Reviewerly/exHarmony huggingface dataset:
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RECOGNITION OF CHARACTER FROM VIDEO SUBTITLES

An important task in content based video indexing is to extract text information from videos. The challenges involved in text extraction and recognition are variation of illumination on each video frame with text, the text present on the complex background and different font size of the text. Using various image processing algorithms like morphological operations, blob detection and histogram of oriented gradients the character recognition of video subtitles is implemented. Segmentation, feature extraction and classification are the major steps of character recognition. Several experimental results are shown to demonstrate the performance of the proposed algorithm.
Deprecating MD5 for LDP

When the MPLS Label Distribution Protocol (LDP) was specified circa1999, there were very strong requirements that LDP should use acryptographic hash function to sign LDP protocol messages. MD5 waswidely used at that time, and was the obvious choices. However, evenwhen this decision was being taken there were concerns as to whetherMD5 was a strong enough signing option. This discussion was brieflyreflected in section 5.1 of RFC 5036 [RFC5036] (and also in RFC 3036[RFC3036]). Over time it has been shown that MD5 can be compromised.Thus, there is a concern shared in the security community and theworking groups responsible for the development of the LDP protocolthat LDP is no longer adequately secured. This document deprecatesMD5 as the signing method for LDP messages. The document also selectsa future method to secure LDP messages - the choice is TCP-AO. Inaddition, we specify that the TBD cryptographic mechanism is to be thedefault TCP-AO security method.
Online Multiclass Boosting with Bandit Feedback

We present online boosting algorithms for multiclass classification with bandit feedback, where the learner only receives feedback about the correctness of its prediction. We propose an unbiased estimate of the loss using a randomized prediction, allowing the model to update its weak learners with limited information. Using the unbiased estimate, we extend two full information boosting algorithms (Jung et al., 2017) to the bandit setting. We prove that the asymptotic error bounds of the bandit algorithms exactly match their full information counterparts. The cost of restricted feedback is reflected in the larger sample complexity. Experimental results also support our theoretical findings, and performance of the proposed models is comparable to that of an existing bandit boosting algorithm, which is limited to use binary weak learners.
Identification and Investigation of Effective Factors on the Development of the Tourism Industry in Bandar-e-Anzali by Delphi Method

Today, the tourism industry, as one of the global leading industries and as a strong social, cultural and economic force, has the ability to form and transform human societies, and therefore the development of the tourism industry is particularly important. The purpose of this study was to identify and investigate the effective factors on the development of Bandar-e-Anzali Tourism Industry. The research method is a survey that the statistical population in the first part (Delphi analysis) consists of experts and in the second part (inferential statistics), all employees and managers in the private and governmental decision-making centers about the tourism industry in Bandar-e-Anzali (Cultural Heritage, Handicrafts and Tourism, municipalities, hotels and hospitality establishments). The sample size in the first part is 20, and in the second part is equal to 172 people. Due to the restriction of the census method, a quantitative research questionnaires were distributed and gathered randomly among the subjects. To analyze the findings, exploratory factor analysis, one-sample t-test and Friedman's rank test were used. The findings showed that five components (increasing the level of management decision making, strengthening cultural and educational issues, developing infrastructure facilities, increasing marketing and advertising, and increasing the participation of the private sector) contributed to develop Bandar-e-Anzali Tourism Industry.
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Rethinking Education for Leadership

We are currently witnessing a crisis of confidence in leadership in all sorts of public institutions. Educationalists are uniquely placed to explore new understandings and demonstrate new practices of leadership. The aim of this paper is to explore the possibility of educating future leaders through the intentional exercise of personal character strengths, in the hope that this may contribute to new understandings and practices of leadership.
Privatization Impact on Economic Growth in Ethiopia: ARDL Approach

The objective of this paper is as to check whether privatization has long run or short run significant impact on economic growth of Ethiopia by considering real GDP growth as a proxy for economic growth and privatization proceeds as to the measure of the magnitude of privatization.A time series data starting form 1994/95S1 up to 2016/17S2 using some explanatory and response variables.Autoregressive Distributed Lag (ARDL) method to characterize long run and the short run relationship between real GDP growth and independent variables was used.The empirical results reveal that both privatization and foreign direct investment due to privatization are found to have a positive impact on economic growth and statically significant at 1 & 5 percent respectively in the long run as well as in the short run.While, inflation and government consumption proxy to corruption affects economic growth negatively in the long run.The unexpected result of private domestic investment had a negative sing and insignificant in the long run.This study has an important policy implication.The findings of this study imply that economic growth can be improved significantly when the privatization police accompanied with other structural change was implemented.Hence policy makers and /or the government should strive to strengthen privatization policies together with other policies.In addition to this effort, there should be a close monitoring and consistent government consumption and budget monitoring strategies, which is used to avoid misallocation and mismanagement of consumption.
Working on One Part at a Time Is the Best Strategy for Software Production: A Proof

When a company works on a large software project, it can often start recouping its investments by selling intermediate products with partial functionality. With this possibility in mind, it is important to schedule work on different software parts so as to maximize the profit. These exist several algorithms for solving the corresponding optimization problem, and in all the resulting plans, at each moment of time, we work on one part of software at a time. In this paper, we prove that this one-part-at-a-time property holds for all optimal plans.
The Standards on a Cloud Service Framework and Protocol for Construction, Migration, Deployment,and Publishing of Internet-Oriented Scalable Web Software Systems in Non-Programming Mode

This draft mainly focuses on the scalable architecture and publishingprotocol standard of REST-based SAAS cloud model Web software in non-programming mode, stipulates the data structure pattern and dataexchange protocol for the construction and release of REST-basedscalable Web cloud service software systems. Using the standardizedframework and protocol, users can easily and quickly design their ownsoftware systems in the cloud, transfer and release data, which maymake conventional software development so ease to improve theefficiency of complex database construction and server management.Without having to write codes under the standard framework, users canget consistent style background to create service, rapidly develop webapplication systems with the function of standard data management anddata maintenance, and directly publish the software system to the endusers of the Internet for access and use. And provide RESTful APIs tofacilitate external access to required service resources. Theframework can thus greatly shorten the software development lifecycle, and save a great deal of development cost and maintenanceoverhead.
Shape-Conditioned Image Generation by Learning Latent Appearance Representation from Unpaired Data

Conditional image generation is effective for diverse tasks including training data synthesis for learning-based computer vision. However, despite the recent advances in generative adversarial networks (GANs), it is still a challenging task to generate images with detailed conditioning on object shapes. Existing methods for conditional image generation use category labels and/or keypoints and are only give limited control over object categories. In this work, we present SCGAN, an architecture to generate images with a desired shape specified by an input normal map. The shape-conditioned image generation task is achieved by explicitly modeling the image appearance via a latent appearance vector. The network is trained using unpaired training samples of real images and rendered normal maps. This approach enables us to generate images of arbitrary object categories with the target shape and diverse image appearances. We show the effectiveness of our method through both qualitative and quantitative evaluation on training data generation tasks.
Spelling errors in official letters in the Ciracas area East Jakarta

The purpose of this research is to describe spelling errors in the official letter in ciracas area, East Jakarta written since February ---- November 2017 while the method used in this research, that is descriptive qualitative. Data collection techniques by collecting six letters of service. After research on six official letters from the "Suci" Islamic Foundation, Al-Hidayah educational institutions, Adhiluhur Mahadika Foundation, Madrasah High School Mahadika, Fathurahman Mosque prosperity Council, and PT PLN in Ciracas region, resulted in erroneous spelling of Indonesian ( EBI) in total amounted to 32 findings relating to the writing of abbreviations amounted to 8 findings or 25%, the composite word writing amounted to 5 findings or 15.62%, the use of punctuation marks 9 findings or 28.12%, writing absorption element 2 findings or 6 , 25%, letter writing amounted to 4 finding or 4.12%, and word writing gamounted to 4 finding or 12.5%. From this finding, it was concluded that the bigges spelling use error in the official letter on the use punctuation is 28, 12%.
A Summer Immersive Program for Global Engineering Education with Focus on 3D Design and Structural Analyses

Abstract As the world is becoming smaller and connected more and more in all levels, future engineers need to be trained to work in more global, adaptable, and teamwork environments where engineers from different cultures and disciplines work together and solve problems. In this paper, we present a summer immersive program that we ran to meet this need. Our program drew about 40 undergraduate students from universities of three different countries with various engineering disciplines including mechanical, industrial, civil, mechatronics, naval architecture and ocean engineering, and automotive engineering. These universities are Southern Illinois University Edwardsville (SIUE) in the United States, Tongmyong University (TU) in South Korea, and Universiti Teknologi Malaysia (UTM) in Malaysia. This program ran for 2 weeks in July 2017 (and August 2016) at TU in Busan, S. Korea. The program content was on engineering design and analysis methods using 3D modeling that have applications to various disciplines. We used well-known engineering design and structure analysis tools, CATIA and ABAQUS, respectively. In the first part of the program, students learned the methods and tools using lectures and individual/group projects, while in the second part students grouped into 11 teams and each team defined its own final project problem, divided work among its members, applied the first part knowledge to the problem and made a team presentation on its findings at the end of the 2-week program. Teams were formed such that students experienced diversity and global nature with respect to their origins, disciplines, and genders. Students in the same teams mostly shared the same dorm rooms for teamwork and cultural exchanges. Students toured global industry plants and visited cultural sites. An invited expert on the naval architecture design and ocean engineering field presented real case studies to students. The post assessment shows that students were very pleased with the program and we plan to run the program again in summer 2018. In this paper, we will present our program content and schedule, sample team final projects, and program assessment outcome, and share experiences we gained from our global engineering education through this summer program.
Board 62: Usability of a Mobile Augmented Reality Application to Teach Structural Analysis

Turkan investigates how LiDAR and virtual design
Effects of capital flight on growth and poverty reduction in Ethiopia

This chapter addresses issues of pervasive poverty and shortage of foreign exchange as evidence of rising capital flight and contributes to literature and policy debate on the growth and poverty reduction impact of capital flight from Africa in general and from Ethiopia in particular. According to official statistics, Ethiopia continued to register double-digit economic growth. The poverty index therefore implies that to eliminate poverty the government of Ethiopia will need to invest 7.8 per cent of the poverty line per capita. Several channels have been identified in literature through which capital flight affects economic growth. Capital flight leads to the erosion of the tax base, resulting in a fall in government revenue that consequently induces a decline in public investments and economic growth. Capital flight may also have a negative effect on the government’s tax revenue as it erodes the country’s tax base.
Image Processing Based Pre-Navigation Strategy for Service Robot in Reticulation Environment: Fulfillment using FPGA

Application of robots as an assistance for the elderly people gave a wakeup call for the way to study and improvement of navigation methods in indoor environments. Based on needs of the subject i.e. person to be served, the mobile robot should execute the accordingly to accomplish the need. This paper focuses on development of pre navigational strategy helpful to serve people in a reticulation environment. Paper also discuss on design of VLSI Architectures to select the subject to serve basing on the type of service request and also navigation mechanism to complete assignment. As a part of this, we simulated conception in Vivado 14.4 tool environment through Verilog HDL programming and also synthesized on FPGA part xc7z010clg400-1 of zynq-7000 family by considering a random environment.
Noether's problem for transitive permutation groups of degree 6

<!-- *** Custom HTML *** --> Suppose that a finite group $G$ is realized in the Cremona group $\mathrm{Cr}_m (k)$, the group of $k$-automorphisms of the rational function field $K$ of $m$ variables over a constant field $k$. The most general version of Noether's problem is then to ask, whether the subfield $K^G$ consisting of $G$-invariant elements is again rational or not. This paper treats Noether's problem for various subgroups $G$ of $\mathfrak{S}_6$, the symmetric group of degree 6, acting on the function field $\boldsymbol{Q}(s, t, z)$ over $k = \boldsymbol{Q}$ of the moduli space $\mathcal{M}_{0,6}$ of $\mathbb{P}^1$ with ordered six marked points. We shall show that this version of Noether's problem has an affirmative answer for all but two conjugacy classes of transitive subgroups $G$ of $\mathfrak{S}_6$, by exhibiting explicitly a system of generators of the fixed field $\boldsymbol{Q}(s,t,z)^G$. In the exceptional cases $G \cong \mathfrak{A}_6, \mathfrak{A}_5$, the problem remains open.
A Full Probabilistic Model for Yes/No Type Crowdsourcing in Multi-Class Classification

Crowdsourcing has become widely used in supervised scenarios where training sets are scarce and difficult to obtain. Most crowdsourcing models in the literature assume labelers can provide answers to full questions. In classification contexts, full questions require a labeler to discern among all possible classes. Unfortunately, discernment is not always easy in realistic scenarios. Labelers may not be experts in differentiating all classes. In this work, we provide a full probabilistic model for a shorter type of queries. Our shorter queries only require “yes” or “no” responses. Our model estimates a joint posterior distribution of matrices related to labelers' confusions and the posterior probability of the class of every object. We developed an approximate inference approach, using Monte Carlo Sampling and Black Box Variational Inference, which provides the derivation of the necessary gradients. We built two realistic crowdsourcing scenarios to test our model. The first scenario queries for irregular astronomical time-series. The second scenario relies on the image classification of animals. We achieved results that are comparable with those of full query crowdsourcing. Furthermore, we show that modeling labelers' failures plays an important role in estimating true classes. Finally, we provide the community with two real datasets obtained from our crowdsourcing experiments.
From the Winter of Messy Data into the Spring of Standardization: E-Book Vendor Data Reenvisioned

The University of South Florida (USF) Libraries run several projects which involve the collection and display of ebook vendor metadata including seven evidence-based acquisitions (EBA) programs, one patron-driven acquisitions (PDA) program and the eBooks for Classroom Plus (EB+) database. These projects are the main focus of the Libraries’ Textbook Affordability Project (TAP). The TAP initiative’s goal is help reduce textbook cost to students by providing faculty with ebook alternatives. The metadata used in these projects is collected from a variety of vendor sources including titles lists, K-Bart files entitlement lists and Marc records. Compiling data from various sources into a useable form can sometimes be a daunting task. The USF Libraries Metadata Team has developed processes which allows the library to collect eBook information from various vendors and multiple sources and combine it into standardized forms. Standardized metadata provides the means for USF Libraries to track and maintain the various ebook projects.
Developing the ontological model for research and representation of Commemoration Speeches in Croatia using a graph property database

This paper demonstrates the ontological model of commemoration speeches given in Croatia that was developed as a part of the project Framing the Nation and Collective Identity in Croatia: Political Rituals and the Cultural Memory of Twentieth Century Traumas. The research gathers linguistic, media and social data about seven commemoration practices connected to the wars of the 20th century using various methodologies involving audio-visual field recordings, transcription of commemoration speeches and the creation of a text corpus. This chapter presents digital humanities methods used to connect various levels of data analysis and digital resources, from natural language processing (NLP) of Croatian to conceptual enrichment through the processing of conceptual metaphors. These resources are integrated using the Neo4j database and the Python Py2Neo library for data manipulation of the ontological model that embeds the linguistic and media research in the context respectively of the social identity of actors, their interaction, institutional affiliations and cultural models they represent and express. The value of this ontological model is in fostering an interdisciplinary approach through the contextualization of data and targeted usage of digital resources.
Good Continuation in Rows or Frieze Symmetry

Repetition of similar objects in equal spacing along a straight line is very salient to the human eye. This kind of symmetry is known as frieze or row symmetry and present in many environments, in particular in the man-made world, such as arts or architecture. A selection of published methods and models for the recognition of such symmetry is reviewed. This chapter also presents a corresponding operation. It differs from the reflection symmetry operation of the previous chapter in its arity: Input is an n-tupel of parts where n is at least two. Given a set of objects of non-trivial size an enumeration of all n-tupels for search for salient friezes is intractable. Accordingly, the chapter presents greedy search methods of low computational complexity. Actually, the parts should also be in proximity, and all kinds of similarity laws can be fused in the assessment of the constructed row.
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Detection of Lymph Nodes Using Centre of Mass and Moment Analysis

A novel technique to determine specific spot where the lymph node is present and also analyse whether it causes cancer or not. Lymph nodes are small structures that filter harmful substances. Their incessant growth may lead to cancer. The two-dimensional image obtained from CT scan is transformed into three-dimensional cube using 3D slicer tool. The centre of mass is calculated and moment of inertia is obtained from centre of mass. The value of moment of inertia is decreased, until a node is detected or it meets a particular threshold. Thus, the proposed method enhances the node detection accuracy and reduces the time taken for detection using possible simple mathematical computations.
Reaching Behind Specular Highlights by Registration of Two Images of Broiler Viscera

The manual postmortem inspection of broilers and their viscera is becoming a bottleneck as the slaughter rate increases. Computer vision can assist veterinarians during the inspection, but specular highlights can hide crucial details when inspecting for diseases on the viscera set. This study aims to restore details behind these specular highlights by capturing two images of the same viscera using shifting light positions. The dataset consists of images captured in-line at a poultry processing plant. The method achieves an average SSIM score of 0.96 over a test set of 100 image sets. The result is visually pleasing images with correct textural information instead of specular highlights.
A Robust Method for Image Copy-Move Passive Forgery Detection with Enhanced Speed

Forgery detection of images is presently one of the fascinated research fields. Copy-move forgery is the most commonly used methods for image forgery. A novel method is proposed in this paper, which is an effective and advanced method for detecting copy-move forgery. The proposed method is a block matching technique with reduced computational speed and less computational complexities. The efficiency of outcome is also improved. The image is segmented into fixed dimensions of overlying blocks and then discrete cosine transform (DCT) is applied to each block to extract its features. Then, the mean of each block is obtained. The mean of each block is compared with other blocks to find the similarity between the blocks. The computational outcomes are shown that indicates the proposed method is robust to detect copy-move forgery efficiently with enhanced speed.
THE EFFECT OF GREENWASH ON PERCEIVED RISK, QUALITY AND SATISFACTION

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