Miracle-dz/UniFAR-FTUs huggingface dataset:
LAPORAN KEUANGAN PEMERINTAH PUSAT (LKPP) TAHUN ANGGARAN 2008 MASIH DENGAN ”DISCLAIMER OPINION”

BPK RI (the state auditor body) plays a significant role to materialize and apply the principle of transparency and accountability on state financial report. Interim audit is conducted before the yearly financial audit. During the process of evidences collection, an auditor frequently faces a limitation of audit scope. An auditor must stay independent and look independent to maintain independency on opinion, judgment, as well as recommendation. The purpose of this research is to examine the effect of interim audit, scope of audit, and independency on auditor opinion judgment of auditors of BPK RI Bali Province Representatives. Data are collected using survey method administered to staffs of BPK Bali Province. Data consisting of 44 responses are analyzed using multiple regression model. The result shows that judgment of auditor opinion is able to be explained by variables of interim audit, scope of audit, and independency with value of R2 of 73.4 percent. While t-test result shows that partially the three variables also affect auditor opinion.
High Rates of Hepatitis B and C and HIV Infections among Blood Donors in Cameroon: A Proposed Blood Screening Algorithm for Blood Donors in Resource-Limited Settings

Background. Infections with human immunodeficiency virus (HIV), hepatitis B (HBV), and hepatitis C virus (HCV) are currently major public health problems. Methods. A retrospective study was conducted from January to June 2008 at the Blood Bank of the Central Hospital, Yaoundé (Cameroon). The objective was to study the prevalence of HIV, HBV, and HCV and their coinfections among blood donors. Results. A total of 4650 donors were identified, and the sex ratio (male/female) was 14/1. The median age of donors was 28 years (range: 16 to 69 years). Among blood donors, HBV, HIV, and HCV infection prevalences were 12.14% (n = 565) , 4.44% (n = 206), and 1.44% (n = 67), respectively. Coinfection with HIV and HBV was observed among 0.77% donors, followed by hepatitis B and C co-infection (0.21%) and HIV and HCV coinfection (0.06%). Co-infection with HIV-HBV-HCV was encountered in 2 donors. The HIV, HBV, and HCV infections lead to a destruction of one out of six sets of blood collected. Conclusion. There is a need to review policies for blood collection from donors, by modifying the algorithm of blood donors testing. Pretesting potential donors using rapid tests could help to avoid collection and destruction of (infected) blood.
Safety aware robot coverage motion planning with virtual-obstacle-based navigation

A coverage motion planning (CMP) is a kind of coverage path planning, which requires the robot path to fill every grid of the workspace. It is an essential issue in plenty of robotic applications. Safety aware collision-free coverage motion planning of an autonomous vehicle is one of the major challenges in intelligent vehicle systems. Many studies have been focused on the obstacle avoidance to prevent “too close” or “too far” from obstacles, but difficult to obtain an optimal path. In this paper, a virtual obstacle (VO) based safety aware strategy integrated with a biologically inspired neural network (BNN) method is proposed for CMP in a non-stationary environment as safety consideration is greatly crucial in vehicle CMP. The real-time vehicle trajectory is planned through the varying neural activity landscape that represents the dynamic environment. The proposed model for vehicle navigation with safety consideration is capable of planning a real-time appropriate trajectory. The proposed approach is capable of overcoming the either “too close” or “too far” shortcoming. Simulation and comparison studies validate that the proposed model is capable of performing CMP mission to plan more reasonable and shorter collision-free trajectories in non-stationary and unstructured environments.
Information Theory Filters for Wavelet Packet Coefficient Selection with Application to Corrosion Type Identification from Acoustic Emission Signals

The damage caused by corrosion in chemical process installations can lead to unexpected plant shutdowns and the leakage of potentially toxic chemicals into the environment. When subjected to corrosion, structural changes in the material occur, leading to energy releases as acoustic waves. This acoustic activity can in turn be used for corrosion monitoring, and even for predicting the type of corrosion. Here we apply wavelet packet decomposition to extract features from acoustic emission signals. We then use the extracted wavelet packet coefficients for distinguishing between the most important types of corrosion processes in the chemical process industry: uniform corrosion, pitting and stress corrosion cracking. The local discriminant basis selection algorithm can be considered as a standard for the selection of the most discriminative wavelet coefficients. However, it does not take the statistical dependencies between wavelet coefficients into account. We show that, when these dependencies are ignored, a lower accuracy is obtained in predicting the corrosion type. We compare several mutual information filters to take these dependencies into account in order to arrive at a more accurate prediction.
Defining the NonProfit Sector: A Cross-National Analysis

The growth of the non-profit, voluntary or third sector has been widely recognized throughout the world. This text seeks to provide a definition and a common classification of the non-profit sector, while recognizing the great diversity of voluntarism internationally. The remainder of the text is devoted to country-by-country definitions of the sector in 13 representative states from the developed, developing and post-socialist worlds. Among the countries covered are: USA, UK, France, Germany, Japan, India, Brazil, Egypt and Hungary. The study demonstrates that the division of societies into public and private is too simplistic, and that a third sector with its own characteristic features and dynamics has already emerged as a powerful force in the global economy.
Learning from Landowners: Examining the Role of Peer Exchange in Private Landowner Outreach through Landowner Networks

More than one-third of forested land in the United States is owned by individuals or families, making these lands a significant source of the nation's forest resources and services. Yet investments in traditional expert-led outreach efforts, including financial incentive programs and technical assistance for management plan development, have failed to engage the vast majority of U.S. forest landowners. Through case studies of five diverse landowner networks, this study explored peer exchange among landowners as an alternative means of fostering engagement. Sixty-one in-depth interviews revealed common themes across cases that contributed to landowner participation and learning, including maintaining an atmosphere conducive to social learning, emphasis on local information and hands-on learning, and access to rich networks that include both practical peer-derived information and trusted technical expert-derived information. These findings enrich existing landowner engagement theory by offering insight into landowner networks as an avenue for serving an ever-growing population of family forest owners.
"Artificial spores" - hybrid alginate microcapsules with encapsulated yeast cells

The present work describes the fabrication, structure and functional characterization of composite microcapsules containing encapsulated viable yeast cells, fluorescently labeled liposomes and magnetic nanoparticles embedded in a calcium alginate matrix produced by ink-jet printing. The proliferation of the encapsulated cells under favorable conditions (presence of nutrients, temperature) is used as a biological trigger for the disintegration of the microcapsules and the liberation of the encapsulated sub-micron particles. The principle of “artificial spores”, i.e. the possibility to repeatedly stop and restart the cell proliferation process has also been demonstrated. Such biologically triggered release from composite microcapsules is novel and offers potentially interesting applications such as autonomous release of bactericides or fungicides only under conditions that are favorable for microbial growth.
Genetic-PSO Fuzzy Data Mining With Divide and Conquer Strategy

Nowadays, discovery the association rules is an important and controversial area in data mining research studies. These rules, describe noticeable association relationships among different attributes. While most studies have focused on binary valued transaction data, in real world applications, there data usually consist of quantitative values. With that in mind, in this paper, we propose a fuzzy data mining algorithm for extracting membership functions from quantitative transactions. This is a hybrid genetic-pso algorithm for finding membership functions suitable for mining problems by a strong cooperation of GA and PSO. This algorithm integrates the two techniques entire run of simulation in each iteration, a part of population are substituted by new ones generated by means of GA, while the other part is the same of previous generation but moved on the solution space by PSO. At the end, best final sets of membership functions in all the populations are gathered to be used for mining fuzzy association rules. According to experimental results, the proposed genetic-pso fuzzy data mining algorithm has a good effect on fitness of membership functions.
Architecture and Design of Efficient 3D Network-on-Chip (3D NoC) for Custom Multicore SoC

During this last decade, Network-on-Chips (NoC) have been proposed as a promising solution for future systems on chip design. It offers more scalability than the shared-bus based interconnection, allows more processors to operate concurrently. Because NoC has dedicated wires, performance can be predicted. In this context, we proposed a 2D-NoC named OASIS, which is a 4x4 mesh topology design using Wormhole switching and Stall-and-Go flow control scheme. Although OASIS-NoC has its advantages over the shared-bus based systems, it has also some limitations such as high power consumption, high cost communication, and low throughput. To overcome those limitations we propose a 3D-NoC (3D OASIS-NoC) which is an extension to our 2D OASIS-NoC. In this paper we describe the 3D OASIS-NoC architecture in a fair amount of detail and present preliminary evaluation results.
The Association between α4-Integrin, P-Selectin, and E-Selectin in an Allergic Model of Inflammation

In this study, we examined the relationship between the endothelial selectins (P-selectin and E-selectin) and whether they are critical for α4-integrin–dependent leukocyte recruitment in inflamed (late phase response), cremasteric postcapillary venules. Animals were systemically sensitized and 2 wk later challenged intrascrotally with chicken ovalbumin. Leukocyte rolling flux, adhesion, and emigration were assessed at baseline and 4 and 8 h postantigen challenge. There was a significant increase in leukocyte rolling flux, adhesion, and emigration in sensitized and challenged mice at both 4 and 8 h. At 8 h, the increase in leukocyte rolling flux was ∼50% inhibitable by an anti–α4-integrin antibody, 98% inhibitable by fucoidin (a selectin-binding carbohydrate), and 100% inhibitable by an anti–P-selectin antibody. P-selectin–deficient animals displayed no leukocyte rolling or adhesion at 8 h after challenge. However, at 8 h there were many emigrated leukocytes in the perivascular space suggesting P-selectin–independent rolling at an earlier time point. Indeed, at 4 h postantigen challenge in P-selectin–deficient mice, there was increased leukocyte rolling, adhesion, and emigration. The rolling in the P-selectin– deficient mice at 4 h was largely α4-integrin dependent. However, there was an essential E-selectin– dependent component inasmuch as an anti–E-selectin antibody completely reversed the rolling, and in E-selectin and P-selectin double deficient mice rolling, adhesion and emigration were completely absent. These results illustrate that P-selectin underlies all of the antigen-induced rolling with a brief transient contribution from E-selectin in the P-selectin–deficient animals. Finally, the antigen-induced α4-integrin–mediated leukocyte recruitment is entirely dependent upon endothelial selectins.
Using Temporal Discovery and Data-Driven Journey-Maps to Predict Customer Satisfaction

Timely identification of potentially dissatisfied customers enables us to take meaningful interventions to improve customer experience. The goal of this work is to create models that can predict customer satisfaction for active insurance claims at any point in time during the claim process. In order to capture relevant temporal information, we introduce the concept of a "journey-map": a data-driven structured timeline where all the relevant events pertinent to the claim process are registered and positioned temporally with respect to each other. We also describe a machine-learning-based framework to extract and discover meaningful information relevant for the task at hand. The result of this work is a deployed system currently used during the claims process.
Learning of agents with limited resources - extended version

In this paper we present our preliminary investigation of rational agents who can learn from their experience. We claim that such agents need to combine at least three attributes ‐ deductive reasoning based on currently possessed knowledge, inductive learning from their history and awareness of passing time (including the necessity to commit computational resources to tasks which need to be carried out). We analyze how those aspects interact and initiate discussion of whether it is feasible, with current technology i n each of the related fields, to combine them in a valuable way. More detailed description of this research can be found at http://www.cs. lth.se/home/Slawomir Nowaczyk/phd-desc/ This document is a more elaborate version of extended
Formation of Social Capital for Common Pool Resource Management

A standard optimal investment model is used to analyze farmers' decision to accumulate social capital in terms of participating in collective activities for irrigation management. Several predictions borne out by the data are presented in this study. Social capital investment in small irrigation groups (1) decreases when the farmer's field is located at the downstream area where water is scarce; (2) increases when farmers have larger ricefields; (3) decreases when farmers pay the irrigation service dues; and (4) increases when the farmer belongs to a heterogeneous group which facilitates collective action when pooling resources to reduce the risks involved in rice farming. Moreover, the farmers' social capital investment in other small irrigation groups in the irrigation system 1) increases when farmers have larger rice-growing areas; 2) increases when there is a high level of trust among the farmers; but 3) declines as the opportunity cost of time increases due to coordination and participation in collective activities with farmers from other areas of the system.
CHARACTERIZATION OF OPTIMAL STOPPING REGIONS OF AMERICAN ASIAN AND LOOKBACK OPTIONS

A general framework is developed to analyze the optimal stopping (exercise) regions of American path‐dependent options with either the Asian feature or lookback feature. We examine the monotonicity properties of the option values and stopping regions with respect to the interest rate, dividend yield, and time. From the ordering properties of the values of American lookback options and American Asian options, we deduce the corresponding nesting relations between the exercise regions of these American options. We illustrate how some properties of the exercise regions of the American Asian options can be inferred from those of the American lookback options.
Hyperprojective hierarchy of qcb0-spaces

We extend the Luzin hierarchy of qcb0-spaces introduced in [ScS13] to all countable ordinals, obtaining in this way the hyperprojective hierarchy of qcb0-spaces. We generalize all main results of [ScS13] to this larger hierarchy. In particular, we extend the Kleene-Kreisel continuous functionals of finite types to the continuous functionals of countable types and relate them to the new hierarchy. We show that the category of hyperprojective qcb0-spaces has much better closure properties than the category of projective qcb0-space. As a result, there are natural examples of spaces that are hyperprojective but not projective.
Circular and elliptical modeling for pupil boundary in closed-up human eye images

This paper proposes a method for detecting and modeling human pupil boundary in closed-up eye images. The proposed method is a model-based approach aiming to detect accurate pupil boundary in iris images. These images inhibit large variations such as different pupil size, shape and intensity background. The proposed method utilizes intensity and gradient information to detect edges of pupil boundary. These edges are often far from actual edges of pupil. Accurate edges of pupil are obtained by refined searching over a blurred input eye image using gradient information. The obtained edges are then modeled using circle and ellipse. From our experimental results, elliptical fitting yields better performance than circular fitting. A correct detection rate (CDR) of circular and elliptical fitting using CASIA-IRISV3-Interval database is 95.93% and 99.4%, respectively, whereas a CDR of circular and elliptical fitting using KSIP_DB01R database is 90.78% and 93.02%, respectively.
Including user devices and context into STEM education for minorities

Learning process can be enhanced by offering students, resources that are closer to their reality. Besides, the wide use of Mobile devices brings the opportunity to go beyond classrooms and computer based learning objects. The AUTO4L Framework for personalized automated composition of Web resources based the user context. AUTO4L is highly applicable to STEM classrooms. The philosophy of AUTO4L allows to students and teachers working collaboratively in order to create dynamic learning resources. AUTO4L integrates these resources with user preferences and context. AUTO4L offers a personal experience based in Mobile devices. This paper discusses the ways in which AUTO4L could be used to extend STEM beyond walls.
Human activity recognition with HMM-DNN model

Activity recognition commonly made use of hidden Markov models (HMMs) to exploit temporal dependencies between activities. The emission distribution of HMMs could be represented by generative models, such as Gaussian mixture models (GMMs), or discriminative models, such as random forest (RF). These models, especially discriminative ones, needed to manually extract features from the sensor data, which relied on the experience of the researchers, and usually was a time-consuming task when complicated features are extracted. Furthermore, with these methods, the process of quantization of the sensor data, i.e., manual feature extraction, might lose much useful information and thus led to a performance debasement. In this paper, we recommend deep neural networks (DNNs) for modeling the emission distribution of HMMs, which automatically learn features suitable for classification from the raw sensor data and then estimate the posterior probabilities of the HMM states. We collected a dataset of daily activities and based on which experiments were performed to compare our HMM-DNN model with both HMM-GMM and HMM-RF. The results illustrated that HMM-DNN outperformed both HMM-GMM and HMM-RF.
A Study on Various Cryptographic Key Management and Distribution System in Secure Multicast Communications

Many emerging web and Internet applications are based on group communication model. In the Internet, multicast has been used successfully to provide an efficient, best-effort delivery service from a sender to a large group of receivers. Thus, securing group communication (i.e., providing confidentiality, authenticity, and integrity of messages delivered between group members) becomes an important Internet design issue. This paper presents a comprehensive summary of recent works addressing the number of scalable approaches which have been proposed for Key Distribution in Secure Multicast Communication.
A novel fully soft switched (zero voltage on and zero current off) boost converter with reduced conduction loss

A novel fully soft switched PWM converter is proposed. By means of two auxiliary resonant inductors the current stresses in the main switches and rectifier diode are reduced. With this new resonant FSS-PWM cell the voltage stress and current stress of the boost diode are both reduced comparing with conventional ZCS-PWM converter. Hence low break-down voltage diodes can be employed to lower the conduction loss of the diode. A 1.5 kW/100 kHz prototype is made, and the theoretical analysis is verified by simulation and experiment.
Hierarchical memory system design for a heterogeneous multi-core processor

Multi-core architecture has become hot issue recently both for performance and power consideration. Memory system is the bottleneck under this circumstance. A multi-core architecture using simple cores based on transport triggered architecture is proposed. This architecture has a uniform programming view. The memory system design exploration and optimization is done and a hierarchical memory system is designed. A balanced memory bandwidth is provided to the multi-core architecture.
Cross-autocorrelations among asset classes: Evidence from the mutual fund industry

Purpose - The purpose of this paper is to examine asset class cross-autocorrelations at the macro-level by exploring the return associations among mutual fund asset classes. The low transactions costs of trading mutual funds make this extension important since informed traders can potentially use mutual funds to exploit asset class return cross-autocorrelations that were not exploitable with individual securities. Design/methodology/approach - The Granger causality tests and correlation results are employed to ascertain whether significant relationships exist among asset classes. Using a time series of 2,739 daily returns for 641 mutual funds comprising 20 asset classes, trading strategies are developed using the initial sample and evaluated out-of-sample on a risk-adjusted basis. Findings - Both the cross-autocorrelations and Granger causality tests suggest that most of the domestic equity asset class returns can predict future global and international equity returns. Further, the trading-rule portfolios provide a greater return per unit of risk (Sharpe and Treynor ratios) thus dominating all buy-and-hold portfolios. Risk-adjusted excess returns (Jensen's a) of the trading rules are positive and statistically significant at the 1 per cent level. The results of trading strategies also reveal that there are no statistically significant return differences between load and no-load funds. Research limitations/implications - Redemption fees seem to be standard practice now, except for money market funds and funds specially designed for market timers. Thus, the trading strategy returns of this paper overestimate actual returns. However, investors may still find the proposed trading strategies beneficial because redemptions fees can be avoided if investors get the opportunities to trade in mutual fund supermarkets. The trading strategies may have implications for other international markets where the sizes and styles of the mutual funds' assets are increasing enormously with a few trading restrictions. Originality/value - A noteworthy and original contribution of this study is the two-day Granger causality test. This paper documents that the duration of mutual funds' return predictability extends beyond a one-day horizon. The duration of daily mutual fund return predictability is believed to be unexplored and should be of considerable relevance to practitioners and regulators.