Reviewerly/exHarmony huggingface dataset:
Color image enhancement algorithm based on improved Retinex algorithm

In order to solve the problem of low expressiveness caused by color distortion and poor saturation when performing image enhancement with classic Retinex algorithm, this paper proposes a color image enhancement algorithm base on the improved Retinex algorithm. In this algorithm, the input image is decomposed into illumination component and reflection component base on Retinex theory first, then logarithmic transfor-mation and Gaussian filtering are performed on the illumination component of HSV color space to approximate the visual system&#x0027;s perception intensity to physical reflectance. Next, the estimated illumination value of scene is used to adjust the multi-scale reflection components of the input image, and to obtain a preliminarily enhanced image. Finally, a color correction factor is introduced into the initial enhanced image to obtain the final enhanced image base on gray world hypothesis. Experimental results show that compared with several classical Retinex algorithms, the proposed algorithm can effectively improve the brightness, contrast and visual information fidelity of the input image without color distortion.
A Visual Analytics Method for Time-Series Log Data Using Multiple Dimensionality Reduction

The size and complexity of supercomputer systems and their power and cooling facilities have continuously increased, thus posing additional challenge for long-term and stable operation. Supercomputers are shared computational resources and usually operate with different computational workloads at different locations (space) and timings (time). Better understanding of the supercomputer system's heat generation and cooling behavior is highly desired from the facility operational side for decision making and optimization planning. In this work, we present a dimensionality reduction-based visual analytics method for time-series log data, from supercomputer system and its facility, to capture characteristic spatio-temporal features and behaviors during the operation.
Behavioral Maps: Identifying Architectural Smells in Self-adaptive Systems at Runtime

Self-adaptive systems (SAS) change their behavior and structure at runtime, depending on environmental changes and reconfiguration plans and goals. Such systems combine architectural fragments or solutions in their (re)configuration process. However, this process may negatively impact the system’s architectural qualities, exhibiting architectural bad smells (ABS). Also, some smells may appear in only particular runtime conditions. This issue is challenging to detect due to the combinatorial explosion of interactions amongst features. We initially proposed the notion of Behavioral Map to explore architectural issues at runtime. This extended study applies the Behavioral Map to analyze the ABS in self-adaptive systems at runtime. In particular, we look for Cyclic Dependency, Extraneous Connector, Hub-Like Dependency, and Oppressed Monitor ABS in various runtime adaptations in the Smart Home Environment (SHE) framework, Adasim, and mRUBiS systems developed in Java. The results indicate that runtime ABS identification is required to fully capture SAS architectural qualities because the ABS are feature-dependent, and their number is highly variable for each adaptation. We have observed that some ABS appears in all runtime adaptations, some in only a few. However, some ABS only appear in the publish-subscribe architecture, such as Extraneous Connector and Oppressed Monitor smell. We discuss the reasons behind these architectural smells for each system and motivate the need for targeted ABS analyses in SAS.
Comparing cyber physical systems with RFID applications: common attacks and countermeasure challenges

The RFID technology is widely used in industrial control systems (ICS) and cyber physical systems (CPS). However, the design of the current RFID protocol is optimal in performance but with less effort invested into security. As such, RIFD infrastructure could be vulnerable against cyber threats. In this paper, we present a positioning of RFID security attacks with CPS attacks. We identified similarities and differences of both type of threats that can serve as baseline to establish an IoT security framework. Additionally, we discuss RFID security countermeasures that we extracted from the literature then we compare it with existing CPS countermeasures. Three security threats categories were identified namely, physical attacks, interception attacks and blocking attacks. Overall, the research avail that attacks are similar for both CPS and RFID systems apart from social engineering attacks that are specific to CPS. However, addressing those attacks requires additional measures due to RFID specificity.
Mobile financial applications development using an integrated approach of the netnography, fuzzy QFD and fuzzy flowsort

The growing popularity of mobile applications and technology has led to developing the relationships of many corporations with consumers through mobile apps. Therefore, designing applications based on consumers' preferences and requirements are very important. This research seeks to evaluate and rank the technical requirements of mobile financial applications according to the customer's needs. Firstly, the netnography technique has been used to identify customer needs through the analysis of customer comments. After determining the technical requirements, using the latest edition of ISO 25010 standards, customer requirements and technical requirements have been analysed using the fuzzy QFD method. Finally, to determine the most important technical requirements, the fuzzy flowsort method was used for ranking. The results showed that security requirements, maturity, availability, appropriateness recognisability, operability, user interface aesthetics, accessibility, and analysability are the most important and most effective requirements related to customer needs in the area of mobile financial applications.
IDENTIFIKASI KEUTUHAN DAN PENANGAN KEAMANAN DATA PADA WIRELESS SENSOR NETWORK

Wireless Sensor Networks (WSN) is becoming a trend of technology along with the development of data transmission and the human need for the Internet of Things (IoT). IoT is a technology term created to connect one object to be able to send data through a transmission medium (internet) without the help of computers and humans. WSN is one of the technological elements in IoT that helps create connectivity. Currently WSN is widely used to assist tasks related to monitoring, evaluating, tracking, controlling things, and others. WSN consists of a collection of small sensors that will collect data and then transmit it. WSN with wireless system is very vulnerable to security holes. Here we will focus on examining the security vulnerabilities of WSN, how to avoid, and protect the WSN network.
FORMATION OF THE IDEA OF MATHEMATICAL PHENOMENOLOGY IN ED UND HUSSERL’S PHILOSOPHY

The article presents the historical prerequisites for the creation of mathematical phenomenology. Within the framework of the infinite numbers problems, the ways of their phenomenological interpretation are dis-cussed. Using the example of cooperation between Cantor and Husserl, the idea of mathematical phenome-nology is formulated, which takes into account the correlation of mathematical objects with our conscious-ness. In formal logic, subjective factors often affect the judgment process. The phenomenological method is valuable in that it makes it possible to conduct both objectively and subjectively oriented research in math-ematics and formal logic. In such a correlative study, subjective acts and objective referents of any phenom-enon should be taken into account. The main goal of correlative research is to create conditions for over-coming relativistic tendencies in mathematics and formal logic. As a result of the analysis, the question of the relationship between descriptive phenomenology and formalized constructions is raised. In the historical and philosophical context, the answer to this question is based on the theoretical developments provided in Husserl’s Formal and Transcendental Logic. Subjective-oriented logic goes back to the latent structures of theoretical reason. Here the problems of consciousness are formulated and solved in its live, actual execu-tion with the help of egological research. In conclusion, historical examples of the subjective transformation of formal logic are provided. In the first example, an interpretation of Descartes’ conclusion cogito, ergo sum is given, showing that the existential inconsistency of «I do not exist» and the reliability of the initial position «I exist» were realized here. Another example of the transformation of logic is Husserl’s phenome-nology. In order to bring logical forms to their subjective obviousness, it is necessary to change the orienta-tion of consciousness and to consider objects as givens of consciousness.
A study on metaphorical thinking and the research contents of &lt;Samogok&gt;

In this study, I tried to prepare educational content by suggesting metaphorical thinking as an alternative to overcome the biased theme consciousness of &lt;Samogok&gt;. To this end, the meaning and structure of metaphorical thinking were clarified, and the actual educational content of &lt;Samogok&gt; was prepared from the point of view of metaphorical thinking.&#x0D; Paying attention to the characteristic of metaphorical mobility, metaphorical thinking was viewed as a concept that includes the expansion of the cognitive structure that learners can form through metaphors, the formation of relationships with objects, and the subjective construction of meanings for the given meanings. And the structure of metaphorical thinking was proposed as the formation of a relationship with a heterogeneous object by similarity, the formation of a new gaze on the object, and a reinterpretation of the given meaning.&#x0D; These contents can be a way for &lt;Samogok&gt; to transmit the value of filial piety and overcome the limited understanding that was perceived as a sanction. In addition, it can be an alternative for in-depth metaphorical education by solving the problem that metaphoric education was limitedly focused on justice and effect in literature education.
Construction and Application of Evaluation Index System of Entrepreneurship Education

Entrepreneurship education evaluation has the function of guiding, motivating and evaluating the development of entrepreneurship education, and the development of effective entrepreneurship education evaluation tools is a hot spot in the field of international entrepreneurship education and evaluation research.This study constructs an evaluation index system of entrepreneurship education in colleges and universities based on Context Evaluation, Input Evaluation, Process Evaluation and Product Evaluation (CIPP) model consisting of 4 primary evaluation indexes, 12 secondary evaluation indexes and 41 descriptive indexes, compiles the questionnaire on the effectiveness of entrepreneurship education implementation in universities, and conducts a survey on the effectiveness of entrepreneurship education for college students in a pilot university in the first round of entrepreneurship education in China as the research object.The questionnaire was tested for reliability using SPSS 25 software, and finally, countermeasures were proposed based on the evaluation results to provide a reference for the research on entrepreneurship education and evaluation in colleges and universities in China.
Deployment Essentials of AVS

Businesses always want cloud migrations to be low risk, low cost, and of low complexity. Cloud consumers’ on-premises environment and all of their existing investments, skills, and tools can be extended to a public cloud platform in a simple, secure manner. A VMware solution from Azure enables this.
Augmented Reality-Based Board Game for Learning English for Junior High School Students

English is the language used by all countries as the main communication tool. By understanding English, young people can have the opportunity to work abroad and gain more knowledge and better job opportunities. But education in Indonesia and the willingness of young people to learn is still low, young people tend to prefer to play games rather than learn. Therefore, a game made with Augmented Reality technology was combined with a Board Game called the game "ArReadSpeed" in hopes of helping young people especially those still sitting in junior high schools (SMP) to learn while playing. This game can be played by 4 people, so we can give free time children the game "ArReadSpeed". But because currently there is a Corona pandemic, the data search and testing process must be changed by going through online classes. The purpose of this study is about how to formulate games so that it can make young people more easily learn English lessons. The formulation in it determines the gameplay, reward system, and punishment for incorrectly answering questions. After the game was finished, some junior high school children were tested and the results were that performance expectations (usability) and entertainment (pleasure) had a correlation with the variable wanting to continue to use (desire to use again).
CLASSROOM INTERACTION: A CASE STUDY IN INDONESIAN PRE-SERVICE ENGLISH TEACHERS' ONLINE WRITING COURSE

In higher education, the impact of online educational technology and the online classroom has had a variety of outcomes. This case study aimed to investigate the characteristics of interaction in an online writing course. It was conducted at one of the State Islamic Institutes in Indonesia. One lecturer and 48 pre-service English teachers participated in the study. In the writing course, the pre-service English teachers had to write narrative text, report text, and descriptive text; and the questions related to the material by using Chatbot application. Online observations done in Google Meet and interviews were utilized to gather the data. Content analysis was used to examine the data gathered. The results indicated that teacher-student (class), teacher-student(group), and student-student interactions were applied in the online class to improve the pre-service English teacher’s engagement and comprehension towards English writing skill. Besides, reward, break online room and peer review in online document were detected as effective ways in improving the classroom interaction effectiveness.
Effectiveness of the Use Hospital Information And Management System (SIMRS) For Services Based on Hot-Fit Theory

The use of a computer-based Hospital Information and Management System (SIMRS) in the Medical Record unit is carried out in an integrated manner. The data management process includes, among others, data collection (registration), data processing (assembling, coding, indexing), and data reporting. The SIMRS implementation at the general hospital of Az-Zahra has not yet been fully implemented. The objective of this study was to determine the effectiveness of the use of hospital information and management systems (SIMRS) for services at the general hospital of Az-Zahra Kalirejo through the HOT-FIT theory. This type of research was qualitative, the research design used exploratory with the objective of describing the effectiveness of the use of Hospital Information and Management systems for services at the general hospital of Az-Zahra Kalirejo. The population in this study was 134 people, and the sample in this study was 9 informants, namely the doctor in charge of services (DPJP), general practitioner and head of finance. The results of the study are known in the human aspect, SIMRS officers at the general hospital of Az-Zahra already understand how to use SIMRS, but for specialist doctors and general practitioners they are still assisted by nurses in inputting. In the organizational aspect, it is known that the directors, management and staff of the hospital fully support the use of SIMRS. The technology aspect of SIMRS at the general hospital of Az-Zahra is in accordance with the accreditation standards of the Hospital and Social Security Administrator’s Health, but often experiences problems with the internet network, which can interfere with the operation of using SIMRS. Researchers suggest that SIMRS training be held for general practitioners and specialists, as well as improving the internet network so that the connection is even better.
Conferences

Journal Article Conferences Get access Logic Journal of the IGPL, jzac062, https://doi.org/10.1093/jigpal/jzac062 Published: 19 August 2022
GenoMus: Representing Procedural Musical Structures with an Encoded Functional Grammar Optimized for Metaprogramming and Machine Learning

We present GenoMus, a new model for artificial musical creativity based on a procedural approach, able to represent compositional techniques behind a musical score. This model aims to build a framework for automatic creativity, that is easily adaptable to other domains beyond music. The core of GenoMus is a functional grammar designed to cover a wide range of styles, integrating traditional and contemporary composing techniques. In its encoded form, both composing methods and music scores are represented as one-dimensional arrays of normalized values. On the other hand, the decoded form of GenoMus grammar is human-readable, allowing for manual editing and the implementation of user-defined processes. Musical procedures (genotypes) are functional trees, able to generate musical scores (phenotypes). Each subprocess uses the same generic functional structure, regardless of the time scale, polyphonic structure, or traditional or algorithmic process being employed. Some works produced with the algorithm have been already published. This highly homogeneous and modular approach simplifies metaprogramming and maximizes search space. Its abstract and compact representation of musical knowledge as pure numeric arrays is optimized for the application of different machine learning paradigms.
Histopathology of lung cancer classification using convolutional neural network with gamma correction

Lung cancer is a degenerative disease that causes the growth of abnormal tissue to become autonomous and malignant. There are two types of lung cancer: adenocarcinoma and squamous cell carcinoma. Both types of cancer can be examined with varied techniques, one of them is histopathological examination. This examination is performed by expert analysts who can distinguish normal tissue from others. Manual inspection requires a long observation time and energy, therefore a computer-based classification system is created. In this study, Convolutional Neural Network (CNN) with gamma correction was implemented. Gamma correction is a process to adjust the image light, while CNN is for feature extraction and classification. The CNN built consists of one gamma correction layer, three convolution layers, three max-pooling layers, and two fully connected layers. The data consists of 3,000 images from the public dataset Lc25000. It has a normal and two lung cancer classes i.e adenocarcinoma and squamous cell carcinoma. In this study, we used gamma values ​​of 0.8, 1.0, and 1.2. The testing was carried out using five-fold cross-validation. It obtained the highest accuracy of 87.16% with a gamma value of 1.2.
Generation of Controlled Synthetic Samples and Impact of Hyper-Tuning Parameters to Effectively Classify the Complex Structure of Overlapping Region

The classification of imbalanced and overlapping data has provided customary insight over the last decade, as most real-world applications comprise multiple classes with an imbalanced distribution of samples. Samples from different classes overlap near class boundaries, creating a complex structure for the underlying classifier. Due to the imbalanced distribution of samples, the underlying classifier favors samples from the majority class and ignores samples representing the least minority class. The imbalanced nature of the data—resulting in overlapping regions—greatly affects the learning of various machine learning classifiers, as most machine learning classifiers are designed to handle balanced datasets and perform poorly when applied to imbalanced data. To improve learning on multi-class problems, more expertise is required in both traditional classifiers and problem domain datasets. Some experimentation and knowledge of hyper-tuning the parameters and parameters of the classifier under consideration are required. Several techniques for learning from multi-class problems have been reported in the literature, such as sampling techniques, algorithm adaptation methods, transformation methods, hybrid methods, and ensemble techniques. In the current research work, we first analyzed the learning behavior of state-of-the-art ensemble and non-ensemble classifiers on imbalanced and overlapping multi-class data. After analysis, we used grid search techniques to optimize key parameters (by hyper-tuning) of ensemble and non-ensemble classifiers to determine the optimal set of parameters to enhance the learning from a multi-class imbalanced classification problem, performed on 15 public datasets. After hyper-tuning, 20% of the dataset samples are synthetically generated to add to the majority class of each respective dataset to make it more overlapped (complex structure). After the synthetic sample’s addition, the hyper-tuned ensemble and non-ensemble classifiers are tested over that complex structure. This paper also includes a brief description of tuned parameters and their effects on imbalanced data, followed by a detailed comparison of ensemble and non-ensemble classifiers with the default and tuned parameters for both original and synthetically overlapped datasets. We believe that the underlying paper is the first kind of effort in this domain, which will furnish various research aspects to with a greater focus on the parameters of the classifier in the field of learning from imbalanced data problems using machine-learning algorithms.
ICT in Malaysian education

In the field of education, the use of information and communications technology (ICT) has enabled teaching and learning to be supported, enhanced, and optimized in the delivery of curriculum across many nations where this was not possible before the mid-20th century. Research and development of newer technologies have also spurred toward improved student learning due to the enhanced teaching methods that teachers could use in and out of their classrooms. Since the onset of the COVID-19 pandemic, ICT is the necessity for online teaching and learning with school closures disrupting structured classroom learning for about 4.9 million students in preschools, primary schools, and secondary schools throughout Malaysia. The disruptions of teaching and learning in physical classrooms, nevertheless, have compelled teachers to become more dependent on ICT to deliver their lessons online. This chapter introduces the development of ICT in Malaysia and describes the Malaysian Ministry of Education’s efforts to equip teachers with technological, pedagogical, and content knowledge. The subsequent sections would highlight the contextual challenges and strategies to better prepare teachers to achieve the five aspirations in the Malaysia Education Blueprint.