Reviewerly/exHarmony huggingface dataset:
Recommendation Systems Applied in Turkish Real Estate Market

Today consumers are confronted with a very large number of products and services to choose from. This makes it difficult for users to find relevant products among a huge number of alternatives. A recommendation system is an extensive class of web applications that involves predicting the user responses to the options and helps users to find products of interest by analyzing their past transactions such as product views and purchases. There is also a similar problem in the real estate industry where thousands of properties are available for rentals or sales. In this work we firstly presented the details of a real estate recommender system developed for Zingat.com and then, we explained how we implemented a fully functional recommendation system for property listings in Turkey. Since the number of listings is huge and new listings come and go frequently, it is a challenge to build a successful recommender system. We tackled this challenge by building a system which uses collaborative filtering and content-based filtering, separately. We also designed a scalable system architecture which can function under heavy load. In the future we plan to further improve this system by using diversification techniques and new solutions.
Analysis of College English Teaching in the Era of “Internet Plus”

The rapid development of the Internet has brought great opportunities to college English teaching. Therefore, college English teaching keeps pace with the trend of the times and constantly adapts to the development of society and the needs of students, so as to improve the quality of teaching. In the new era, people put forward higher requirements for the cultivation of talents in colleges and universities. This requires universities to realize the importance of “Internet plus” in the process of English teaching, and constantly innovate the English teaching model, so as to provide high-quality talents for the society. This paper analyzes the English Teaching in colleges and universities in the era of “Internet Plus”, with a view to providing some references for college English educators.
THE USE OF PICTURE SERIES-AIDED LEARNING STARTEGY TO IMPROVE STUDENTS’ WRITING ABILITY; A Case Study

This research is CAR (Classroom Action Research) conducted in SMP Negeri 1 Lamongan. This research uses picture aided learning startegy to improve students’ writing ability. The subjects of this study are the 28 (twenty eight) students from grade VII. The research was conducted in year 2018-2019. The results shows that picture series-aided learning can improve students’ writing ability. Their average scores increase from 56.86 into 77.87 (21.01 increase points), that can be elaborated as follows: 10.43 points increase, from 20.86 into 31.29, for content; 5.28 points increase, from 11.79 into 17.07, for language; and 5.29 points increase, from 24.21 into 29.50, for organization.
Mantis The Black-Box Scanner : Finding XSS vulnerabilities through parse errors

Abstract [en]Background. Penetration testing is a good technique for finding web vulnerabilities. Vulnerability scanners are often used to aid with security testing. The increased scope is becoming ...
Gradient-Based Competitive Learning: Theory

Abstract Deep learning has been recently used to extract the relevant features for representing input data also in the unsupervised setting. However, state-of-the-art techniques focus mostly on algorithmic efficiency and accuracy rather than mimicking the input manifold. On the contrary, competitive learning is a powerful tool for replicating the input distribution topology. It is cognitive/biologically inspired as it is founded on Hebbian learning, a neuropsychological theory claiming that neurons can increase their specialization by competing for the right to respond to/represent a subset of the input data. This paper introduces a novel perspective by combining these two techniques: unsupervised gradient-based and competitive learning. The theory is based on the intuition that neural networks can learn topological structures by working directly on the transpose of the input matrix. At this purpose, the vanilla competitive layer and its dual are presented. The former is representative of a standard competitive layer for deep clustering, while the latter is trained on the transposed matrix. The equivalence of the layers is extensively proven both theoretically and experimentally. The dual competitive layer has better properties. Unlike the vanilla layer, it directly outputs the prototypes of the data inputs, while still allowing learning by backpropagation. More importantly, this paper proves theoretically that the dual layer is better suited for handling high-dimensional data (e.g., for biological applications), because the estimation of the weights is driven by a constraining subspace which does not depend on the input dimensionality, but only on the dataset cardinality. This paper has introduced a novel approach for unsupervised gradient-based competitive learning. This approach is very promising both in the case of small datasets of high-dimensional data and for better exploiting the advantages of a deep architecture: the dual layer perfectly integrates with the deep layers. A theoretical justification is also given by using the analysis of the gradient flow for both vanilla and dual layers.
LibGuides: Technical Support: Olds College Account & Passwords

Get answers to your tech questions. Technical support for students and staff at Olds College is provided by the Learning Commons Service Desk and the Information Technology Department.
Redundancy Gateway Menggunakan Metode Failover dan Load Sharing Gateway

Failure to transfer data packets on a network becomes a big threat, both caused by link failures and heavy traffic loads. To maintain stability in the network, the VRRP gateway redundancy protocol is applied. From the results of the research conducted, it takes an average time to failover for 3.75ms from the master router to the backup router and an average packet loss that occurs as many as 3 packets and the average time needed to failover from the backup router back to master router for 1.37ms and 1.5 packet loss occurred. The results of load sharing research are able to make 1 router device as a master router in 2 VRID at once. Implementing both Failover and Load Sharing methods can improve connectivity in the network by ensuring connectivity can run stably and equally. Failover is used as a backup gateway redundancy and load sharing is used to divide the gateway load equally.
Combining User Feedback and Monitoring Data to Support Evidence-based Software Evolution

Context. Companies continuously explore their software systems to acquire evidence for software evolution, such as bugs in the system and new functional or quality requirements. So far, managers ha ...
Lessons from Walden: Thoreau and the Crisis of American Democracy. By Bob Pepperman Taylor. Notre Dame, IN: University of Notre Dame Press, 2020. 240p. $29.00 cloth.

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LibGuides: Centre for Arts, Memory and Communities (AMC): Research Data Management

Outlines how the library can support you in the effective management of the data you generate during your research.
Mining Association Rules from Semantic Web Data without User Intervention

With the introduction and standardization of the semantic web as the third generation of the web, this technology has attracted and received more human attention than ever. Thus, the amount of semantic web data is continuously growing, which makes them a rich source of useful data for data mining techniques. Semantic web data have some complexities, such as the heterogeneous structure of data, the lack of well-defined transactions, and the existence of typed relations between items. In this paper, a new technique named SWApriori is presented, which by using both entities and relations in the extraction of frequent itemsets, generates a new class of association rules (ARs) from semantic web data. The proposed technique by considering the complex heterogeneous nature of semantic web data, without any need to a domain expert, and without any data conversion to transactional data format extracts ARs from semantic web data directly. For evaluation, the proposed technique is applied to Factbook and DBPedia datasets. The experimental results demonstrate the ability of the proposed technique in extracting relational ARs from semantic web data by considering the mentioned challenges. Supplementary experiments show that the proposed technique can extract interesting patterns that are not discoverable by state-of-the-art association rule mining techniques.
Application of Virtual Reality Technology in the Real Estate Marketing Practices

This research has been carried out to archive the objectives of this study which are to identifythe challenges of applying virtual reality technology into the real estate marketing practices,to assess the acceptance level of real estate practitioners towards the application of virtualreality technology and to recommend the motivators that encourage the application of virtualreality technology into the real estate marketing practices.Apart from that, the problem statement is described in this study and the insight of thechallenges of VR into the practices of real estate in Malaysia are provided as well. Thechallenges are found to be the cost consideration of the application of VR, no sensoryexperience and not as matured to be adopted at the moment.The adopted research method has been carried with primary and secondary data collection.Primary data collection consists of quantitative and qualitative, quantitative can be thequestionnaire survey that constructed based on the aims and objectives of this research whichdistributed to the experienced respondents and the qualitative research method is includinginterviews with particular qualified personnel for a further and more detailed data collection.Then, the secondary data collection is from the literature study that found in the journal orarticle on the internet.For the research findings, most of the real estate practitioners are having high acceptancelevel towards the applications of VR technology. On top of that, the challenges of applyingthe VR technology into the real estate marketing practices are well identified from bothquestionnaire survey and interview. In fact, the main concern and challenges is the highcapital budget that required to apply this VR technology. Overall, the data collected has been considered to achieve the research objectives. On top of that, the contribution and theimplications of the findings is from the literature study as well as the data collected from theexperienced respondents that involved in real estate industry.
Automatic generation of anomaly reports in a Train Control System: Using Natural Language Generation and Case-Based Reasoning

In this thesis, we study automatically generating explanatory reports for anomalous incidents in a train control system (TCS) using Natural Language Generation (NLG). A TCS is a type of safety-critical software that allows train controllers to correctly set the tracks for a train to pass. The goal of this research is to process the majority of log files generated by such a system, detect anomalies that have occurred and represent that data in human-readable reports that explain anomalous incidents. The reports are generated by making use of NLG techniques, namely data-to-text. We design an NLG pipeline that incorporates novel graphical components. We perform all steps of the report generation process, which is the processing of data, anomaly detection and representing the data in natural language. To process the data we incorporate complex domain-specific rules which require extensive work to accommodate five separate types of event log files. Analyzing logs and detecting anomalous incidents proved complex due to the complicated structure of logs and the ill-defined relationships between different log file types. The log data explained with the NLG pipeline is more extensive than we have seen in literature, as it needs to be linked using complex domain-specific rules and includes temporal and geographical aspects of the railway system. Furthermore, the detected anomalies are very diverse and thus it is unclear what aspects should be included in a report for each anomalous case. We research whether a purely textual presentation or a combination of modalities provides higher information quality. The product of the NLG system are three presentation versions of incident reports, Text, TimeText and RailText. Each version focuses on different important aspects of the nature of the data, to explain anomalous incidents. Due to the diverse properties of the anomalous cases detected, we implement a Case-Based Reasoning (CBR) system to predict the appropriate presentation to explain each incident. We evaluate our work in two expert-based evaluation phases. The first phase evaluates the quality of the different report presentations. The second phase evaluates the feasibility of the CBR system and the quality of the reports chosen by CBR. The work in this thesis is significant as we manage to translate complex data into human-readable reports that are well received by experts and help in understanding anomalous cases. We learn that there is a difference in what presentation format provides the highest information quality of reports depending on the anomalous case being explained. Therefore we conclude that the properties of anomalous cases should be taken into account when generating anomalous reports in a TCS to ensure the highest perceived information quality of the reports. CBR is shown to perform that task well. Furthermore, we find that data familiarity of experts effects their preferences for report presentations.
Identifying Challenges in Cybersecurity Data Visualization Dashboards

Nowadays, a massive amount of cybersecurity data-objects, such as security events, logs,messages, are flowing through different cybersecurity systems. With the enormous fastdevelopment of different ...
한국어 중의적 비교 구문의 처리에 관한 안구운동추적연구

We investigated (1) whether the preferred interpretation of ambiguous Korean comparative constructions would be shifted depends on lexical-semantic features, (2) whether the processing differences between the Plain-NP comparatives and the Clausal-NP comparatives would be revealed during online processing, and (3) whether the parallelism effect in comparative sentences would occur. The results in sentence completion and comprehension tasks showed that participants recognized the difference between the Plain-NP comparatives and the Clausal-NP comparatives and distinguished them according to the meaning-based information such as the typicality of an event structure and the semantic relationship between the nouns which were the objects of comparing. The linear mixed-effects regression models in the eye-tracking experiment revealed that the reading times when the nouns with semantically-related information were used were significantly faster than when the proper names were used. However, the parallelism effect was not revealed significantly. Taken together, our results indicate that semantic information does affect processing ambiguous comparatives, while it is unlikely that this effect is sufficient to lead the parallelism effect.
FBI stresses online safety as virtually learning resumes for many

As more students head online for virtual learning, the importance of online safety for children and families has increased.
LibGuides: ENG102, Part I - MCCC Library resources, Searching and Databases: Home

Covering effective computer searching for locating academic resources using the MCCC Library’s online databases
Dispersion in Photonic Time Crystals

We present a framework for predicting the behavior of materials which are simultaneously strongly dispersive and time-dependent. We show that dispersion and time-dependence can cooperate to strongly enhance frequency conversion.
Uso de un ambiente virtual de aprendizaje en la ingeniería en sistemas computacionales del Tecnológico de Ciudad Valles como herramienta de apoyo a las clases presenciales

The article is the result of an educational research project of the National Technological Institute of Mexico that involves Virtual Learning Environments (AVA). The objective is to determine the impact of using a VPA as a tool in the teaching-learning process of the face-to-face classes of the Ciudad Valles Technology. The methodology is mixed, qualitative and quantitative. The quantitative number determines the number of teachers used by AVA, the number of students in a Blending Learning (B-Learning) course, the number of courses designed in Moodle. In the qualitative, the impact of B-Learning on students is analyzed; determining the degree of motivation and performance that is generated when using AVA and the ability to use information technology to generate their learning strategies. A composite and structural analysis of the AVA used in the institute is presented, the research hypothesis is disclosed: the use of an AVA as a b-learning strategy, improves the level of performance of student competencies compared to students who follow classroom learning strategies. The manner in which the research is conducted, the frame of reference is described and relevant results and conclusions are shown.
Regulating the Output Voltage of Buck-Boost Converters Using General Type2 Fuzzy Controller

Power electronic converters have been considered by many researchers and their control and robustness under various operating conditions has a great importance. The proposed type-2 fuzzy controller employs expert experience to control the power electronic converters, considering to their non-linear and time variant structure. Using type-2 fuzzy controller enhances the stability and robustness of system. This paper's attempt is to compare general and interval type-2 fuzzy controllers in terms of dealing with non-linear uncertain plants. It is shown that general type-2 fuzzy controller leads to more accuracy in comparison with interval type-2 and type-1 fuzzy controllers in regulating the output voltage, as it is shown in simulation part. To compare the performance of the controlling methods, the Euclidean norm of regulating error is calculated.
ANALISIS METODE PENGUKURAN KEMAMPUAN BERBAHASA BAGI ANAK: STUDI PADA ANAK PENDERITA AUTIS

This study aims to determine the language skills of children affected by autistic syndrome. In previous studies, children with autism were compared with a comparison group usually adjusted for age, IQ, or mental age to identify which aspects of language were uniquely impaired in autism. There are several drawbacks that arise from research using this approach, namely the heterogeneity of the autism population, mental retardation, developmental changes with age, and sample size and predictability. A new method is needed that is more capable of identifying aspects of language use for children with autism so that it can cover the deficiencies that exist from previous research methods.
Need Analysis of Development Work Sheet of Student (LKPD) in Writing Explanatory Text based on Fishbone Diagram

This research is a stage in the development of LKPD writing explanatory texts based on fishbone diagrams for senior high schools. This study is to describe needs analysis of students in writing explanatory texts. The research method used was a survey method. Data collection techniques in this study were questionnaires. This research uses a Likert scale to measure the attitudes, opinions, and or perceptions of students regarding LKPD developed. This study uses a questionnaire that was made in the form of a checklist with an assessment range of 1 to 5. The questionnaire compiled was addressed to students in four high schools in Pekanbaru. This sampling technique is based on quota sampling determined by the researcher. The data analysis technique is done by changing the category value into an assessment score and analyzing the score. The results showed that 51.2% of students were unfamiliar with the fishbone strategy and 88.2% of the students wanted a LKPD that was designed clearly and detail. This shows the need for preparation of LKPD to write explanatory texts based on fishbone diagrams.
Research Guides: Chromebooks for Class: Screenshots & Keyboard Shortcuts

This guide aims to be a basic introduction of the capabilities of a Chromebook for online classes and homework. It outlines how to access certain tools on a Chrome OS. For technology support, please submit a support ticket at help.evergreen.edu.
LibGuides: Diversity, Equity, and Inclusion in STEM: Articles

A guide to resources related to underrepresented groups in science, technology, engineering and mathematics.
Fluid Dynamics as a Foundation for Game Mechanics

This thesis investigates whether a game world based solely on fluid dynamics could be an interesting alternative to one based on rigid bodies by presenting a prototype to players where they can con ...
LibGuides: KU Online MGMT 620: Business Communication + Presentation: Citations

A resource guide to connect Kettering University Online students in MGMT 620 to research resources provided by the library.
EXPLORING THE LINKAGE BETWEEN CORRUPTION AND ECONOMIC DEVELOPMENT IN THE CASE OF SELECTED DEVELOPING AND DEVELOPED NATIONS

Corruption is like an epidemic that has the power to destroy a country's socioeconomic, financial, human and political environment. It has severe consequences in developing countries. This study has examined the impact of existing human, political, financial and economic factors on corruption for a set of panel countries. The data from 1995 to 2004 is used to serve this purpose. For examining the stationarity of the variables, Levin- Lin-Chu (2002), Fisher-ADF and Fisher-PP tests are applied. Pedroni Residual based Co-integration and FMOLS by Phillips and Hansen (1990) test has been used for examining the co-integration among the variables of the model. The speed of adjustment and short-run relationship has been tested through VECM. The estimated results show that exports, GDP per capita and political stability have a negative impact on corruption, whereas imports, financial development, human development index, bureaucracy, democracy and the rule of law have a positive relationship with corruption. The simplified procedures of import and export will help reduce the practice of bribes and corruption. The governments should take steps not only to increase the income, but also to improve the people's standard of living. There should be improvements in the political system. Democracy is also helpful to get rid of corruption.Keywords: Corruption, Economic Development, Financial Development, Human Development, Political Development, EthicsJEL Classifications: D7, O11, O15DOI: https://doi.org/10.32479/ijefi.8052
Improved particle swarm optimization by fast annealing algorithm

This paper proposes a hybrid particle swarm optimization with the fast-simulated annealing (PSO-FSA). The proposed algorithm is meant to solve high dimensional optimization problems based on two strategies, which are utilizing the particle swarm optimization to define the global search area and utilizing the fast-simulated annealing to refine the visited search area. To evaluate its performance, we examined the algorithm on 14 benchmark functions. Based on the results, PSO-FSA has higher accuracy result compared with particle swarm, simulated annealing. We also apply the algorithm in clustering problem, and the results shows that the proposed method has better accuracy than the optimization methods.
For Climbing Robots, the Sky's the Limit

A new generation of robots being developed by NASA's Jet Propulsion Laboratory can crawl, walk and even climb cliffs.