents choosing actions that produce optimal system outcomes in strategic settings. Our framework combines multi-agent reinforcement learning to simulate (real-world) agent behaviour and black-box optimisation to determine the optimal modifications to the agents' rewards or incentives given some fixed budget that results in optimal system performance. By modifying the reward functions and generating agents' equilibrium responses in a sequence of offline Markov games, our method enables optimal incentive structures to be determined offline through iterative updates of the reward functions of a simulated game. Our theoretical results show that our method converges to reward modifications that induce system optimality. We demonstrate the applications of our framework by tackling a challenging problem in economics that involves thousands of selfish agents and tackle a traffic congestion problem.
A Case for Asymmetric Non-Volatile Memory Architecture

The byte-addressable Non-Volatile Memory (NVM) is a promising technology since it simultaneously provides DRAM-like performance, disk-like capacity, and persistency. The current NVM deployment is symmetric, where NVM devices are directly attached to servers. Due to the higher density, NVM provides larger capacity and can be shared among servers. Unfortunately, in the symmetric setting, the availability of NVM devices is affected by the specific machine it is attached to. High availability can be realized by replicating data to NVM on a remote machine. However, it requires full replication of data structure in local memory, limiting the size of the working set. This paper rethinks NVM deployment and makes a case for the asymmetric NVM architecture, which decouples servers from persistent data storage. In the proposed AsymNVM architecture, NVM devices (back-end nodes) can be shared by multiple servers (front-end nodes) and provide recoverable persistent data structures. The asymmetric architecture is made possible by RDMA, and follows the recent industry trend of resource disaggregation. We build AsymNVM framework based on AsymNVM architecture that implements: 1) high performance persistent data structure update; 2) NVM data management; 3) concurrency control; and 4) crash-consistency and replication. The central idea is to use operation logs to reduce the stall due to RDMA writes and enable efficient batching and caching in front-end nodes. To evaluation performance, we construct eight widely used data structures and two applications based on AsymNVM framework, and use traces of industry workloads. In a cluster with ten machines, the results show that AsymNVM achieves comparable performance to the best possible symmetric architecture while avoiding all the drawbacks with disaggregation. Compared to the baseline AsymNVM, speedup brought by the proposed optimizations is 6~22x.
An approximate Itô-SDE based simulated annealing algorithm for multivariate design optimization problems

This research concerns design optimization problems involving numerous design parameters and large computational models. These problems generally consist in non-convex constrained optimization problems in large and sometimes complex search spaces. The classical simulated annealing algorithm rapidly loses its efficiency in high search space dimension. In this paper a variant of the classical simulated annealing algorithm is constructed by incorporating (1) an It\^o stochastic differential equation generator (ISDE) for the transition probability and (2) a polyharmonic splines interpolation of the cost function. The control points are selected iteratively during the research of the optimum. The proposed algorithm explores efficiently the design search space to find the global optimum of the cost function as the best control point. The algorithm is illustrated on two applications. The first application consists in a simple function in relatively high dimension. The second is related to a Finite Element model.
Video Summarization through Human Detection on a Social Robot

In this paper, we propose a novel video summarization system which captures images via a social robot's camera but processes images on a server. The system helps remote family members easily be aware of their seniors' daily activities via summaries. The system utilizes two vision-based algorithms, one for pose estimation and the other for human detection, to locate people in frames to guide the robot through people tracking and filter out improper frames including the ones without a person or blurred, or with a person but too small or not at the center of the frame. The system utilizes a video summarization method to select keyframes by balancing the representativeness and diversity. We conduct experiments of the system through three in-the-wild studies and evaluate the performance through human subject studies. Experimental results show that the users of the system think the system is promising and useful for their needs.
Multi-Tier Buffer Management and Storage System Design for Non-Volatile Memory

The design of the buffer manager in database management systems (DBMSs) is influenced by the performance characteristics of volatile memory (DRAM) and non-volatile storage (e.g., SSD). The key design assumptions have been that the data must be migrated to DRAM for the DBMS to operate on it and that storage is orders of magnitude slower than DRAM. But the arrival of new non-volatile memory (NVM) technologies that are nearly as fast as DRAM invalidates these previous assumptions. This paper presents techniques for managing and designing a multi-tier storage hierarchy comprising of DRAM, NVM, and SSD. Our main technical contributions are a multi-tier buffer manager and a storage system designer that leverage the characteristics of NVM. We propose a set of optimizations for maximizing the utility of data migration between different devices in the storage hierarchy. We demonstrate that these optimizations have to be tailored based on device and workload characteristics. Given this, we present a technique for adapting these optimizations to achieve a near-optimal buffer management policy for an arbitrary workload and storage hierarchy without requiring any manual tuning. We finally present a recommendation system for designing a multi-tier storage hierarchy for a target workload and system cost budget. Our results show that the NVM-aware buffer manager and storage system designer improve throughput and reduce system cost across different transaction and analytical processing workloads.
InfoBot: Transfer and Exploration via the Information Bottleneck

A central challenge in reinforcement learning is discovering effective policies for tasks where rewards are sparsely distributed. We postulate that in the absence of useful reward signals, an effective exploration strategy should seek out {\it decision states}. These states lie at critical junctions in the state space from where the agent can transition to new, potentially unexplored regions. We propose to learn about decision states from prior experience. By training a goal-conditioned policy with an information bottleneck, we can identify decision states by examining where the model actually leverages the goal state. We find that this simple mechanism effectively identifies decision states, even in partially observed settings. In effect, the model learns the sensory cues that correlate with potential subgoals. In new environments, this model can then identify novel subgoals for further exploration, guiding the agent through a sequence of potential decision states and through new regions of the state space.
Invariant Feature Mappings for Generalizing Affordance Understanding Using Regularized Metric Learning

This paper presents an approach for learning invariant features for object affordance understanding. One of the major problems for a robotic agent acquiring a deeper understanding of affordances is finding sensory-grounded semantics. Being able to understand what in the representation of an object makes the object afford an action opens up for more efficient manipulation, interchange of objects that visually might not be similar, transfer learning, and robot to human communication. Our approach uses a metric learning algorithm that learns a feature transform that encourages objects that affords the same action to be close in the feature space. We regularize the learning, such that we penalize irrelevant features, allowing the agent to link what in the sensory input caused the object to afford the action. From this, we show how the agent can abstract the affordance and reason about the similarity between different affordances.
Robotics-Based Learning Interventions and Experiences From our Implementations in the RobESL Framework

In this article, the author presents Robotics-based learning interventions and the experiences at 56th Junior High School of Athens within the RoboESL Erasmus project; as well as a teaching approach using Educational Robotics. The RoboESL project aims to exploiting the potential of robotics for developing extra-curricular constructivist learning activities in schools that will help children at risk of failure or Early School Leaving (ESL) practice and develop their creativity skills, raise self-esteem, motivate their interest in schooling, and finally encourage them towards staying at school. During the implementation, students worked in a constructionist learning environment and were engaged in team activities. The author runs the project for two consecutive school years using EV3 Lego Mindstorms and participated in dissemination events organizing workshops where the students participated in the program taught elementary school pupils.
High Frequency of Hemolysin Associated Genes among Staphylococcus Aureus Clinical Isolates in Iraq

Abstract In current study, 120 clinical isolates of Staphylococcus aureus were collected from different hospitals in Diyala. In addtion of phenotypic method, all isolates diagnosed as S. aureus by genotypic method was done by Polymerase Chain Reaction (PCR) technique to detection nuc gene. PCR technique has been used to investigate hemolysin associated genes that encoding for hla , hlb , hlg and hld by using specific primers which showed the prevalence in percentage (95%, 79.17%, 90% and 96.67%) respectively. All isolates were found to be positive for at least two or more hemolysin genes and 69.17% of isolates were carrying all hemolysin genes. Keywords : Staphylococcus aureus , Thermo nuclease gene, Virulence genes, Alpha, Beta, Gamma and delta hemolysin.
Immunological Detection of Avian Influenza Virus in Infected Ducks by Monoclonal Antibodies Against AIV-H 5 N 1 NYOMAN

South-East Asia in the recent years have led to the death of millions of domesticated birds and millions others have to be sacrificed in an effort to eradicate the disease (Swayne and Halvorson 2003; Stegeman and Bouma 2004). During this outbreak, many affected countries suffer a great deal of economic losses brought out by the collapse of their poultry industries (Perkins and Swayne 2002; Perkins and Swayne 2003; Lewis 2006). More importantly, the disease also affects human causing a great concern among health authorities in the world. The availabilities of accurate, simple, safe, and fast diagnostic methods are important for an effort to prevent and to control a future outbreak of AI in both animals and man. Most diagnostic methods developed in the recent years still require expensive facilities and reagents are slow to perform, lack of sensitivity and specificity, unsafe to perform, and unable to determine the virus subtype directly (Gough 2004). Avian influenza viruses (AIVs) are a group of viruses with great genetic and antigenic diversities in nature. On the basis the antigenic characteristics of their two surface glycoproteins, haemagglitinin (HA) and neuraminidase (NA), AIVs are grouped into many subtypes. As many as 16 HA subtypes that can combine with 9 NA subtypes have been identified (Foucier et al. 2005). Such antigenic diversities have often caused a great difficulty in establishing an appropriate test for an accurate detection of AIV subtypes (Fouchier et al. 2005; Kida dan Sakoda 2006). MAbs which react only with a single epitope on an antigenic structure have been widely used to detect the viral antigen in the infected hosts and also to differentiate closely related viruses (Zheng et al. 2001; Vareckova et al. 2002; Ohnishi et al. 2005). In human influenza virus, for instance, the use of MAbs MICROBIOLOGY INDONESIA, December 2007, p 119-124 Volume 1, Number 3 ISSN 1978-3477
Internal Whistleblowing Intentions by Internal Auditors: A Prosocial Behaviour Perspective

Despite extensive research having been undertaken on the issue of whistleblowing globally, empirical study in this area is still scarce in Malaysia. This paper examines internal whistleblowing intentions among internal auditors in Malaysian organisational settings. Although, internal auditors hold a unique position in their organisations to prevent, deter and detect corporate wrongdoings, the role of this profession in investigating their ethical decision-making behaviour towards internal whistleblowing has been much neglected. A mail survey was conducted to investigate a variety of demographic, organisational and situational factors that could influence the internal auditors’ ethical decision-making process. Results are generally consistent with predictions based on a model of whistleblowing as a type of prosocial behaviour. The findings confirm those from previous studies, suggesting that organisational members have different reactions to different types of wrongdoings. Implications of the findings on Malaysian organisations for research and practice are discussed.Keywords: ethics, internal auditors, prosocial behaviour, whistleblowing
Improving Educational Outcomes in Developing Countries: Lessons from Rigorous Evaluations

In this article, we reviewed and interpreted the evidence from 223 rigorous impact evaluations of educational initiatives conducted in 56 low- and middle-income countries. We considered for inclusion in our review all studies in recent syntheses that have reached seemingly conflicting conclu- sions about which interventions improve educational outcomes. We grouped interventions based on their theory of action. We derived four lessons from the studies we review. First, reducing the costs of going to school and expanding schooling options increase attendance and attain- ment, but do not consistently increase student achievement. Second, pro- viding information about school quality, developmentally appropriate parenting practices, and the economic returns to schooling affects the actions of parents and the achievement of children and adolescents. Third, more or better resources improve student achievement only if they result in changes in children? s daily experiences at school. Fourth, well-designed incentives increase teacher effort and student achievement from very low levels, but low-skilled teachers need specific guidance to reach minimally acceptable levels of instruction.
Distribution of Growth Stimulating and Degradation Factors in Cow Endometrium in Postparturition Period

The aim of the research was to reveal distribution of the growth stimulating and degradation factors, inflammatory factors, and neuropeptide-containing innervation, as well as apoptosis in the cow’s endometrium in postparturition period. Haematoxylin and eosin were used for routine staining of each sample. Matrix metalloproteinases type 2 and type 9 (MMP-2 un MMP-9, working dilution (w.d.) 1:100, R&D, England), tumor necrosis factor-α (TNF-α, w.d. 1:100, Abcam, England), interleukin-10 (IL-10, w.d. 1:400, Abcam, England), vascular endothelial growth factor (VEGF, w.d. 1:50, DakoCytomation, Denmark), nerve growth factor receptors p75 (NGFR p75, w.d. 1:150, DakoCytomation, Denmark), and protein gene product 9.5 (PGP 9.5, w.d. 1:1600, DakoCytomation, Denmark) were detected immunohistochemically (IMH). TUNEL method was used for detection of apoptosis (programmed cells death – PCD). A mild positive correlation (p<0.05) was observed between amount of inflammatory cells and TNF-α (r=0.52), PCD and TNF-α (r= 0.58), TNF-α and NGFR p75 (r=0.51), NGFR p75 and PGP 9.5 (r=0.49), VEGF and PCD (r=0.59), and VEGF and NGFR p75 (r= 0.64). A strong positive correlation (p<0.01) was observed between TNF-α and VEGF (p<0.01; r=0.72), as well as between VEGF and NGFR p75 (r=0.64). The research suggests that uterus endometrial tissue degradation and repairing were in balance during postparturition. The intensity level of tissue repairing process in the cow’s endometrium was specific for the individual organism, which might be connected with immunity of each of them.
The characteristics of sexual abuse in sport: A multidimensional scaling analysis of events described in media reports

Abstract Most research on sexual abuse has been conducted within family settings (Fergusson & Mullen, 1999). In recent years, following several high profile convictions and scandals, research into sexual abuse has also encompassed institutional and community settings, such as sport and the church (Gallagher, 2000; Woolfe, Jaffe, Jette, & Poisson, 2003). Research into sexual abuse in sport, for example, began with both prevalence studies (Kirby & Greaves, 1996; Leahy, Pretty, & Tenenbaum, 2002) and qualitative analyses of the processes and experiences of athlete sexual abuse (Brackenridge, 1997; Cense & Brackenridge, 2001, Toftegaard‐Nielsen, 2001). From such work, descriptions of the modus operandi of abusers in sport, and the experiences and consequences for athlete victims, have been provided, informing both abuse prevention work and coach education. To date, however, no study has provided empirical support for multiple associations or identified patterns of sex offending in sport in ways that might allow comparisons with research‐generated models of offending outside sport. This paper reports on an analysis of 159 cases of criminally defined sexual abuse, reported in the print media over a period of 15 years. The main aim of the study was to identify the nature of sex offending in sport, focusing on the methods and locations of offenses. The data were analysed using multidimensional scaling (MDS) as a data reduction method in order to identify the underlying themes within the abuse and explore the inter‐relationships of behavior, victim, and context variables. The findings indicate that there are specific themes that can be identified within the perpetrator strategies that include “intimate,” “aggressive,” and “dominant” modes of interaction. The same patterns that are described here within the specific context of sport are consistent with themes that emerge from similar behavioral analyses of rapist (Bishopp, 2003; Canter & Heritage, 1990) and child molester groups (Canter, Hughes, & Kirby, 1998). These patterns show a correspondence to a broader behavioral model—the interpersonal circumplex (e.g., Leary, 1957). Implications for accreditation and continuing professional education of sport psychologists are noted
Gesture Use - From Real to Virtual Humans and Back

When we are face to face with others, we use not only speech, but also a multitude of nonverbal behaviors to communicate with each other. A head nod expresses accordance with what someone else said before. A facial expression like a frown indicates doubts or misgivings about what one is hearing or seeing. A pointing gesture is used to refer to something. More complex movements or configurations of the hands depict the shape or size of an object. Of all these nonverbal behaviors, gestures, the spontaneous and meaningful hand motions that accompany speech, stand out as they are very closely linked to the semantic content of the speech they accompany, in both form and timing. Speech and gesture together comprise an utterance and externalize thought; they are believed to emerge from the same underlying cognitive representation and to be governed, at least in part, by the same cognitive processes (Kendon, 2004; McNeill, 2005). Despite this important role of co-speech gestures in communication, little is known, however, about the mechanisms that underlie gesture production in human speakers (cf. Bavelas et al. (2008), de Ruiter (2007)) as well as the functions gesture use fulfills in communication and even beyond, e.g. in educational or therapeutic contexts. My talk at the symposium showed how building computational simulation models of natural, communicative behavior and employing these models in virtual humans allows to address these research issues.
ROMANIAN JOURNAL OF EXPERIMENTAL APPLIED PSYCHOLOGY

Borderline personality disorder (BPD) is both a common and serious psychiatric disorder, associated with high level of psychiatric care and high levels of psychosocial impairment. The individuals with this disorder can have negative and distorted views of themselves, along with feelings of low self-worth; they might easily become argumentative, moody and impulsive. SSRI may be a good pharmacotherapy for BPT, but psychotherapy is considered the primary treatment for this personality disorder. The aim of this paper is to describe the basic treatment strategies used in DBT. There are two psychotherapeutic approaches that have been shown to have efficacy in randomized controlled trials: psychoanalytic/psychodynamic therapy and dialectical behavior therapy. Dialectical behavior therapy (DBT) is a cognitive-behavioral approach to treating borderline personality disorder, developed by Marsha Linehan.