Reviewerly/exHarmony huggingface dataset:
AUTOMATED NEGOTIATION BASED ON ENSEMBLE LEARNING AND OPTIMAL COUNTER PROPOSAL

Agent-mediated automated negotiation is a key form of interaction in the e-commerce environment. Agents reach an agreement through an iterative process of making offers. However, agents are prone to conceal their private negotiation information, which decreases the efficiency of negotiation. In this paper, an ensemble learning-based negotiation method is proposed. The new method labels the proposals automatically by mining the implicit information in negotiation history data. Then, the labeled proposals become the training samples of the ensemble learning algorithm, which generates the estimation of the opponent’s utility function. At last, based on the utility function of both sides, a win-win negotiation counter-proposal is generated through a particle swarm optimization algorithm. The experimental results indicate the benefits and efficiency of the proposed method.
Linguistic Features in E-commerce Slogans

Slogan is one of the powerful tools to advertise e-commerce products and services. The power of slogan to promote commodities lies primarily on the language style that it employs. This study is aimed at analyzing the linguistic feautures in 38 e-commerce slogans that are popular in Indonesia. The data were analyzed quantitatively and qualitatively. Quantitatively, the data were calculated regarding the frequency of each identified linguistic features: semantic devices, syntactic devices, phonetic devices, orthographic devices, syntactic errors, code-mixing, and moods. Qualitatively, the data were verbally analyzed, described, and discussed. The findings show that regarding linguistic devices, the most prevalent case is semantic device (self-reference). Concerning syntactic errors, the most apparent errors relate to word order typology and ommission of articles &amp; prepositions. Speaking of code-mixing, the most frequently used term is the word ‘online’. In relation to moods, the most dominant mood is declarative. This study suggests further study with a wider context of data
Four-Page Fabric Books to Help Students in Story Telling

Educators and parents often look for teaching and learning materials for students based on a number of features, namely, materials that are easy to find, affordable and teacher-parent-friendly. Researchers have created a four-page fabric book as a resource to help teachers and parents engage in story-telling activities during class. The purpose of storytelling activities is to increase vocabulary, improve communication ability and student confidence. Four-page fabric books have storylines through characters, objects and situations created using a variety of fabrics. This qualitative study uses observation and interview methods to obtain data. The findings show that teachers can produce four-page storybooks and that teachers are confident that activities can be carried out with students. The formulation of appropriate aids can help teachers diversify the material in their student storytelling activities.
Aspetti metodologici dell’onomastica letteraria

Literary onomastics teeters between literary studies and linguistic onomastics. Therefore it is often the case that specialists in literature show little understanding of onomastics, while linguistically orientated onomasticians sometimes lack an understanding of literary theory. In this paper, after giving examples of this lack of interdisciplinary understanding, I propose different ways in which literary studies and linguistic onomastics can work together fruitfully, taking advantage of new developments like text linguistics and pragmaonomastics as well as computerized literary onomastics.
Combined Methods of Remote Sensing and Fieldwork in Geological and Mineral Exploration in the Mballe Locality, Adamawa Region of Cameroon

Much of Cameroon's sub-surface wealth is still to be discovered and valorised.In the quest to step up the exploration of these non-renewable natural resources, many techniques are being developed amongst which we have Remote sensing.To boost mineral exploration in Cameroon, this study applied Remote sensing techniques in the Mballe area in order to establish the geological and mineral wealth on thematic maps.This exploration was characterised by the treatment of Landsat satellite 8 images coupled with intensive fieldwork.With each phase having a specific objective, results of the two activities were compiled for analysis.It was found out that of the eight rock samples collected from the field (amphibole gneiss, quartzite, schist, gneiss, granite, granodiorite, syenite and laterite), they were mainly of metamorphic and plutonic origins.These rocks project to the surface in different forms and the local population uses them in different ways.Their fractures constitute the main paths through which the hydrographic network follows.The treated satellite image showed that gold concentrated in areas where clay and laterite are found especially in the south of the Mballe area.Furthermore, fieldwork also proved that this mineral concentrated at river meanders and confluences.Such a study can be applied in any locality of the country in order to boost mineral exploitation that will contribute to the GDP as the government has embarked on attaining an emerging nation by 2035.
Improvement of BCI operation accuracy by the VR human body motion feedback

This paper proposes a brain-computer interface virtual reality (BCI-VR) to improve brain-computer interface (BCI) operation accuracy using hand animation feedback by virtual reality. At first, we thought event-related desynchronization/synchronization (ERD/ERS) response is easier to detect in the case of imagining of hand than in the case of imagining of arm since the corresponding area of the motor cortex of the hand is larger than that of the arm. As a result, we assumed that BCI operation accuracy is improved. Thus, we compared the effect of imagining of making fists and of imagining of conventional arm raising. Also, we conducted an experiment to operate the BCI to find BCI accuracy of operation, and a sense of agency (SOA) was obtained using the seven-point Likert scale. The results demonstrated that the imagine of making fists was higher than the conventional imagine of arm raising in both the average of operation accuracy and the SOA. However, the Mann-Whitney's U test depicted no significant difference between the accuracy of the imagining of making fists and of imagining of arm raising. Additionally, it was found that there was a positive correlation between BCI operation accuracy and SOA. Therefore, motor imagery of making fists is considered to be good for improving the accuracy of the BCI operation but it needs to be verified. It was also suggested that the accuracy of BCI operation could be improved if the SOA could be obtained. In the future, we will continue to develop BCI-VR to improve the BCI.
Some features of the use of parceling in Internet communication

The subject of the research in the article is the peculiarities of using the parceling method in modern Internet communication. Based on the analysis of language material extracted from the Internet resources of Russian forums, an attempt is made to analyze the regularity and frequency of the use of the parceling method. The relevance of the study lies in the absence of special literature on this topic in the context of Internet linguistics. At the stage of preparation for the study, it was determined that the authors mainly studied the phenomenon of parceling on the basis of the material of fiction and journalism, mainly in newspapers and magazines. During the study, the following goals were set: to allocate the necessary amount of language material for the study of the phenomenon of parceling in Internet linguistics; based on the analysis of special literature, to isolate the main functions of parceling that are characteristic of Internet linguistics; to classify the phenomenon of parceling in Internet linguistics by structure, to make a detailed description of each category. The article uses the works of such linguists engaged in the study of parcelling as N.S. Valgina, Y.V. Vannikov, E.A. Ivanchikova, N.V. Inozemtseva, T.N. Kolokoltseva, A.P. Skovorodnikov, and others. Russian-language personality has used more than 500 language units extracted from federal and regional websites to draw conclusions about the relative frequency of using parceling and different structures as part of parceling, about the main functions of parceling in Internet communication, as well as about changes in Russian punctuation related, among other things, to the dictated features of using parceling in Internet communication of the XXI century and active processes occurring in modern Russian.
Strange Behaviors and Root Cause in the Compression of Previously Compressed Videos

In video compression class projects, students may observe some strange behaviors when using video codecs.Some performance metrics from a mediocre codec such as motion JPEG-2000 (or simply JPEG2000) may have exceptionally high values at certain compression ratios as compared to other high performing codecs.This strange behaviors may be overlooked by instructors and students may never understand why this is happening.In this paper, we will first highlight the strange behaviors.We will then use experiments to systematically determine the root cause.Our experiments show that, if one uses a previously compressed and decompressed video in some compression experiments, then it is highly likely that some strange behaviors will show up.Some advice will be provided to instructors, tutors, and students on how one can prevent such behaviors from occurring.
Valuable Advantages of Smart Doorbell Cameras | Great Valley Lockshop

Homeowners are constantly looking for ways to make their lives easier and increase security. Smart doorbell cameras can help you do both.
Algorithms for Crime Prediction in Smart Cities Through Data Mining

The concentration of police resources in conflict zones contributes to the reduction of crime in the region and the optimization of those resources. This paper presents the use of regression techniques to predict the number of criminal acts in Colombian municipalities. To this end, a set of data was generated merging the data from the Guardia Civil with public data on the demographic structure and voting trends in the municipalities. The best regressor obtained (Random Forests) achieves a RRSE (Root Relative Squared Error) of 40.12% and opens the way to keep incorporating public data of another type with greater predictive power. In addition, M5Rules were used to interpret the results.
Modified Network of Generalized Neural Elements as an Example of a New Generation Neural Network

The article is devoted to the analysis of neural networks consisting of generalized neural elements. The first part of the article proposes a new neural network model a modified network of generalized neural elements (MGNE-network). This network developes the model of generalized neural element, whose formal description contains some flaws. In the model of the MGNE-network these drawbacks are overcome. A neural network is introduced all at once, without preliminary description of the model of a single neural element and method of such elements interaction. The description of neural network mathematical model is simplified and makes it relatively easy to construct on its basis a simulation model to conduct numerical experiments. The model of the MGNEnetwork is universal, uniting properties of networks consisting of neurons-oscillators and neurons-detectors. In the second part of the article we prove the equivalence of the dynamics of the two considered neural networks: the network, consisting of classical generalized neural elements, and MGNE-network.We introduce the definition of equivalence in the functioning of the generalized neural element and the MGNEnetwork consisting of a single element. Then we introduce the definition of the equivalence of the dynamics of the two neural networks in general. It is determined the correlation of different parameters of the two considered neural network models. We discuss the issue of matching the initial conditions of the two considered neural network models. We prove the theorem about the equivalence of the dynamics of the two considered neural networks. This theorem allows us to apply all previously obtained results for the networks, consisting of classical generalized neural elements, to the MGNE-network.
SuperNet: An Efficient Image Super-Resolution Preserving Neural Network

Due to large development in multimedia information processing and fashion styling in commercial and social applications, cloth image recognition creates a huge impact. However, the large variations due to blurring in cloth image appearances and their complicated style formation conditions create challenges in image recognition. Moreover, Super Resolution (SR) technique raises the high frequency components that are used to generate a high-resolution image with good perceptual quality from a low-resolution image. A novel residual deep neural network called SuperNet approach that converts a low-resolution image to a high-resolution image by providing more advanced features for better characterization of clothing genre is introduced in this work. Furthermore, the proposed framework reduces the complexity of the network without content loss of the original image.
PEDAGOGICAL FUTUROLOGY: 21ST CENTURY PROSPECTS

The article discusses the subject of futurology, the development of different scenarios of foreseeing about the future of mankind, the role and place of education in them. In particular, the article presents the viewpoint that at present Pedagogical Futurology lacks the necessary fundamental, world-wide conceptions about the man of future, without which the existence of human development today and tomorrow will be jeopardized
Single Model Ensemble using Pseudo-Tags and Distinct Vectors

Model ensemble techniques often increase task performance in neural networks; however, they require increased time, memory, and management effort. In this study, we propose a novel method that replicates the effects of a model ensemble with a single model. Our approach creates K-virtual models within a single parameter space using K-distinct pseudo-tags and K-distinct vectors. Experiments on text classification and sequence labeling tasks on several datasets demonstrate that our method emulates or outperforms a traditional model ensemble with 1/K-times fewer parameters.
Mobility Irregularity Detection with Smart Transit Card Data

Identifying patterns and detecting irregularities regarding individual mobility in public transport system is crucial for transport planning and law enforcement applications (e.g., fraudulent behavior). In this context, most of recent approaches exploit similarity learning through comparing spatial-temporal patterns between normal and irregular records. However, they are limited in utilizing passenger-level information. First, all passenger transits are fused in a certain region at a timestamp whereas each passenger has own repetitive stops and time slots. Second, these differences in passenger profile result in high intra-class variance of normal records and blur the decision boundaries. To tackle these problems, we propose a modelling framework to extract passenger-level spatial-temporal profile and present a personalised similarity learning for irregular behavior detection. Specifically, a route-to-stop embedding is proposed to extract spatial correlations between transit stops and routes. Then attentive fusion is adopted to uncover spatial repetitive and time invariant patterns. Finally, a personalised similarity function is learned to evaluate the historical and recent mobility patterns. Experimental results on a large-scale dataset demonstrate that our model outperforms the state-of-the-art methods on recall, F1 score and accuracy. Raw features and the extracted patterns are visualized and illustrate the learned deviation between the normal and the irregular records.
Intelligent healthcare and monitoring system using Internet of Things for railway passengers

Among different modes of transportation, railway transportation offers reduced travel time, dependability, and excellent energy conservation. Invariably, this mode of transportation plays a vital role not only in the transportation of goods and commodities but also helps in the passenger itinerary. Many technological developments have ascended in the field of railways but healthcare is a major concern. Internet of Things(IoT) is a revolutionary technology that is being widely used to integrate advanced medical resources thereby offering effective health care services to human beings in an effortless way. In this project, we are proposing a controller-based technique to give first aid support in case of emergency, to the patients who are in immediate requirement of medical assistance. The abnormality is detected with the help of wearable sensors. Once the abnormality is detected, the first aid system is triggered by life. The information is transferred to the loco pilot who is in charge of operating the train and the nearest station. Thus, with the help of this system, we will be able to save the life of patients in case of an emergency during transit.
NSGA-II DESIGN FOR FEATURE SELECTION IN EEG CLASSIFICATION RELATED TO MOTOR IMAGERY

Feature selection is an important step regarding Electroencephalogram (EEG) classification, for a Brain-Computer Interface (BCI) systems, related to Motor Imagery (MI), due to large amount of featu ...
Cartesian Tree Matching and Indexing.

We introduce a new metric of match, called Cartesian tree matching, which means that two strings match if they have the same Cartesian trees. Based on Cartesian tree matching, we define single pattern matching for a text of length n and a pattern of length m, and multiple pattern matching for a text of length n and k patterns of total length m. We present an O(n+m) time algorithm for single pattern matching, and an O((n+m) log k) deterministic time or O(n+m) randomized time algorithm for multiple pattern matching. We also define an index data structure called Cartesian suffix tree, and present an O(n) randomized time algorithm to build the Cartesian suffix tree. Our efficient algorithms for Cartesian tree matching use a representation of the Cartesian tree, called the parent-distance representation.
Application of intelligent algorithm in trajectory optimization of hypersonic vehicle

Abstract Aiming at the application problem of intelligent algorithm in trajectory optimization of hypersonic vehicle, the basic theoretical framework to solve this problem is discussed. Based on the flight characteristics of hypersonic flight vehicle, the demand for intelligent algorithm application is put forward. According to the principle of intelligent optimization, the key problems such as initial selection of trajectory optimization, intelligent algorithm and parallel computation are discussed. On this basis, the system application framework of intelligent algorithm is designed, which optimizes trajectory and guidance synchronously, and provides a new typical application mode for flight vehicle intelligent control technology.
HYBRID APPROACH FOR HUMAN FACIAL EXPRESSION DETECTION THROUGH TLBO AND PFEF

This paper introduces facial expression detection method which is based on facial’s selected feature and optimized those selected features. The study says that human face generally faced generally consist of skin color, texture shape and size of face in this paper we study skin color and texture of human face .This process consist two steps for the same. In first known as detection of expression which uses PFEF (partial feature extension function) and in second, for optimization we used TLBO algorithm is basically a population base searching technics. Also uses soft computation technics because we cannot actual and accurate for human related activity. Varieties of technic are used for the same purpose this as per use hybrid approach to get better result.
A hybrid control strategy based on CSA and ELM for uncertain nonlinear chaotic system

The study of nonlinear chaotic systems and their control is an important topic. In this paper, a hybrid control strategy based on cuckoo search algorithm and extreme learning machine is proposed. Cuckoo search algorithm is used in a hybrid control strategy in order to optimise the weights and biases in extreme learning machine leading to the improvement of its performance. Simulations indicate that the proposed method is able to fit nonlinear chaotic systems and control chaotic systems effectively. Data used in the nonlinear chaotic system are also tested for uncertainty and unknown systems. Simulation results confirm that the proposed method shows robustness for noisy data and perturbed parameters.
LibGuides: Changes in the Library: Home

This is a guide to the upcoming changes to the ICC Library, including new login information, OpenAthens, and Primo VE.
Informatologia in the area of planetary communication

The scientific and editorial programming orientation of the scientific journal INFORMATOLOGIA (1969. – 2019.) was based on the historical, present and future promotion of information and communication sciences, publishing of selected scien-tific and professional papers by renowned internationally recognized information and communication scientists, who have earned their scientific achievements on an ongoing basis place on the pages of the reputable magazine INFORMATOLOGIA. The editorial and programmatic orientation of the scientific journal Informatologia (1969. – 2019.) was based on, numerous scientific and professional critical editorial dilemmas, analyzing, valorizing and selecting quality scientific information and communication production for publication in the journal Informatologia. In a strategic journalistic sense, the editorial board members respected high scientific standards, peer-reviewed expert opinion, and affirmed selection based on critical awareness and ethical editorial principles in the selection of copyrighted productions for the publication of scientific and professional papers.
Assessing the Quality of Paraphrases Written by Third Year Costa Rican EFL Students

&#x0D; &#x0D; &#x0D; The aim of this study was to assess factors affecting the quality of paraphrases written by college level EFL learners. A three-dimensional paraphrasing competence model by McCarthy, Guess, and McNamara (2009) was followed to assess the texts for seman- tic completeness, lexical difference, and syntactic difference. The selected method was a mixed method approach. The quantitative analysis was used to measure the rate of success of each paraphrasing competence whereas the qualitative analysis aimed to de- scribe the perceived difficulty of the competences and the reasons behind it. The subjects were 17 EFL students enrolled in a third year English composition course at the Univer- sity of Costa Rica. The corpus of the study consisted of 51 paraphrases. Following three rounds of examinations and the analysis of students’ perceptions, the lexical dimension emerged as the most challenging area interfering with paraphrase quality, with seman- tic completeness also emerging as difficult. Other factors affecting paraphrase quality were inappropriate use of passive voice, style and register, and inaccurate lexical substi- tutions. The study concluded with recommendations to improve instructional cycles by reinforcing reading comprehension and lexical development, and by assessing the differ- ent dimensions of paraphrasing separately. &#x0D; &#x0D; &#x0D;