Reviewerly/exHarmony huggingface dataset:
Geological Mapping of the Panafrican Mokong Gneisess and Granitoides (Far North Cameroon): Contribution of Semi-automatic Processing from Landsat 8 OLI/TIRS Images

Field studies, Landsats 8 OLI/TIRS processing and the digital elevation model of SRTM images permit us to map the Mokong area, region situated in arid zone and located to the Northen part of the central African Orogenic belt in Cameroun. The use of Landsat’s number 3 band of made it possible to highlight the lineaments. It has been noticed after analyses that the maximum number of lineaments are oriented N-S direction. The second major trends of lineaments in the study area are respectively, ENE-WSW, E-W and SSE-NNW. The landsat OLI/TIRS processing (colorful composition, band math, and principal component analysis) are permitted to discriminate four mains rocks types: gneisses-amphibolite; biotite granite, diorite-granodiorite and tonalite. All those facies are partially covered by alluvial deposits in the southern erea. The digital elevation model has permitted to identify some volcanic cover. The method used in this work offers promising prospects for geological mapping of arid regions where there is usually little map, because with this method, the time is reduced and the result is more precise.
Critical Components Identification for Service-Oriented Systems

Identifying critical components are of great significance to the overall reliability of service-oriented systems (SOSs). As the size of the SOS increases, identifying critical components in the process of predicting the SOS reliability can reduce the number of components that need to be predicted and shorten the prediction time. Moreover, predicting the reliability of critical components can also ensure the stability of the SOS. Therefore, we transform the relationships among service components of the SOS into a service dependency graph. Then, an improved weighted LeaderRank algorithm (IW-LeaderRank) is proposed to measure the importance of components and obtain the sequence of critical components. Through experimental analysis, the method can accurately and efficiently identify critical components in SOSs.
Learning an Orientation and Scale Adaptive Tracker With Regularized Correlation Filters

Spatial and temporal constraints are very important for correlation filter (CF)-based trackers. However, the existing methods usually fail to regularize the CF learning by the spatio-temporal information because of the ineffective target representation. To address the issue, we propose a novel Orientation and Scale adaptive tracker with Regularized Correlation Filters (OSRCF) for visual tracking. First, we directly employ the target region to build a spatio-temporally regularized CF, which is solved efficiently by the alternating direction method of multipliers (ADMM). Especially, the spatial regularization module can alleviate boundary effects by suppressing the outside background, while the temporal one can handle rapid appearance changes by smoothing the CF updating. Second, we obtain a non-axis-aligned bounding box for the target region representation by orientation and scale adaptive strategy, which cooperates a straightforward orientation estimation with a discriminative scale space correlation filter. We perform comprehensive experiments on two recent visual tracking benchmark datasets: VOT2017 and OTB2015. The results show that our OSRCF tracker outperforms top-ranked methods with handcrafted features in VOT2017 and achieves outstanding performance compared to some state-of-the-art methods in OTB2015.
Development of a Multi-copter Simulator and a Projection System for Virtual Operation Experience

Our motivation is to utilize simulation technology to accelerate the decommissioning of Fukushima Daiichi Nuclear Power Station (FDNPS) by remote operated robots. We already developed several simulation functions in our previous work. Recently multi-copter was utilized for reconnaissance tasks at FDNPS. This paper described to design a simulation function for multi-copter operation training. Fluid dynamics affected to flying body are simulated by implemented function. We also attempt the demonstration of immersive operation environment based on a 3D projection system that provides virtual operation experience.
The functional arrangement of objects biases gaze direction

A growing number of studies suggest that semantic knowledge can influence the control of gaze in scenes. For example, observers are more likely to look toward objects that are semantically related to the currently fixated object. Recent evidence also suggests that an object’s functional orientation can bias gaze direction. However, it is unknown whether these semantic and functional relationships can interact to determine gaze control. To address this issue, the present study assessed whether the functional arrangement of multiple objects can influence gaze control. Participants fixated a central object (e.g., a key) flanked by two peripheral objects. After a brief delay, participants were free to shift their gaze toward the peripheral object of their choice. One of the peripheral objects was semantically related to the central object (e.g., a lock), and the objects were arranged to depict a functional or non-functional interaction (e.g., a key pointing toward or away from a lock). When the orientation of the central object was manipulated, participants were more likely to look in the direction this object was pointing. Moreover, the functional arrangement of objects modulated this central orienting bias. However, when the orientation of the peripheral objects was manipulated, only the peripheral objects’ semantic relationships influenced gaze control. Together, these findings suggest that functional relationships play an important role in the allocation of gaze, and can interact with semantic relationships to determine gaze control.
Video instance search via spatial fusion of visual words and object proposals

Most popular systems for object instance search are based on the bag-of-visual-word model. The inherent weaknesses of this standard model such as quantization error, unstructured representation, burstiness phenomenon are to some extent solved. However, it has a serious problem of searching small objects on a database with cluttered background. In many situations, even the irrelevant objects which share the same texture or shape with a query object get higher score than relevant ones. To overcome this problem, we propose a novel fusion method to significantly boost the accuracy of instance search systems. Firstly, we use the state-of-the-art object detector with denser feature for finding object bounding box and similarity score. Secondly, to exploit the spatial relationship of each visual word with an object proposal, a detected area that might contain a query object, we define three categories of visual word pairs, i.e., discriminative, weak relevant, and context inferred ones. Finally, we propose a new re-ranking scheme with three weighting functions corresponding to the three categories of visual word pairs to compute the final similarity score between a query topic and a video shot. To illustrate the efficiency of the proposed method, we conduct experiments on datasets which have a wide variety of types of query objects. Experimental results on TRECVID Instance Search datasets (INS2013 and INS2014) show the superiority of our proposed method over the state-of-the-art approaches.
STATE-OF-THE-ART, CHALLENGES: PRIVACY PROVISIONING IN TTP LOCATION BASED SERVICES SYSTEMS

Nowadays, Location-based services (LBS) System is commonly used by Mobile users worldwide due to the immense growth of the Internet and Mobile devices. A mobile user uses LBS to access services relevant to their locations. LBS usage raises severe privacy concerns. A secure LBS system is required to protect three fundamentals metrics such as temporal information, user identity, and spatial information. Different models are being used to deal with such privacy metrics such as TTP and NTTP. In current study, we have conducted a comprehensive survey on TTP privacy protecting techniques which are being used in LBS systems. Primarily, it would be facilitating the mobile users with full privacy when they interact with the LBS system. Moreover, it is aimed to provide a promising roadmap to research and development communities for right selection of privacy approach.
Learning Numerical Attributes in Knowledge Bases

Knowledge bases (KB) are often represented as a collection of facts in the form (HEAD, PREDICATE, TAIL), where HEAD and TAIL are entities while PREDICATE is a binary relationship that links the two. It is a well-known fact that knowledge bases are far from complete, and hence the plethora of research on KB completion methods, specifically on link prediction. However, though frequently ignored, these repositories also contain numerical facts. Numerical facts link entities to numerical values via numerical predicates; e.g., (PARIS, LATITUDE, 48.8). Likewise, numerical facts also suffer from the incompleteness problem. To address this issue, we introduce the numerical attribute prediction problem. This problem involves a new type of query where the relationship is a numerical predicate. Consequently, and contrary to link prediction, the answer to this query is a numerical value. We argue that the numerical values associated with entities explain, to some extent, the relational structure of the knowledge base. Therefore, we leverage knowledge base embedding methods to learn representations that are useful predictors for the numerical attributes. An extensive set of experiments on benchmark versions of FREEBASE and YAGO show that our approaches largely outperform sensible baselines. We make the datasets available under a permissive BSD-3 license.
Text Classification of British English and American English Using Support Vector Machine

English is a language commonly used in the international world. Meanwhile, English that is often used in society is British English and American English. Beyond of the similarities, they all have fundamental differences, starting from the vocabulary to the grammar used. In learning English, people must ensure the type of English that they will learn. Therefore, this study is created a text classification system that can classify sentences according to the type of English used in the text. By that, it is expected to facilitate the language learning process in English. The dataset is divided into two classes namely British English and American English. The data will be divided by 10-fold-cross-validation. In this study, a combination of N-gram features, Term Frequency-Inverse Document Frequency (TF-IDF) weighting, and additional word dictionary as features were used. In the TF-IDF weighting process, a threshold of 2,0 in the Document-Frequency (DF) is given. The classification process is carried out using Support Vector Machine (SVM) algorithm with a linear kernel and the best accuracy obtained is 96.53%.
Exploring EFL Students’ Problems in Listening Comprehension

Listening is a challenging sll for my EFL learners. They seem to do the assignment without showing good comprehension on their answers. This research aims to find out the students’ problems in listening comprehension and identify the factors contributing to the problems. The second semester students in academic year 2017/2018 are the subject of the research. The data were collected by using observation, interview and documentation. The results of the research showed that the students still have low listening comprehension. The most difficult indicator of listening comprehension is making inference. There are only 28% students can answer the questions related making inference. The students also have low confidence in listening skill. They cannot concentrate well in listening to the spoken texts. Those problems are influenced by two factors, internal and external factors. Understanding students' problems leads to the idea of providing better strategies and materials in learning activities.
Designing and Evaluating Learning Technology: An African Dilemma and Approach

This position paper is concerned with understanding, evaluating and designing technologies to support learning in African higher education. Its central focus is on epistemological and methodological issues and commitments – specifically whether stereotypical and established Western methodological approaches are suited for investigating African contexts. Considering various ideas about ‘indigenous knowledge’ and sensitivities, an eclectic approach is adopted and deployed. The resulting ‘method’ presented can be adopted by those interested in finding indigeneity in conventional forms of investigation, and those that wish to engage in having a rather eclectic standpoint in research. This perspective has important implications for those investigating ‘technology acceptance and adoption’ in Africa; the use and development of learning technologies and the idea of ‘blended learning’ and those considering ‘post-colonial’ computing.
En dan zit je met de gebakken peren!

You have to face to consequences! Strategic maneuvering with the argumentum ad consequentiam In argumentative discourse fallacies occur regularly, but often they seem not to be noticed by the participants. This also goes for the fallacy known as the argumentum ad consequentiam, in spite of the fact that people generally denounce this fallacy when confronted with clea r cases. In this paper it is argued that the explanation of this paradox is that the different types of argumentum ad consequentiam are modes of strategic maneuvering which take on a reasonable appearance when they mimic legitimate pragmatic argumentation or reductio ad absurdum argumentation. The following hypothesis was tested in an experiment: instances of the argumentum ad consequentiam are regarded less unreasonable than clear cases if they are presented as reasonable pragmatic argumentation.
Space-Efficient Computation of the Burrows-Wheeler Transform

The Burrows-Wheeler Transform (BWT) has become an essential tool for compressed text indexing. Computing it efficiently and within little space is essential for the practicality of the indexes that build on it. A recent algorithm (Munro, Navarro & Nekrich, SODA 2017) computes the BWT in O(n) time using O(nlgσ) bits of space for a text of length n over an alphabet of size σ. The result is of theoretical nature and its practicality is far from obvious. In this paper we engineer their solution and show that, while a basic implementation is slow in practice, the algorithm is amenable to parallelization. For a wide range of alphabet sizes, our resulting implementation outperforms all the compact constructions in the space/time tradeoff map. On the smallest alphabets we are outperformed in time, but nevertheless achieve the least space within reasonable time. For example, in DNA sequences, the most widely used application of BWTs, our construction uses 4.84 bits per base and builds the BWT at a rate of 2.13 megabases per second, whereas the closest previous alternative uses around 7.09 bits per base and runs at 4.17 megabases per second.
Introducing Sentiment Analysis for the Evaluation of Library’s Services Effectiveness

Increasingly, text mining approaches have come to academic and commercial foreground as an effective solution for managing textual resources. Users‟ and consumers‟ comments and reviews hyper proliferation due to web 2.0 emergence, generated the need for such techniques implementation as a way to get insights from an active world expressed textually and not limited to specific scales and options. Sentiment analysis constitutes a NLP method aiming at sentiment detection out of textual snippets. On the other hand, it is a common truth that academic libraries have been intensively based their evaluation attempts on quantitative methods. The current study proposes the use of Sentiment analysis on user comments about Hellenic Open University Distance Library and Information Center which were included to the institutional annual survey. The analysis highlighted latent information about specific aspects of the library that couldn‟t be detected through the constraints that scaling pοses.
The Politeness of Bungo Pasang Language Using Kato Nan Ampek in Minangkabau

&lt;em&gt;The purpose of this study was to describe the factors of politeness marker at expression of demand in the Minangkabau language in Bungo pasang area, Pesisir Selatan Regency of West Sumatra. Today the use of kato nan ampek in the expression of demand has begun to fade along with the times and technology. Linguistically, the expression of demand is reflected through (1) the length of speech, and (2) the use of non-imperative sentences. The object of this study was the Bungo Pasang community in the South Coastal District of 40-60 years who have a maximum junior high school education, with respondents who have the perfect utterance. The research method was descriptive qualitative that produces descriptive data in the form of written or verbal words from the respondents who were observed and interviewed. The results of this study are factors that determine politeness in demand; (a) implementation of performance, (2) variation of speech, and (3) completeness of speech. Then the politeness of demand in the Minangkabau language is manifested in (Lii) pragmatics and suprasegmental aspects, and kinesik. linguistic elegance is characterized by the use of the word help, and the use of the appropriate greeting.&lt;/em&gt;&lt;em&gt;&lt;span style="font-size: 10.0pt; font-family: 'Times New Roman',serif; mso-fareast-font-family: 'Times New Roman'; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;" lang="EN-US"&gt;The purpose of this study was to describe the factors of politeness marker at expression of demand in the Minangkabau language in Bungo pasang area, Pesisir Selatan Regency of West Sumatra. Today the use of kato nan ampek in the expression of demand has begun to fade along with the times and technology. Linguistically, the expression of demand is reflected through (1) the length of speech, and (2) the use of non-imperative sentences. The object of this study was the Bungo Pasang community in the South Coastal District of 40-60 years who have a maximum junior high school education, with respondents who have the perfect utterance.&lt;/span&gt;&lt;span style="font-size: 10.0pt; font-family: 'Times New Roman',serif; mso-fareast-font-family: 'Times New Roman'; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;" lang="EN-US"&gt;The research method was descriptive qualitative that produces descriptive data in the form of written or verbal words from the respondents who were observed and interviewed. The results of this study are factors that determine politeness in demand; (a) implementation of performance, (2) variation of speech, and (3) completeness of speech. Then the politeness of demand in the Minangkabau language is manifested in (Lii) pragmatics and suprasegmental aspects, and kinesik. linguistic elegance is characterized by the use of the word help, and the use of the appropriate greeting&lt;/span&gt;&lt;/em&gt;
P‐45: Position Correction against Vehicle Vibration for Augmented Reality on Head‐up Display

In this paper, we present a head‐up display system that displays augmented reality objects on a vehicle windshield. Vehicle vibration results when the vehicle plies on the road. We propose a position correction method against vehicle vibration for a head‐up display system. This method corrects the positions of computer graphic images on the LCD panel of a head‐up display by referring to an inclination angle generated from the vehicle vibration. We evaluated this method by capturing the overlay images of augmented reality objects on a head‐up display system.
INVESTIGATION INTO OPEN EDUCATIONAL RESOURCES FOR LEARNING ENGLISH IN DEVELOPING FUTURE PHILOLOGISTS’ INSTRUMENTAL VALUES

The authors present the results of the research carried out in the 2016/2018 academic years among 338 students earning BA in the English language and literature regarded in our study as future philologists. Experimental work was conducted at four higher educational institutions in Ukraine. The aim of the study was to find out the influence of open educational resources for learning English on the development of future philologists’ instrumental values. We used methods of mathematical statistics, computer data processing and a descriptive method for interpreting experimental data. The authors theoretically substantiate and practically prove the efficiency of the use of open educational resources for learning English which influence the development of future philologists’ instrumental values necessary for adequate evaluating own activity and meeting various real-life and professional challenges. These open educational resources are The Internet Encyclopedia of Ukraine, Encyclopedia Britannica, The Cambridge History of English and American Literature, Learn English. The results obtained in the experimental and control groups are compared and conclusions on the efficiency of the use of open educational resources for learning English in the educational process of higher education institutions in the context of development of future philologists’ instrumental values are drawn.
Cloud service composition using an inverted ant colony optimisation algorithm

In recent years, clouds are becoming an important platform for scientific applications. Service composition is a growing approach that increases the number of applications of cloud computing by reusing attractive services. However, more available approaches focus on producing composite services from a single cloud, limiting the benefits derived from other clouds. Furthermore, in many traditional service composition methods, there is a key problem called load balancing that was inefficient among cloud servers. Therefore, this paper proposes the inverted ant colony optimisation (IACO) algorithm, a variation of the basic ant colony optimisation (ACO) algorithm, to solve this problem. This method inverts its logic by converting the effect of pheromone on the selected path by ants in order to improve load balancing among cloud servers. In this method, ants begin to traverse the graph from the start node and each ant selects the best node for moving, then other ants may not follow the track travelled by the previous ants. We evaluate the performance of the proposed method in comparison with the ACO, greedy and COM2 algorithms in terms of the obtained optimal cloud composition, load balancing, waiting time, cost and execution time.
Perceptual loss for light field reconstruction in high-dimensional convolutional neural networks

We explore the benefits of perceptual loss for light field (LF) spatial recon struction in a high-dimensional convolutional neural network. The results outperform some state-of-the-art methods for LF or image super-resolution.