Miracle-dz/UniFAR-FTUs huggingface dataset:
The design of traffic control system in networks —— Kalman control algorithm

The rate-based traffic control is one of the important means that avoid congestion and guarantee high throughput for ABR communication in ATM networks. However, the propagation delay in networks has a great adverse effect on it. This paper applies Kalman control algorithm for the design of traffic controller, which can overcome the adverse effect caused by propagation delay better. Theoretical analysis shows that the scheme guarantees no buffer overflow and utilizes the bandwidth fairly and sufficiently, and the dynamical quality is much better than PID controller, which are verified by simulation.
The Effects of Public Investments and Accessibility to National Markets on the Demand for Distance Education

Public investments are directed to the social and economic areas. The state must carry public investments and services to every corner of the country, such as transportation, sewage, energy, education and health care by considering social stability and meeting human needs. Otherwise, unrest and disobedience may start to be experienced in the under developed regions and migration begins towards the developed areas in which the infrastructure services are completed. The regional insufficiency in public investments creates political, social and economic imbalances and instability. Differences in physical, social and geographical conditions between the regions of a country are generally based on the problems such as, the uneven distribution of the population, the differences in agricultural production and dissemination of industrial activities only in certain regions. The regions which are close to the national market are generally known to be more developed due to the use of market advantage. Transportation infrastructure and access to the national market affect the economic performance of the regions. In all provinces of Turkey, Anadolu University Open Education System has an important place by providing open and distance learning services. In this study, the relationship between the demands of open education system is investigated both with public investments and national market accessibility index respectively. For this purpose, different regression models were established and these models were evaluated statistically. In conclusion, the presence of linear positive correlation was determined.
Pet Loss: Understanding Disenfranchised Grief, Memorial Use, and Posttraumatic Growth

ABSTRACT The growing body of literature exploring pet loss suggests that many bereaved pet owners experience disenfranchised grief. Disenfranchised grief occurs when a loss is unacknowledged and the bereaved are unable to express their grief. When grief is considered illegitimate, the bereaved may experience a variety of adverse psychological outcomes, including increased distress and reduced quality of life. Additionally, when grief is inhibited, the individual may be less likely to experience positive changes such as posttraumatic growth. Few studies have considered the relationship between disenfranchisement and posttraumatic growth following the loss of a companion animal. This study investigated the relationship between disenfranchised grief, memorialization, and posttraumatic growth in bereaved pet owners. Grief severity was assessed as a moderator. Using an online survey, respondents (n = 133) completed standardized measures, including the Pet Bereavement Questionnaire, the Loss of Social Support subscale from the Grief Experience Questionnaire, and the Posttraumatic Growth Inventory-Short Form (PTGI-SF). As hypothesized, there was a significant interaction between disenfranchised grief, grief severity, and posttraumatic growth, suggesting that disenfranchised grief inhibits posttraumatic growth when grief severity is high. Contrary to the hypothesis, there was no relationship between memorial quantity or type and posttraumatic growth. Overall, this study shows that disenfranchised grief can inhibit posttraumatic growth following the loss of a pet, highlighting the complicated relationship between posttraumatic growth, grief intensity, and disenfranchised grief.
Transmission and Documentation of Orang Asli Indigenous Knowledge in ‘Green Technology’ for Sustainable Development in Malaysia

This study aims to preserve and document the corpus of Orang Asli Indigenous Knowledge in ‘Green Technology’ (IKGT). This knowledge is at risk of being lost due to the impact of colonization, habitat destruction and modernization. Indigenous knowledge of Orang Asli is naturalistic and environmentally friendly which is used to reduce the human impact on the environment as well as to create a sustainable development. Hence, this study was conducted to explore the indigenous knowledge in green technology of Orang Asli and how they transmit this knowledge to preserve their environment. This study adopts a qualitative approach through exploratory study whereby the study was carried out at the Orang Asli settlements located in Peninsular Malaysia. Data sources were obtained from the village headman (Tok Batin) and tribal elders who served as informants using indepth interview, field observation, and document analysis. The conceptual framework in this study was based on An Integrated Model of Indigenous Economy, Social World and Ecosystems Model. Five aspects; (i) medicine, (ii) food, (iii) handicraft, (iv) music, and (v) forestry were selected to be studied. The interviews were audio-recorded for data analysis, transcribed verbatim and analyzed through International Journal of Academic Research in Business and Social Sciences Vol. 9 , No. 5, May, 2019, E-ISSN: 2222-6990 © 2019 HRMARS 196 Atlas.ti software. The key result of this study reveals that Orang Asli tribes in the designated area practice IKGT throughout their lives. This study contributed to the body of knowledge in terms of expanding the Orang Asli indigenous knowledge. The finding also shows that Orang Asli conserves natural resources without damaging the biodiversity. The implication of this study is to educate and inculcate awareness among all levels of the community to practice environmental sustainability and in the future to make the environment ‘greener’.
Integrated characters with dialogue and tutorial strategies

In this deliverable, we introduce three new virtual character support types (Critic, Quiz and Diagnosis) which are linked to different kinds of conceptual knowledge (such as semantic feedback or multiple choice questions) generated within the DynaLearn software. We show how this knowledge is extracted and transformed into character-specific dialogs that are presented by the virtual characters but also encourage the learner to engage and participate. For this process, we rely on the architecture and dialog management system developed in earlier deliverables. Finally, we investigate how different characters and support types can be combined with each other to from integrated dialogs to even further support and engage learners.
Categorizations of structure living arrangements of adolescents after parental separation

Abstract This study identified the different categorizations of “living arrangements of adolescents” after parental separation in the literature and examined the situations in which health and wellbeing differences were observed among adolescents. Twenty-two peer-reviewed articles based on original data produced by self-administered questionnaires from quantitative studies were selected. Grouping studies according to the type of custody categorization allowed the comparison of different studies using the same categorization. It is of note that the same categorization of adolescent custody gave rise to inconsistent results in terms of health and wellbeing outcomes.
A Service quality evaluation system of third party logistics by college students under the Chinese E-commerce environment

Chinese e-commerce has developed rapidly in the recent years, making the scale of the third party logistics (3PL) business constantly larger and the competition fiercer. Hence, ensuring service quality of logistics and improving satisfaction of logistics service have been the keys to survive for 3PL enterprises. Meanwhile, college students have been important members in the online shopping industry, while their needs for logistics service differ with other customer groups. Consequently, 3PL enterprises should find out the need of college students and constantly improve their logistics service to achieve success in competition. The paper presents a service quality evaluation system of 3PL enterprises by college students under the Chinese e-commerce environment, based on SERVQUAL model. Anempirical analysis of STO Express, a leader of Chinese 3PLenterprises, is conducted then to test the service quality oflogistics and excavate the main driving factors to improve servicefor STO Express.
Nonlinearity and Endogeneity in Macro-Asset Pricing

Linear asset-pricing relations, with macroeconomic factors as state variables, have found wide usein empirical finance. Applications of such relations range from academic studies of market efficiency andmarket anomalies to practical uses such as risk management and estimation of the cost of capital. Theseapplications make two key assumptions: that the relationship is exclusively linear, and that the macroeconomicfactors are exogenous to returns. For the set of macrofactors commonly used in these applications, bothassumptions run counter to economic intuition. We set out to demonstrate that they are also counter toempirical evidence.We carry out this task using tests for linear and nonlinear Granger causality. We find linear and nonlinearfeedback between stock returns and commonly used macroeconomic pricing factors. We also find linear andnonlinear feedback between residuals from linear pricing relations and returns. In addition, there is littleevidence to suggest that neglected autoregressive or autoregressive conditionally heteroskedastic dynamics areresponsible for these findings, implying that the underlying dynamics are complicated. Thus, linearasset-pricing relations omit interesting and potentially useful aspects of the relationship between stock returnsand the macroeconomy.
Deep RNNs for video denoising

Video denoising can be described as the problem of mapping from a specific length of noisy frames to clean one. We propose a deep architecture based on Recurrent Neural Network (RNN) for video denoising. The model learns a patch-based end-to-end mapping between the clean and noisy video sequences. It takes the corrupted video sequences as the input and outputs the clean one. Our deep network, which we refer to as deep Recurrent Neural Networks (deep RNNs or DRNNs), stacks RNN layers where each layer receives the hidden state of the previous layer as input. Experiment shows (i) the recurrent architecture through temporal domain extracts motion information and does favor to video denoising, and (ii) deep architecture have large enough capacity for expressing mapping relation between corrupted videos as input and clean videos as output, furthermore, (iii) the model has generality to learned different mappings from videos corrupted by different types of noise (e.g., Poisson-Gaussian noise). By training on large video databases, we are able to compete with some existing video denoising methods.
Reading Motivation of Online News among Youth in Sub-Urban Area

In studying Internet, we need to take account for differences in places. This is because the Internet affords to show different patterns in which people in different types of places access and use the Internet. Meanwhile, many current studies proved that people increasingly turn to the Internet for daily news and this trend also included youth as one of the increasing readers. Therefore, we seek to explore the gratifications gained by youth through reading online news by specifically focusing youths in suburban area. Findings through survey among 300 youths in Perak, Malaysia suggested that reading online news and youth is not a new trend anymore and all online news publishers need to reconsider some betterment in order to produce better online news in future.
Reinventing Public Sector for Innovativeness and Performance: A Case Study of University of the Punjab, Lahore

Today’s complex and competitive work environment has urged organizations both public and private for revisiting their practices, management styles and attitudes for improved performance. There is a great realization that when an organization adopts innovativeness, creativity and sate of the art practices in all of its dimensions, it becomes successful. Literature on this subject also reveals that public sector organizations universally suffer from bureaucratic behaviors, centralized systems and rigid practices and therefore, needs more of such innovativeness through reinventing their existing ways, behaviors and systems (Moghaddam et al., 2015, Osborne and Gaebler 1992). This study towards its attempt towards reinventing the public sector organization aims to access how organizational innovativeness impacts the performance using University of the Punjab as a case in point. The study sample consisted of 50 head of departments. The study used a modified instrument that measures both innovative orientation, which is based on the extensively tested Covin and Slevin (1989) scale and innovation management, which is based on Stevenson’s (1983) conceptualization of innovation as a set of opportunity-based management practices. Performance is multi-dimensional in nature; therefore, both financial and non-financial performance indicators have been used. Relationships between these constructs have been analyzed through PLS-SEM (Partial Least Square Structural Equation Modeling). The results demonstrate that a greater strategic orientation and better reward philosophy positively influence organizational performance and satisfaction. Limited evidence was found about the direct relationship between innovative orientation and financial performance. The results indicate that there is limited innovative orientation and innovation management in University of the Punjab which has theoretical and practical implications. The study offers recommendations for reinventing public sector through bringing in innovativeness, efficiency and agility towards improved organizational performance.
Traffic Engineering Design Principles And Practice

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Knowledge Acquisition in Nepalese Telecom Industry

This research paper presents the Knowledge Management practice in Nepalese telecom sector. This study is based on cross section analysis of 85 observations for analyzing relationship between the knowledge management (KM) practices status in Nepalese telecom sector. The methodology used by Kohli (1993) and Daroch (2003) has been used for the research. Survey instruments we reorganized into one part and five factors. Spearman Rank Correlation, Analysis of variance (ANOVA), Cranach’s alpha etc. is used for data analysis. The valid response rate of 70 % was found. Among the factors that designed for knowledge acquisition, information input- employee has less mean score and information input-financial has high mean score than the others factors. In case of Information input-competitors, Nepalese telecom industry analyzes the financial contribution of their products or services. Employees of Nepal telecom has rated higher mean value in the KM practices i.e. knowledge acquisition, which means Nepal telecom appeared good in KM practices than Ncell. There is a significant difference between Nepal telecom and Ncell in term of the knowledge acquisition. Nepal telecom has better KA (Knowledge Acquisition) practices. Correlation matrix was computed to assess the extent or degree of relationship in between the factors or the research variables.
Health systems characteristics

In 2018, the Inter-American Development Bank and the OECD launched a survey to collect information on key health systems characteristics in Latin American and Caribbean (LAC) countries. This paper presents the information provided by 21 of these countries. It describes country-specific arrangements to organise the population coverage against health risks and the financing of health spending. It depicts the organisation of health care delivery, focusing on the public/private mix of health care provision, provider payment schemes, user choice and competition among providers, as well as the regulation of health care supply and prices. Finally, this document provides information on governance and resource allocation in health systems (decentralisation in decision-making, nature of budget constraints and priority setting).
Korean Named Entity Recognition and Classification using Word Embedding Features

Named Entity Recognition and Classification (NERC) is a task for recognition and classification of named entities such as a person's name, location, and organization. There have been various studies carried out on Korean NERC, but they have some problems, for example lacking some features as compared with English NERC. In this paper, we propose a method that uses word embedding as features for Korean NERC. We generate a word vector using a Continuous-Bag-of-Word (CBOW) model from POS-tagged corpus, and a word cluster symbol using a K-means algorithm from a word vector. We use the word vector and word cluster symbol as word embedding features in Conditional Random Fields (CRFs). From the result of the experiment, performance improved 1.17%, 0.61% and 1.19% respectively for TV domain, Sports domain and IT domain over the baseline system. Showing better performance than other NERC systems, we demonstrate the effectiveness and efficiency of the proposed method.
Feature selection methods for SVM classication of microarray data

Linear support vector machines have been used in microarray experiments to predict a certain class of a sample tissue (e.g. healthy or tumor) using the mRNA expression of different genes. In measuring tens of thousands of genes, a microarray dataset includes many genes that are uninformative with respect to the classes. Finding subsets of genes for the SVM to train on could help improve the generalization of the algorithm and reveal a small set of relevant genes that could be used to build a cheaper diagnostic test.
Enforcing Security Policies in Open Source JVM

Safe execution of untrusted mobile code is one of the most important problems in mobile code security.Model Carrying Code(MCC) provides a model-centered framework for safe execution of untrusted mobile code by taking both code producers and code consumers into consideration.Security policy specification and enforcement are important parts of MCC.An approach to formal specification and runtime enforcement of security policy has been proposed and implemented for Java mobile code running on open source JVM Kaffe and Linux operating system.Some useful works have been done on specification of security policies,the enforceable Extend Finite State Automata(EFSA) model and the method of monitoring on process level to catch system call information.It is indicated that our approach present a effective way to support MCC and implement security policy enforcement.
Extracting reliability of the products through user reviews

As the number of available products increases, consumers are often feel enforced to search through online reviews to make an informed product choice. Therefore, it has become important to develop methods to help customers to find the best products that fit their request. This paper analyzes the two dimensions of the review rating process: feature extraction and sentiment analysis. In feature extraction, we used term frequencies and adopted several algorithms to reduce the dimension of the feature set. For sentiment analysis, extracted feature set is used with developed algorithms to determine the polarity of the reviews. Several experiments are done to test the success of the system. As a result, we did not only able to provide detailed feature-based ratings to the users but also able to propose more reliable rating scores than the websites of the products. Keywords: Sentiment Analysis, Feature Extraction, User Review, Rating, WordNet, Polarity
An All-sky Autonomous Star Map Identification Algorithm Based on Genetic Algorithm

As a spacecraft attitude measurement instrument,CCD star tracker has a lot of advantages.But it needs an all-sky autonomous star map identification al gorithm to support its operation.The existing star map identification algorithm can be considered as a mode identification method.The article considers the sta r map identification as a combined optimal problem and tries to solve it by mean s of genetic algorithm.The simulation results show that compared with the exist ing star map identification algorithm,the algorithm presented in the paper has the advantages of robust and real time properties and it only needs a sams sized dat abase.
Automatic supervised thesauri construction with roget's thesaurus

Thesauri are important tools for many Natural Language Processing applications. Roget's Thesaurus is particularly useful. It is of high quality and has been in development for over a century and a half. Yet its applications have been limited, largely because the only publicly available edition dates from 1911. This thesis proposes and tests methods of automatically updating the vocabulary of the 1911 Roget's Thesaurus. I use the Thesaurus as a source of training data in order to learn from Roget's for the purpose of updating Roget's. The lexicon is updated in two stages. First, I develop a measure of semantic relatedness that enhances existing distributional techniques. I improve existing methods by using known sets of synonyms from Roget's to train a distributional measure to better identify near synonyms. Second, I use the new measure of semantic relatedness to find where in Roget's to place a new word. Existing words from Roget's are used as training data to tune the parameters of three methods of inserting words. Over 5000 new words and word-senses were added using this process. I conduct two kinds of evaluation on the updated Thesaurus. One is on the procedure for updating Roget's. This is accomplished by removing some words from the Thesaurus and testing my system's ability to reinsert them in the correct location. Human evaluation of the newly added words is also performed. Annotators must determine whether a newly added word is in the correct location. They found that in most cases the new words were almost indistinguishable from those already existing in Roget's Thesaurus. The second kind of evaluation is to establish the usefulness of the updated Roget's Thesaurus on actual Natural Language Processing applications. These applications include determining semantic relatedness between word pairs or sentence pairs, identifying the best synonym from a set of candidates, solving SAT-style analogy problems, pseudo-word-sense disambiguation, and sentence ranking for text summarization. The updated Thesaurus consistently performed at least as well or better the original Thesaurus on all these applications.