Reviewerly/exHarmony huggingface dataset:
PENERAPAN ALGORITMA EXPECTATION-MAXIMIZATION (EM) DALAM MENGELOMPOKKAN POPULARITAS OBJEK WISATA DI MALANG RAYA BERDASARKAN INDIKATOR BANYAK PENGUNJUNG

The Malang Raya Area is one of the tourist destinations in East Java..Batu City is an area of Malang Raya which is visited by many for sightseeing. Given the development of tourism in Malang Raya, it is necessary to classify the popularity of tourist objects so that they can be used as a reference in policymaking by the tourism office and tourism object managers. In this study, the Expectation Maximation (EM) algorithm is used to determine the clustering of tourist objects in Malang Raya using data on the number of visitors. The results of grouping the popularity of leading tourist attractions in Malang Raya based on the number of visitors are divided into 5 groups, namely: Group 1: Selecta; Group 2: Balekambang, Wendit Baths, and Brawijaya Souvenir Tour; Group 3: Transport Museum, Coban Rondo, Animal Museum, Jatim Park, BNS, Picking Apples “Makmur Abadi and Agro Wonosari Tea Plantation; Group 4: Kusuma Agro Wisata, Kampoeng Kidz, Cangar Hot Springs, Eco Green Park, Predator Fun Park, Coban Rais Tourism Area, Mount Banyak, Mahajaya T-Shirt & Souvenirs, Ngliyep and Selorejo Dam; Group 5: “Dammadhipa Arama” Temple, “Kaliwatu” Rafting, Batu Rafting, Coban Talun Tourism Wana, Tirta Nirwana Baths, Songgoriti Natural Hot Springs, Wonderland Waterpark, Friends of Water Rafting, Independent Apple Picking, Apple Agro Stone, Tourism Village.
Demo: Secure Marketplace for Access to Ubiquitous Goods

Smart contracts in decentralized blockchains can be used to implement neutral exchanges of goods, i.e. decentralized marketplaces. The marketplace actors can audit and trust the correctness and neutrality of the smart contract to act as a neutral third party. While many such marketplaces have been demonstrated, they are constrained to operate in a single blockchain. We present a decentralized marketplace spread over two blockchains, allowing separation of concerns between different blockchains and simultaneously increasing overall performance. The presented marketplace shows how smart lockers are rented on the platform, and how access tokens to the rented lockers are communicated securely in a manner that facilitates off-grid physical access.
Cloud Based Point of Sale System with Face Recognition

A Point of Sale (POS) is an electronic banking outlet that enables customers to complete the basic financial transactions using debit or credit cards without the aid of bank representative or teller. It is an electronic banking outlet that enables customers to complete the basic financial transactions using debit or credit cards without the aid of bank representative or teller. The Traditional POS system runs on closed networks and the user data is stored on local servers. They need to be updated manually on-site. POS systems generally accept credit and debit cards to process bills. It is found that there is increase in levels of fraud among the users of credit and debit card. So there is a requirement to build a system that can store the data securely and also do the transactions without giving scope to any fraudulent activities. For the effective and efficient operations of security systems, accurate and automatic recognition of persons is becoming increasingly important. As a solution our proposed system ‘Cloud Based POS System with Face Recognition and Password with Cloud implementation’ is proposed as a method of payment making POS systems both card less and cashless. FaceNet which was proposed by Google Researchers was used for implementing face verification and recognition, along with password verification as a two-step authentication. We use FaceNet and Multi-Task Cascaded Convolutional Neural Network, for detection and identification of faces. This POS system will do more, than just accepting payments. Here we also try to Integrate Cloud Computing (CC) with the system which makes it more secure. The combination of POS system with Cloud Computing will make our new system more reliable and faster. It is studied that this technique is not very expensive and it gives us an accuracy rate of about 96.75%
El pensamiento crítico y creativo en segundo grado mediante el uso de organizadores gráficos

Critical and creative thinking is a topic that has now had a great boom in education, because we are in a time where the development of skills not only serves for school but for life. In this case, critical and creative thinking is a fundamental part of the development of learning, as the demands of the new educational models are increasing, and it is the teacher’s job to fulfill their work in such a way that the students learn significantly. The present action research shows how critical and creative thinking is favored in second grade children by using graphic organizers; Apart from the design, application and analysis of various graphic organizers, one can observe how critical and creative thinking was favored. The study offers teachers the possibility to see new perspectives of educational work, as well as how to provide new learning where the mainstreaming and the choice of various teaching techniques allow to promote and build meaningful learning.
Microseismicity in the Eastern Alps: Preliminary Results From the Swath-D Network

&amp;lt;p&amp;gt;The AlpArray seismological experiment is an international and interdisciplinary project to advance our understanding of geophysical processes in the greater Alpine region. The heart of the project consists of a large seismological array that covers the mountain range and its surrounding areas. To understand how the Alps and their neighbouring mountain belts evolved through time, we can only study its current structure and processes. The Eastern Alps are of prime interest since they currently demonstrate the highest crustal deformation rates. A key question is how these surface processes are linked to deeper structures. The Swath-D network is an array of temporary seismological stations complementary to the AlpArray network located in the Eastern Alps. This creates a unique opportunity to investigate high resolution seismicity on a local scale.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;In this study, a combination of waveform-based detection methods was used to find small earthquakes in the large data volume of the Swath-D network. Methods were developed to locate the seismic events using semi-automatic picks, and estimate event magnitudes. We present an overview of the methods and workflow, as well as a preliminary overview of the seismicity in the Eastern Alps.&amp;lt;/p&amp;gt;
ПРОГРАММИРОВАНИЕ МЕТОДА ЗАЩИТЫ ИНФОРМАЦИИ

In this article an encryption is examined by transposition with the use of enciphering table the being a matrix dimension of nm. For generating encryption, the compiled tabs are followed by tabulators in the table. If the text is blocked by the text, you will receive the encrypted message. The process of decrypting is executed in the reverse order. Most effective from the considered keys over is using of dimension of table.
Cloud Computing in IT and How It’s Going to Help United States Specifically

Cloud computing is amongst the leading and most promising set of IT services in the current era. There is no doubt that it has taken the computer society by a storm in recent years. What is so apparent with this system is the tremendous efforts made to ensure the computing resources come as a service. Cloud computing as a platform has an enormous potential of doing away with some previous expensive requirements for setting up computing infrastructure. This is a good move as it offers IT-based solutions that are optimal for use and other crucial services essential in the operations of the IT industry. Furthermore, Cloud computing shows promising signs of achieving a flexible IT infrastructure that can enable individuals with small portable devices to access it through the internet. The efficiency coupled with potential gains from the use of Cloud Computing resources (large bandwidth, ample storage space, and processing power) is attracting massive investment in various industries such as banking, education, and healthcare worldwide. This research paper will explore Cloud computing in IT and how it’s going to help America specifically.
Map Merging for an Autonomous Multi-robotic System

Map-merging technique is a well-studied and challenging domain in the field of autonomous mobile robotics. It is not always possible to create a map only using a single robot. Thus, the most common practice is to collect maps of individual robots of the region it has been able to reveal, also known as sub-maps and merge all of them to create a single map. In this paper, we propose an algorithm for merging sub-maps acquired from different autonomous mobile robots. We also show that the merging of the maps is dependent on the degrees of freedom of the robots.
Robot Design Needs Users: A Co-design Approach to HRI

The rapid technological growth that we are facing has highlighted issues about human-computer interaction, specifically with reference to the scope of robotics; this kind of dynamics open up new challenges for UX designers. We refer specifically to the category of social robots, which is a growing sector in the market of humanoid robots. Social robots must provide a good level of interaction with human beings, who interlace complex and deep relationship with them; they are able to learn from the environment in which they are located as from the interactions with users and to develop some sort of decision-making autonomy. Designing a social humanoid robot is not just the development of a consumer product as a household appliance and is not just the engineering of a body to a vocal assistance, but it also requires taking into account the psychological impact of the robot and evaluating social dynamics. Therefore, it is fundamental to place the individual at the center of the design process in order to study an acceptable user experience. Co-design methodologies are now considered an essential practice, especially in technological projects, due to the fact that a high-tech product, system or service is most likely capable to actively interact with users for which is intended. Designing an interactive and funny co-design experience is fundamental in order to positively engage users and get valuable data and insight about their perspective on the project that is being developed. Reflecting on the main themes and issues that must be taken into consideration in the design of a social robot based on UCD principles, the paper aims to propose new challenges and approaches for co-design activities for the robotic project, taking advantage of digital platforms and innovative IT solutions.
การป้องกันพื้นที่น้ำท่วมในลุ่มน้ำลำพระเพลิงด้วยแบบจำลอง Hec Ras

The Lam Phra Phloeng reservoir is a big reservoir in the Lam Phra Phloeng river basin.  If there are big storms in the upper area of reservoir, there is a water drainage to the downstream of reservoir.  Then, there is a flooding in Pak Thongchai district as a heavy flooding in 2010 and 2019.  The objective of this study are (1) to evaluate the flooding areas in the return period 2, 5, 10, 25, 50, 100 and 500 yrs., and (2) to analyze the guidelines for preventing and reducing flood damage in the Lam Phra Phloeng river basin by using Hec Ras modelling.  The Hec Ras modelling can simulate both 1D and 2D flow conditions.  The results can be concluded that the flooding area in the return period 2, 5, 10, 25, 50, 100 and 500 yrs. are 4.62, 25.53, 37.28, 48.42, 55.63, 61.83, and 73.74 km2, respectively.  To protect and reduce a flooding, many projects has to be concerned that consists of (1) building a water barrier flap, (2) increasing the potential for water transmission and drainage, (3) study and design of the installation of flood alarm systems along the Lam Phra Phloeng river, (4) study, design and installation of runoff stations, (5) study and design of river network system and (6) database system for flood and drought prevention.
Rancang Bangun Game Edukasi Mengenal Resep Kue Khas Masyarakat Lampung Berbasis Android

AbstractTypical cakes or traditional cakes are snacks that have special characteristics and come from a certain area whose recipes are passed down from generation to generation in people's lives, such as getuk, dodol, wajik and many more, each of which has a special taste and characteristic and originates from different places. different. Currently, typical cakes or traditional cakes are less desirable and are also increasingly being forgotten. This is due to the limitations of parents who are willing to spend their time teaching traditional cake making recipes, in addition to the long process and recipes for which only some people know. Based on this, the combination of educational games and recipe books for the Lampung people is the main focus of this research. The introduction of typical cake recipes with a fun concept that makes it easy for users to learn which is packaged in the form of an Android-based educational game. Educational game application contains 10 cake recipes, jigsaw puzzle games and answers from games. The educational game proposed by the researcher is in the form of a technology introduction model that is packaged in the form of a game that not only focuses on stage by stage but also on the introduction of recipes and cake material in the introduced game.
Advancing the FAIRness and Openness of Earth system science in Europe

&amp;lt;p&amp;gt;Focused environmental research projects and continuously operating research infrastructures (RIs) designed for monitoring all subdomains of the Earth system contribute to global observing systems and serve as crucial information sources for environmental scientists in their quest for understanding and interpreting the complex Earth System and contribute to global observing systems. The EU funded ENVRI-FAIR project [1] builds on the Environmental Research Infrastructure (ENVRI) community that includes principal European producers and providers of environmental research data and services.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;ENVRI-FAIR targets the development and implementation of both technical frameworks and policy solutions that make subdomain boundaries irrelevant for environmental scientists and prepare Earth system science for the new Open Science paradigm. Cross-discipline harmonization and standardization activities, together with the implementation of joint data management and access structures at the RI level, facilitate the strategic coordination of observation systems required for truly interdisciplinary science. ENVRI-FAIR will ultimately create the open access ENVRI-Hub delivering environmental data and services provided by the contributing environmental RIs.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The architecture and functionalities of the ENVRI-Hub are driven by the applications, use cases and user needs, and will be based on three main pillars: (1) the ENVRI Knowledge Base as the human interface to the ENVRI ecosystem; (2) the ENVRI Catalogue as the machine-actionable interface to the ENVRI ecosystem; and (3) subdomain and cross-domain use cases as demonstrators for the capabilities of service provision among ENVRIs and across Science Clusters. The architecture is designed in anticipation of interoperation with the European Open Science Cloud (EOSC) and is intended to act as a key platform for users and developers planning to include ENVRI services in their workflows.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The ENVRI community objectives of sharing FAIRness experience, technologies and training as well as research products and services will be realized by means of the ENVRI-Hub. The architecture, design features, technology developments and associated policies will highlight this example of how ENVRI-FAIR is promoting FAIRness, openness and multidisciplinarity of an entire scientific area by joint developments and implementation efforts.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Acknowledgment: ENVRI-FAIR has received funding from the European Union&amp;amp;#8217;s Horizon 2020 research and innovation programme under grant agreement No 824068.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;[1] Petzold, A., Asmi, A., Vermeulen, A., Pappalardo, G., Bailo, D., Schaap, D., Glaves, H. M., Bundke, U., and Zhao, Z.: ENVRI-FAIR - Interoperable environmental FAIR data and services for society, innovation and research, 15th IEEE International Conference on eScience 2019, 1-4, doi: http://doi.org/10.1109/eScience.2019.00038, 2019.&amp;lt;/p&amp;gt;
Improved Vehicle Detection and Tracking Using YOLO and CSRT

Vehicle detection and tracking plays an important role in Intelligent Transportation Systems (ITS). This paper reports an improved vehicle detection and tracking performance of combined You Only Look Once (YOLO) and Discriminative Correlation Filter (with Channel and Spatial Reliability) (CSRT). CSRT is mainly used for face prediction and moving object detection. The proposed system uses CSRT for vehicle tracking, particularly for cars, buses, and trucks. To perform the vehicle detection task, we have used the YOLO v3 pre-trained model. The accuracy and effectiveness of our vehicle detection and tracking system are tested with 8 different commonly available trackers in various publicly available traffic videos. Experimental results show that the CSRT gives the best performance among all the other trackers. CSRT gives 100% accuracy in all the four publicly available traffic videos even though vehicles with poor lighting conditions.
AN EXPLORATORY STUDY TOWARDS APPLYING AND DEMYSTIFYING DEEP LEARNING CLASSIFICATION ON BEHAVIORAL BIG DATA

The superior performance of deep learning (DL) in natural language processing and machine vision and has ignited renewed interest in applying these technologies more broadly in research and practice. This study looks at how deep learning approaches can be used in the classification of large volumes of sparse behavioral data, which in the age of big data is becoming increasingly common. The excellent performance of deep learning algorithms in tasks such as classification and natural language processing has attracted the interest of both academics and professionals of these algorithms [1]. Since then, many researchers have tried, in the expectation of achieving comparable superior outcomes, to extend these algorithms to other machine learning situations with various data types. The above-mentioned study is based on inspiration and correlates the predictive performance of deep learning classification techniques with several behavioral examples. In addition to the usage of new data categories and a thorough comparison of its outputs with widespread classifications, this study seeks to highlight where and why the approaches to deep learning perform best. It demonstrates that an uncontrolled pre-training process does not improve classification efficiency and that tanh nonlinearity delivers the best predictive results by utilizing profound knowledge about this specific data sort. Deep learning achieves results that are equal or equivalent to traditional low classifiers as it is applied to massive behavioral data sets [1]. However, the findings have not changed much. Looking at how well deep learning performs; it finds that data sets with low signal-to-noise separation had the worse effects. We examine the significance of the clustered, hierarchical characteristic of the learning process to learn why deep learning usually works well on this kind of data. In contrast to superficial classifiers, neurons in the distributed model are more complex in certain behavioral functions [1]. Deep learning classification is also referred to as a black-box technique, and this article addresses how to determine whether and when these strategies perform well. Keywords: Deep learning, Behavioral big data, Neural Convolutional Networks, Feed-Forward Neural Networks
DESIGN OF EMPLOYEE PERFORMANCE APPRAISAL USING THE GRAPHIC RATING SCALE METHOD IN LEARNING RESOURCES AND LIBRARIES AT PGRI ADI BUANA UNIVERSITY

In the world of work, employee performance appraisal has an important role. This is related to decisions to be taken by the leadership, regarding the performance of their employees. From the preliminary research at the Learning Resources and Libraries of the PGRI Adi Buana University Surabaya, it turns out that it does not have an employee performance appraisal system. After conducting interviews and observations by studying the library operational cycle, this study focused on the design of employee performance appraisals using the Graphic Rating Scale Method by separating several elements of the appraiser to be compared with one another.The purpose of this research is to determine the performance of each employee so that it makes it easier for leaders to provide training, mentoring and supervision in the management of Human Resources (HR) at Learning Resources and Libraries PGRI Adi Buana University Surabaya. This research is a field research, which is a research carried out systematically by raising existing data in the field. The research method used in this research is to use descriptive qualitative research methods.The results showed that the performance appraisal design that will be made has gone through the process of gathering information through interviews and Focus Group Discussion (FGD). The rating scale used in the Graphic Rating Scale Method is the Likert scale with the same 5-point interval scale. There are 8 (eight) statements to be filled in and made using the online google form.
Learning Translation Invariance in CNNs

When seeing a new object, humans can immediately recognize it across different retinal locations: we say that the internal object representation is invariant to translation. It is commonly believed that Convolutional Neural Networks (CNNs) are architecturally invariant to translation thanks to the convolution and/or pooling operations they are endowed with. In fact, several works have found that these networks systematically fail to recognise new objects on untrained locations. In this work we show how, even though CNNs are not 'architecturally invariant' to translation, they can indeed 'learn' to be invariant to translation. We verified that this can be achieved by pretraining on ImageNet, and we found that it is also possible with much simpler datasets in which the items are fully translated across the input canvas. We investigated how this pretraining affected the internal network representations, finding that the invariance was almost always acquired, even though it was some times disrupted by further training due to catastrophic forgetting/interference. These experiments show how pretraining a network on an environment with the right 'latent' characteristics (a more naturalistic environment) can result in the network learning deep perceptual rules which would dramatically improve subsequent generalization.
МНОГОПЕРИОДИЧЕСКИЕ РЕШЕНИЯ СИСТЕМ ВТОРОГО ПОРЯДКА С ОПЕРАТОРОМ ДИФФЕРЕНЦИРОВАНИЯ ПО ВЕКТОРНОМУ ПОЛЮ ЛЯПУНОВА

The problem of the existence and integral representation of a unique multiperiodic solution of a second-order linear inhomogeneous system with constant coefficients and a differentiation operator on the direction of the main diagonal of the space of time variables and of the vector fields in the form of Lyapunov systems with respect to space variables were considered. The multiperiodicity of zeros of this operator and the condition for the absence of a nonzero multiperiodic and real-analytic solution of the homogeneous system corresponding to the given system are established. An integral representation of solutions of an inhomogeneous linear autonomous system that multiperiodic in time variables and realanalytic in space variables is obtained. The existence theorem of a unique multiperiodic in time variables and real-analytic in space variables solutions of the original linear system in terms of the Green's function under sufficiently general conditions is substantiated.