Miracle-dz/UniFAR-FTUs huggingface dataset:
SAĞLIK HİZMETLERİ ARZINDA DEFANSİF TIP VE HEKİMLERİN KARAR VERME ALGISI

Amaç: Bu çalışmada, sağlık hizmetleri arzında defansif tıp ve hekimlerin karar verme algıları arasındaki ilişkinin incelenmesi amaçlanmıştır. Gereç ve Yöntem: Araştırma, Konya ilinde Özel Akademi Meram Hastanesi, Özel Akademi Konya Hastanesi, Farabi Hastanesi ve Konya Göz Hastanesi’nde görev yapmakta olan hekimler üzerinde uygulanmıştır. Nicel araştırma deseni kullanılan araştırmaya 32 kadın 70 erkek olmak üzere toplam 102 hekim katılmıştır. Araştırmada örneklem grubunun oluşturulmasında kolayda örneklem yöntemi, verilerin toplanmasında ise anket tekniği kullanılmıştır. Çalışmada demografik bilgileri içeren “kişisel bilgi formu” kullanılmıştır. Hekimlerin karar verme algılarını ölçmek için Scott ve Bruce (1995) tarafından geliştirilen Taşdelen (2002) tarafından Türkçeye uyarlanan Karar Verme Stilleri Ölçeği ile birlikte hekimlerin defansif tıp tutumlarını ölçmek amacıyla Başer ve Ark. (2014) tarafından geliştirilen Defansif Tıp Tutum Ölçeği kullanılmıştır. Bulgular: Araştırmaya katılan hekimlerin %31,4’i kadın, %68,6’sı erkektir. Katılımcıların %39,2’si 35-44 yaş aralığındadır. Çalışılan birimlere baktığımızda hekimlerin çoğu %44,1 ile dahili birimlerde çalışmaktadır. Katılımcıların %60,8’i 11 yıl ve üstü süre hekimlik yaptığı görülmüştür. Çocuk sayısı incelendiğinde %39,2’inin 2 çocuk sahibi olduğu görülmüştür. Karar verme ile defansif tıp arasında negatif yönde düşük düzeyde anlamlı bir ilişki tespit edilmiştir. Hekimlerin karar verme ile defansif tıp tutumları arasındaki ilişki incelenmiş ve sonucunda karar verme stilleri ile defansif tıp arasında negatif yönde düşük düzeyde anlamlı bir ilişki tespit edilmiştir (r=-,229; p<0,05). Defansif tıp ile karar verme puan ortalamaları ile cinsiyet ve medeni durum değişkenleri arasında bağımsız gruplarda t testi analizi yapılmış ve anlamlı farklılık görülmemiştir. Çalışmamıza katılan hekimlerden “Hekimlik mesleğiniz sürecinde malpraktis nedeni ile dava açıldı mı” sorusuna 13 hekim (%2,7) evet cevabını verirken, 89 hekim (%87,3) hayır cevabı vermiştir. Defansif tıp uygulamaları kavramının içeriği konusunda yeterli bilgiye sahip misiniz? sorusuna 56 hekim (%54,9) “hayır” cevabını vermiştir. Sonuç: Araştırmamızın sonuçlarına göre hekimler defansif tıp konusunda yeterli bilgiye sahip değildir ve defansif tıp davranışı gösterme eğilimleri fazladır.
Strategies for the efficient auralization of complex scenes containing multiple sound sources

Simulation models for geometrical acoustics are often based on a image source method [1], a ray tracing algorithm or a hybrid model combining these methods in an efficient way [2]. Modern computer architectures made it possible to apply these models in real-time auralization software. The typical auralization process consists of the simulation of the propagation paths, a binaural filter synthesis and a convolution with an anechoic sound source file. While these steps can be processed for one sound source in real-time applications on a standard computer [3], update rates have to be reduced as soon as the scene contains multiple sound sources. For each source, the computational workload increases proportionally. To simplify such scenes by reducing the computational complexity while maintaining the same auditory impression for the listener, a clustering method similar to the concept proposed by Tsingos [4][5] was developed. This method replaces groups of closely spaced sources by a single representative source by taking advantage of spectral masking. Another approach was discussed by Herder [6], who also analyzed the effects of clustering and removing less salient sources (Culling). Both of these methods aim at reducing the number of propagation paths which have to be calculated during the update process of the virtual scene. The presented algorithm creates sound source clusters and culls inaudible sources based on geometrical and psychoacoustical properties. To adjust the source count of the virtual scene, the clustering intensity can be varied. This paper first presents the concept of the algorithm and then evaluates the concept based on a performance analysis and a listening test which was conducted for two example scenes.
The Role Of Corporate Governance Mechanism On Voluntary Disclosure

Basically, the purpose of this research is to examine empirically whether the Corporate Governance is the proportion of independent commissioners, the commissioners who have accounting capabilities, and the proportion of independent auditors can influence disclosure voluntarily. Voluntary disclosure is measured through the complete disclosure of voluntary index (IPS). This index contains 37 items in disclosure in the annual report. The sample is a manufacturing company listed on the Indonesia Stock Exchange, where the data analysis technique that will use the Multiple Regression Analysis using SPSS 23.
Detection of cyber threats to network infrastructure of digital production based on the methods of Big Data and multifractal analysis of traffic

The article offers an approach to analyzing data security of network infrastructure of digital production providing for contraction of network traffic size and detecting anomalies in the network traffic on the basis of multifractal analysis. The contraction of data size will be provided due to extraction of significant parameters from the network packets and dropping the rest data, as well as due to application of such Big Data method as aggregation. The experimental investigations on contracting data size on analyzing security have proven the operability and efficiency thereof. The method of contracting data size has demonstrated a possibility of traffic volume contraction from hundreds of Gbit to several Mbyte. The suggested approach to security analysis using the assessment of width of multifractional spectrum as a criterion of anomaly presence has detected both simulated attacks of denial of servicing SYN-flood and smurf. Thus, the suggested approach can be efficiently used for analyzing big volumes of dissimilar traffic of network infrastructure of digital production.
Research and Application about Posture Recognition Based on G-Sensor

At present, without full use of the mobile phone around us, most of the research in human body posture recognition field is use camera or portable acceleration sensor to collect data. In this paper, G-sensor built- in mobile phone is use to collect data. After gaining joint point’s space three-dimensional coordinates through motion acceleration integral, a set of vectors calculated by those data are put up as the description of every pair’s joint points, which changes instead of motion trajectories. Then using the DTW (dynamic time warping) algorithm recognize position category, the results show that this gesture recognition method has good recognition effect.
Teaching indigenous languages in Chile: perceptions of Traditional Educators

ABSTRACT Intercultural Bilingual Education has been public policy in Chile for more than 20 years. One of its key components is the emergence of the Traditional Educator, an indigenous person with the linguistic and cultural competencies necessary for teaching an indigenous language in a school context. Hence, this research is directed towards examining the perceptions of Traditional Educators regarding the teaching of indigenous languages. The contents of relevant documents and interviews with Traditional Educators from three groups of indigenous peoples (Mapuche, Aymara and Lican Antay) who participated in the study were analyzed using a qualitative methodology. Using the Critical Language Policies approach, the results were organized into three categories: (a) perceptions of Traditional Educators regarding the Intercultural Bilingual Education Program, (b) the relationship of Traditional Educators with other participants in the school system, and (c) teaching strategies declared by Traditional Educators for teaching in the Indigenous Language Class (Sector Lengua Indígena). We concluded that the work of Traditional Educators within schools is isolated and lacks the support of local communities and the Intercultural Bilingual Education Program.
Advancing Theory on Knowledge Governance: From Knowledge-Based Firms to Knowledge-Based Organizations

In an exploratory case study of a university merger, this study inductively examines how governance structures in universities impact the creation and exploitation of knowledge, both in core academic activities (research and teaching) and in related and supporting administrative tasks. Similarities and differences in relation to knowledge governance in firms are identified. The findings suggest that university governance arrangements provide advantages primarily in knowledge creation through intra-disciplinary articulation of tacit knowledge, and in the transfer of such knowledge through master-apprentice type of personal relationships, but make them inferior to firms in the pursuit of innovative, inter-disciplinary combinations of knowledge. The reasons behind these similarities and differences are explained, possible extensions of the knowledge-based theory of the firm are proposed and some tentative managerial implications for the organization of knowledge work in modern universities are outlined.
Existing Object Oriented Design Metrics a Study and Comparison

Software Quality still a vague and multifaceted concept, which means different things to different people, metrics for object oriented design focuses on measurements that are applied to the class and design characteristics. These measurements allow designers to access the software early in process, making changes that will reduce complexity and improve the continuing capability of the design. This paper focused on a set of object oriented metrics that can be used to measure the quality of an object oriented design. We study carefully Metrics for object oriented design and focus on MOOD model.
Design of a competent Aging-Aware Reliable Multiplier using Variable Latency with Adaptive Hold Logic

: Digital multipliers are along with the majority critical arithmetic functional units. The general performance of the Digital multiplier systems depends on throughput of the multiplier. The negative bias temperature instability effect occurs when a pMOS transistor is under negative bias (Vgs = −Vdd), increasing the threshold voltage of a pMOS transistor and falling the multiplier speed. In the same way, positive bias temperature instability occurs when an nMOS transistor is under positive bias. Both effects degrade the speed of the transistor and in the long term, the system may be fail due to timing violations. For that reason, it is required to design reliable high-performance multipliers. In this paper, we implement an aging-aware multiplier design with a novel adaptive hold logic (AHL) circuit. The multiplier is able to provide the higher throughput through the variable latency and can adjust the adaptive hold logic (AHL) circuit to lessen performance degradation that is due to the aging effect. The proposed design can be applied to the column bypass multiplier. Additionally, the proposed design can be applied to a column- or row-bypassing multiplier. The experimental results show that our proposed design with 16bit and 32bit, 64bit column-bypassing multipliers
Information Asymmetry in the Post-IFRS Adoption Period: Evidence from Developing Countries

Objective - The adoption of IFRS aims to reduce the level of information asymmetry. Prior studies conducted in developed countries prove that the adoption of IFRS enhances transparency and diminishes information asymmetry. However, in developing countries with a low level of openness, limited regulation, and more centralized ownership, the ability of IFRS to reduce information asymmetry remains unknown. To address this issue, this study aims to investigate whether IFRS adoption will reduce information asymmetry in some developing countries in South East Asia. Methodology/Technique - This research is applied in three developing countries: Indonesia, the Philippines and Thailand. Information asymmetry is proxied by the cost of capital using the Easton model (2004) and a bid-ask spread. Listed firms from the three countries are selected as the research sample resulting in 5.313 firm-years for the period between 2007 and 2016. Findings - This study concludes that the adoption of the IFRS decreases information asymmetry in developing countries. These finding confirm that the benefit of the adoption is the same as in developed countries, despite the level of law enforcement in developing countries being lower. Managers, standard authorities and investors must note that the IFRS conveys benefits to the market, which increases transparency by asking lower returns and valuing company stocks appropriately. Novelty - This study examines the benefits of the adoption of the IFRS in reducing information asymmetry in some emerging countries to enhance the generalization of the results from prior studies that are mostly conducted in developed countries. Type of Paper Empirical Keywords: Bid-ask Spread; Cost of Capital; Information Asymmetry; IFRS Adoption. JEL Classification: M41, M48.
A Robust Reliable Forward-reverse Supply Chain Network Design Model under Parameter and Disruption Uncertainties

Social responsibility is a key factor that could result in success and achieving great benefits for supply chains. Responsiveness and reliability are important social responsibility measures for consumers and all stakeholders that strategists and company managers should be concerned about them in long-term planning horizon. Although, presence of uncertainties as an intrinsic part of supply chains could adversely affect the best set plans by field experts. Accordingly, uncertainty of parameters and uncertainties caused by disruptions should be regarded in planning process of networks to prevent unpredictable negative consequences of such uncertainties for all echelons of supply chain. Based on enumerated matters, the aim of this paper is to design a reliable multi-echelon closed loop supply chain network model that maximizes social responsibility while minimizing fixed establishing and variable processing costs of network design. To cope with uncertainty of parameters, stochastic programming is applied and an effective reliable modelling method is employed to appropriately control unpleasant economic impacts of disruptions. Notably, an efficient robust programming method is applied to give the decision makers the capability to control level of risk-averseness of decisions while modelling uncertain parameters. Finally, the proposed model is solved and its outputs are analyzed on the basis of generated test problems which shows correct performance and applicability of extended model in real world problems.
Promoting Awareness of Self: Cultural Immersion and Service-Learning Experiences of Counselors-in-Training

Promoting Awareness-of-Self: Cultural Immersion and Service-Learning experiences Abstract Counselor education is committed to exploring innovative pedagogy to provide opportunities for counselor trainees to increase multicultural competence. International cultural immersion and service –learning create an environment for counselors-in-training to explore their cultural competence through cultural interactions, relationships, and heightened self-awareness. This exploratory, qualitative, phenomenological study using focus group data collection investigated the lived experience of counselors-in-training through international cultural immersion and service-learning. Awareness-of-self emerged as the overarching theme which included themes of personal and national privilege, cultural encapsulation, sense of belonging, and racism. Subthemes include attitudes and beliefs, cultural norms, time, gender roles, community vs. individualism, intra-group differences, and intra-community racism. Findings can serve to inform counselor educators on the use of international service-learning and cultural immersion as pedagogy for advancing self-awareness and multicultural competence.
From Layout to System: Early Stage Power Delivery and Architecture Co-Exploration

With the reduced noise margin brought by relentless technology scaling, power integrity assurance has become more challenging than ever. On the other hand, traditional design methodologies typically focus on a single design layer without much cross-layer interaction, potentially introducing unnecessary guard-band and wasting significant design resources. Both issues imperatively call for a cross-layer framework for the co-exploration of power delivery (PD) and system architecture, especially in the early design stage with larger design and optimization freedom. Unfortunately, such a framework does not exist yet in the literature. As a step forward, this paper provides a run-time simulation framework of both PD and architecture and captures their interactions. Enabled by the proposed recursive run-time PD model, it can achieve smaller than 1% deviation from SPICE for an entire PD system simulation. Moreover, with seamless interactions among architecture, power and PD simulators, it can simulate actual benchmarks within reasonable time. The experimental results of running PARSEC suite have demonstrated the framework’s capability to discover the co-effect of PD and architecture for early stage design optimization. Moreover, it also shows multiple over-pessimism in traditional PD methodologies. Finally, the framework is able to investigate the impact of dynamic noise on system level oxide breakdown reliability and shows 31%–92% lifetime estimation deviations from typical static analysis.
Improving the efficiency of deep convolutional networks

• A submitted manuscript is the author's version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers.
Multi-Interface Connectivity On Modern Mobile Devices

Modern mobile devices are equipped with multiple network interfaces such as Wi-Fi, 4G, bluetooth, NFC and others. However, current software allows us to use only one of them at any given time. This is done by assigning a static priority to each interface, and enabling the one with the highest priority among the interfaces available. This causes unnecessary network disruption especially since the users could be mobile, and does not provide a seamless experience that is desirable.
Trade Elasticities and Market Expectations in Brazil

This paper provides econometric estimates of trade elasticities for Brazil obtained through cointegration and vector auto regression models and controlling for the effects of exchange rate volatility, capacity utilization, and changes in import tariffs. The results suggest that (i) recent market expectations may have been unduly pessimistic regarding the responsiveness of Brazil's trade flows to the real exchange rate, but (ii) the GDP growth rates targeted by the new government may put downward pressure on the exchange rate and thus render the achievement of official inflation targets considerably more difficult if structural reforms are not implemented.
Lectures in Mathematical Neuroscience

Contents Lectures in mathematical neuroscience 1 Lecture 1. Single neuron models 3 1.1. Conductance–based models 3 1.2. Periodically forced neural oscillator 6 1.3. Integrate–and–fire models 13 Lecture 2. Synaptic and dendritic processing 23 2.1. Excitatory and inhibitory synapses 23 2.2. Kinetic model of a synapse 27 2.3. Dendritic filtering of synaptic inputs 31 2.4. Synaptic plasticity 34 Lecture 3. Firing rates, spike statistics and the neural code 45 3.
3D data fusion from multiple sensors and its applications

The introduction of depth cameras in the mass market contributed to make computer vision applicable to many real world applications, such as human interaction in virtual environments, autonomous driving, robotics and 3D reconstruction. All these problems were originally tackled by means of standard cameras, but the intrinsic ambiguity in the bidimensional images led to the development of depth cameras technologies. Stereo vision was first introduced to provide an estimate of the 3D geometry of the scene. Structured light depth cameras were developed to use the same concepts of stereo vision but overcome some of the problems of passive technologies. Finally, Time-of-Flight (ToF) depth cameras solve the same depth estimation problem by using a different technology. This thesis focuses on the acquisition of depth data from multiple sensors and presents techniques to efficiently combine the information of different acquisition systems. The three main technologies developed to provide depth estimation are first reviewed, presenting operating principles and practical issues of each family of sensors. The use of multiple sensors then is investigated, providing practical solutions to the problem of 3D reconstruction and gesture recognition. Data from stereo vision systems and ToF depth cameras are combined together to provide a higher quality depth map. A confidence measure of depth data from the two systems is used to guide the depth data fusion. The lack of datasets with data from multiple sensors is addressed by proposing a system for the collection of data and ground truth depth, and a tool to generate synthetic data from standard cameras and ToF depth cameras. For gesture recognition, a depth camera is paired with a Leap Motion device to boost the performance of the recognition task. A set of features from the two devices is used in a classification framework based on Support Vector Machines and Random Forests.
An improved graph-based visual localization system for indoor mobile robot using newly designed markers

To address the localization problem for a mobile robot in an indoor environment, an improved visual localization system based on artificial markers is proposed in this article. First, we will present a novel artificial marker which can be detected and identified easily and correctly. We will then introduce how it is designed, recognized, and verified. The markers are arranged on the ceiling and the mobile robot moves around on the ground to capture images with an up-facing monocular camera. The markers’ information, including the position and direction, will be obtained by processing the images. The camera’s uncertainty model is then put forward based on the distortion of the camera. The uncertainty of the obtained markers’ information is analyzed through the uncertainty model. Finally, with the obtained information, the marker map in global image coordinate system is established and optimized through a graph-based algorithm in which the edges can be updated to reduce the uncertainty using Bayes Estimation method. To verify the effectiveness of the localization system, numerous experiments have been conducted. Additionally, the proposed method has also been applied to industrial forklift to test its robustness in a factory environment.