Reviewerly/exHarmony huggingface dataset:
KETERCAPAIAN SEKOLAH BERASRAMA DALAM UPAYA PENINGKATAN MUTU DAN AKSES PENDIDIKAN

One of the main problems in the field of education in Indonesia to date is quality and access. The decline in the results of the UN 2017 and APK to the next level indicates that a more comprehensive and affordable education model is needed. Dormitory education models in the form of boarding schools can implement a comprehensive-holistic education program including religion, academic development, the ability to survive (soft skills and hard skills), the insight of the Unitary Republic of Indonesia (NKRI), and building global insight. Considering the importance of boarding schools, up to now many boarding schools have been established but little research has been conducted on the conditions of their achievement based on the National Education Standards. Based on this, the purpose of this study was to analyze the achievement of boarding schools in an effort to improve access and quality of education seen from the National Education Standards (SNP). This research method uses purposive sampling by taking a sample in the Province of South Sumatra in 2017. The unit of analysis in this study is boarding schools in South Sumatra Province. Based on the achievement of boarding schools in South Sumatra Province, which consists of aspects of policy in the area about the existence of boarding schools, grades values of boarding schools, and collaboration with outside parties indicate that the existence of boarding schools can overcome the problems of access and quality of education in South Sumatra Province. Regarding access, students in remote areas have been provided with SMK Negeri 1 Gelumbang and for special access to athletes who need time and special curriculum, there is a Sriwijaya State Sports Middle School. To overcome the problem of efforts to improve the quality of education, there have been 17 Palembang State Senior High Schools and South Sumatra State High Schools which have educators and education personnel, learning and care curricula as well as very adequate facilities and infrastructure.
CONTRACTUALISTIC MEASUREMENTS OF THE GENDER: POSSIBILITIES AND BORDERS

Purpose. The purpose of the study is critical reconstruction of gender issues within the framework of modern political philosophy and political anthropology, in-depth reflection of the phenomena of justice, identity, human dignity in the aspect of their gender measurements and the search for the answer to the fundamental question for leading gender discourses: is freedom and justice, in fact, possible only together with stresses, a feeling of one’s sense-rooted belonging to one or another community? Theoretical basis. The supplement of the phenomenological and transcendental methodology by the method of contractualism directs the study of the topic specified in the article’s title into a new direction, and reflects its essential measurements and aspects. Understanding gender as an important philosophical and anthropological problem and a complex "social construct" precisely within the framework of the latest critical and self-critical versions of the theory of social contract reveal fruitful perspectives for political philosophy and anthropology. Originality. The study of the phenomena of "recognition" (A. Honneth) of "gender justice" (N. Fraser), "moral sense" (E. Tugendhat) outlines the possibilities and sense of filling the principle of social contract with a specific theoretical and practical content, substantiates the need to expand the philosophical and anthropological interpretation space of gender issues. Conclusions. Significance of the gender community for the sociocultural and existential identity of the individual enables (through organic, life-world belonging to a certain tradition and culture) his/her security and the ability to adequately orient in difficult life situations. However, the main purpose of human life is the ability to self-identity, even after profound changes in the structure of personality that arise in difficult situations of contempt and injustice.
House Hunting

Image-based geo-localization is an emerging field of computer vision that has drawn much attention over the past decade. The problem, however, is not trivial and presents a number of significant difficulties. In this paper we present a novel technique of addressing this problem by combining several Machine Learning techniques and demonstrate its effectiveness in the case of a particularly challenging city. In particular, we train a classifier to isolate buildings from images, then propose a novel EFM-HOG representation to match shape of buildings between images, and finally combine all of this to demonstrate geo-localization and retrieval results on a dataset that we created for this purpose.
Sensor Fusion in Multiscale Inspection Systems

In modern inspection and testing processes of technical objects, there is an increasing demand for flexible, fast and precise inspection systems. Especially with complex parts, the inspection can often not be carried out in one step with only a single sensor or measurement principle. Instead, different inspection steps have to be executed for individual subregions of the object’s surface. The defects to be inspected, as well as the appearance or condition of the surfaces can vary greatly. In order to realize such differing inspection tasks, the use of flexible, multisensor systems consisting of different sensors with individual properties is proposed. This chapter aims to give an insight about the major topics that must be considered, especially in an automated data registration within such multisensor systems. At first, different sensor fusion strategies are presented. In order to fuse data obtained by different sensors or multiple acquisitions or compare the results with the given model, it is necessary to register all sensors, all axes, the object, and its model within one common coordinate system. Solutions to this in the context of scalable and varying optical sensors are then shown in the subsequent section. Afterwards, a combined sensor and view planning system is presented, which is used to automatically select the best sensors, their parameterization, and poses in order to obtain high-quality measurements for verifying a given specification for the subsurface under test. This chapter concludes with an exemplary setup for such an automated and flexible multisensor inspection system.
Privacy Preservation of Semi-structured Data Based on XML

In the information age, people’s various behavioral data are collected in large quantities. The sharing of information makes it convenient for some scientific investigations, but there is a leakage of personal privacy at the same time. The current research on privacy preservation is mostly based on relational tables or social network graphs. This paper focuses on semi-structured data, which is often ignored in privacy preservation. We propose a new privacy guarantee called X-km-anonymity and propose a bottom-up heuristic algorithm that provides protection by satisfying X-km-anonymity. We verified the feasibility of the algorithm through a reliable utility analysis method on the simulation data.
A Stable Video Stitching Technique for Minimally Invasive Surgery

One of the major challenges in Minimally Invasive Surgery (MIS) is the limited field of vision (FOV) of the endoscope. We have designed an MIS Panoramic Endoscope (MISPE) to provide doctors with a broad field of view. However, there was an issue in its stability for video stitching. In this paper, we propose a novel algorithm to improve the MISPE's performance. Experimental results show that our revised MISPE can operate stably and enhance the camera's FOV up to 70%.
How to Turn Yourself into a Virtual Travel Companion in Someone Else’s Car: Drawing Design Approaches from the Philosophy of Mind

Technological advancements in the development of autonomous vehicles have been focusing on the very fundamental issues such as functionality and safety. On the other hand, design researchers have started to explore possible everyday life interactions between people and automated vehicles, as well as probing the acceptance of such a disruptive technology by people and the emergence of trust from humans towards such cars. In this paper, I speculate on the possibility that autonomous driving might enable new human-to-human relationships. Departing from the Co-Drive concept, which envisions a new way of travelling and socializing inside the car by sharing a car trip with a remote virtual companion, I focus on the design challenges into the creation of one’s own virtual avatar who inhabits the car as the remote passenger and I draw possible design approaches into the construction of a (virtual) self-representation from the philosophy of mind.
Aeromagnetic noise reduction and interpretation by Multifractal Singular Value Decomposition

Abstract The aeromagnetic signal often has a minority of noise in it, which may be composed of random noise caused by the aircraft itself, fringe pattern noise caused by the differences between the aircraft airlines, or linear features aligned along the declination direction after reduction to the pole, which are usually hard to distinguish visually but will make useful information submerged In this paper, the aeromagnetic data of a polymetallic deposit-accumulated area in Inner Mongolia Province, northwest China, is taken as an example, from which the aeromagnetic noise is extracted by multifractal singular value decomposition (MSVD), the singular values are automatically fitted into limited number of fractal straight lines according to their inflection points and minimum fitting error, each line represents a certain kind of noise or signal, the noises are chosen and removed in this way. The last two decomposed components are usually a band pass and a low pass filter that can be used for tectonic faults and geological bodies’ interpretation, respectively.
State of the Art: The Basic Principles of Optical 3D Metrology

This chapter introduces a selection of basic principles for the acquisition of three-dimensional surface data of macroscopic objects with scattering surfaces. As depicted in Chap. 2 , most of the applied principles in this regime rely on triangulation. During the following descriptions, special attention is paid to advantages and drawbacks in reference to the desired specs speed, precision, high feature resolution and data density as well as how the correspondence problem, introduced in Sect. 2.1.1 , is solved. Of course, sensors which apply the basic methods in their ‘pure form’ are rarely found in the literature or in the market. Most available sensors exploit a modification of the ‘pure form’. It is clear, that not all of these modifications can be discussed here. However, some single-shot principles will be discussed in more detail.
A Note on Unification, Subsumption and Unification Type

Various forms of subsumption preorders are used in the literature for comparing unifiers and general solutions of a unification problem for generality and for defining the unification type. This note presents some of them and discusses their pros and cons. In particular arguments against the exist-substitution-based subsumption preorder (ess) are discussed. A proposal for a further partition of unification type nullary is made. Also some historical notes are included.
Working with Text

MakeCode has many blocks to offer when it comes to manipulating text strings. In this chapter you will learn how to find the length of a text, joining together any number of pieces of text, comparing two strings, extracting a part from a string, converting a string to a number, and extracting a character from a string at the specified index.
Substantive and Procedural Legislation in the Republic of Croatia to Combat Webcam-Related Child Sexual Abuse

This report contains analysis of substantive and procedural criminal law in Croatia regarding the protection of children from web-cam sexual abuse in the light of the possibility of the use of artificial intelligence in the form of the child avatar in the investigation and prosecution of web-cam sexual offenses concerning children. The report presents existing criminal law framework applicable to the cases of web-cam sexual abuse of children and deals with the question of its adequacy to combat web-cam sexual offences. Also, the report deals with the question of limitations in criminal procedure regarding entrapment as well as the issue of applicability of criminal law to virtual victims.
Formulations in Cluster Analysis

In this chapter we shall present and analyse in a bit more of detail the examples of application of the bi-partial approach in the domain, from which it actually arose, that is—from cluster analysis. We shall start from the “leading example” that was presented in Chap. 3 , Sect. 3.2 . Then, we shall present, in a relatively extensive treatment, the bi-partial version of the well known k-means algorithmK-means algorithm , and a couple of other potentially applicable versions of the bi-partial clustering formulations.
MMCDN

Quality of Experience (QoE) for the internet users has remained a matter of serious concern and a main focus in order to retrieve multimedia content. Video content distribution has greater impact upon QoE, which may be improved by using specialized protocols that are responsible for video transmission over internet. Unlikely, HTTP also allows video distribution, caching and streaming. This paper presents an architecture for multimedia distribution, caching and streaming by using off-the-shelf components for applications such as Video on Demand (VoD) and live streaming services. Moreover, video transmission is done by an adaptive bit rate mechanism over HLS standard. HTTP load balancing and DNS load balancing is also introduced to enhance QoE and to address the issue of single point of failure. The presented architecture has been validated as a testbed in a project "3GPP-IMS compliant E2E Mobile IPTV solution for 4G/LTE Networks".
Identity preserving face synthesis using generative adversarial networks

This paper provides a comparative analysis between two recent image-to-image translation models based on Generative Adversarial Networks. The first one is UNIT which consists of coupled GANs and variational autoencoders (VAEs) with shared-latent space, and the second one is Star-GAN which contains a single GAN model. Given training data from two different domains from dataset CelebA, these two models learn translation task in two directions. For evaluation, we conduct some experiments and provide a quantitative comparison using direct metric GAM (Generative Adversarial Metric) to quantify the ability of generalization and the ability of generating photorealistic photos. In addition, StarGAN and UNIT are tested in generating new head poses with preserving identity, where there is no prior information about their ability to translate faces from a source pose domain to a target pose domain. Furthermore, some modifications on reconstruction loss function are proposed to improve synthesis of new poses with identity preserving. The experimental results show the superiority of cross-model UNIT over multi-model StarGAN on generating age and eye glasses attributes, and the equivalent performance to synthesize other attributes. While with regard to synthesizing new poses, they show the superiority of multi-model StarGAN over cross-model UNIT and better performance on our loss functions.
Improved Time Complexity and Load Balance for DFS in Multiple NameNode

Apache Hadoop is a software framework delivered by the open basis communal. This is supportive in storing and processing of data sets of bulky scale on clusters of commodity hardware. HDFS (Hadoop Distributed File System) is a principal distributed storage used by the Hadoop applications. An HDFS cluster mainly is made up of a NameNode and the DataNode. The NameNode accomplishes the file system metadata and DataNodes procedure to store the actual data. Hadoop is ascendable, fault tolerant, and very simple to increase. NameNode frequently converts bottleneck, particularly when handling huge number of minor files. To maximize proficiency, NameNode stores the complete metadata of HDFS in the core memory. With too several small files, NameNode can be run out of memory. In this paper, we present a solution used by numerous NameNode. Our explanation has topmost returns than existing one: we implement a system for load balancing, NameNode bottleneck problem solution and time requirements are reduced average in read and write.
Developing a Technique for Overcoming the Searching Limitations of Documents

Searching in documents plays a vital role in our daily life. We use different kinds of documents for different purposes. Automatic searching of information in these documents is very important for us as it reduces our valuable time to find out necessary information from documents. Although there are many techniques for searching documents that are available in present days, there are many limitations in these searching techniques. The existing systems are unable to perform group search operation, search with spelling mistakes in input and search with missing words in input query. Considering this fact, in this paper, we propose a technique that can overcome the above limitations while searching in documents. We consider our system for both Bangla and English documents. For reducing the search time, in our system, we store the search information and search results in the database so that if anyone searches for the same information in the same document again, our system can provide the results directly from the database without searching the document again. Our system can also perform search operation in multiple documents at the same time. We have compared our system’s output with manually calculated output and found that our system can produce satisfactory results.
Development of a classifier system for a continuous environment

A learning classifier system is an adaptive system that obtains a set of appropriate action rules that adapts to multi-step problems by training action rules defined in if-then form by trial and error process, in a similar framework as reinforcement learning. Because of that the input signals of the classifier system are encoded into binary values, bit strings are often lengthened when dealing with such a problem that the state of the environment continuously changes. A neural network can treat with real values as input signal, however, it cannot be applied to multi-step problems. This paper proposes a system that responds to problems such that the state of the environment continuously changes by combining a neural network and a classifier system, and actions are selected from multiple options, so that output can be defined as discrete values. In order to verify the effectiveness of the proposed system, this paper conducts several numerical experiments using benchmarks corresponding to muti-step problems defined by continuous values.
Communication Design and Medical Procedures: Inform Citizens to Act in Emergency Situations

Emergency situations are unpredictable and happen very quick. They require citizens to be able to act to help victims until they are stable or until emergency entities arrive. Acting in these situations is crucial to save someone’s life. However, the average citizen does not always know about first aid. Communication for this matter is important as it allows a set of information to be transmitted in a variety of ways, such as verbal, non-verbal or pictographic. Therefore, first aid procedures should be communicated in a simple and objective way, to motivate citizens to act in emergency situations. We present a set of analog and digital media as part of a design project developed as a solution for these circumstances, where we explain basic life support and recovery position. We undertook an evaluation of project outcome, through questionnaires. Perception and effective learning of techniques to deal with emergency situations was improved.
Humanized Design of Interaction Interfaces for Small Screen Devices: Take Intelligent Lock as an Example

This paper summarizes the results of preliminary user tests with 3 intelligent lock interfaces as an example for application of small screens. 12 Volunteers (6 males and 6 females) from 20 to 60 years old (M = 35.00, SD = 10.45) were recruited to complete typical tasks of intelligent lock. The difference of subjective satisfaction scores were compared and analyzed. We concluded that the comprehensibility of terminologies and icons of function buttons presented on the interface, learnability of manipulation programs, and the accessibility and effectiveness of help and documentation all affected the results.
Multilayer Based Improved Priority Scheduling Algorithm in Cloud Environment

Load balancing is one of the big challenges nowadays in cloud computing environment. End users requests distribute the load dynamically across multiple nodes. Load balancing among different virtual machines of different distributed system is very much important to improve efficiency in resource utilization. In this paper a Multi layer based load balancing approach has been proposed where traffic of incoming requests is managed using improved priority scheduling algorithm in multiple level of controlling while balancing the loads of different virtual machines in different clusters or data centers. Expected response time finding of each job to virtual machine and comparing the average response time with the existing algorithms of cloud load balancing has been discussed in this paper. The process of multilayer based approach for balancing load among all the virtual machines starting from dynamic load balancer and managed by Local cluster Scheduler (LCS), is better than existing load balancing algorithms has been shown in this paper.
Pedagogical conditions of a corporate culture development in a health-improving type of educational institution

Features of a health-care establishment corporate culture are described in the article along with the system of complementary pedagogical conditions for the development of corporate culture in such institutions. The article substantiates the necessity of employees' professional community development, advancement of their competence and expansion of the opportunities for self-realization within the process of dealing with professional tasks. The author perceives the involvement of all the employees in the process as well as the increase in the number of initiatives and aspiration for bettering the quality of their work as substantial pedagogical conditions for the formation of a corporate culture.
Rising Star Classification Based on Extreme Learning Machine

Rising stars are junior individuals in social networks who will have high impacts with time accumulation. In this paper, we study the problem of rising star evaluation in geo-social networks. Specifically, given a topic keyword, we aim at evaluating the latent influence of users to find rising star, which refer to expert that may have few activities and little impact currently in the underlying geo-social network, but he or she will become influential experts in the future. Most of the current research studies focus on experts finding rather than rising stars. Rising stars can bring great opportunities. We investigate a novel processing framework based on extreme learning machine (ELM) called FS-ELM to efficiently evaluate future stars. Our experimental studies conducted on real-world datasets demonstrate that our method is efficient in predicting rising star with potential impact.