Reviewerly/exHarmony huggingface dataset:
Improved Eliminate Particle Swarm Optimization on Support Vector Machine for Freshwater Fish Classification

Freshwater fish is a type of fish for consumption to substitute saltwater fish in areas far from the sea. Freshwater fish production is not as much as saltwater fish because the selection of freshwater fish is not suitable in the cultivation process. Therefore, a classification method to determine the type of freshwater fish that is good for aquaculture is proposed, one of the classification methods that can be used is the Support Vector Machine (SVM). SVM is used to process the classification of freshwater fish that have the potential to be cultivated. SVM has weaknesses in the classification process, so SVM requires an optimization method that can overcome it's weaknesses, one optimization method that can be used is Improved Eliminate Particle Swarm Optimization (IEPSO). IEPSO is used to optimize features and parameters in the SVM method. The data used in the research came from the Fish and Livestock Breeding Center of Nganjuk Regency with a percentage of 90% of training data and 10% of test data. The results of the study using SVM-IEPSO using feature selection and parameter optimization obtained 88% accuracy in the classification process to determine the type of freshwater fish. The classification results will be more optimal if there are more types of freshwater fish species used in the training process, because this study only uses data on freshwater fish species that are only found in Livestock Breeding Center of Nganjuk Regency.
Security for Digital Image and Text Message with Steganography and Watermarking Technique

In the normal feeling of the world, the word ‘security’ signifies the condition of being safe and the measures taken to guarantee security. In any case, wellbeing isn't an objective or an outright thing in light of the fact that regardless of utilizing a considerable lot of the security systems accessible there is no 100 percent security. Individuals have been making and utilizing numerous wellbeing strategies since antiquated occasions to secure their lives. Before, just things with physical nearness required insurance and security (physical security); for instance: a house was utilized to get security against the brutality of nature, watches were utilized to secure spots, and weapons were utilized to ensure people, watchtowers, doors, channels, locks, and different types of insurances. This paper present digital watermarking (DW) and steganography based secured technique to secure the text and image. The proposed technique is implemented MATLAB software and calculates MSE and PSNR.
Application of Blockchain Technology in Distributed Generation Marketized Transaction

In open market environment, the number of prosumers is huge, and their self-interest makes them more demanding on fairness, privacy and non-discrimination. Blockchain technology has characteristics of decentralization, transparency, security and credibility. Introducing ideas and technologies of blockchain into distributed generation transactions, makes transactions based on the principle of cryptography, so that the whole transaction will be transparent, safe, non-discriminatory and fully automated, effectively avoiding problems such as low efficiency, high cost and low transparency of centralized transactions. This paper first analyzes the traditional distributed generation transaction architecture and characteristics. Secondly, it proposes a distributed generation transaction architecture based on blockchain technology. Then it describes the specific application mechanism of blockchain technology in intelligent power purchase contract and measurement certification. At last, conclusions of this paper are given.
A complex conjugate gradient training algorithm with Barzilai-Borwein stepsize for complex-valued neural networks

Complex-valued neural networks (CVNNs) have become a hot research topic in neural network community for their powerful ability in dealing with complex-valued signal problems. However, as one of the most popular training methods for CVNNs, complex gradient method still suffers from slow convergence and easily traps into the local minima. To this end, in this paper we combine the conjugate gradient method and the Barzilai-Borwein method, and propose a complex conjugate gradient training method with Barzilai-Borwein stepsize for complex-valued neural networks. The superiority of the proposed method is substantiated with two numerical examples.
An optimal dynamic KC&lt;SUB align="right"&gt;i-slice model for privacy preserving data publishing of multiple sensitive attributes adopting various sensitivity thresholds

Optimal KCi-slice model is an extension of KC-slice, KCi-slice and Novel KCi-slice models for publishing the data with multiple sensitive attributes. The proposed Optimal KCi-slice model imposes the privacy threshold only on high sensitive values instead of applying on all the sensitive values of each sensitive attribute. It imposes the necessary privacy threshold to each sensitive attribute based on their sensitiveness. It automatically leads to a good utility rate and required privacy levels on all high sensitive values of each sensitive attribute. Optimal KCi-slice model finishes the data publishing process in two steps. Firstly, it uses the Enhanced semantic l-diversity algorithm to attach the tuples into the buckets and splits the sensitive attributes into several sensitive tables. The second step decides the correlated quasi attributes and also concatenates the correlated quasi attributes with SIDs (Sensitive bucket identifiers) of sensitive buckets. Proposed Optimal KCi-slice model achieves a high utility rate and required privacy levels compared to all the existing models.
Structural Similarity Measurement with Metaheuristic Algorithm for Content based Image Retrieval

Content based image retrieval (CBIR) model is highly employed for the retrieval of images that is connected to the query image (QI) from massive dataset. The feature set filtered from the existing CBIR models are less effective in case of massive dataset. In this paper, the feature extraction takes place in an efficient way where the features are hold in a feature set. This feature set contains a set of color signatures which contains the features of shape as well as color. In this instant, the feature extraction takes place from the provided QI. Based on this, similarity measurement takes place using genetic algorithm with Iterated local search. In addition, the validation takes place by the use of Structural Similarity (SSIM) measure to analyze the difference between QI and retrieved images. The values are measured and the comparative analysis is made with respect to precision and recall.
Research on data traceability of unified identity construction of physical assets of power grid

It is a management innovation project based on the traditional equipment management and the whole life cycle management of assets. The uniform identity code of the physical assets of the power grid is unique and runs through the whole life cycle of the assets, which can effectively push the digital management process of asset management and is an important embodiment of the ubiquitous power Internet of things. At the same time, it puts forward the correlation and traceability of real asset identity, and simultaneously promotes various business applications based on data connection. The physical assets data can be traced to substation as the main body in the stock of equipment data control, can also be regional unit as the main force, analyze the main 14 and substation and regional affiliations, such equipment based on GIS map data dynamically generated power grid assets close-up view, intuitive display station distribution of the main equipment, the equipment in PMS2.0, accounting, operations, maintenance, production technical and other business data verification and quality tracking.
Sentence Similarity Measurement for Smart Education Based on Thematic Role and Semantic Network Techniques

In smart education, Automated Short Essay Assessment is a subjective assessment that emphasizes on contents. Word Order Technique and Syntactic-Semantic Knowledge Technique have been used in previous researches. However, it cannot differentiate sentence pair that is not similar semantically and only proven to produce excellent result on short sentence. Thematic Role for every significant argument seems able to provide information regarding the relations between the word. The lack of Malay lexical semantics database has caused constraints in solving ambiguity and backward tracking problems. Wordnet Semantics Network calculates semantic similarities of two synsets (token) by taking into account the depth of semantic relations. This study is conducted on Compiler course in Malay. The average of f-measure test accuracy rate is 93.53% using Thematic Role and Semantic Network Techniques compared to 82.36% using Pola Grammar Technique. The findings will contribute in achieving smart education as one of the elements in smart city.
Using the Program for Cooperative Cataloging’s Past and Present to Project a Linked Data Future

Drawing on the PCC’s history with linked data and related work this article identifies and gives context to pressing areas PCC will need to focus on moving forward. These areas include defining plausible data targets, tractable implementation models and data flows, engaging in related tool development, and participating in the broader linked data community.
The Role Of Blockchain As A Security Support For Student Profiles In Technology Education Systems

The sophistication of education technology (edu-tech) from the perspective of the blockchain has not been well implemented, because so far the methods used in education are still centralized and tend to be any student data such as class schedules and student profiles can be falsified. So an edu-tech research was made that applied the blockchain to facilitate learning related to the industrial revolution 4.0 and was able to optimize the delivery of information that is currently still one-way. Although there are a number of benefits that have been felt about edu-tech, digital disruptions remain, many challenges related to information security and privacy. The presence of the blockchain in security work integrated with a smartphone will be able to optimize the existing security system, authentication, and information that has been distributed in relation to student profiles, which can be assured of their originality.
Sensor Fault Mitigation for MAVs under Ground Effect*

Small multirotors are suitable to navigate in complex and confined environments that are otherwise inaccessible to larger drones. In such conditions, airflow interactions between the rotors and nearby surface take place. The most common of these interactions is the ground effect. Besides the increment in thrust efficiency, the ground effect affects the onboard sensors of the vehicle. In this paper, we present a fault diagnosis scheme and a control strategy for a multirotor with sensor faults caused by the ground effect. We assume a hierarchical control structure composed of an external PD controller and an internal PI controller. We consider that sensor faults occur on the inner loop and counteract them in the outer one. The fault diagnosis scheme is designed as a logical process which depends on the weighted residual. The control strategy combines the external controller and a function of the residual. Finally, we evaluate the effectiveness of our controller in simulation.
Automation of Tacit Knowledge Using Machine Learning

This paper presents an approach to capture tacit knowledge effortlessly and efficiently. It is a well-known fact that at a work place, converting tacit knowledge into explicit knowledge is difficult and hence organizations lose critical information and best practices when a skilled employee leaves. Hence, regular capture of implicit data becomes critical. This paper focusses not only on a technique to acquire this tacit knowledge but also how to make it as seamless as possible so that it does not become cumbersome on the employee. This paper discusses about a bot, which captures data from the employee on a regular basis and transforms this data into tacit knowledge using text analytics. The bot also self learns about the employee's role and the work that the employee is currently working on. The bot tunes itself to ask the right set of questions to the employees. This approach is generic and can be customized and extended to fit to one's project need.
Motion Sensing Eyewear for Daily Healthcare Monitoring

We have investigated a motion sensing device attached to the eyeglasses for monitoring the daily activity of the user. By utilizing the fact that angular velocity becomes the same on a single rigid body, angular velocity-related motion parameters such as angular acceleration showed quite similar characteristics for the head-mounted and the eyewear motion-sensing devices. As a result, we obtained the motion parameters related to the sense of balance as well as the eating behavior of the user wearing the proposed eyewear device in daily life.
Improve Crowd Size Estimation by Leveraging Deformable Convolutional Neural Network and Deformable Region of Interest

Either in still image or sequence images (video), counting is a challenging task due to many factors such as: scale variations, crowded scene, lighting, orientation, camera position and pedestrian appearance. Despite the fact that practitioners have applied deep network to deal with crowd counting and its increase gain in momentum, challenges still remain. Therefore, we propose a new model for Crowd Estimation with help of Deformable Convolutional Neural Network (DCN) and Deformable Region of Interest (DRoI) pooling. The proposed model is mainly divided in two blocks: a front-end for feature extraction and a back-end comprised by larger reception fields. In both blocks, we replaced standard pooling with Deformable Region of Interest Pooling. The experiment results show better accuracy performance, cost effectiveness of the network and robustness of our model, for less parameters are employed in the proposed model during training as compared to previous models.
Ensuring Environmental Performance of Pharmaceutical Companies of Thailand: Role of Robotics and AI Awareness and Technical Content Knowledge in Industry 4.0 Era

The contradictions regarding the improvements of environmental performance and the factors that possibly might play a very significant role in that case, led this study to happen. So, the study took robotic and artificial intelligence awareness and technical content knowledge to check their impacts on environmental performance. The study also took industry 4.0 implementation as a mediator to check how well it enhances the impacts of robotic and artificial intelligence awareness and technical content knowledge on environmental performance. By reviewing their past literature, the study devised hypothesis. Then to testify them, researcher collected data from 319 individuals from Pharmaceutical Companies of Thailand. The data was analyzed using SPSS and AMOS, though the past relevant studies did not analyze the relevant problem with such modern techniques. The results showed that the impact of robotic and artificial intelligence awareness and technical content knowledge on environmental performance is significant and positive and also role of industry 4.0 implementation as a mediator is significant. The study is beneficial for environmentally friendly organizations to implement robotic and artificial intelligence and use and technical content knowledge to give positivity to the environment. However, the study chose a small sample and lacks generalizability as well.
DEVELOPMENT OF ASSESSMENT SYSTEM IN SCHOOL EDUCATION

This article discusses the history of assessment as an important component of the content of education. Updates in the content of education in the Republic of Kazakhstan are directly related to changes in the assessment system. Therefore, this problem is one of the urgent problems. The article analyzes the interpretation of the definitions "assessment" and "mark" in various pedagogical and psychological studies of scientists. The advantages and disadvantages of the traditional assessment system are considered while investigating the prerequisites for the introduction of criteria-based assessment. The five-point assessment system introduced in 1944 is characterized by its simplicity, clarity, consistency and versatility. But long-term practice of teachers also revealed its shortcomings. The authors highlight some of the main shortcomings of this system of assessment and give detailed explanations. In conclusion, the recommendations of various researchers on the modernization of the five-point assessment system are given. Conclusions are made about the necessity of transition to the model of criteria-based assessment including the quality of traditional assessment and assessment based on criteria.
Data Leakage Prevention and Detection Techniques Using Internet Protocol Address

A data breach is the intentional or inadvertent exposure of confidential information to unauthorized users. In the digital world, data has become most important thing in enterprise. Data leaks provide serious threat to organizations, financial, and reputation of the company. As the data growing exponentially and data breaches are also increasing, detecting, and preventing data leaks become most one of the security concerns for company. Here we use the IP address to identify the users and hackers and administrator looks for the users IP address and block Hackers IP address so that data leakage is not possible from a third party. Hackers try to acquire information through SQL injection and our paper suggests a way to prevent it. This paper helps to detect and prevent the data breach while sharing the data with the consumer and improve the probability of preventing the unauthorized users while sharing the data.
Digital surveillance and access to encrypted communications in Australia

Australia’s counterterrorism laws have significantly expanded the powers of its law enforcement and intelligence agencies with regard to digital surveillance. In this article, we explain and evaluate Australia’s counterterrorism laws with respect to intercepting telecommunications, other forms of digital surveillance and access to encrypted communications. We focus on the statutory powers held by federal law enforcement agencies and the Australian Security Intelligence Organisation (ASIO), Australia’s domestic security intelligence agency. These powers confirm several important trends. They have further blurred the lines between intelligence and evidence and they have granted law enforcement and ASIO extraordinary powers to modify consumer technologies. They also create significant potential for conflict of laws across national boundaries. Significant strengthening of existing accountability mechanisms is needed to ensure public transparency and reduce opportunities for misuse.
Exploring Perception of EFL Teachers towards Use of Media in Teaching English

This Research is against the backdrop of demand in mastering English. EFL teacher becomes one of the main important parts of teaching-learning English to handle a certain role in maximal the students’ achievement. The students’ achievement here means not only someone that has a lot of knowledge and high value but also someone that can give a positive contribution to other people. Because of that, the teachers have a big responsibility to facilitate students in learning. One of the facilitation of teaching-learning that has to be prepared by teachers is media. This study aims to investigate the teachers’ perceptions of ELT media. This study is classified into three main dimensions of perception proposed by Vernon (1987) namely understanding, outlook and action. By conducting a survey study, the researcher collected, analyzed, elaborated and eventually drew conclusions dealing with the teachers’ perceptions of ELT media. The main data of this study were collected with an interview and a questionnaire, which was distributed to 29 English teachers in the city of Tulungagung. The findings showed that Media is able to be a benefit for both teachers and students, be applicable to every class. To select criteria of Media is based on Media Mastery or flexibility due to different reference and less facility. Besides that, The teachers have positive responses towards the two of the dimensions, understanding, and view. The teachers, however, do not show positive responses toward the action. However, in general, the English teachers’ perceptions of ELT media in this study were categorized as a good perception. In other words, all the teachers have a positive perception of ELT media. &#x0D;
Nearest Centroid Classifier with Outlier Removal for Classification

Classification method is misled by outlier. However, there are few research of classification with outlier removal, especially for Nearest Centroid Classifier Method. The proposed methodology consists of two stages. First, preprocess the data with outlier removal, removes points which are far from the corresponding centroid. Second, classify the outlier removed data. The experiment covers six data sets which have different characteristic. The results indicate that outlier removal as preprocessing method provide better result for improving Nearest Centroid Classifier performance on most data set.
'Man is the Measure of All Things'

The term Man, and the humanist tradition which followed from it, have been challenged in feminist, queer, poststructuralist, and postcolonial critiques, which questioned its nature, or even pondered if we are actually human. What we seek in this issue of Footprint is to add to these perspectives cases of what we call radical conditioning, in which some architectures bypass assumed values of humanism and operate under a wholly different set of values, emanating from industrial and post-industrial economies and its technological developments. These architectures dictate the creation of spaces in which the human body has to operate, and to which it needs to adapt in order to survive. The research articles and visual essays included in this issue shed light on the many ways architects, advertently or inadvertently, coalesce with forces intending to condition humans. Unfolding in the study of histories, architectural types, aesthetics, atmospheres, systems, and users, authors propose inquiries along two main directions: the first trajectory highlights the prolific use in spatial design of concepts borrowed from cybernetics and information technology for the conditioning of human behavior through the built environment; the second deals with architecture conditioning the creation of new subjectivities, placing the body as the territory of intervention. Understanding these spaces, in which humans and their artifacts interact in unprecedented ways, could provide architecture with the timely opportunity to challenge our anticipated redundancy, and reconsider its own humanism in order to charge it with new meanings.