Miracle-dz/UniFAR-FTUs huggingface dataset:
Public administration employees’ readiness and acceptance of e-government

Despite the widespread use of digital technology in public administration, little attention has been given to understanding e-government adoption and acceptance by its employees. This paper examines the level of public administration employees’ ICT literacy and the extent to which they support e-government. The influence of background variables is also explored in the analysis. A structured online questionnaire was used to gather data from employees of Croatian central government bodies. According to the results, surveyed employees rated their general ICT literacy as high. They are more confident in their basic ICT skills than in advanced ones. The level of such skills is associated with socio-demographic characteristics. The findings also indicate that employees accept e-government, but they are less satisfied with its implementation. However, socio-demographic factors do not affect to a great extent employees’ acceptance and satisfaction with e-government. The study expands previous research by analysing the group differences at both manifest and latent levels. It also contributes to the identification of factors that may influence e-government success.
Analysis of Regional Economic Competitiveness of Gorontalo Province (Case Study of Gorontalo Province Corn Commodity)

This study aims to determine the analysis of regional economic competitiveness in Gorontalo Province by looking at the value of export of superior corn commodity agriculture. This research covers regional areas in Gorontalo Province. The specific objective to be achieved is to obtain analytical data on the economic competitiveness of the Gorontalo Province in terms of the competitiveness of corn commodity exports. This list is expected to be an input for stakeholders to issue policies in increasing economic competitiveness in corn commodities in Gorontalo Province. This research was carried out in Gorontalo Province with objects in 5 districts and 1 city in Gorontalo Province detecting the competitiveness of each region. The method of analysis of this study uses the RCA (Revealed Comparative) comparative analysis method with the time of the 2013-2017 study. The results of the RCA (Revealed Comparative Advantage) analysis describe the competitiveness of Gorontalo Province's corn commodity exports experiencing fluctuations in which Gorontalo Province's corn commodity exports in 2014, 2015 and 2017 had strong competitiveness, while in 2013 and 2016 Gorontalo Province's maize commodity decreased due to that year Gorontalo Province did not export corn besides the absence of exports because domestic corn prices were quite good.Keywords: Competitiveness, Corn Leading Commodities
Influences of Knowledge Sharing in Improving Facilities Management Performance of Private Finance Initiative Projects

Managing organization performance is very important in supply chain management. The situation is more critical in delivering public demands to develop and supply new facilities under Private Finance Initiative (PFI) projects. Thus, numerous issues and problems occurs in PFI projects that can affect the performance of Facilities Management (FM) phase has been highlighted by many researchers repetitively. This cross-sectional research aims are to discovers the influences of Knowledge Sharing (KS) in improving performance of PFI projects at FM phase. A set of questionnaires was developed and distributed to 151 respondents who is directly involve as practitioners in PFI-FM projects. However, only 111 responses were analysed using the SmartPLS 3.0 software. The finding shows that working culture (WC), staff attitude (SA), motivation to share (MV) and opportunities to share (OP) has significant influences with KS towards performance of PFI projects at FM phase. Meanwhile, nature of knowledge to share (NK) not significantly influences KS in PFI-FM projects.
Illegal Parking Detection Algorithm Based on Video Surveillance

Aiming at the shortcomings of traditional illegal parking detection methods such as low accuracy rate and high costs,this paper proposes a detection algorithm based on video surveillance.The moving objects are detected in video by using a codebook background modeling algorithm.The interference of other objects is filtered by computing the area of the connected region.Vehicles are classified according to the parking time.If illegal parked vehicles are found,the system will alarm.Experimental results demonstrate that the algorithm obtains high accuracy and achieves real-time performance.
Mining search logs for usage patterns

One of the greatest opportunities and challenges of the 21st century is the ever increasing significance of data. Data underpins our businesses and our economy, providing awareness and insight into in every sphere of life; from politics to the environment, arts and society. The everyday interactions between people and devices can be harnessed to power a new generation of products and services, allowing us to better understand human needs, aspirations and behaviour. Of all the data to which we have access, there is none more valuable than the trace people leave when they search for digital information. In browsing the web, people reveal something about their behaviour and habits, but little about their intent. By contrast, when people search for information, they express in their own words their explicit needs and goals. This data represents a unique resource that offers extraordinary potential for delivering insights that can drive the next generation of digital services and applications. Various studies have been undertaken to understand how and why people interact with search engines. Such studies have led to the creation of frameworks that describe distinct patterns of use, ranging from individual queries to entire information seeking episodes. These patterns may focus on information seeking behavior [9], the types of search tasks that users perform [10], their goals and missions [5], their task switching behavior [4], or the tasks, needs and goals that they are trying to address when using search systems [10, 11]. Moreover, the academic community is not alone in showing an interest in mining search logs. Two highly influential commercial organisations, ElasticSearch and LucidWorks, have both recently released independent logfile analysis platforms (Kibana and SiLK respectively [13, 14]). What unites all of these efforts is the belief that finding distinct, repeatable patterns of behaviour can lead to a better understanding of user needs and ultimately a more effective search experience. In this chapter, we explore the use of data mining techniques to find patterns in search logs, focusing on the application of open source tools and publicly available data.
MOVING ONWARD: TRANSNATIONALISM AND FACTORS INFLUENCING ROHINGYAS’ MIGRATION FROM BANGLADESH TO MALAYSIA

Continuous human rights persecutions have forced nearly one million Rohingyas to flee from Myanmar and seek refuge in Bangladesh. While their forced migration to the first asylum country of Bangladesh is inevitable, some have been compelled to move onward to other transit countries. Existing studies indicate various factors influencing cross-border activities among different segments of immigrants. They also suggest that the degree of transnationalism affects different kind of people on the move, subsequently brings about unique consequences to receiving community. In this study, we aim to determine factors contributing to the onward movement of Rohingyas from their refugee camps in Cox’s Bazar, Bangladesh to Malaysia. We utilize the broader concept of transnationalism in order to gauge the Rohingyas’ perception and the realities they face in relation to their onward movement from Bangladesh to Malaysia. This study employed three methods of data collection namely a survey, an in-depth interview and a focus group discussion in engaging the Rohingyas in Klang Valley, Malaysia. Resulting from a two-part of data collection conducted in 2013 and 2016, we found that the onward movement of Rohingyas was mostly driven by poverty, unconducive livelihood experiences, limited access to humanitarian aid, and inadequate refugee protection in Bangladesh. Meanwhile, positive Rohingyas’ perception toward Malaysia, coupled with the availability of job opportunities have attracted them to choose Malaysia as the next asylum country. While this study enriches the existing literatures on transnationalism and onward movement of refugees, it also provides empirical evidences for humanitarian assistances in Bangladesh and Malaysia. Keywords: Forced migration, onward movement, refugees, Rohingya, transnationalism. Cite as: Ab. Wahab, A. & Khairi, A. (2019). Moving onward: Transnationalism and factors influencing Rohingyas’ migration from Bangladesh to Malaysia. Journal of Nusantara Studies, 4(1), 49-68. http://dx.doi. org/10.24200/jonus.vol4iss1pp49-68
Secure Data Sharing In Multi-Owner for Dynamic Groups in Cloud

The major aim of this technique is a secure multi-owner knowledge sharing theme. It indicates that any user within the cluster will firmly share knowledge with others by the world organization trust worthy cloud. This theme is ready to support dynamic teams. Efficiently, specifically, new granted users will directly rewrite knowledge files uploaded before their participation whereas not contacting with knowledge owners. User revocation square measure is just achieved through a very distinctive revocation list whereas not modification of the key. The keys of the remaining users then the size and computation overhead of cryptography square measure constant and freelance with the amount of revoked users. We've a bent to gift a secure and privacy-preserving access management to users that guarantee any member throughout a cluster to anonymously utilize the cloud resources. Moreover, the $64000 identities of information owners square measure disclosed by the cluster manager once disputes occur. We offer rigorous security analysis, and perform intensive simulations to demonstrate the potency of our theme in terms of storage and computation overhead. Cloud computing provides a cheap associated economical resolution for sharing cluster resource among cloud users sharing knowledge associate degree passing throughout a terribly multi-owner manner whereas protecting knowledge Associate in Nursing identity privacy from an world organization responsible cloud continues to be a issue, because of the frequent modification of the membership.
AGRICULTURAL DEVELOPMENT LED INDUSTRIALIZATION IN ETHIOPIA: STRUCTURAL BREAK ANALYSIS

The Ethiopian economy is heavily dependent on agriculture. Unlike other emerging African countries, Ethiopian economic growth is driven mostly by public investments in infrastructure and agricultural productivity improvement. However, the performance of agriculture was not satisfactory as poverty remained. Lack of appropriate policies and strategies was considered as the ultimate reason for the sector’s past stagnation. Consequently, to solve this problem and promote agricultural and economic growth, government a national development strategy called Agricultural Development Led Industrialization (ADLI). While, ADLI argues for a mutually re-enforcing transformation of agriculture and industry, the primary goal of ADLI was to alleviate absolute poverty. The strategy was also complemented by different plans so as to empower industrial sector in addition to agriculture. Therefore, ADLI policy’s effectiveness was tested with Structural Break Analysis. The results showed that there was structural break in economic growth in 2004, indicating a higher and steady growth afterwards. The descriptive results also showed that agricultural sector remained the dominant contributor to the GDP growth of the country with only recently that the service sector is outperforming agricultural sector. The contribution of the industrial sector remained low, even though recently it started performing well.
Recommendation System Based On Association Rules For Distributed E-Learning Management Systems

Abstract Traditional Learning Management Systems are installed on a single server where learning materials and user data are kept. To increase its performance, the Learning Management System can be installed on multiple servers; learning materials and user data could be distributed across these servers obtaining a Distributed Learning Management System. In this paper is proposed the prototype of a recommendation system based on association rules for Distributed Learning Management System. Information from LMS databases is analyzed using distributed data mining algorithms in order to extract the association rules. Then the extracted rules are used as inference rules to provide personalized recommendations. The quality of provided recommendations is improved because the rules used to make the inferences are more accurate, since these rules aggregate knowledge from all e-Learning systems included in Distributed Learning Management System.
From Natural Language Text to Visual Models: A Survey of Issues and Approaches

Over the last 20 years, research groups focused on automating the process of extracting valuable information from Natural Language text in order to discover data and process models. In this context, several tools and approaches have been proposed. The overall objective of this survey is to examine existing literature works that transform textual specifications into visual models. This paper aims to give a comprehensive account of the existing tools meant to discover data and process models from natural language text. Our analysis focuses on approaches of these tools in the model extraction process and highlight issues of each proposed approach. In the case of object oriented software modelling of data models extraction we analyze the degree of automation, efficiency and completeness of the transformation process. Regarding process models extraction, the study is not limited only to business process discovery, but it also provides case studies from several fields such as medical or archaeological. Even if not all the tools developed are clearly depicting a Natural Language Processing technique, a review of each approach is presented.
Analysis of a Global Futures Trend-Following Strategy

Systematic traders employ algorithmic strategies to manage their investments. As a result of the deterministic nature of such strategies, it is possible to determine their exact responses to any conceivable set of market conditions. Consequently, sensitivity analysis can be conducted to systematically uncover undesirable strategy behavior and enhance strategy robustness by adding controls to reduce exposure during periods of poor performance/unfavorable market conditions, or to increase exposure during periods of strong performance/favorable market conditions. In this study, we formulate both a simple systematic trend-following strategy (i.e., trading model) to simulate investment decisions and a market model to simulate the evolution of instrument prices. We then map the relationship between market model parameters under various conditions and strategy performance. We focus, in particular, on identifying the performance impact of changes in both serial dependence in price variability and changes in the trend. The long-range serial dependence of the true range worsens performance of the simple classic trend-following strategy. During periods of strong performance, the dispersion of trading outcomes increases significantly as long-range serial dependence increases.
The space - time cube revisited from a geovisualization perspective

At the end of the sixties Hagerstrand introduced a space-time model which included features such as a Space-TimePath, and a Space-Time-Prism. His model is often seen as the start of the time-geography studies. Throughout the years his model has been applied and improved to understand our movements through space. Problems studied can be found in different fields of geography, and range from those on an individual movement to whole theories to optimize transportation. From a visualization perspective the Space-Time-Cube was the most prominent element in Hagerstrand’s approach. In its basic appearance these images consist of a cube with on its base a representation of geography (along the x- and y-axis), while the cube’s height represents time (z-axis). A typical Space-Time-Cube could contain the space time-paths of for instance individuals or bus routes. However, when the concept was introduced the options to create the graphics were limited to manual methods and the user could only experience the single view created by the draftsperson. An alternative view on the cube would mean to go through a laborious drawing exercise. Today’s software has options to automatically create the cube and its contents from a database. Data acquisition of space-time paths for both individuals and groups is also made easier using GPS. Today, the user’s viewing environment is, by default, interactive and allows one to view the cube from any direction. In this paper an extended interactive and dynamic visualization environment is proposed, and demonstrated, in which the user has full flexibility to view, manipulate and query the data in a Space-Time-Cube. Included are options to move slider planes along each of the axes to for instance select, or highlight a period in time or location in space. Examples will be discussed in which the time axis is manipulated by for instance changing world time for event time (time cartograms). Creativity should not stop here since it has been shown that especially an alternative perspective on the data will sparkle the mind with new ideas. The user should be allowed to for instance let the x- and/or y-axis be represented by other variables of the theme studied. Since the cube is seen as an integral part of a geovisualization environment the option to link other views with other graphic representation does exist.
eCREST: a novel online patient simulation resource to aid better diagnosis through developing clinical reasoning

In this In Practice report, we describe a novel educational resource using online patient simulations—the electronic Clinical Reasoning Educational Simulation Tool (eCREST). eCREST seeks to improve the quality of diagnoses from common respiratory symptoms seen in primary care by focusing on developing clinical reasoning skills. It has recently been tested with final-year medical students in three UK medical schools. In response to interest, we are exploring the use of eCREST to other medical schools in the UK and internationally and to other professional groups and will conduct further evaluation. The idea for eCREST arose following research using online patient simulations assessing how physicians make decisions about whether to investigate for cancer. This research found that general practitioners (GPs) made appropriate decisions when they had the relevant information they needed (ie, including common, non-specific symptoms that were not initially volunteered by patients). In cases where they did not have essential information, they were less likely to investigate for possible cancer. In 40% of cases, however, GPs did not elicit this essential information.1 If these patterns are seen in clinical practice, they could lead to delays in diagnosis of cancer. To reduce diagnostic delays, the Institute of Medicine, among others, recommends the teaching of clinical reasoning should start in medical school, to equip future doctors with the skills necessary to elicit essential information.2 Clinical reasoning can be broadly defined as the thought processes required to apply clinical knowledge to seek information, identify likely diagnoses and reach clinical decisions. Clinical reasoning teaching in medical schools often relies on exposure to real patients, for example during clinical placements.3 There are several logistical and educational reasons to introduce …
Monotone Structure In Discrete Event Systems

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Forecasting Real-Time Data Revisions in the Presence of Model Uncertainty 1

Traditionally, researchers have used linear regression models when working with real-time data revisions. In this paper, we forecast real-time data revisions with a wide set of models including linear, structural break and regime-switching models with and without heteroskedasticity. We address the issues raised by the presence of model uncertainty through the use of Bayesian model averaging (BMA). Using UK data, we calculate predictive densities for real-time data revisions which average over the model space and compare them with the single best model and the linear model. We also present evidence about whether the revision process is unbiased and calculate various functions of the predictive density which might be of interest to a statistical agency. In contrast to the BMA approach, the traditional linear model yields very misleading predictives.
Designing and Implementing a Modeling and Verification Tool for Object-aware Processes

This master’s thesis focuses on the modeling component of PHILharmonicFlows. This component had to be reworked based on the Universal Windows Platform. Therefore the thesis explains the design and the implementation itself. The rework was needed to ensure that the framework can be used in the future and also to be able to use the modeling tool on different devices. The design focuses especially on the expressions and the roles and permissions. While all points did exist in previous versions they were not satisfying for the user. Therefore the original concept was adapted and extended. For the expressions a new concept was created that allows the modeler to create expressions that are understandable by the system. While the expression-modeling is completely free it is guided at the same time and errors are automatically prevented whenever this is possible. In case of the roles and permissions the old concept allowed the user to see and adapt them in a table. This table was not very intuitive and the user had to invest much time to understand the whole concept. This was simplified in the course of this thesis. The goal was to give the modeler an understandable way to set and adapt roles as well as permissions. To achieve this goal the input of both was shifted from the table to the single objects they belong to. This way the user can adapt them better. Furthermore the verification process has been analyzed and an example of how the verification can be done and a way for errors to be reported to the user was built to demonstrate the applicability. It is important to note that although there is only a single verification running at the moment the concept is built so that it can be extended in the future without any problems.