Search results for: similarity transformation

Authors: Nazira Kakulia

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The analysis of transformation of institutional changes outlines two important characteristics. These are: the speed of the changes and their sequence. Successful transformation must be carried out in three different stages; On the first stage, macroeconomic stabilization must be achieved with the help of fiscal and monetary tools. Two-tier banking system should be established and the active functions of central bank should be replaced by the passive ones (reserve requirements and refinancing rate), together with the involvement growth of private sector. Fiscal policy by itself here means the creation of tax system which must replace previously existing direct state revenues; the share of subsidies in the state expenses must be reduced also. The second stage begins after reaching the macroeconomic stabilization at a time of change of formal institutes which must stimulate the private business. Corporate legislation creates a competitive environment at the market and the privatization of state companies takes place. Bankruptcy and contract law is created. he third stage is the most extended one, which means the formation of all state structures that is necessary for the further proper functioning of a market economy. These three stages about the cycle period of political and social transformation and the hierarchy of changes can also be grouped by the different methodology: on the first and the most short-term stage the transfer of power takes place. On the second stage institutions corresponding to new goal are created. The last phase of transformation is extended in time and it includes the infrastructural, socio-cultural and socio-structural changes. The main goal of this research is to explore and identify the features of such kind of models.

Keywords: competitive environment, fiscal policy, macroeconomic stabilization, tax system

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Authors: Tebogo Sethibe, Jabulile Mabuza

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The COVID-19 pandemic has been commonly referred to as a ‘black swan event’; it has changed the world, from how people live, learn, work and socialise. It is believed that the pandemic has fast-tracked the adoption of technology in many organisations to ensure business continuity and business sustainability; broadly said, the pandemic has fast-tracked digital transformation (DT) in different organisations. This paper aims to study the impact of the COVID-19 pandemic on DT in organisations in South Africa by focusing on the changes in IT capabilities in the DT framework. The research design is qualitative. The data collection was through semi-structured interviews with information communication technology (ICT) leaders representing different organisations in South Africa. The data were analysed using the thematic analysis process. The results from the study show that, in terms of ICT in the organisation, the pandemic had a direct and positive impact on ICT strategy and ICT operations. In terms of IT capability transformation, the pandemic resulted in the optimisation and expansion of existing IT capabilities in the organisation and the building of new IT capabilities to meet emerging business needs. In terms of the focus of activities during the pandemic, there seems to be a split in organisations between the primary focus being on ‘digital IT’ or ‘traditional IT’. Overall, the findings of the study show that the pandemic had a positive and significant impact on DT in organisations. However, a definitive conclusion on this would require expanding the scope of the research to all the components of a comprehensive DT framework. This study is significant because it is one of the first studies to investigate the impact of the COVID-19 pandemic on organisations, on ICT in the organisation, on IT capability transformation and, to a greater extent, DT. The findings from the study show that in response to the pandemic, there is a need for: (i) agility in organisations; (ii) organisations to execute on their existing strategy; (iii) the future-proofing of IT capabilities; (iv) the adoption of a hybrid working model; and for (v) organisations to take risks and embrace new ideas.

Keywords: digital transformation, COVID-19, bimodal-IT, digital transformation framework

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Authors: Karine B. de Oliveira, Carina F. Dorneles

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The structure level matching is the problem of combining elements of a structure, which can be represented as entities, classes, XML elements, web forms, and so on. This is a challenge due to large number of distinct representations of semantically similar structures. This paper describes a structure-based matching method applied to search for different representations in data sources, considering the similarity between elements of two structures and the data source context. Using real data sources, we have conducted an experimental study comparing our approach with our baseline implementation and with another important schema matching approach. We demonstrate that our proposal reaches higher precision than the baseline.

Keywords: context, data source, index, matching, search, similarity, structure

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Authors: Alexis Aldo Mendoza Villarroel, Ademir Clemente Villena Zevallos, Cristian Jose Lopez Del Alamo

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With the advancement of technology it is now possible to scan entire objects and obtain their digital representation by using point clouds or polygon meshes. However, some objects may be broken or have missing parts; thus, several methods focused on this problem have been proposed based on Geometric Deep Learning, such as GCNN, ACNN, PointNet, among others. In this article an approach from a different paradigm is proposed, using metric data structures to index global descriptors in the spectral domain and allow the recovery of a set of similar models in polynomial time; to later use the Iterative Close Point algorithm and recover the parts of the incomplete model using the geometry and topology of the model with less Hausdorff distance.

Keywords: 3D reconstruction method, point cloud completion, shape completion, similarity search

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Authors: Dongxu Chen, Yipeng Li

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This paper presents an information geometry NonlocalMeans(NLM) algorithm for Poisson denoising. NLM estimates a noise-free pixel as a weighted average of image pixels, where each pixel is weighted according to the similarity between image patches in Euclidean space. In this work, every pixel is a Poisson distribution locally estimated by Maximum Likelihood (ML), all distributions consist of a statistical manifold. A NLM denoising algorithm is conducted on the statistical manifold where Fisher information matrix can be used for computing distribution geodesics referenced as the similarity between patches. This approach was demonstrated to be competitive with related state-of-the-art methods.

Keywords: image denoising, Poisson noise, information geometry, nonlocal-means

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Authors: Saki Makume

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Misogyny is a serious problem in the world that is predominantly patriarchal. South Africa is a very unequal society, so are the companies in this country. After 1994, laws were promulgated to outlaw unfair discrimination, amongst them discrimination based on gender. The presentation aims to share the experiences and learnings of Rand Water through its transformation journey. The environment was so hostile to women in the workplace that policies and practices excluded or unfairly discriminated against women. The paper will be in the form of a case study, predominantly qualitative and to a lesser extent quantitative. The results will show that the number of women at Board, Executive and Management levels have increased; and policies amended to be gender sensitive. Policies were developed that specifically protected women’s rights e.g. sexual harassment. A program like TechnoGirl was introduced to lure girl learners to Rand Water.

Keywords: gender mainstreaming, policies, transformation, unfair discrimination

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Authors: Takashi Mitsuishi, Koji Saigusa

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This paper presents circular polar coordinates transformation of periodic fuzzy membership function. The purpose is identification of domain of periodic membership functions in consequent part of IF-THEN rules. The proposed methods are applied to the simple color construct system.

Keywords: periodic membership function, polar coordinates transformation, defuzzification, circular coordinates

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Authors: Dino Carpentras, Alejandro Dinkelberg, Michael Quayle

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Opinion dynamics models use an agent-based modeling approach to model people’s opinions. Model's properties are usually explored by testing the two 'degrees of freedom': the interaction rule and the network topology. The latter defines the connection, and thus the possible interaction, among agents. The interaction rule, instead, determines how agents select each other and update their own opinion. Here we show the existence of the third degree of freedom. This can be used for turning one model into each other or to change the model’s output up to 100% of its initial value. Opinion dynamics models represent the evolution of real-world opinions parsimoniously. Thus, it is fundamental to know how real-world opinion (e.g., supporting a candidate) could be turned into a number. Specifically, we want to know if, by choosing a different opinion-to-number transformation, the model’s dynamics would be preserved. This transformation is typically not addressed in opinion dynamics literature. However, it has already been studied in psychometrics, a branch of psychology. In this field, real-world opinions are converted into numbers using abstract objects called 'scales.' These scales can be converted one into the other, in the same way as we convert meters to feet. Thus, in our work, we analyze how this scale transformation may affect opinion dynamics models. We perform our analysis both using mathematical modeling and validating it via agent-based simulations. To distinguish between scale transformation and measurement error, we first analyze the case of perfect scales (i.e., no error or noise). Here we show that a scale transformation may change the model’s dynamics up to a qualitative level. Meaning that a researcher may reach a totally different conclusion, even using the same dataset just by slightly changing the way data are pre-processed. Indeed, we quantify that this effect may alter the model’s output by 100%. By using two models from the standard literature, we show that a scale transformation can transform one model into the other. This transformation is exact, and it holds for every result. Lastly, we also test the case of using real-world data (i.e., finite precision). We perform this test using a 7-points Likert scale, showing how even a small scale change may result in different predictions or a number of opinion clusters. Because of this, we think that scale transformation should be considered as a third-degree of freedom for opinion dynamics. Indeed, its properties have a strong impact both on theoretical models and for their application to real-world data.

Keywords: degrees of freedom, empirical validation, opinion scale, opinion dynamics

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Authors: Nuur Ezaini Akmar Ismail, Norbazilah Rahim, Norul Huda Md Rasdi, Maslina Daud

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A web application is the most targeted by the attacker because the web application is accessible by the end users. It has become more advantageous to the attacker since not all the end users aware of what kind of sensitive data already leaked by them through the Internet especially via social network in shake on ‘sharing’. The attacker can use this information such as personal details, a favourite of artists, a favourite of actors or actress, music, politics, and medical records to customize phishing attack thus trick the user to click on malware-laced attachments. The Phishing attack is one of the most popular attacks for social engineering technique against web applications. There are several methods to detect phishing websites such as Blacklist/Whitelist based detection, heuristic-based, and visual similarity-based detection. This paper illustrated a comparison between the heuristic-based technique using features of a uniform resource locator (URL) and visual similarity-based detection techniques that compares the content of a suspected phishing page with the legitimate one in order to detect new phishing sites based on the paper reviewed from the past few years. The comparison focuses on three indicators which are false positive and negative, accuracy of the method, and time consumed to detect phishing website.

Keywords: heuristic-based technique, phishing detection, social engineering and visual similarity-based technique

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Authors: Pouyan Motamedi, Ken Bosnick, Ken Cadien, James Hogan

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Growth of conformal ultrathin metal films has attracted a considerable amount of attention recently. Plasma-enhanced atomic layer deposition (PEALD) is a method capable of growing conformal thin films at low temperatures, with an exemplary control over thickness. The authors have recently reported on growth of metastable epitaxial nickel thin films via PEALD, along with a comprehensive characterization of the films and a study on the relationship between the growth parameters and the film characteristics. The goal of the current study is to use the mentioned films as a case study to investigate the temperature-activated phase transformation and agglomeration in ultrathin metallic films. For this purpose, metastable hexagonal nickel thin films were annealed using a controlled heating/cooling apparatus. The transformations in the crystal structure were observed via in-situ synchrotron x-ray diffraction. The samples were annealed to various temperatures in the range of 400-1100° C. The onset and progression of particle formation were studied in-situ via laser measurements. In addition, a four-point probe measurement tool was used to record the changes in the resistivity of the films, which is affected by phase transformation, as well as roughening and agglomeration. Thin films annealed at various temperature steps were then studied via atomic force microscopy, scanning electron microscopy and high-resolution transmission electron microscopy, in order to get a better understanding of the correlated mechanisms, through which phase transformation and particle formation occur. The results indicate that the onset of hcp-to-bcc transformation is at 400°C, while particle formations commences at 590° C. If the annealed films are quenched after transformation, but prior to agglomeration, they show a noticeable drop in resistivity. This can be attributed to the fact that the hcp films are grown epitaxially, and are under severe tensile strain, and annealing leads to relaxation of the mismatch strain. In general, the results shed light on the nature of structural transformation in nickel thin films, as well as metallic thin films, in general.

Keywords: atomic layer deposition, metastable, nickel, phase transformation, thin film

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Authors: Tobias Huttche, Marco Canipa-Valdez, Corinne Mühlebach

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This article discusses the role of leasing on the digital transformation process of companies and corresponding economic effects. Based on the traditional mechanisms of leasing, this article focuses in particular on the benefits of leasing as financing instrument with regard to the innovation potential of companies. Practical examples demonstrate how leasing can become an integral part of new business models. Especially, with regard to the digital transformation and corresponding investments in know-how and infrastructure, leasing can play an important role. Furthermore, findings of an empirical survey are presented dealing with the usage of leasing in Switzerland in an international context. The survey shows not only the benefits of leasing against the backdrop of digital transformation but gives guidance on how other countries can benefit from promoting leasing in their legislation and economy. Based on a simulation model for Switzerland, the economic effect of an increase in leasing volume is being calculated. Again, the respective results underline the substantial growth potential. This holds true especially for economies where asset-based lending is rarely used because of a lack of entrepreneurial or private security of the borrower (cash-based financing for developing and emerging countries). Overall, the authors found that leasing using companies are more productive and tend to grow faster than companies using less or none leasing. The positive effects of leasing on emerging digital challenges for companies and entire economies should encourage other countries to facilitate access to leasing as financing instrument by decreasing legal-, tax- and accounting-related requirements in the respective jurisdiction.

Keywords: Cash-Based financing, digital transformation, financing instruments, growth, innovation, leasing

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Authors: M. A. Talha, M. Osman Gani, M. Ferdows

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This paper focuses on the study of two dimensional magnetohydrodynamic (MHD) steady incompressible viscous Williamson nanofluid with exponential internal heat generation containing gyrotactic microorganism over a stretching sheet. The governing equations and auxiliary conditions are reduced to a set of non-linear coupled differential equations with the appropriate boundary conditions using similarity transformation. The transformed equations are solved numerically through spectral relaxation method. The influences of various parameters such as Williamson parameter γ, power constant λ, Prandtl number P_r, magnetic field parameter M, Peclet number P_e, Lewis number Le, Bioconvection Lewis number Lb, Brownian motion parameter Nb, thermophoresis parameter Nt, and bioconvection constant σ are studied to obtain the momentum, heat, mass and microorganism distributions. Moment, heat, mass and gyrotactic microorganism profiles are explored through graphs and tables. We computed the heat transfer rate, mass flux rate and the density number of the motile microorganism near the surface. Our numerical results are in better agreement in comparison with existing calculations. The Residual error of our obtained solutions is determined in order to see the convergence rate against iteration. Faster convergence is achieved when internal heat generation is absent. The effect of magnetic parameter M decreases the momentum boundary layer thickness but increases the thermal boundary layer thickness. It is apparent that bioconvection Lewis number and bioconvection parameter has a pronounced effect on microorganism boundary. Increasing brownian motion parameter and Lewis number decreases the thermal boundary layer. Furthermore, magnetic field parameter and thermophoresis parameter has an induced effect on concentration profiles.

Keywords: convection flow, similarity, numerical analysis, spectral method, Williamson nanofluid, internal heat generation

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Authors: E. Zippelius

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Urban design aims to provide a stage for public life that, when once brought to life, is right away subject to subtle but continuous transformation. This paper explores such transformations and searches for ways how public life can be reinforced in the case of a housing settlement for the displaced in Nicosia, Cyprus. First, a sound basis of theoretical knowledge is established through literature review, notably the theory of the Production of Space by Henri Lefebvre, exploring its potential and defining key criteria for the following empirical analysis. The analysis is pinpointing the differences between spatial practice, representation of space and spaces of representation as well as their interaction, alliance, or even conflict. In doing so uncertainties, chances and challenges are unraveled that will be consequently linked to practice and action and lead to the formulation of a design strategy. A strategy, though, that does not long for achieving an absolute, finite certainty but understands the three dimensions of space formulated by Lefebvre as equal and space as continuously produced, hence, unfinished.

Keywords: production of space, public space, urban life, urban transformation

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Authors: Mustafa Yorgancılar, Emine Atalay, Necdet Akgün, Ali Topal

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In this study, polymerase chain reaction based Inter-simple sequence repeat (ISSR) from DNA fingerprinting techniques were used to investigate the genetic relationships among barley crossbreed genotypes in Turkey. It is important that selection based on the genetic base in breeding programs via ISSR, in terms of breeding time. 14 ISSR primers generated a total of 97 bands, of which 81 (83.35%) were polymorphic. The highest total resolution power (RP) value was obtained from the F2 (0.53) and M16 (0.51) primers. According to the ISSR result, the genetic similarity index changed between 0.64–095; Lane 3 with Line 6 genotypes were the closest, while Line 36 were the most distant ones. The ISSR markers were found to be promising for assessing genetic diversity in barley crossbreed genotypes.

Keywords: barley, crossbreed, genetic similarity, ISSR

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Authors: Aydin M. Torkabadi, Ehsan Pourjavad

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A decade after the introduction of Lean in Saskatchewan’s public healthcare system, its effectiveness remains a controversial subject among health researchers, workers, managers, and politicians. Therefore, developing a framework to quantitatively assess the Lean achievements is significant. This study investigates the success of initiatives across Saskatchewan health regions by recognizing the Lean healthcare criteria, measuring the success levels, comparing the regions, and identifying the areas for improvements. This study proposes an integrated intelligent computing approach by applying Fuzzy Inference System (FIS) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). FIS is used as an efficient approach to assess the Lean healthcare criteria, and TOPSIS is applied for ranking the values in regards to the level of leanness. Due to the innate uncertainty in decision maker judgments on criteria, principals of the fuzzy theory are applied. Finally, FIS-TOPSIS was established as an efficient technique in determining the lean merit in healthcare systems.

Keywords: lean healthcare, intelligent computing, fuzzy inference system, healthcare evaluation, technique for order of preference by similarity to ideal solution, multi-criteria decision making, MCDM

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Authors: M. Aladwani, Y. Alarfaj

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The construction industry is currently experiencing a shift towards digitisation. This transformation is driven by adopting technologies like Building Information Modelling (BIM), drones, and augmented reality (AR). These advancements are revolutionizing the process of designing, constructing, and operating projects. BIM, for instance, is a new way of communicating and exploiting technology such as software and machinery. It enables the creation of a replica or virtual model of buildings or infrastructure projects. It facilitates simulating construction procedures, identifying issues beforehand, and optimizing designs accordingly. Drones are another tool in this revolution, as they can be utilized for site surveys, inspections, and even deliveries. Moreover, AR technology provides real-time information to workers involved in the project. Implementing these technologies in the construction industry has brought about improvements in efficiency, safety measures, and sustainable practices. BIM helps minimize rework and waste materials, while drones contribute to safety by reducing workers' exposure to areas. Additionally, AR plays a role in worker safety by delivering instructions and guidance during operations. Although the digital transformation within the construction industry is still in its early stages, it holds the potential to reshape project delivery methods entirely. By embracing these technologies, construction companies can boost their profitability while simultaneously reducing their environmental impact and ensuring safer practices.

Keywords: BIM, digital construction, construction technologies, digital transformation

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Authors: Baba Mbaye

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In collaborative filtering recommendation systems, a user receives suggested items based on the opinions and evaluations of a community of users. This type of recommendation system uses only the information (notes in numerical values) contained in a usage matrix as input data. This matrix can be constructed based on users' behaviors or by offering users to declare their opinions on the items they know. The cold start problem leads to very poor performance for new users. It is a phenomenon that occurs at the beginning of use, in the situation where the system lacks data to make recommendations. There are three types of cold start problems: cold start for a new item, a new system, and a new user. We are interested in this article at the cold start for a new user. When the system welcomes a new user, the profile exists but does not have enough data, and its communities with other users profiles are still unknown. This leads to recommendations not adapted to the profile of the new user. In this paper, we propose an approach that improves cold start by using the notions of similarity and semantic proximity between users profiles during cold start. We will use the cold-metadata available (metadata extracted from the new user's data) useful in positioning the new user within a community. The aim is to look for similarities and semantic proximities with the old and current user profiles of the system. Proximity is represented by close concepts considered to belong to the same group, while similarity groups together elements that appear similar. Similarity and proximity are two close but not similar concepts. This similarity leads us to the construction of similarity which is based on: a) the concepts (properties, terms, instances) independent of ontology structure and, b) the simultaneous representation of the two concepts (relations, presence of terms in a document, simultaneous presence of the authorities). We propose an ontology, OIVCSRS (Ontology of Improvement Visitor Cold Start in Recommender Systems), in order to structure the terms and concepts representing the meaning of an information field, whether by the metadata of a namespace, or the elements of a knowledge domain. This approach allows us to automatically attach the new user to a user community, partially compensate for the data that was not initially provided and ultimately to associate a better first profile with the cold start. Thus, the aim of this paper is to propose an approach to improving cold start using semantic technologies.

Keywords: visitor cold start, recommender systems, collaborative filtering, semantic filtering

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Authors: Ahmad Shahin, Fadi Chakik, Walid Moudani

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Our study is about elaborating a potential solution for a search engine that involves semantic technology to retrieve information and display it significantly. Semantic search engines are not used widely over the web as the majorities are still in Beta stage or under construction. Many problems face the current applications in semantic search, the major problem is to analyze and calculate the meaning of query in order to retrieve relevant information. Another problem is the ontology based index and its updates. Ranking results according to concept meaning and its relation with query is another challenge. In this paper, we are offering a light meta-engine (QESM) which uses Google search, and therefore Google’s index, with some adaptations to its returned results by adding multi-query expansion. The mission was to find a reliable ranking algorithm that involves semantics and uses concepts and meanings to rank results. At the beginning, the engine finds synonyms of each query term entered by the user based on a lexical database. Then, query expansion is applied to generate different semantically analogous sentences. These are generated randomly by combining the found synonyms and the original query terms. Our model suggests the use of semantic similarity measures between two sentences. Practically, we used this method to calculate semantic similarity between each query and the description of each page’s content generated by Google. The generated sentences are sent to Google engine one by one, and ranked again all together with the adapted ranking method (QESM). Finally, our system will place Google pages with higher similarities on the top of the results. We have conducted experimentations with 6 different queries. We have observed that most ranked results with QESM were altered with Google’s original generated pages. With our experimented queries, QESM generates frequently better accuracy than Google. In some worst cases, it behaves like Google.

Keywords: semantic search engine, Google indexing, query expansion, similarity measures

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Authors: Yunseok Noh, Chang-Uk Kwak, Sun-Joong Kim, Seong-Bae Park

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Scripts are one of the basic text resources to understand broadcasting contents. Since broadcast media wields lots of influence over the public, tools for understanding broadcasting contents are more required. Topic modeling is the method to get the summary of the broadcasting contents from its scripts. Generally, scripts represent contents descriptively with directions and speeches. Scripts also provide scene segments that can be seen as semantic units. Therefore, a script can be topic modeled by treating a scene segment as a document. Because scripts consist of speeches mainly, however, relatively small co-occurrences among words in the scene segments are observed. This causes inevitably the bad quality of topics based on statistical learning method. To tackle this problem, we propose a method of learning with additional word co-occurrence information obtained using scene similarities. The main idea of improving topic quality is that the information that two or more texts are topically related can be useful to learn high quality of topics. In addition, by using high quality of topics, we can get information more accurate whether two texts are related or not. In this paper, we regard two scene segments are related if their topical similarity is high enough. We also consider that words are co-occurred if they are in topically related scene segments together. In the experiments, we showed the proposed method generates a higher quality of topics from Korean drama scripts than the baselines.

Keywords: broadcasting contents, scripts, text similarity, topic model

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Authors: Loai AbdAllah, Mahmoud Kaiyal

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Missing values in real-world datasets are a common problem. Many algorithms were developed to deal with this problem, most of them replace the missing values with a fixed value that was computed based on the observed values. In our work, we used a distance function based on Bhattacharyya distance to measure the distance between objects with missing values. Bhattacharyya distance, which measures the similarity of two probability distributions. The proposed distance distinguishes between known and unknown values. Where the distance between two known values is the Mahalanobis distance. When, on the other hand, one of them is missing the distance is computed based on the distribution of the known values, for the coordinate that contains the missing value. This method was integrated with Wikaya, a digital health company developing a platform that helps to improve prevention of chronic diseases such as diabetes and cancer. In order for Wikaya’s recommendation system to work distance between users need to be measured. Since there are missing values in the collected data, there is a need to develop a distance function distances between incomplete users profiles. To evaluate the accuracy of the proposed distance function in reflecting the actual similarity between different objects, when some of them contain missing values, we integrated it within the framework of k nearest neighbors (kNN) classifier, since its computation is based only on the similarity between objects. To validate this, we ran the algorithm over diabetes and breast cancer datasets, standard benchmark datasets from the UCI repository. Our experiments show that kNN classifier using our proposed distance function outperforms the kNN using other existing methods.

Keywords: missing values, incomplete data, distance, incomplete diabetes data

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Authors: Shohei Maruyama, Yasuo Matsuyama, Sachiyo Aburatani

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The development of the method to annotate unknown gene functions is an important task in bioinformatics. One of the approaches for the annotation is The identification of the metabolic pathway that genes are involved in. Gene expression data have been utilized for the identification, since gene expression data reflect various intracellular phenomena. However, it has been difficult to estimate the gene function with high accuracy. It is considered that the low accuracy of the estimation is caused by the difficulty of accurately measuring a gene expression. Even though they are measured under the same condition, the gene expressions will vary usually. In this study, we proposed a feature extraction method focusing on the variability of gene expressions to estimate the genes' metabolic pathway accurately. First, we estimated the distribution of each gene expression from replicate data. Next, we calculated the similarity between all gene pairs by KL divergence, which is a method for calculating the similarity between distributions. Finally, we utilized the similarity vectors as feature vectors and trained the multiclass SVM for identifying the genes' metabolic pathway. To evaluate our developed method, we applied the method to budding yeast and trained the multiclass SVM for identifying the seven metabolic pathways. As a result, the accuracy that calculated by our developed method was higher than the one that calculated from the raw gene expression data. Thus, our developed method combined with KL divergence is useful for identifying the genes' metabolic pathway.

Keywords: metabolic pathways, gene expression data, microarray, Kullback–Leibler divergence, KL divergence, support vector machines, SVM, machine learning

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Authors: Tanish Mittal, Preyansh Agrawal, Esha Pahwa, Aarya Makwana

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Multi-Scale and U-shaped Networks are widely used in various image restoration problems, including deblurring. Keeping in mind the wide range of applications, we present a comparison of these architectures and their effects on image deblurring. We also introduce a new block called as NFResblock. It consists of a Fast Fourier Transformation layer and a series of modified Non-Linear Activation Free Blocks. Based on these architectures and additions, we introduce NFResnet and NFResnet+, which are modified multi-scale and U-Net architectures, respectively. We also use three differ-ent loss functions to train these architectures: Charbonnier Loss, Edge Loss, and Frequency Reconstruction Loss. Extensive experiments on the Deep Video Deblurring dataset, along with ablation studies for each component, have been presented in this paper. The proposed architectures achieve a considerable increase in Peak Signal to Noise (PSNR) ratio and Structural Similarity Index (SSIM) value.

Keywords: multi-scale, Unet, deblurring, FFT, resblock, NAF-block, nfresnet, charbonnier, edge, frequency reconstruction

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Authors: Jakub Havlicek, Jiri Cajthaml

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The article describes the effect of the replacement of the used reference coordinate system in the georeferencing of an old map of Europe. In particular, it was the map entitled “Europe, the Map of Rivers and Mountains on a 1 : 12 000 000 Scale”, elaborated by professor D. Cipera and Dr. J. Metelka for Otto’s Geographic Atlas of 1924. The work was most likely produced using the equal-area conic (Albers) projection. The map was georeferenced into three types of projection – the equal-area conic, cylindrical Plate Carrée and cylindrical Mercator map projection. The map was georeferenced by means of the affine and the second-order polynomial transformation. The resulting georeferenced raster datasets from the Plate Carrée and Mercator projection were projected into the equal-area conic projection by means of projection equations. The output is the comparison of drawn graphics, the magnitude of standard deviations for individual projections and types of transformation.

Keywords: georeferencing, reference coordinate system, transformation, standard deviation

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Authors: G. S. Thakur

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This paper presents a Fuzzy Soft Recruitment Model (FSRM) for faculty selection of MHRD technical institutions. The selection criteria are based on 4-tier flexible structure in the institutions. The Advisory Committee on Faculty Recruitment (ACoFAR) suggested nine criteria for faculty in the proposed FSRM. The model Fuzzy Soft is proposed with consultation of ACoFAR based on selection criteria. The Fuzzy Soft distance similarity measures are applied for finding best faculty from the applicant pool.

Keywords: fuzzy soft set, fuzzy sets, fuzzy soft distance, fuzzy soft similarity measures, ACoFAR

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Authors: Jia Xu

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There is a lot of bottom space in the teaching area of Zijingang Campus of Zhejiang University, which benefits to the ventilation, heat dissipation, circulation, partition of quiet and noisy areas and diversification of spaces. Hangzhou is hot in summer but cold in winter, so teachers and students spend much less time in the bottom space of buildings in winter than in summer. Recently, depending on the teachers and students’ proposals, the school transformed the bottom space in the teaching area to provide space for relaxing, chatting and staying in winter. Surveying and analyzing the existing ways to transform, the paper researches deeply on the transformation projects of bottom space in the teaching buildings. It is believed that this paper can be a salutary lesson to make the bottom space in the teaching areas of universities richer and bring more diverse activities for teachers and students.

Keywords: bottom space, teaching area, transformation, Zijingang Campus of Zhejiang University

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Authors: A. Selmi

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Free vibration analysis of homogenous and axially functionally graded simply supported beams within the context of Euler-Bernoulli beam theory is presented in this paper. The material properties of the beams are assumed to obey the linear law distribution. The effective elastic modulus of the composite was predicted by using the rule of mixture. Here, the complexities which appear in solving differential equation of transverse vibration of composite beams which limit the analytical solution to some special cases are overcome using a relatively new approach called the Differential Transformation Method. This technique is applied for solving differential equation of transverse vibration of axially functionally graded beams. Natural frequencies and corresponding normalized mode shapes are calculated for different Young’s modulus ratios. MATLAB code is designed to solve the transformed differential equation of the beam. Comparison of the present results with the exact solutions proves the effectiveness, the accuracy, the simplicity, and computational stability of the differential transformation method. The effect of the Young’s modulus ratio on the normalized natural frequencies and mode shapes is found to be very important.

Keywords: differential transformation method, functionally graded material, mode shape, natural frequency

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Authors: Hsin Hua He

Abstract:

The purpose of this study is to strengthen the social cohesion of the local community by injecting the cultural and creative concept into the industrial heritage transformation. The paradigms of industrial heritage research tend to explore from the perspective of space analysis, which concerned less about the cultural regeneration and the development of local culture. The paradigms of cultural quarter research use to from the perspective of creative economy and urban planning, concerned less about the social impacts and the interaction between residents and industrial sites. This research combines these two research areas of industrial heritage and cultural quarter, and focus on the social and cultural aspects. The transformation from the industrial heritage into a cultural park not only enhances the cultural capital and the quality of residents’ lives, but also preserves the unique local values. Internally it shapes the local identity, while externally establishes the image of the city. This paper uses Westergasfabriek Cultural Park in Amsterdam as the case study, through literature analysis, field work, and depth interview to explore how the cultural regeneration transforms industrial heritage. In terms of the planners’ and residents’ point of view adopt the theory of community participation, social capital, and sense of place to analyze the social impact of the industrial heritage transformation. The research finding is through cultural regeneration policies like holding cultural activities, building up public space, social network and public-private partnership, and adopting adaptive reuse to fulfil the people’s need and desire and reach the social cohesion. Finally, the study will examine the transformation of Taiwan's industrial heritage into cultural and creative quarters. The results are expected to use the operating experience of the Amsterdam cases and provide directions for Taiwan’s industrial heritage management to meet the cultural, social, economic symbiosis.

Keywords: cultural regeneration, community participation, social capital, sense of place, industrial heritage transformation

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Authors: Bilge Ozel

Abstract:

Cities are high-complex living organisms and are subjects to continuous transformations produced by the stress that derives from changing conditions. Today the metropolises are seen like “development engines” of the countries and accordingly they become the centre of better living conditions that encourages demographic growth which constitutes the main reason of the changes. Indeed, the potential for economic advancement of the cities directly represents the economic status of their countries. The term of “resilience”, which sees the changes as natural processes and represents the flexibility and adaptability of the systems in the face of changing conditions, becomes a key concept for the development of urban transformation policies. The term of “resilience” derives from the Latin word ‘resilire’, which means ‘bounce’, ‘jump back’, refers to the ability of a system to withstand shocks and still maintain the basic characteristics. A resilient system does not only survive the potential risks and threats but also takes advantage of the positive outcomes of the perturbations and ensures adaptation to the new external conditions. When this understanding is taken into the urban context - or rather “urban resilience” - it delineates the capacity of cities to anticipate upcoming shocks and changes without undergoing major alterations in its functional, physical, socio-economic systems. Undoubtedly, the issue of coordinating the urban systems in a “resilient” form is a multidisciplinary and complex process as the cities are multi-layered and dynamic structures. The concept of “urban transformation” is first launched in Europe just after World War II. It has been applied through different methods such as renovation, revitalization, improvement and gentrification. These methods have been in continuous advancement by acquiring new meanings and trends over years. With the effects of neoliberal policies in the 1980s, the concept of urban transformation has been associated with economic objectives. Subsequently this understanding has been improved over time and had new orientations such as providing more social justice and environmental sustainability. The aim of this research is to identify the most applied urban transformation methods in Turkey and its main reasons of being selected. Moreover, investigating the lacking and limiting points of the urban transformation policies in the context of “urban resilience” in a comparative way with European interventions. The emblematic examples, which symbolize the breaking points of the recent evolution of urban transformation concepts in Europe and Turkey, are chosen and reviewed in a critical way.

Keywords: resilience, urban dynamics, urban resilience, urban transformation

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Authors: Alexander Scott English, Yilin Ma, Xiaoying Liu

Abstract:

The widespread use of artificial intelligence in everyday life has triggered a fervent discussion covering a wide range of areas. However, to date, research on the influence of gender in various segments and factors from a social science perspective is still limited. This study aims to explore whether there are gender differences in human trust in AI for its application in basic everyday life and correlates with human perceived similarity, perceived emotions (including competence and warmth), and attractiveness. We conducted a study involving 321 participants using a two-subject experimental design with a two-factor (masculinized vs. feminized voice of the AI) multiplied by a two-factor (pitch level of the AI's voice) between-subject experimental design. Four contexts were created for the study and randomly assigned. The results of the study showed significant gender differences in perceived similarity, trust, and perceived emotion of the AIs, with females rating them significantly higher than males. Trust was higher in relation to AIs presenting the same gender (e.g., human female to female AI, human male to male AI). Mediation modeling tests indicated that emotion perception and similarity played a sufficiently mediating role in trust. Notably, although trust in AIs was strongly correlated with human gender, there was no significant effect on the gender of the AI. In addition, the study discusses the effects of subjects' age, job search experience, and job type on the findings.

Keywords: artificial intelligence, gender differences, human-robot trust, mediation modeling

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Authors: Jiya Mohammed, Tsadu Shuaib, Yusuf Abdulhakeem

Abstract:

The research work focuses on the cases of MHD boundary layer flow past a stretching plate with heat transfer and viscous dissipation. The non-linear of momentum and energy equation are transform into ordinary differential equation by using similarity transformation, the resulting equation are solved using Adomian Decomposition Method (ADM). An attempt has been made to show the potentials and wide range application of the Adomian decomposition method in the comparison with the previous one in solving heat transfer problems. The Pade approximates value (η= 11[11, 11]) is use on the difficulty at infinity. The results are compared by numerical technique method. A vivid conclusion can be drawn from the results that ADM provides highly precise numerical solution for non-linear differential equations. The result where accurate especially for η ≤ 4, a general equating terms of Eckert number (Ec), Prandtl number (Pr) and magnetic parameter ( ) is derived which was used to investigate velocity and temperature profiles in boundary layer.

Keywords: MHD, Adomian decomposition, boundary layer, viscous dissipation

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