Miracle-dz/UniFAR-FTUs huggingface dataset:
A literature review about sequencing ITIL processes

In this paper, we present a review of different approaches for implementing Information Technology Infrastructure Library (ITIL) practices. One of the main issues when implementing ITIL processes is the order of the processes to be implemented. Different works developed in the past were focused in the critical success factors for the ITIL implementation. Nevertheless, the order in which processes should be implemented is still being studied. The approaches discovered vary from static sequences in which the sequence is predefined and common to all organizations, to those ones which are dynamically defined depending on the characteristics of the organization, so they may differ from one company to other. A literature review is presented to compile the status of the art.
Procedural modeling of buildings

CGA shape, a novel shape grammar for the procedural modeling of CG architecture, produces building shells with high visual quality and geometric detail. It produces extensive architectural models for computer games and movies, at low cost. Context sensitive shape rules allow the user to specify interactions between the entities of the hierarchical shape descriptions. Selected examples demonstrate solutions to previously unsolved modeling problems, especially to consistent mass modeling with volumetric shapes of arbitrary orientation. CGA shape is shown to efficiently generate massive urban models with unprecedented level of detail, with the virtual rebuilding of the archaeological site of Pompeii as a case in point.
The Progress of PVDF as a Functional Material for Triboelectric Nanogenerators and Self-Powered Sensors

Ever since a new energy harvesting technology, known as a triboelectric nanogenerator (TENG), was reported in 2012, the rapid development of device fabrication techniques and mechanical system designs have considerably made the instantaneous output power increase up to several tens of mW/cm2. With this innovative technology, a lot of researchers experimentally demonstrated that various portable/wearable devices could be operated without any external power. This article provides a comprehensive review of polyvinylidene fluoride (PVDF)-based polymers as effective dielectrics in TENGs for further increase of the output power to speed up commercialization of the TENGs, as well as the fundamental issues regarding the materials. In the end, we will also review PVDF-based sensors based on the triboelectric and piezoelectric effects of the PVDF polymers.
Complex and Ambiguous

Stickers, though similar in appearance to emoji, have distinct characteristics because they often contain animation, diverse gestures, and multiple characters and objects. Stickers can convey richer meaning than emoji, but their complexity and placement constraint may result in miscommunication. In this paper, we aim to understand how people perceive emotion in stickers, as well as how miscommunication related to sticker occurs in actual chat contexts. Toward this goal, we conducted an online survey (n = 87) and in-depth interviews (n = 28) in South Korea. We found emotional and contextual aspects of sticker misinterpretation. In particular, emotion misinterpretation mostly happened due to stickers' ambiguous (multiple) facial/bodily expressions and different perception of dynamism in gestures. In real chat settings, there were also contextual misinterpretations where senders and receivers differently interpret stickers' visual representation/reference, or/and corresponding textual messages. Based on these findings, we provide several practical design implications such as context awareness support in sticker interaction.
Post-Release Deformation and Motion Control of Photonic Waveguide Beams by Tuneable Electrothermal Actuators in Thick SiO2

Photonic packaging, which includes high-precision assembly of photonic sub-systems, is currently a bottleneck in the development of commercially-available integrated photonic products. In the pursuit of a fully-automated, high-precision, and cost-effective photonic alignment scheme for two multi-channel photonic chips, this paper explores different designs of the on-chip electrothermal actuators for positioning mechanically-flexible waveguide structures. The final alignment goal is ∼100 nm waveguide to waveguide. The on-chip actuators, particularly for out-of-plane actuation, are built in a 16 μm-thick SiO2 photonic-material stack with 5 μm-thick poly-Si as an electrothermal element. A major challenge of out-of-plane positioning is a 6 μm height difference of the waveguides to be aligned, due to different built-up material stacks, together with a misalignment tolerance of 1 μm–2 μm from the pre-assembly (flip-chip) process. Therefore, the bimorph-actuator design needs to compensate this height difference, and provide sufficient motion to align the waveguides. We propose to exploit the post-release deformation of so-called short-loop bimorph actuator designs to meet these joint demands. We explore different design variants based on the heater location and the integration of actuator beams with waveguide beams. The actuator design (with 30 μm poly-Si and 900 μm SiO2 in length) has ∼8 μm out-of-plane deflection and is able to generate ∼4 μm motion, which meets the design goal.
Cross‐cultural, population‐based study on adolescent body image and eating distress in Japan and Finland

This cross‐sectional population‐based survey compares the prevalence of self‐reported body image and eating distress symptoms among adolescents in Japan and Finland, and associations between emotional/behavioral problems, body image and eating distress from a cross‐cultural perspective. The study included 1,840 Japanese and 1,135 Finnish 8th grade students. The self‐reported questionnaire included the Body Image and Eating Distress Scale and Strengths and Difficulties Questionnaire (SDQ). The female adolescents from both Finland and Japan reported much greater dissatisfaction with, and concern about, their bodies than the males and Japanese females expressed even higher distress than Finnish females. High levels of body image and eating distress were associated with psychiatric problems measured with the SDQ. There was a significant three‐way interaction effect of body image and eating distress, gender and country with SDQ peer problems and prosocial behavior.
Ensemble of Translators with Automatic Selection of the Best Translation – the submission of FOKUS to the WMT 18 biomedical translation task –

This paper describes the system of Fraunhofer FOKUS for the WMT 2018 biomedical translation task. Our approach, described here, was to automatically select the most promising translation from a set of candidates produced with NMT (Transformer) models. We selected the highest fidelity translation of each sentence by using a dictionary, stemming and a set of heuristics. Our method is simple, can use any machine translators, and requires no further training in addition to that already employed to build the NMT models. The downside is that the score did not increase over the best in ensemble, but was quite close to it (difference about 0.5 BLEU).
LeapChain: Efficient Blockchain Verification for Embedded IoT

Blockchain provides decentralized consensus in large, open networks without a trusted authority, making it a promising solution for the Internet of Things (IoT) to distribute verifiable data, such as firmware updates. However, verifying data integrity and consensus on a linearly growing blockchain quickly exceeds memory and processing capabilities of embedded systems. As a remedy, we propose a generic blockchain extension that enables highly constrained devices to verify the inclusion and integrity of any block within a blockchain. Instead of traversing block by block, we construct a LeapChain that reduces verification steps without weakening the integrity guarantees of the blockchain. Applied to Proof-of-Work blockchains, our scheme can be used to verify consensus by proving a certain amount of work on top of a block. Our analytical and experimental results show that, compared to existing approaches, only LeapChain provides deterministic and tight upper bounds on the memory requirements in the kilobyte range, significantly extending the possibilities of blockchain application on embedded IoT devices.
PAREEKSHA: a machine learning approach for intrusion and anomaly detection

Membership functions help us to identify and know the similarity between two elements such as vectors or sequences. The objective of this paper is to suggest a membership function and apply this membership function for learning the nature of dataset. In the initial learning process, the element vectors obtained are grouped to obtain clusters. The grouping is carried using incremental clustering technique. The initial knowledge thus build is later validated using the extended membership function so that any wrongly classified elements are placed properly. We name the approach as PAREEKSHA. The membership function is obtained by extending the basic Gaussian membership function and is inspired by approaches such as CLAPP, G-SPAMINE, and GARUDA in the recent research literature.
The association between Medicare accountable care organization enrollment and breast, colorectal, and prostate cancer screening

Despite the rapid diffusion of accountable care organizations (ACOs), the effect of ACO enrollment on cancer diagnosis, treatment, and survivorship remains unknown. The objective of this study was to determine whether Medicare Shared Savings Program (MSSP) ACO enrollment was associated with changes in screening for breast, colorectal, and prostate cancers.
Non-negative Matrix Factorization for Medical Imaging

A non-negative matrix factorization approach to dimensionality reduction is proposed to aid classiﬁcation of images. The original images can be stored as lower-dimensional columns of a matrix that hold degrees of belonging to feature components, so they can be used in the training phase of the classiﬁcation at lower runtime and without loss in accuracy. The extracted features can be visually examined and images reconstructed with limited error. The proof of concept is performed on a benchmark of handwritten digits, followed by the application to histopathological colorectal cancer slides. Results are encouraging, though dealing with real-world medical data raises a number of issues.
mmappickle: Python 3 module to store memory-mapped numpy array in pickle format

This library allows working on matrices bigger than the size of the RAM, and allows concurrent read/write access from multiple processes, while having data stored in a structure behaving like a normal Python dictionary. This structure is mutable, as keys can be added and removed without having to rewrite the entire file. Moreover, the file complies with the Python Pickle format, and can be loaded on computers which don’t have mmappickle installed (provided enough RAM is available to load all the matrices).
Feasibility of a trauma-informed parent–teacher cooperative training program for Syrian refugee children with autism

Although the number of Syrians affected by the civil war rises, little work has been done to address the needs of Syrian refugee children with autism spectrum disorder. This research aimed to test the feasibility and acceptability of a culturally sensitive intervention developed specifically for children with autism spectrum disorder affected by trauma. Local partners advised the program team on cultural norms. Nine parents and 11 teachers were recruited to participate in 12-week parent–teacher cooperatives in a large Turkish city. We used qualitative methods to analyze interviews with each participant after intervention completion. A total of 14 participants completed the program (70%). All interviewees were women and Syrian refugees. Local political events, transportation costs and safety, and illnesses impacted attrition and attendance. All participants were satisfied with program content, including gains in autism knowledge, behavior management skills, and social support. Program-related challenges included applying skills to nonverbal children. The majority of participants made recommendations for program improvement, including a need for services outside urban areas. Flexible program delivery methods, including online options, might better accommodate participants unable to travel due to distance, political unrest, or safety. More research is needed to rigorously test program outcomes and to evaluate efforts to train local program leaders.
Role of estradiol and testosterone in Ucp1 expression in brown/beige adipocytes

Activity of brown/beige adipocytes is higher in women than in men. The expression level of uncoupling protein 1 (UCP1) is largely consistent with the thermogenic activity in brown/beige adipocytes. The present study examined the direct effects of sex hormones on Ucp1 expression in brown adipocytes and beige adipocytes, which were differentiated from HB2 brown preadipocytes and 3T3‐L1 white preadipocytes, respectively; treatment with estradiol or testosterone was used during the early (days 0‐8) or late stage (days 8‐12) of brown adipogenesis and beige adipogenesis. On day 8 or day 12, cells were treated with or without isoproterenol (Iso), an agonist for the β‐adrenergic receptor, for 4 hours. Furthermore, the sex of cells was examined; the sex‐determining region y gene, which is located on the y chromosome, was present in HB2 cells, but not in 3T3‐L1 cells, suggesting that HB2 cells and 3T3‐L1 cells are male and female cells, respectively. Treatment with 17β‐estradiol during the early stage of brown adipogenesis enhanced the responsiveness to Iso on Ucp1 induction, whereas treatment during the late stage of brown adipogenesis decreased Ucp1 expression in unstimulated brown adipocytes. Estradiol decreased Iso‐induced Ucp1 expression during the early stage of beige adipogenesis. Treatment with testosterone during the early stage of brown adipogenesis did not affect Ucp1 expression but increased the responsiveness to Iso on Ucp1 induction by the treatment during the late stage of brown adipogenesis. The present results suggest that sex hormones modulate the expression level of Ucp1 in brown/beige adipocytes in a stage‐dependent manner. Direct effects of sex hormones in brown/beige adipogenesis were evaluated. Treatment with 17β‐estradiol during the early stage of brown adipogenesis enhanced the responsiveness to isoproterenol (Iso), an agonist for the β‐adrenergic receptor, on Ucp1 induction, whereas treatment during the late stage of brown adipogenesis decreased Ucp1 expression in unstimulated brown adipocytes. Estradiol decreased Iso‐induced Ucp1 expression during the early stage of beige adipogenesis. Testosterone during the late stage of brown adipogenesis increased the responsiveness to Iso on Ucp1 induction. Sex hormones modulate the expression level of Ucp1 in brown/beige adipocytes in a stage‐dependent manner.
Modeling of Interlocking Systems based on Patterns

The equipment faults of the interlocking system in rail transit system has occurred frequently, and these faults can cause serious accidents. The modeling of the interlocking system must aim at the stochasticity and real-time characteristics of equipment faults. Therefore, this paper proposes to model the interlocking system using stochastic hybrid automata. In order to improve model efficiency, we try to extract the pattern of the interlocking system model, and reuses these patterns in system modeling. The main contributions include: (1) Based on the business analysis of the interlocking system, 12 model patterns of the interlocking system are extracted; and (2) the modeling process of the interlocking system based on patterns reuse is given to guide system modeling. Finally, a case study is presented to illustrate the feasibility and effectiveness of our approach. Keywords-Interlocking system; Pattern reuse; Stochastic hybrid automata; Modeling; UPPAAL-SMC
Capturing Flood Risk Perception via Sketch Maps

The fact that an increasing number of people and local authorities are affected by natural hazards, especially floods, highlights the necessity of adequate mitigation and preparedness within disaster management. Many governments, though, have only insufficient monetary or technological capacities. One possible approach to tackle these issues is the acquisition of information by sketch maps complemented by questionnaires, which allows to digitally capture flood risk perception. We investigate which factors influence information collected by sketch maps and questionnaires in case studies in an area prone to pluvial flooding in Santiago de Chile. Our aim is to gain more information about the methods applied. Hereby, we focus on the spatial acquisition scale of sketch maps and personal characteristics of the participants, for example, whether they live at this very location of the survey (residents) or are pedestrians passing by. Our results show that the choice of the acquisition scale of the base map influences the amount and level of detail of information captured via sketch maps. Thus, detail base maps lead to more precise results when compared to reference data, especially in the case of residents. The results also reveal that the place of living of the respondents has an effect on the resulting information because on the neighborhood level the risk perception of residents is more detailed than the one of pedestrians. The study suggests that the integration of citizens via sketch maps can provide information about flood risk perception, and thus can influence the flood mitigation in the area.
Semantic selection of Internet sources through SWRL enabled OWL ontologies

This research examines the problem of Information Overload (IO) and give an overview of various attempts to resolve it. Furthermore, argue that instead of fighting IO, it is advisable to start learning how to live with it. It is unlikely that in modern information age, where users are producer and consumer of information, the amount of data and information generated would decrease. Furthermore, when managing IO, users are confined to the algorithms and policies of commercial Search Engines and Recommender Systems (RSs), which create results that also add to IO. this research calls to initiate a change in thinking: this by giving greater power to users when addressing the relevance and accuracy of internet searches, which helps in IO. However powerful search engines are, they do not process enough semantics in the moment when search queries are formulated. This research proposes a semantic selection of internet sources, through SWRL enabled OWL ontologies. the research focuses on SWT and its Stack because they (a)secure the semantic interpretation of the environments where internet searches take place and (b) guarantee reasoning that results in the selection of suitable internet sources in a particular moment of internet searches. Therefore, it is important to model the behaviour of users through OWL concepts and reason upon them in order to address IO when searching the internet. Thus, user behaviour is itemized through user preferences, perceptions and expectations from internet searches. The proposed approach in this research is a Software Engineering (SE) solution which provides computations based on the semantics of the environment stored in the ontological model.
ComD2: Family of Techniques for Inspecting Defects in Models that Affect Team Communication

This technical report presents a family of techniques for inspecting defects that affecting team communication, called ComD2 (Communication between Designers and Developers). The ComD2 family was developed based on theories that investigate different ways of communication. We have initially developed three specific inspection techniques for UML class diagrams, activity diagrams, and state machine diagrams. The techniques were developed for these models because they are among the most frequently used in the industry. We present the development of the verification items in the ComD2 family of techniques. From this technical report, we believe that other specific techniques can be created for the different models. Furthermore, we present a material to evaluate the feasibility of inspection techniques.
Integrating Challenge Based Learning Into a Smart Learning Environment: Findings From a Mobile Application Development Course (P)

Training students on mobile application development inherits the challenges of teaching software engineering where the target computer is a device that has a large number of features accessible by software. Furthermore, the most related experience in teaching students reveals difficulties in developing software engineering competencies. In this paper we present results from an iOS course held in a smart learning environment that adopted the Challenge Based Learning framework as the teaching methodology. Our results indicate that combining an active methodology along with an engaging environment can foster and improve software development learning. Keywords—Smart Learning Environments, Challenge Based Learning, Mobile Software Development, Teaching.
Evolutionary Composition of Customized Fault Localization Heuristics

Fault localisation is one of the most diﬃcult and costly parts in software debugging. Researchers have tried to automate this process by formulating measures for assessment of code elements’ suspiciousness. This paper reports an evolutionary-based approach to combine non-linearly 34 previous measures to formulate a new program oriented fault localisation heuristic. The method was evaluated with 107 single-bug programs and compared against 35 approaches – 34 spectrum-based heuristics and a previous evolutionary linear combination approach. The experiments have shown that the proposal consistently achieved competitive results compared to the others according to several eﬀectiveness metrics.
An Amplitudes-Perturbation Data Augmentation Method in Convolutional Neural Networks for EEG Decoding

Brain-Computer Interface (BCI)system provides a pathway between humans and the outside world by analyzing brain signals which contain potential neural information. Electroencephalography (EEG)is one of most commonly used brain signals and EEG recognition is an important part of BCI system. Recently, convolutional neural networks (ConvNet)in deep learning are becoming the new cutting edge tools to tackle the problem of EEG recognition. However, training an effective deep learning model requires a big number of data, which limits the application of EEG datasets with a small number of samples. In order to solve the issue of data insufficiency in deep learning for EEG decoding, we propose a novel data augmentation method that add perturbations to amplitudes of EEG signals after transform them to frequency domain. In experiments, we explore the performance of signal recognition with the state-of-the-art models before and after data augmentation on BCI Competition IV dataset 2a and our local dataset. The results show that our data augmentation technique can improve the accuracy of EEG recognition effectively.