Reviewerly/exHarmony huggingface dataset:
Hardware-bound virtual TPM for cloud computing deep attestation

Nowadays the cloud computing paradigm changed the IT industry, reshaping the the hardware provisioning and the how services and infrastructures are developed. Cloud computing is in fact a method to increase capabilities without the need for investment in infrastructure as well as in software. However, this evolution leads to integrity and security issues. Data integrity is nothing but the guarantee that the data is not accessed or modified by those that are not authorized. It can be achieved on a system through the usage of the Trusted Platform Module, through the collection and generation of integrity measures, it offers tamper resistance. Despite everything, this procedure cannot be supported in a virtual environment since a virtual TPM, vTPM, although it provides the same functionalities of a physical TPM ,pTPM, has the same weaknesses of any software. Since Data Integrity is a crucial point in the cloud computing environment in order to provide reliability to the whole system, this thesis work proposes to investigate a solution for the Deep Attestation based on virtual TPM and its binding to a physical TPM, in order to retain the security strength of hardware-based root of trusts and the capability to correctly evaluate the reliability of a system.
A Subsethod Interval Associative Memory with Competitive Learning.

Morphological perceptrons with competitive learning (MP/CLs) are constructive artificial neural network models having a modular architecture. Not only the weights but also the architecture of the MP/CL is automatically generated by the MP/CL training algorithm. The resulting architecture is determined by hyperboxes, i.e., closed intervals, contained in \(\mathbb {F}^n\), where \(\mathbb {F}\) is a totally ordered group. The group operations and the total ordering are used to perform a competition among the outputs of each module. In this paper, we present an interval subsethood associative memory whose hidden nodes compute degrees of subsethood of the input pattern in each of the closed intervals generated by the MP/CL training algorithm. We show that the resulting interval subsethood associative memory with competitive learning (S-IAM/CL) can be viewed as a \(\varTheta \)-fuzzy associative memory (\(\varTheta \)-FAM) model. We compare the performance of S-IAM/CLs for a particular choice of interval subsethood measure with the ones of the original MP/CL model and several competitive models in a number of classification problems.
Detecting the Object from Clutter using Speeded up Robust Feature

In our hectic day to day life, there are many things that we forget or want to identify from a clutter. If we spend lot of time searching for misplaced objects, then we may not be able to do our work at the right time. Suppose if we have a technique to find whether the object that we are looking for is there in a specified area, lying with a clutter of things, then we save a lot of time. This paper highlights a concept that can detect the lost product by knowing the features. The paper presents the detection of objects based on the SURF (Speeded up Robust Feature) features. It is a novel scale- and rotation-invariant interest point detector and descriptor. It became more important because of its repeatability, distinctiveness, and robustness, and the computation time is much faster. This paper presents the experimental result of the object detection and its accuracy. Here, the images are taken in the context of real-life situations.
Hybrid time decay model and probability decay window model for data stream closed frequent pattern mining

ABSTRACTData stream is continuous and uncertain. Frequent pattern mining for data stream will cause that data distributes unevenly and concept drift. In order to improve mining efﬁciency and decrease data storage, we propose a hybrid time decay model and probability decay window model (HTPDWM) for data stream closed frequent pattern mining. This new method is divided into three steps. First, we adopt mining closed frequent pattern of sliding window model and time decay model in data stream to deal with new and old things. Second, we use probability decay window model and closure operator to calculate expected support degree and improve efﬁciency of close pattern mining respectively. Third, we use decay factor to correct concept drift and data distributes evenly. Finally, we make experiments to verify the effectiveness of the new method. Results show that HTPDWM can present stable with different sliding window and have better performance when processing time and memory space.
The Purpose of Bellman-Ford Algorithm to Summarize the Multiple Scientific Indonesian Journal Articles

Text is a one of huge type data in the big data era today. It can be processed to be valuable information with Natural Language Processing approach, such as Automated Text Summarization. This study aims to purpose the text summarization automatically for multiple text documents with graph approach at once. The graph approach that purposed in this research as methodology is Bellman-Ford algorithm. This research uses scientific journal articles documents in Indonesian language as the case study. The result of this research is the logical framework based on literature review ana analysis of Bellman-Ford algorithm for automated text summarization. This framework can be implemented and evaluated in the further works.
Ontology-driven compilation of geological map database

This note presents an ontology-driven method for the representation of knowledge in the geological maps. The OntoGeonous ontology for the geological knowledge, obtained from the encoding of the international standards (e.g., GeoScienceML and INSPIRE), has addressed the design of a geodatabase, named OntoGeoBase. Axioms and formal conditions drive the description of the feature properties in the database structure and thus constrain the data entry process. This paper illustrates the advantages of this method, namely the standard-compliant description of the items of a geological map and the fleshing out of the relations between the items of the map, with the geologic event as a description key. An example (based on an ideal geological map drawn “ad hoc”) shows how this system can help in the reduction of the amount of implicit knowledge and of the ambiguities in the reading of a geological map.
Penerapan Mikroalga Sebagai Pewarna Alam Terhadap Produk Tekstil Menggunakan Teknik Screen Printing

Abstract Lifting up previous research made by Balqis (2018), a Telkom University student on the Application of Microalgae Natural Dyes on Tukel Yarns and Gedog Tuban Weaving. Based on dyes which are divided into two, namely natural dyes and synthetic dyes, this research optimizes previous studies of the techniques used, the resulting color pigments and their application to fashion products using microalgae as natural dyes. The last technique used in this research are the screen printing technique using microalgae of arthrospira plantesis type which previously had various benefits in various fields such as sources of nutrition, food and rapid growth. Keyword : Natural Dyes, Microalga Arthrospira Plantesis, Surface, Textile.
Creating Digital Artwork

In this chapter, we’ll create some basic digital artwork using mostly selection tools, and filling the selections with various colors, gradients, and patterns. If you have little or no experience in creating graphics, this chapter will serve as an introduction.
Information Ranking Based on a Semantic Network for Constructing Digital Services for Personalized Support of Museum Activities

This paper explores the tasks of personalized support of the museum, for which it is proposed to use digital services. Services implement the selection of information sources using an additional semantic level. The seman­tic level is created above the catalog-oriented information storage of the museum. An ontological model has been developed, in accordance with which information is presented in the form of a semantic network. The local ranking model of semantic network objects is proposed, on the basis of which a ranking algorithm is developed. The software implementation of the local ranking algorithm in digital services of personalized support is presented on the example of the Museum of History of Petrozavodsk State University. The services provide personalized recommendations to museum visitors when studying the exposition. It requires various options for ranking exhibits and selecting exhibits with the highest rank.
The limits of the Mataf and Mas'a A jurisprudential study of contemporary events, and use of technology

The problem of this study lies in finding legitimate solutions to the limited Mataf (area of circumambulation around the Holy Kabba) and mas'a, and raising their capacity in light of the large number of pilgrims and visitors, taking into account the difficulty of horizontal expansion of the Mataf and both of which have a legally binding limit, and collect the new legitimate issues related to these expansions. This study included an introduction, a preface, two demands and a conclusion as follows: The introduction included the objectives, problematic and methodology of the study and the definitionof the terms of the study. The boot deals with search terms:  Limit, Mas'a, Contemporary events and Technology. The first topic dealt with the expansion of the Mataf and the in two demands: the limits of the end and its elements and historical expansion and the rule of this expansion, and the second requirement: the limits of the Mas'a in length and breadth, and the rule of the expansion of the offer of Mas'a and the new expansion and the position of scientists on it. The second topic dealt with the jurisprudential provisions on the expansion of the end and the in three demands, the first: the jurisprudential issues related to the expansion of the Mataf, and the second: use technology in Tawaaf and Sa'i, And the third: the jurisprudential provisions on the expansion of the Mas'a. Then the conclusion, main results of the research, recommendations and suggestions.
The Influence of Entrepreneurial Leadership on Team Performance –Focusing on the Mediating Role of Team Efficacy

With the advent of the Fourth Industrial Revolution, companies pursue innovation and opportunities, and corporate performance is also newly defined. As a result, the demand for new leadership is stronger. This paper conducted an empirical analysis to examine the role of team efficacy between entrepreneurial leadership and team performance. Using the SPSS 21.0 and AMOS 20.0 Statistics Package, 530 members in 79 work teams in China collected data was analyzed. The results showed that entrepreneurial leadership has a positive (+) effect on team performance, and team efficacy has a partial mediating effect between entrepreneurial leadership and team performance. This study deepened the understanding of entrepreneurial leadership and revealed the importance of entrepreneurial leadership in organizations. Future research can focus on multi-level research involving self-efficacy and individual entrepreneurial intent.
Spatiotemporal dynamics of a nonlinear algorithmic primitive (XOR) in brain networks

A fundamental challenge in neuroscience is to understand where, when and how brain networks process information. Neuroscientists have approached this question partly by measuring brain activity in space, time and at different levels of granularity. However, rather than measuring brain activity per se, our aim is to understand the specific algorithmic functions that this activity reflects [1-3]. To address this, we studied the XOR primitive, a foundational algorithmic nonlinear function that returns “true” when only one of its inputs is true. To study this transformation in the brain, we manipulated the lenses of a pair of glasses presented to the left and right visual hemifield. Each participant (N = 10) responded “yes” when only one of the lenses was dark, while we recorded their brain activity with MEG (SupMat Fig 1, caption). Other participants performed AND (N = 9) and OR (N = 8) tasks on the same stimuli. We analyzed the spatiotemporal representation of the binary lens color (dark or clear) to find out where (i.e. which brain regions), when and how (i.e. in MEG voxel activity) each lens is individually represented vs. the two lenses are nonlinearly integrated for decision (SupMat Fig 2, caption). We performed this comparison per participant, on all cortical voxels, 0 to 300 ms post stimulus. Our analyses reveal the brain as a network of regions that initially (60-100 ms post-stimulus) linearly represents the left and right lenses in the lateral-occipital regions (SupMat Fig 2). Their critical nonlinear integration occurs later (200-300 ms) primarily in the right parietal-temporal cortices, with the explicit representation of XOR, AND or OR functions within the MEG activity (SupMat Fig 3). To conclude, we can start framing the brain as a network that performs specific algorithmic functions and start understanding the where, when and how of specific information processing.
Design and Development of Information System for Tractor Distribution in Maros Regency

One of the major issues in agricultural machinery aids program from the central government is the difficulty to access information regarding distribution of the machines. Therefore, it is important to design and develop an application that provides the information about location of the four wheels and two wheels tractors distributed by the local, provincial, and central government in Maros Regency. The aim of this study was to develop a Geographical Information System that can be used to locate and map the agricultural machinery distribution. So far the data collection process is still done manually. This system need to be replaced with a system that makes it easier and efficient to map the distribution of hand tractors and four-wheel tractors. The tools used in developing the GIS application were Android Studio software and Google Maps API. The system developed can be easily maintained and data can be updated in real-time by an administrator and accessed by anyone through a login procedure.
LibGuides: Streaming Video Resources at the RLB Library: Licensed Streaming Video

This guide presents information on streaming video licensed by the RLB Library or freely available on some internet sites. The RLB Library licenses film for educational use upon request by UB faculty. Listed by vendor below are the films currently licensed by the library, with the dates the licenses expire.
Verifiable Random Number Based on B-Spline Curve

In this paper, we focus on the randomness of random numbers and pseudorandom numbers, which cannot be verified without disclosing the seed key. Based on the B-spline curve formula, a widely validated random number production scheme is constructed. The verifiable random number based on B-spline curve has the characteristics of low computational complexity and high efficiency. When the number of participants increases exponentially, the computation increases linearly. The scheme is still efficient when there are many participants in the protocol and suitable for mobile uses.
한국인 공무원의 글쓰기에 나타난 단어 ‘한글’의 사용

This study shows an analysis about use of word ‘Hangeul’ in Korean public servant’s writing. The analysis was focused on cases of wrong use, that is the cases another word should be used instead of ‘Hangeul’. The wrong use of words was confirmed according to whole meaning in the context of texts. ‘Hangeul’ has same meaning with ‘Woorigeul(우리글)’. And ‘Hangugeo(한국어, Korean language as a foreign language)’ or ‘Gugeo(국어, Korean language as a first language)’ and ‘Woorimal(우리말)’ have different meaning with ‘Hanguel’. However, the public servant’s texts contained many cases of wrong use of ‘Hanguel’. In each cases, ‘Hangeul’ was misused as a meaning of Gugeo‘(Hangugeo)’ or ‘Woorimal’. The rate of wrong use was 42.8%. This study identifies some cases of the misuse.
Menu anchor interactors in mobile website contexts : The perceived usability of menu navigation on three different types of websites

In 2018, there were 3.6 billion mobile internet users worldwide, which shows that digital designers have to tackle navigational patterns and menu anchor interactors for smartphone-sized screens ear ...
Lambek–Grishin Calculus: Focusing, Display and Full Polarization

Focused sequent calculi are a refinement of sequent calculi, where additional side-conditions on the applicability of inference rules force the implementation of a proof search strategy. Focused cut-free proofs exhibit a special normal form that is used for defining identity of sequent calculi proofs. We introduce a novel focused display calculus fD.LG and a fully polarized algebraic semantics $$\mathbb {FP.LG}$$ for Lambek–Grishin logic by generalizing the theory of multi-type calculi and their algebraic semantics with heterogenous consequence relations. The calculus fD.LG has strong focalization and it is sound and complete w.r.t. $$\mathbb {FP.LG}$$ . This completeness result is in a sense stronger than completeness with respect to standard polarized algebraic semantics, insofar as we do not need to quotient over proofs with consecutive applications of shifts over the same formula. We also show a number of additional results. fD.LG is sound and complete w.r.t. LG-algebras: this amounts to a semantic proof of the so-called completeness of focusing, given that the standard (display) sequent calculus for Lambek–Grishin logic is complete w.r.t. LG-algebras. fD.LG and the focused calculus fLG of Moortgat and Moot are equivalent with respect to proofs, indeed there is an effective translation from fLG-derivations to fD.LG-derivations and vice versa: this provides the link with operational semantics, given that every fLG-derivation is in a Curry–Howard correspondence with a directional $$\overline{\lambda }\mu \widetilde{\mu }$$ -term.
Using Big Data Technology to Assist in Analyzing the Language Differences between English and Chinese Cultures and Translation Capabilities

Abstract Driven by increasing trend of globalization and more frequent international exchanges, students in universities and colleges should distinguish the differences between Chinese and Western cultures to solve the problems and avoid mistakes in translating. Influenced by different cultures, there also exist differences between the cultural connotation of English and Chinese, directly having effects on the language expression. With the development of the times, big data technology is particularly important in terms of language differences and translation between English and Chinese cultures. Therefore, it is necessary for translators to adopt relevant optimization strategies to carry out the smooth English-Chinses translating work. Based on the linguistic differences between these two cultures, relevant suggestions will be put forward for English-Chinese translating work to improve the accuracy.
Psychopath Balram in Aravind Adiga’s The White Tiger

The White Tiger is the 2008 Man Booker Prize winning novel in which the psychopathic character plays a role in telling the dramatic tale of his life. The protagonist Balram’s unpredictable journey from the underprivileged to the wealthy tycoon in India is amazing. The novel is a psychopathic story of murder and success. The genius memory of psychopath Balram sparks not only to map an excellent text space, but more than this, regulates Balram’s nerves. His struggle to be wealthy is full of compassion and sympathy. Balram is a blazingly savage, brilliant, and psychopathic on his journey. In the new alien world, he experiences a state mental disorder. That's why Balram, the narrator of the letter, has the mark of a Psychopath. The present research is an effort to examine and investigate the dimension of Balram's psychopathic character. This will give another heading to rising literary examination to character in an alternate psychopathic style.
Klasifikasi Bunga Melati dengan Menggunakan Local Binary Pattern

Jasmine is the one of the national flower. Each jasmine type has unique characteristic and different between each other. Sadly, Indonesia is not the only one who have the Jasmine as the national flower, the other countries such as Malaysia and Philippine have their jasmine. In this research we tried to classify between Indonesia and Other country Jasmine. We proposed using Local Binary Pattern as the feature extraction and K-Nearest Neighbour as the classifier. The result shows the best accuracy from our proposed methods is 55%.
A Novel Gripping System for Delivery of Packages via Unmanned Aerial Vehicles

Abstract An Unmanned Aerial Vehicle (UAV) can carry packages to locations that are unreachable by a ground vehicle using a gripper that can handle standard sized packages. This paper presents a UAV-mounted system for grasping corrugated boxes. The proposed gripping system uses two pairs of end effectors which are arranged perpendicular to each other. All four grippers are geared so that they can be actuated by a single control input. The mechanism is designed to handle position and orientation errors of the box relative to the gripper. The gripper was experimentally validated using a test box that was misaligned in position and orientation.
A face recognition algorithm based on multiple convolution kernels and double layer sparse automatic encoder

The prevailing face recognition algorithms adopt the manual design feature or the automatic extraction feature of deep learning in the process of characteristic extraction. In order to extract the distinguishing characteristics of the target more accurately, a face recognition algorithm based on the multiple convolution kernels and double-layer sparse automatic encoder was proposed. Initially, the proposed algorithm pre-treated the image with zero-phase component analysis (ZCA) whitening to decrease the correlation of the characteristic and reduced the complexity of the network training. Subsequently, a deep network characteristic extractor was designed, based on the convolution, pooling and multi-layer sparse automatic encoder. The convolution kernel was obtained by an independent unsupervised learning, and an automatic deep characteristic extractor was obtained by pre-training and fine-tuning. Finally, the extracted characteristics were classified using the Softmax regression model. The experiment results manifest that the presented algorithm was superior to the existing algorithms and conventional deep learning algorithms.
Anemia Hemolitik Autoimun pada Anak

Anemia hemolitik autoimun (AIHA) disebabkan oleh antibodi terhadap eritrosit sendiri yang menyebabkan hemolisis dan anemia. Penyebab paling sering idiopatik. Pada anak biasanya bersifat akut dan dapat mengancam jiwa. Terapi lini pertama AIHA adalah kortikosteroid dan immunoglobulin. Respon paling baik terhadap steroid didapatkan pada anak. Autoimmune hemolytic anemia (AIHA) is caused by autoantibodies against own erythrocytes leading to hemolysis and anemia. The most common cause is idiopathic. This anemia is usually acute and can be life-threatening. First line therapy is corticosteroid and can be combined with intravenous immunoglobulin. Best response to steroids is among children.