Reviewerly/exHarmony huggingface dataset:
Formation of personality of children with mental retardation and readiness of future defectologists for practical work

The conceptual foundations of general pedagogical and methodological training of defectologists for the formation of the personality of children time-lagged psychical development (TLPD) include: the need to educate teachers to treat themselves as a subject of the educational process by means of integrating professional disciplines, filling the students with humanistic meanings of educational practice and engaging them in research activities. The criteria, indicators, types, and psychological and pedagogical conditions for optimizing the didactic process for the formation of the defectologist are determined. Personal and professional competence are considered as components of this readiness.
Comparative Analysis of Different Wavelet Families, Applied for Steganography on Two Cover Images

Transform domain image steganography involves embedding secret image in cover image, before that, any of the transforms is applied to convert it from spatial domain to frequency domain. The transform domain technique applied in the proposed work is the combined technique of DWT and DCT, which ensures advantages of both techniques like robustness and higher imperceptibility. Moreover, encrypted secret image is embedded in two frequency domain transformed cover images, this enhances the security. In this paper, the comparative analysis of application of different discrete wavelet families like Coiflet, Daubechies, Biorthogonal, Reverse biorthogonal and Discrete meyer, for steganography on two cover images girl and Lenna is presented. The simulation results illustrate the comparative values of MSE and PSNR, on application of different DWT techniques with DCT one by one, on two cover images.
DGA Domain Name Detection Based on SVM Under Grey Wolf optimization Algorithm

At present, malwares are used by attackers to generate many malicious domain names and implant malicious instructions in malicious domain names. These bring huge losses to users that visit. This paper proposes a DGA domain name detection model based on SVM under GWO. It uses GWO to optimize the parameters of SVM and improve the search speed of optimal parameters. Through the training and testing for the domain name data set composed of the DGA domain names and the legal domain names, and the comparison of the traditional SVM algorithm classification, the results showed that the accuracy of the GWO optimized SVM classification algorithm reaches 97.49%, increased by 3.46%. With faster calculation speed and higher accuracy, the performance of the algorithm is significantly improved.
Research Guides: Remote Learning Library Resources: Contact Us

This guide provides information about Kenyon's library services while our campus is learning remotely.
THE APPLICATION OF SOCIAL ACCOUNTING IN JORDANIAN HOTELS, THE ROLE IN ACCOUNTING DISCLOSURE AND ITS IMPACT ON THE QUALITY OF THE FINANCIAL STATEMENTS

Aim/Purpose: This paper aims to investigate the application of social accounting in Jordanian hotels, the role in accounting disclosure and its impact on the quality of the financial statements. The primary objective of the study is to determine the extent of applied social responsibility accounting on the accounting disclosure, and the role of applied social responsibility accounting on the quality of financial statements. Background: The research focuses on the effect of applied social responsibility on the accounting disclosure in financial statements, through Intermediate variable (accounting disclosure). Materials and Method s : This study adopted the qualitative method and based on the theoretical framework and previous studies. This paper examines the extent of applied social responsibility accounting on the accounting disclosure, and the role of applied social responsibility accounting on the quality of financial statements. Results : The findings showed that Jordanian hotels provide good care for their employees in most areas. This is what distinguishes the hotel sector from other sectors. Conclusion: The social performance of hotel workers shows that Jordanian hotels provide good care for their employees in most areas. This is what distinguishes the hotel sector from other sectors.the role of Jordanian hotels in the scope of  social services appear substandard performance, hotels Does not do its duty as required in terms of providing financial and moral support to charities  in the area in which it operates, or the construction of health and educational centers, Most of this support goes to conferences and seminars that highlight the role of these hotels in the field of environmental protection or only  is to allow university and school students to training and conduct field visits to hotel facilities.
Creative sustainability initiative for Jakarta’s urban spaces

Abstract This paper will discuss the creative initiative made by designer, architect, and contractor under the JKT Play movement and community towards the urban spaces in Jakarta. Their initiative is intended to encourage creative activities, and playful experience for the citizens, and as an alternative material to support sustainable architecture concept. The discussion will be based on the project’s collaboration by designer, contractor, multinational company, food and beverages industry to create playful objects which can be used and explored by the communities. The initiative is based on the concern of the consumer waste, especially plastic cup, paper, and plastic bottle. The project has opened opportunities for creative industries, and designers to rethink and to approach the design methods and design exploration towards plastic wastes. It also can be a tool as an urban fabric or installation that can help creating colourful atmosphere for the city of Jakarta.
Education and Employment Opportunities in Computer Technology

Two decades before there are number of educational institutes in all the trades like Agriculture, Mechanical, Electrical and Electronics and so on. But today in the Modern digital world though there are many subjects available in the market, the trend is a man cannot live without the technology, such as mobile, computer and internet, because communication from all parts of the world updating to each and every one. India is the second largest population in the world, having high infrastructure to educate and improve the young students to develop their career Government provides number of educational institutes under the Ministry of Human Resources and Development. But today the only avenue where you get lot of information and various opportunities in short period of time with the minimum cost from their regional language about the technology and to know about it, explore the technology and earn money in different arenas.
Planejamento de caminho de robôs futebolistas utilizando busca em grafo.

Mobile robotics has proven to be a promising area, with notable progress in research in recent decades. This innovation in the area is leading to the creation of robots that surpass the fundamental characteristics of a robot such as locomotion and environmental perception, advancing towards increasingly intelligent robots that have the autonomy to perform tasks without human intervention. One of the steps that need to be taken to make this happen is path planning, where given a start position and an end position, the path between these points is calculated. To do so, the robot needs to know information about its environment. Thus, this work proposes a study of path planning using graph search algorithms for a previously known environment map containing static obstacles. The results obtained are satisfactory, being possible the best obstacle-free path for the robot in the environment, with a low execution time of the search algorithm.
Towards Naturally Responsive Spoken Dialog Systems by Modelling Pragmatic-Prosody Correlations of Discourse Markers

Human speakers in a dialog adapt their responses and the way they convey them to their interlocutors by appropriately tuning their prosody, taking into account the context in which the dialog takes place. Today's spoken dialog systems are incapable of exhibiting such natural responsive behavior. Hence, there is a need for models that enable the selection of better prosody in system responses to make them appropriate to the pragmatic intentions and the dialog context. This submission includes the detailed description of my preliminary study on the prosody of discourse markers, the methods used and my initial findings that corroborate the existence of correlations between prosody and pragmatic intentions of discourse markers in human-human dialogs. These correlations, if modeled accurately, can help dialog systems respond with context-appropriate prosody.
Pengembangan Perangkat Pembelajaran Kosakata Bahasa Inggris Berbasis Role Playing Pada Siswa SMP di Kota Makassar

Abstract . The problem statement of this research is how to develop instructional tools of teaching model and material design of Basic English vocabulary based on Role Plying for Junior High School in Makassar. This research is an extensive process to investigate students’ needs and then develop a product which is specifically design to fulfill them . This research is development research at aimed at developing instructional model and material design of basic English vocabulary based on Role Plying for SMP students in Makassar. The development of instructional design followed model of research design and development by Borg & Gall (1983). This research is an extensive process to investigate students’ needs. Subject of this research are experts of English and learning material, teacher of English and students of SMPN 2 Makassar. The result of the research showed that the development of instructional material design of basic English vocabulary for SMP students were composed well and  can be used in teaching and learning process in the class room Keywords : develop instructional tools , teaching model and material design, Basic English vocabulary , Role Plying
Automatic brain structure-guided registration of pre and intra-operative 3D ultrasound for neurosurgery

Image guidance aids neurosurgeons in making critical clinical decisions of safe maximal resection of diseased tissue. The brain however undergoes significant non-linear structural deformation on account of dura opening and tumor resection. Deformable registration of pre-operative ultrasound to intra-operative ultrasound may be used in mapping of pre-operative planning MRI to intraoperative ultrasound. Such mapping may aid in determining tumor resection margins during surgery. In this work, brain structures visible in pre- and intra-operative 3D ultrasound were used for automatic deformable registration. A Gaussian mixture model was used to automatically segment structures of interest in pre- and intra-operative ultrasound and patch-based normalized cross-correlation was used to establish correspondences between segmented structures. An affine registration based on correspondences was followed by B-spline based deformable registration to register pre- and intra-operative ultrasound. Manually labelled landmarks in pre- and intra-operative ultrasound were used to quantify the mean target registration error. We achieve a mean target registration error of 1.43&plusmn;0.8 mm when validated with 17 pre- and intra-operative ultrasound image volumes of a public dataset.
A Systematic Review on the Various Approaches used for Achieving Energy Consumption in Cloud

Cloud computing is an infrastructure for performing the organization and web application is cost effective way. The implementation of cloud computing has gained attention of computing as an advantage and enhances applications from consumer, business and scientific domains. Though, this operation faces huge energy consumption, carbon dioxide emission and related cost concerns. With energy consumption becoming the major problem for the maintenance and operation of cloud data centres, the cloud computing providers are becoming profoundly concerned. Greater consumption of energy not only translates to greater cost of operation but also badly influences the surroundings. The cloud design is such that it must be power efficient. Data centres are becoming essential infrastructure for assisting the provided services by cloud computing. They consume huge amount of energy reporting for 3 percent of electrical energy consumption globally. The impact of this is that the providers of cloud faces greater costs of operation which leads to data centre’s infrastructure increased usage. The main aim of this study is to develop the utilization of computing resources and reduce the consumption of energy under independent quality of service constraints of workload. This study presents the survey of various techniques used for consumption of energy in cloud computing.
No-reference quality metric for high dynamic range imaging system based on curvature analysis in tensor domain

High dynamic range imaging systems can offer a more complete representation of scene, aiming to capture all brightness information of a visible range of scene, even in extreme lighting conditions.This paper proposes a no-reference quality metric for high dynamic range image (HDRI), in which a combination of tensor decomposition and curvature analysis is used to construct an efficient feature set that is sensitive to degradation levels of patches in HDRIs.Tensor decomposition maintains the majority of color information of an HDRI, and the geometric structure information of the HDRI is then extracted by a curvature analysis.A quality-related label feature matrix is subsequently defined and obtained by using a feature set and a sparse dictionary with quality-related labels.Then, the multi-dimensional local feature set of the HDRI is determined from the quality-related label feature matrix.Finally, the local feature set and other global feature set are pooled to predict the quality of the HDRI.The prediction performance of the proposed metric is verified by three public test databases, and the experimental results indicate that both its Pearson linear correlation coefficient and Spearman rank-order correlation coefficient are better than those of other no-reference metrics.The proposed metric produces statistically better assessment results, implying a higher consistency with human visual perception.
How to Build a Stablecoin: Certainty, Finality, and Stability Through Commercial Law Principles

New market practices and business models are emerging around so-called stablecoins, a type of crypto asset with certain features that seek to stabilize the price of the coin. Stablecoins have the potential to offer a borderless and more accessible way to pay, addressing many shortcomings in existing payment systems around the world. Yet, these developments also raise fundamental legal issues. What questions should lawyers and financial advisors be asking to ensure risks are adequately addressed? What answers can stablecoin innovators give to financial authorities and industry stakeholders to provide comfort that there is a sound legal basis for the business models and market practices around their coin? U.S. commercial law, which is chiefly designed to support financial market activities, contains powerful principles that can usefully serve as building blocks for a foundational legal framework to uniquely advance a stablecoin’s economic purpose as a medium of exchange — allowing technologists to move fast, but safely. This Article spells out how to build such a legal basis by leveraging the core commercial law principles of (i) focusing on the principles of settlement finality, (ii) rules for adverse claims, (iii) discharge of the underlying obligation, and (iv) the concept of a security entitlement. It maps out how these principles are embodied under the U.S. commercial laws of investment securities (UCC Article 8) and of payments (UCC Articles 3, 4, and 4A). The goal in doing so is to show how innovators can incorporate novel, technology-driven market practices and business models into the existing financial law framework in a proven and effective way — how to leverage what is working today and does not need to be invented again. Awareness of the availability of these commercial law tools, and their limitations, can provide important help to stablecoin developers and market participants in managing their exposure, designing efficient financial innovations, and controlling the risk to the broader financial market.
AN ANALYSIS OF MAXIM VIOLATIONS IN A MOVIE AND THEIR IMPACTS ON EFFECTIVE COMMUNICATION

This research analyzes the occurrences of maxim violations produced by the characters in the movie Confessions of a Shopaholic and their impacts on the effectiveness of communication. The objects are the maxim violations found in the utterances of the characters, the reasons behind those violations, and their impacts on effective communication. Those data were taken from a movie Confessions of a Shopaholic which was released in 2009. This is a qualitative research using content analysis as the method. Data were analyzed using the framework of Cooperative Principle and the Effective Communication theory. The research findings show that there are 40 utterances containing maxim violations which produces by all characters: 19 times violated maxim manner (47.5%), 9 times violated maxim quantity (22.5%), 9 times violated maxim quality (22.5%), and 3 times violated maxim relation (7.5%). The characters violated the maxims with different reasons and contexts. Moreover, maxim violation that affect the effectiveness of communication the most is violation of maxim relation, followed by violation of maxim quantity, manner, and quality. It is implied that maxim violation holds an important role in maintaining the effectiveness of communication. It seems that the less of maxim violations occur, the more effective communication is ensued.
Image processing algorithms for synthetic image resolution improvement

The aim of this thesis is to develop a Machine Learning algorithm for Multi-image Super-resolution (MISR). Super-resolution is a well known image processing problem, whose aim is to process low resolution (LR) images in order to obtain their high resolution (HR) version. The super-resolution process tries to infer the possible values of missing pixels in order to generate high frequency information as coherently as possible with the original images. In general, we can distinguish between two different super-resolution approaches: Single-image Super-resolution (SISR) and Multi-image Super Resolution (MISR). The former tries to build the best LR-HR mapping analysing the features of a single LR image, while the latter takes as input multiple LR images exploiting the information derived from the small differences between the images such as changes in the point of view position and orientation, in the lightening condition and in the image exposition and contrast. The thesis had as first objective to take part to the competition called “PROBA-V Super Resolution”, organized by the Advanced Concept Team of the European Space Agency. The goal of the challenge was to obtain High-resolution images from low resolution ones from a dataset of pictures took from the PROBA-V satellite of the ESA. The work has been developed under the direction of the PIC4SeR (PoliTO Interdepartmental Centre for Service Robotics), which aims to integrate it into its agricultural related projects, for the satellite monitoring of the fields status. The analysis of the state of the art for what concerns super-resolution reveals that Machine Learning approaches outperform the classical algorithms proposed for this problem. In particular, Neural Networks have been widely used in literature for Single-image Super-resolution, while this approach for Multi-image Super-resolution is relatively new. An original model to deal with competition problem has been studied, trained and tested. The obtained results show that the multi-image approach can help in the improvement of existing algorithms for super-resolution. However, several issues can be further addressed to increase the model efficiency and performance, making this particular topic interesting for future work development.
Automatic accuracy management of quantum programs via (near-)symbolic resource estimation.

When compiling programs for fault-tolerant quantum computers, approximation errors must be taken into account. We propose a methodology that tracks such errors automatically and solves the optimization problem of finding accuracy parameters that guarantee a specified overall accuracy while aiming to minimize a custom implementation cost. The core idea is to extract constraint and cost functions directly from the high-level description of the quantum program. Then, our custom compiler passes optimize these functions, turning them into (near-)symbolic expressions for (1) the total error and (2) the implementation cost (e.g., total gate count). All unspecified parameters of the quantum program will show up as variables in these expressions, including accuracy parameters. After solving the corresponding optimization problem, a circuit can be instantiated from the found solution. We develop two prototype implementations, one in C++ based on Clang/LLVM, and another using the Q# compiler infrastructure. We benchmark our prototypes on typical quantum computing programs, including the quantum Fourier transform, quantum phase estimation, and Shor's algorithm.