Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Method to Associate Sensor Data with Domain Ontology

With the development of the Internet of Things, sensor ontologies have been applied to a variety of fields. Most sensor ontologies are currently built for applications in specific domains, and these ontologies are usually heterogeneous, making it difficult to share or reuse knowledge and concepts. The ontology association methods can be used to construct the semantic mapping between heterogeneous ontologies, so as to effectively determine the similarity between concepts in the ontologies. However, most of the contemporary methods do not make full use of the information that is stored in ontologies and are insufficient for the effective association. This paper proposes a novel association method based on comprehensive similarity. In our proposed method, we first use How-Net to obtain concept representation and calculate the semantic similarity of ontology concepts through sememe Tree and sememe Hierarchy. Then we calculate the structural similarity by the internal structure and the hierarchical relationship between the ontologies and remove the conceptual pairs with low relevance. Finally, we combine the semantic similarity and structural similarity to calculate the similarity matrix between ontology concepts to achieve association. The experimental results on real data show that our method can effectively associate sensor data with domain ontology by combining two different similarity calculation methods.
Effectiveness and Users’ Experience of Face Blurring as a Privacy Protection for Sharing Photos via Online Social Networks

Photo sharing on online social networks (OSNs) can cause privacy issues. Face blurring is one strategy to increase privacy while still allowing users to share photos. To explore the potential blurring has as a privacy-enhancing technology for OSN photos, we conducted an online experiment with 47 participants to evaluate the effectiveness of face blurring compared to the original photo (as-is), and users’ experience (satisfaction, information sufficiency, enjoyment, social presence, and filter likeability). Users’ experience ratings for face blurring were positive, indicating blurring may be an acceptable way to modify photos from the users’ perspective. However, from a privacy-enhancement perspective, while face blurring may be useful in some situations, such as those where the person in the photo is unknown to the viewer, in other cases, such as in an OSN where the person in the image is known to the viewer, face blurring does not provide privacy protection.
Designing a MOOC for Learners of Spanish: Exploring Learner Usage and Satisfaction.

The authors of the Learn Spanish: Basic Spanish for English Speakers Massive Open Online Course (MOOC) explored how registered users interacted amongst themselves, providing peer-support and becoming ‘tutors’ to their peers. The analysis was based on data collected through two surveys, as well as through comments on a learner-initiated private Facebook group and course-specific forum posts. Instances of learner usage and learner satisfaction are addressed.
Modified Perturb and Observe MPPT Algorithm for Partial Shading Conditions

Tracking the maximum power output is significantly important for the optimized photovoltaic operation. Maximum power point (MPP) is never constant and directly depends upon the solar irradiance and temperature of the cell. Hence, it is primordial to employ any technique to track MPP. This paper uses a modified Perturb and Observe (P&O) algorithm based on the Global Maximum Power point (GMPP) for a standalone photovoltaic system. It turns out to be a novel, simpler and efficient approach to accommodate the aforementioned problem and efficiently track MPP under varying climatic conditions. Simulation results verify the effectiveness of our proposed scheme in terms of accuracy, tracking time, robustness, simplicity and efficiency under static and dynamic atmospheric circumstances. Under normal conditions, MPP is tracked within 0.1 seconds, while for partial shading, GMPP is tracked within 0.15 seconds with an efficiency of 99.19%.
Validating convolution neural networks for automatic polyp detection in robotic colonoscopy

European Community's Horizon 2020 Programme (H2020/20142020) under Grant Agreement num. 688592 (EndoVESPA Project). Validating convolution neural networks for automatic polyp detection in robotic colonoscopy P. Brandao, E. Mazomenos, G. Ciuti, F. Bianchi, Menciassi, P. Dario, A. Koulaouzidis, D. Stoyanov Centre for Medical Image Computing, University College London 2 The BioRobotics Institute, Scuola Superiore Sant'Anna 3 Endoscopy Unit, The Royal Infirmary of Edinburgh
Improving End-to-End Throughput in Wireless Network using Spatial Reusability

The optimal route from the source node to the destination node that guarantees a high end-to-end throughput is the main issue of routing in multi-hop wireless network. As the environment is heterogeneous the issue seems to be much complex, most of the solutions end with local optimum because those algorithms mostly fail to ensure an end to end throughput. By considering spatial reusability of wireless media, the end-to-end throughput in wireless multi-hop remote systems can be enhanced massively. To support the argument, Spatial-reusability Aware Single-path Routing (SASR) algorithm is proposed and compared with existing single path routing protocol. The assessment showed that proposed protocol show significant improvement in end-to-end throughput in comparison with existing protocols.
Image Description Using Deep Neural Network

Recent research in computer vision and machine learning has demonstrated some great abilities at detecting and recognizing objects in natural images. Image description is a good starting point for imparting artificial intelligence to machines by allowing them to analyze and describe complex visual scenes. Computer software recently become smart enough to recognize objects in pictures, but not finding exactly what activities happening inside pictures. So, there is a need to develop system that can generate natural language descriptions from images. Such system can be useful for childhood education, image retrieval and visually impaired people. Automatic description from image is a challenging problem that contains interest from the domain like computer vision and natural language processing. The vision based image description system uses deep learning Convolution Neural Network and Recurrent Neural Network for generating description of images. As a result, Neural Network shows better result for description of images with increasing Bilingual Evaluation Understudy (BLEU) score of 0.64, Consensus-based Image Description Evaluation (CIDEr) score of 0.72 and minimizes validation loss to 2.5.
An Efficient Routing Protocol in Wireless Sensor Networks

In wireless sensor networks, faster and efficient data transfer is required. So a shortest path should be established as a first step. Previous methods use hop-by-hop communication for path establishment. Because of its high time consumption it is inefficient for faster communications. ‘Adaptive Bidirectional Protocol’ is used in this work. This protocol provides shortest path from source to destination. This method can be incorporated in sensor networks for better data transmission.
Theory and Diagnostics for Selection Biases in Historical Height Samples

Long-run changes in living standards occupy an important place in development and growth economics, as well as in economic history. An extensive literature uses heights to study historical living standards. Most historical heights data, however, come from selected subpopulations such as volunteer soldiers, raising concerns about the role of selection bias in these results. Variations in sample mean heights can reflect selection rather than changes in population heights. A Roy-style model of the decision to join the military formalizes the selection problem. Simulations show that even modest differential rewards to the civilian sector produce a military heights sample that is significantly shorter than the cohort from which it is drawn. Monte Carlos show that diagnostics based on departure from the normal distribution have little power to detect selection. To detect height-related selection, we develop a simple, robust diagnostic based on differential selection by age at recruitment. A companion paper (H. Bodenhorn, T. Guinnane, and T. Mroz, 2017) uses this diagnostic to show that the selection problems affect important results in the historical heights literature.
Distributed Algorithms for Voronoi Diagrams and Applications in Ad-hoc Networks

The Voronoi diagram is a fundamental structure in computational geometry and arises naturally in many applications including wireless networking. In this paper, we propose a distributed algorithm by which each node u can compute its Voronoi region in O(d(u)) time, where d(u) is the number of the Voronoi neighbors of node u. Then we show how the algorithm can be applied in topology control of wireless ad-hoc networks, and also propose a revised version of the algorithm to minimize transmission energy consumption. Further applications of the algorithm in different areas are expected.
Conservative reasoning about epistemic uncertainty for the probability of failure on demand of a 1-out-of-2 software-based system in which one channel is “ possibly perfect ”

In earlier work, (Littlewood and Rushby 2011) (henceforth LR), an analysis was presented of a 1-out-of-2 system in which one channel was “possibly perfect”. It was shown that, at the aleatory level, the system pfd could be bounded above by the product of the pfd of channel A and the pnp (probability of non-perfection) of channel B. This was presented as a way of avoiding the well-known difficulty that for two certainly-fallible channels, system pfd cannot be expressed simply as a function of the channel pfds, and in particular not as a product of these. One price paid in this new approach is that the result is conservative – perhaps greatly so. Furthermore, a complete analysis requires that account be taken of epistemic uncertainty – here concerning the numeric values of the two parameters pfdA and pnpB. This introduces some difficulties, particularly concerning the estimation of dependence between an assessor’s beliefs about the parameters. The work reported here avoids these difficulties by obtaining results that require only an assessor’s marginal beliefs about the individual channels, i.e. they do not require knowledge of the dependence between these beliefs.
Recommendations for Evaluating & Implementing Proximity Warning Systems on Surface Mining Equipment

Researchers at the National Institute for Occupational Safety and Health, Spokane Research Laboratory, studied technology and methods that could reduce accidents involving surface mining equipment that collides with other vehicles or workers, or drives over an unseen road edge. These accidents are partially attributed to the lack of full visibility around these large pieces of equipment. Blind areas can be extensive and this report presents plots of blind areas for five pieces of surface mining equipment. Several technologies designed for detecting obstacles in blind areas and providing a warning to the operator were evaluated on off-highway dump trucks. These proximity warning systems included radar, sonar, GPS, radio transceiver tags, and combinations of radar and cameras. A summary of test results is presented in this report, along with guidance on effective proximity warning technology, installation and maintenance considerations, and recommendations for effective implementation. This study found several commercially available systems that could effectively warn an equipment operator of an impending collision. Several new technologies also show promise for reducing these accidents. In most applications, it is recommended that sensor-based systems be combined with video cameras to provide important alarming functions along with an actual view of the blind area. Evaluating Proximity Warning Systems on Surface Mining Equipment ix
Chapter 2 Validation of Hardware Events for Successful Performance Pattern Identification in High Performance Computing

Hardware performance monitoring (HPM) is a crucial ingredient of performance analysis tools. While there are interfaces like LIKWID, PAPI or the kernel interface perf_event which provide HPM access with some additional features, many higher level tools combine event counts with results retrieved from other sources like function call traces to derive (semi-)automatic performance advice. However, although HPM is available for x86 systems since the early 90s, only a small subset of the HPM features is used in practice. Performance patterns provide a more comprehensive approach, enabling the identification of various performance-limiting effects. Patterns address issues like bandwidth saturation, load imbalance, non-local data access in ccNUMA systems, or false sharing of cache lines. This work defines HPM event sets that are best suited to identify a selection of performance patterns on the Intel Haswell processor. We validate the chosen event sets for accuracy in order to arrive at a reliable pattern detection mechanism and point out shortcomings that cannot be easily circumvented due to bugs or limitations in the hardware. 2.
Studying MCS package design through managers’ incremental control choices

Aware of the dangers of studying control elements in isolation, many management control systems (MCS) researchers try to explain and observe of the design of packages of control in aggregate, using various approaches to capture the ‘complete’ picture of management control. However such approaches are challenging to conceptualise, conduct and communicate. In this paper we offer an alternative entry point to studying the design of MCS packages, by recognising that they will be the result of choices made by individual managers, who, we propose, design incremental control solutions to mitigate and manage the perceived potential for control problems. Not only is this relation – between a perceived control problem potential and an incremental control solution – relatively simple to observe; it also provides the starting point for a series of useful questions, which if pursued by future research, may complement existing approaches to studying the design of MCS packages in organisations.
Frontiers in Crowdsourced Data Integration

Abstract There is an ever-increasing amount and variety of open web data available that is insufficiently examined or not considered at all in decision making processes. This is because of the lack of end-user friendly tools that help to reuse this public data and to create knowledge out of it. Therefore, we propose a schema-optional data repository that provides the flexibility necessary to store and gradually integrate heterogeneous web data. Based on this repository, we propose a semi-automatic schema enrichment approach that efficiently augments the data in a “pay-as-you-go” fashion. Due to the inherently appearing ambiguities we further propose a crowd-based verification component that is able to resolve such conflicts in a scalable manner. Zusammenfassung Die stetig wachsende Zahl offen verfügbarer Webdaten findet momentan viel zu wenig oder gar keine Berücksichtigung in Entscheidungsprozessen. Der Grund hierfür ist insbesondere in der mangelnden Unterstützung durch anwenderfreundliche Werkzeuge zu finden, die diese Daten nutzbar machen und Wissen daraus genieren können. Zu diesem Zweck schlagen wir ein schemaoptionales Datenrepositorium vor, welches ermöglicht, heterogene Webdaten zu speichern sowie kontinuierlich zu integrieren und mit Schemainformation anzureichern. Auf Grund der dabei inhärent auftretenden Mehrdeutigkeiten, soll dieser Prozess zusätzlich um eine Crowd-basierende Verifikationskomponente unterstützt werden.
ICAT : Developmentof an Internet-BasedDataCollectionMethod for EcologicalMomentaryAssessment UsingPersonal Cell Phones

Rapid advances in mobile data-transfer technologies offer new possibilities in the use of cell phones to conduct assessments of a person’s natural environment in real time. This paper describes features of a new Internet-based, cell phone-optimized assessment technique (ICAT), which consists of a retrospective baseline assessment combined with text messages sent to the participants’ personal cell phones providing a hyperlink to an Internet-stored cell phone-optimized questionnaire. Two participation conditions were used to test variations in response burden. Retention rates, completion rates, and response times in different subgroups were tested by means of χ2 tests, Cox regression, and logistic regression. Among the 237 initial participants, we observed a retention rate of 90.3% from the baseline assessment to the cell-phone part, and 80.4% repeated participation in the 30 daily assessments. Each day, 40–70% of the questionnaires were returned, a fourth in less than 3 minutes. Qualitative interviews underscored the ease of use of ICAT. This technique appears to be an innovative, convenient, and cost-effective way of collecting data on situational characteristics while minimizing recall bias. Because of its flexibility, ICAT can be applied in various disciplines, whether as part of small pilot studies or large-scale, crosscultural, and multisite research projects.
A I ] 1 3 A ug 2 01 9 Design Space Exploration as Quantified Satisfaction

We propose novel algorithms for design and design space exploration. The designs computed by these algorithms are compositions of function types specified in component libraries. Our algorithms reduce the design problem to quantified satisfiability and use advanced solvers to find solutions that represent useful systems. The algorithms we present in this paper are sound and complete and are guaranteed to discover correct designs of optimal size, if they exist. We apply our method to the design of Boolean systems and discover new and more optimal classical and quantum circuits for common arithmetic functions such as addition and multiplication. The performance of our algorithms is evaluated through extensive experimentation. We have first created a benchmark consisting of specifications of scalable synthetic digital circuits and real-world mirochips. We have then generated multiple circuits functionally equivalent to the ones in the benchmark. The quantified satisfiability method shows more than four orders of magnitude speed-up, compared to a generate and test method that enumerates all nonisomorphic circuit topologies. Our approach generalizes circuit optimization. It uses arbitrary component libraries and has applications to areas such as digital circuit design, diagnostics, abductive reasoning, test vector generation, and combinatorial optimization.
Cloning of Laccase Gene from a Newly Isolated 2 , 4-Dichlorophenol Degrading Bacillus subtilis from Dyeing Industry Sites

In an attempt to isolate 2, 4-Dichlorophenol degrading bacteria, 30 soil samples were collected from the near by places of dyeing industry in Erode district of Tamil Nadu, India. Out of 2400 bacteria, around 200 from each sample, 13 isolates showed 2, 4-Dichlorophenol degrading activity. Among these the most promising isolate was identified, morphologically as an aerobic gram positive motile rod shaped bacterium and biochemically respective results made it confirm that isolate is Bacillus subtilis. Molecular characterization using 16S rRNA further confirmed its identity as Bacillus subtilis strain. Extracellular laccase activity was measured spectrophotometrically with ABTS (2, 2’-azinobis (3-ethyl-benzothiazoline-6-suphonate) as substrate. Maximum production of enzyme (200 U/ml) and protein 123 mg/ml were observed at pH 8.0. Different carbon and nitrogen sources tested revealed fructose and peptone more supportive for the production of Laccase from Bacillus subtilis. The cell free extract of Bacillus subtilis was extracted with 50mM sodium acetate buffer and protein precipitated with 70% ammonium sulphate saturation. The laccase enzyme plate assay showed the presence of laccase in cultural filtrate. The SDS PAGE analysis revealed presence of extracellular 62kDa Laccase enzyme. Amplification with Laccase specific primer gave a product of around 1.5 kb which was cloned into E. coli DH5 . Sequencing and blast analysis of cloned product further confirmed presence of laccase gene.
Mechanisms of Organizational Behavior Control: A Survey

Basics are surveyed of a version of mechanism design theory tailored to solve management problems. The concept of a mechanism of organizational behavior control is introduced. Methodological grounds of the theory are discussed along with mechanisms classication. Mechanism implementation process is characterized. Also, basic mechanisms are sketched, which help solving important management problems on all stages of management cycle. An example of the mechanism of incentive-compatible planning is considered.
Trade Openness and Cross-country Income Di erences ∗

Development accounting literature usually attributes the observed cross-country variation in per capita income to di erences in countries' factor endowments and total factor productivity (the Solow residual). While the former can be relatively straightforward interpreted and measured, the latter remains at least partly a black box. In this paper, we provide a structural interpretation for di erences in total factor productivity across countries and quantitatively explore the role of trade barriers in explaining cross-country income di erences. In particular, we nd that giving all countries the same market entry costs or giving all country-pairs the same variable trade costs reduces inequality by around 13%.
IoT System Development Methods

It is generally believed that the application of methods plays an important role in developing quality systems. A development method is mainly necessary for structuring the process in producing largescale and complex systems that involve high costs. Similar to the development of other systems, it is important for IoT systems to be developed in a systematic manner in order to achieve a proper system with respect to both the functional and nonfunctional requirements. Development methods for IoT systems are more complex than traditional software systems and possess challenges from the process perspective. So far, several IoT system development methods (SDMs) have already been proposed in the literature, but an overview and evaluation of SDMs for IoT is still missing.
Virtual Machine Placement to Minimize Data Transmission Latency in MapReduce

Many factors affect the time cost of Cloud computing tasks. One of the most serious factors is data transmission latency, which reduces the efficiency of Cloud computing. Many notable schemes that have been proposed to overcome this factor ignore the communication cost among virtual machines (VMs) in the MapReduce environment. In this paper, we propose a VM placement approach to reduce data transmission latency by focusing on the communication cost among VMs. In this approach, we first propose two VM placement optimization algorithms to minimize the total data transmission latency and the maximum data transmission latency in the MapReduce environment. Then, we use the algorithms to place VMs for Map and Reduce phase. Finally, we analyze the time complexity for our approach. We implement our approach by simulation. The simulation results show that our approach reduces the average data transmission latency by 26.3% compared with other approaches.