Reviewerly/exHarmony huggingface dataset:
Intuitive User Interface for Enhanced Search Experience

In the early years of the Internet, due to limitations on availability and speed, it was preferred to convey information in a textual manner. Even though the Internet connections have much higher speed and can handle huge amounts of data today, the search engine interface is still relying on textual layouts to convey results. The huge amount of information available on the Internet is accessed via search engines. Search engines have essentially become a gateway to the Internet for the majority of users. Hence it is important that the search engine interface evolves to serve the growing user requirements. Presenting the results to a user's query graphically is much more informative and visually appealing to a user. Since gestures serve as a natural means of interaction for humans, an interface that can be controlled by gestures will make user interaction more engaging. This paper is aimed at developing a search engine interface based on hand gesture recognition. The system has been developed using convolutional neural networks, giving it 94% accuracy.
WeChat Redesign for Foreigners Living in China from Culturally Adaptive Design Perspective

As an approach of human-centered design, the culturally adaptive design is flexible to integrate cultural specific attributes into design thinking. This study chooses WeChat to exemplify how to resign from a culturally adaptive view. WeChat has become a universal social media tool in the Chinese market, with 960 million users. However, the lack of culture adaption in interaction interfaces results in some usability problems for foreigners. To be globally accepted, the design should adapt to different users’ cultural preferences. In this paper, we conducted a systematic research focusing on incorporating cultural factors, and Human-Computer Interaction factors into mobile interface design. It consists of five main steps include data collection, problem definition, ideation, prototype implementation, and evaluation. The statistical evaluation metrics of evaluation illustrates that interfaces that accommodate culture can significantly increase the user experience. The design process also provides deep insights into how WeChat can improve its interaction ways, which will enhance foreigners’ satisfaction and their future usage intentions.
Effective and Efficient LDA+ELM Model for Supervised Classification of Brain Tumor Types Using 2D MRI Scans

Application of machine learning in multiclass classification of brain tumor types has contributed to the development of computer aided diagnosis (CAD) system that can potentially enhance accuracy and speed up diagnosis of the disease. LDA+ELM model with different activation functions were investigated to achieve the optimum performances in terms of accuracy, Kappa statistic, sensitivity, precision, F-measure, training time and test time. We also proposed a user-friendly GUI in characterizing brain tumor types using MR images. First, a total of 3064 slices of CE T1-weighted brain MR images with ground truth were downloaded from a free online database. The manually segmented tumor region was augmented and then undergo several feature extraction techniques. All the feature descriptors obtained were then concatenated, followed by LDA dimensionality approach. Performance of different number of LDA features and ELM activation functions were investigated by repeated training and test. The ELM output of training data for each class was used to fit GMM and these probabilistic models used to estimate posterior probabilities of test data. LDA+ELM model with 5 LDA feature input, utilizing sigmoid function as hidden nodes activation functions achieves the best generalization performance with accuracy of 98.92% and corresponding F-scores for meningioma, glioma and pituitary tumor of 97.81%, 99.1% and 99.5% respectively. The proposed method (LDA+ELM) model performs better compared to other previous works using the same dataset and performing the same classification task.
Attribute based Encryption for Improved Multi-Keyword Search in Information Network

Within Information Networks, proprietors can store their archives over various servers that have been transmitted. By settling down anywhere and on any computer, it allows clients to store and access their information in and from various servers. Giving successful searching on disseminated documents additionally gives privacy on owners' archives is an exceedingly difficult task. The existing system offers one possible structure which is indexing protecting privacy (PPI). In this sense, records are disseminated via different private repositories, all managed by cloud / open servers. It has been inquired to open the cloud at the point where the client requires few details and then returns to clients the hopeful rundown which is private server rundown. However, in this process, in the wake of having rundown, clients will search for the records on a specific private server; reports are exchanged in plain document form on a private server that is privacy. The new program would in any case improve the current framework to make it stronger and more professional. To start with the data, the key distribution center (KDC), which allows information to be decoded from a private server, is put on the private servers in an encoded system. The proposed framework also implements TF-IDF, which helps clients place their tests.
Trend of Culture and Arts Education for Infants and Children and Policy Challenges to Spread Programs

The purpose of this study is to identify the current status of culture and arts education for infants and to provide data on policies for the efficient and effective dissemination of culture and arts education programs for infants through the survey of the current status of related projects and programs.BR To this end, through the analysis of the five major policies announced for the dissemination of culture and arts education in 2004 and the results of the Korea Culture and Arts Education Promotion Agency’s Culture and Arts Education Support Project, through the analysis of the results of the Korea Culture and Arts Education Promotion Agency’s project to support early childhood culture and arts education, which has been promoted since 2009, the purpose and purpose of the study are to establish basic data for the establishment of the basic data for the promotion of the national culture and arts education policies for the distribution of effective cultural and arts education programs for the arts experience of the Nuri program by analyzing the five major educational areas and tasks of infants promoted under the revised Nuri program.
Evaluating Portable Touch Projectors in the Context of Digital Education

In digital education, it is becoming increasingly important to provide devices that lower the entry point and motivate high levels of participation, especially during group work scenarios. Within the context of digitization of education projects at Ruhr-University Bochum, we conducted studies in multiple courses using touch-based portable projectors. Teaching collaborative and creative modeling was the setting of these experiments. The experiments were conducted and evaluated in three different phases. Finally, the gathered data was used to improve the method and the software requirements for the following phases iteratively and also to assess whether the use of the touch projector improves the collaborative learning of the modeling process. During the evaluation, we found out that the participants using the touch projector always ranked their level of participation in the modeling process much higher than it was actually observable.
Historical Aspects of Pedagogical Reperture Formation

An essential factor in music education is a competent selection of the performing repertoire, which contributes to a better achievement of the required level of musical development. In turn, the question of forming a pedagogical repertoire depends largely on the skills of its analysis, the ability to assess the artistic and technical complexity of the works performed. At the beginning of the third millennium, the demands for a pedagogical process in the whole and in the field of culture and art in particular increased significantly. In the context of the transformation processes of the art education system, considerable emphasis is placed on the professional training of the personnel of the field of culture and art. Like all components of art and aesthetic education, performing is one of the important factors in reflecting the centuries, as past centuries life experience, wisdom and beauty of an ethnic group. Ukrainian thinkers and artists play the role in preserving and fostering cultures, moral aesthetic and ethical values. If we talk about the preparation of performers in the field of musical art, we note that the quality of the final artistic result is a properly selected performing repertoire. Thus, the problem of selection of pedagogical repertoire as the basis of qualitative preparation of musician in the process of performing activity remains relevant today. When addressing the problems of musical education, scientists’ attention is mainly focused on the theoretical foundations of the performers’ reparation, and on the psychological and pedagogical conditions of the creative individuality formation. However, the preparation of skilled performers is impossible without knowledge of the components and all the spectra of the specificity of the selection of the performing repertoire. The paper deals with the essence and means of approach to solving the problems of selection of the performing repertoire, which is of great importance in the realization of the tasks of the pedagogical process in forming the independent creative personality of the performer.
Optimizing Generative Adversarial Networks for Low-Resolution Image Enhancement

Current high-resolution camera and video systems require expensively complex equipment and an excessive amount of digital storage to function, effectively limiting their practicality and availability. The research seeks to address this issue by optimizing Generative Adversarial Networks (GANs) for image super-resolution using an evolutionary-based scheme for successive network modification. The capability of GANs to selectively enhance the resolution of a desired image without increasing costs is extremely significant for a substantial range of industries and practices. The network's capabilities are expressed in terms of produced image quality and network metrics, with preference given to increases in image quality. Using the DIV2K dataset as common input, the highest performing network achieved a comparative increase of 2.22 dB PSNR (29.1%) over the base model, the Super-Resolution Generative Adversarial Network (SRGAN). The most notable contribution to network enhancement with regards to image quality was caused by removing the batch normalization layers from the Generator network. Network performance with regards to subjective image quality was most affected by the inclusion of a second convolutional layer in each residual block of the modified SRGAN Generator. Possible applications of the improved system include enhancing images of license plates for traffic monitoring systems and improving still images from body camera footage to reveal crucial details. Beyond the scope of surveillance, resolution-enhancing GANs may be applied to develop media content or national defense capabilities.
Study on Learning Effectiveness of Virtual Reality Technology in Retail Store Design Course

Information and communication technology is regarded as a crucial tool in the field of education. The Retail Store Design course in Shunde Polytechnic includes industry–education integration and a project-oriented teaching approach. Various types of retail store design projects are introduced through different channels, and project-based teaching is implemented in accordance with a market-oriented design studio workflow. The interactive nature of virtual reality technology can transform conventional teaching from passive into active learning, thus improving teacher–student communication and information transmission in the classroom. This study adopted virtual reality technology as a tool to facilitate teaching and learning. A 720° virtual reality training system was developed using Photoshop and the 720yun application to provide students with a virtual survey experience for the retail store construction site before remodeling. The Retail Store Design course of Shunde Polytechnic was used as an example to evaluate the system according to three aspects: onsite survey accuracy, onsite survey speed, and learning enjoyment. Participants were recruited from students enrolled in the Retail Store Design course at Shunde Polytechnic; a set of objective and subjective questionnaire measurements were designed and distributed to the aforementioned students. The results demonstrated that virtual reality yielded more satisfactory learning achievements compared with conventional teaching methods. Using virtual reality technology for the virtual survey of construction sites in the Retail Store Design course was extremely valuable and effective for students.
A Comparative Usability Analysis of Handheld Game Consoles

A handheld game console is a small and portable video game console with a built-in screen, game controls and speakers. Playing a handheld game console involves multiple operations and buttons. The usability of game consoles is influenced by users' expertise and skills. In this study, we mainly focused on testing the usability of products instead of video games and we adopted three variables from Leventhal and Barnes' usability model (reference) to analyze two game consoles (Switch and 3DS-LL) on three variables: task match, the ease of learning, and the ease of use. We recruited novice users and compared the usability of the two-handle mode and single-handle mode of Switch, and of Switch and 3DS-LL. Finally, we raised some suggestions for the design of handheld game consoles regarding usability.
Estimation of Degree of Interest in Comics Using a Stabilometer and an Acceleration Sensor

The current widespread usage of the Internet has made it possible to easily browse through various types of web content. However, owing to the large amount of available web content, it is difficult to recommend items that match the viewer’s preferences. Although existing recommendation systems can recommend content based on the viewer’s browsing history and previous purchases, there is still a lack of content relevance. Hence, a system is required that can quantitatively evaluate the viewer’s degree of interest by incorporating biometric information and thereby recommend the appropriate content. In previous studies, the viewer’s concentration was measured by employing an acceleration sensor on the back surface of a chair. However, the viewer’s posture cannot be estimated when the viewer does not lean against the backrest. Hence, in this study, we propose a method for estimating the degree of interest by employing a chair equipped with a body stabilometer on the seat and an acceleration sensor on the back. In this study, when the subject was leaning against the backrest, we determined the position of the center of gravity by employing a body stabilometer, and we acquired acceleration data by employing an acceleration sensor. Furthermore, we analyzed the movement vectors of the position of the center of gravity and the acceleration. Consequently, the vector angle was divided after every 15°, and the analysis was conducted by examining the vector magnitude in the angle. The obtained results indicate a positive correlation between the interest in each story and the vector magnitude. Therefore, it can be concluded that the degree of interest can be evaluated by incorporating the vector magnitude of the position of the center of gravity and the acceleration.
Boosting Non-oil Export Revenue in Nigeria Through Non-traditional Agricultural Export Commodities: How Feasible?

Available data indicated that, some traditional agricultural export commodities like cocoa and rubber have remained on Nigeria’s agricultural export list, while others like groundnut and coffee have almost disappeared from the export list. In the same vein, non-traditional agricultural export commodities like sesame seed and cashew nuts have started featuring prominently on the export list. In line with theory, the econometric analysis carried out confirmed that a major policy change, which can provide a boost for agricultural exports, is the depreciation of the real exchange rate. For all the agricultural export commodities analyzed in the study, the coefficient of the exchange rate was positive and highly significant.
Determining Moving Object Properties using "Controlled" Image Blurring

The paper proposes an approach to detecting, capturing and identifying vehicles in an image in order to determine their geometrical, kinematic and dynamic properties. Monitoring the properties determined in real time will assist in detecting violations of vehicle regulations, in analysing and preventing potential accidents by means of using the parameters obtained to control vehicle motion, as well as in implementing a digital model of the environment, including its possible virtual reality representation. To detect the object, we employ the YOLOv3 algorithm using convolutional neural network training. Canny and Hough detectors are used to determine the object boundaries and its axle positions. We propose a method for determining the object boundary blurring based on numerically finding the first, second and third derivatives with respect to each coordinate axis and subsequently refining the result at different resolutions. After detecting the axles in a vehicle and determining their number via passive image analysis, a model of vertical oscillations is selected for the vehicle; the geometrical and kinematic parameters obtained are then used to assess the automotive vehicle dynamics. We describe in detail brour vehicle model featuring two axles. We assume the parameters of an artificial obstacle such as a speed breaker to be the initial conditions of the oscillating system
Intensive Pedestrian Detection Algorithm Based on Key Points

There are two problems in the intensive pedestrian detection task: a large span of pedestrian scale and serious crowded. This paper adopts the object detection of the new trend in 2019. The algorithm of anchor-free mechanism to solve the first problem, and the soft-NMS mechanism to solve the second problem. We used FoveaBox based on soft-NMS algorithm improvement. First of all, compared with the traditional anchor-based detector, anchor free detector has a stronger generalization ability and also performs better in dealing with the size changes of different aspect ratios, anchor covers a limited scale range and shows some struggling in the intensive pedestrian detection task. Secondly, we improved the general NMS algorithm by adopting a soft-NMS algorithm. Soft-NMS algorithm can effectively improve the recall rate and average accuracy in the face of crowded problems. We used the subway passenger flow in peak period as the data, and compared the FoveaBox based on soft-NMS with the generic Faster R-CNN and YOLOv3, which proved that the FoveaBox improved by soft-NMS was an effective algorithm to deal with intensive pedestrian detection tasks.
Symbolic localization of institutionalized patients for detection of daily living activities

It is essential for elder people to maintain their independence, and for that it is necessary to prevent them from reaching states of frailty. As one of the fundamental parameters in the evaluation and detection of frailty is the walking speed, monitoring this parameter in institutionalized patients would be of great help to the health staff. The goal of this work is to track physical parameters of older adults and to perform a symbolic location that allows to follow up behavioural routines as complementary information for their diagnosis. For this purpose, it is proposed that the patient carries a light multi-sensory system on his/her ankle that integrates an inertial measurement unit (IMU), a barometer and a WiFi receiver. Short range WiFi transmitters should be deployed in the rooms where monitoring is desired. Different algorithms have been developed to daily identify the number of steps and floor changes. This information and the detection of the WiFi signal strength, provide a very precise symbolic location at room level, as the preliminary results with real patients show. This is the first step to generate algorithms for automatically detecting daily living activities (ADL).
Development of Microcontroller Based Portable Solar Irradiance Meter Using Mini Solar Cell

The aim of this paper is to design and develop a portable solar irradiance meter which allows the users to measure the real-time solar irradiance. The measuring device used a solar cell as the main sensor in order to convert solar energy into electrical energy. The actual solar irradiance will be measured and displayed on the LCD. The project used a microcontroller to obtain and process the output parameters from the solar cell. In addition, the developed devices also provide ambient temperature in real-time. Based on experiment, the developed system showed the accuracy more than 90% which is the overall error less than 10%.
On the sensitivity analysis of cartesian genetic programming hyper-heuristic

The research on Genetic-Programming Hyper-heuristics (GPHH) for automated design of heuristic-based methods has been very active over the last years. Most efforts have focused on the development or improvements of GPHH methods or their applications to different problem domains. Studies that target on the analysis and understanding of the GPHH behavior are still scarce, despite their relevance for easing the application of GPHH in practice and for advancing this research field. In order to advance the body of knowledge on the understanding of GPHH behavior, this paper aims at analyzing the impact of its parameters on the evolution, diversity, and quality of generated algorithms. In particular, a Cartesian Genetic-Programming hyper-heuristic (CGPHH) applied to an NP-Complete problem of production planning (multi-level capacitated lot-sizing problem) is considered. The effects of five parameters on response variables that reflect various aspects of the CGPHH behavior, such as diversity and quality of generated algorithms, are analyzed based on a full-factorial design of experiments. Results indicate that mainly three factors affect the CGPHH behavior in different ways: mutation rate, the CGP representation, and the number of graph nodes. Nonetheless, the CGPHH still generates competitive algorithms, despite the changes applied to its parameters.