Miracle-dz/UniFAR-FTUs huggingface dataset:
Managing Ethical Dilemmas under Stressful Economic Circumstances among Journalists in Northern Ghana

This article explores the management of ethical dilemmas in stressful economic circumstances among journalists in the three Northern Regions of Ghana. It analyses the experiences of journalists during difficult ethical moments. In-depth interviews were conducted with a total of 30 working journalists, drawing 10 from each of the three northern regions. These are the Upper West, Upper East and Northern Regions. The study revealed that in practice, rather than working with the normative ethical framework defined by the codes of ethics of the Ghana Journalists Association, journalists are influenced by context-based pragmatism and their conduct is very much influenced by economic realities of satisfying basic needs. Again, the study revealed that most Ghanaian journalists understand the idealism of ethical norms and are very much aware of the GJA code of ethics, but see the practicability of the code as problematic. We recommend that the GJA increases its advocacy role on improving the working conditions of its members. It should also facilitate continuous professional development programs on media ethics in the changing media landscape. Improved working conditions and continuous professional development programs can assist its members in managing ethical dilemmas in stressful economic and social circumstances.
The LAB studio model: enhancing entrepreneurship skills in higher education

Entrepreneurship is increasingly being included as a component in higher education and training curriculum internationally. This paper introduces a multidisciplinary studio model, called LAB studio model, for higher education established at the Oulu University of Applied Sciences (OUAS) in Finland. This LAB studio model is theoretically grounded in a constructivist view of learning with problem-based education at its core and draws from traditional studio models for training (Schon, 1987). Furthermore, the model merges work-life experience with studio training in a multidisciplinary and multi-professional environment. Using the categories outlined by Bull et al. (2013), this paper compares existing studio training models with the LAB studio model. This comparison suggests that the LAB studio model is more closely aligned with industry needs and work place reality, in contrast to existing studio models, because it focuses on instruction in a competitive structure; integrates experienced professionals and coaches from the industry; includes problems or ideas from industry; and builds multidisciplinary project teams. Overall, it is suggested that the LAB studio model holds promise to more fully integrate entrepreneurial competences in contrast to existing training models. Further research is currently being conducted to explore this hypothesis.
A novel white blood cell segmentation scheme using scale-space filtering and watershed clustering

In this paper, a novel white blood cell (WBC) segmentation scheme using scale-Space filtering and watershed clustering is proposed. In this scheme, nucleus and cytoplasm, the two components of WBC, are extracted respectively using different methods. First, a sub image containing WBC is separated from cell image. Then, scale-space filtering is used to extract nucleus region from sub image. Later, a watershed clustering in 3-D HSV histogram is processed to extract cytoplasm region. Finally, morphological operations are performed to obtain the entire connective WBC region. By using feature space clustering technique, this scheme successfully avoids the variety and complexity in image space, and can effectively extract various WBC regions from cell images of peripheral blood smear. Experiments demonstrate that the proposed scheme performs really well and HSV space is more appropriate than RGB space in WBC segmentation due to its low correlation.
Neuro-Fuzzy Approach: A Robust Way to Restore Degraded Documents

— Document binarization is one of active research area in image processing domain in which wide varieties of techniques are proposed so far. But when it comes to document restoration only few algorithms are only marginally satisfactory. As documents are degraded by several factors like Paper aging effects, Contrast variation, Smearing and Smudging of text, Shadow through, Ink bleeding etc which impose tough scenarios for any method. The Degraded documents may contain vital information, so efficiency and accuracy is must required while restoring it. In this paper a new perspective of Neuro-Fuzzy restoration is presented and compared with other existing techniques both qualitatively (visual inspection) and quantitatively (Accuracy, NRM, MSE, PSNR).
An Adaptive Inter Frame Video Sequence Denoise Method

classic image denoise method includs low-pass filter,median filter and most effective wavelet denoise filter.These methods both have good effect in real world application.But in video denoise domain,these method only use special information and don′t use time domain information.So this kind of filter wouldn′t have best effects.This paper proposes an self-adaptive time domain filter which uses video sequence′s time information.The new method has superior effect than all kinds of space domain filter.The method is quite simple and don′t need lots of CPU cycle and is easy to use in all kinds of application.
Missile Recognition Based on the Fuzzy Dynamic AHP Algorithm

Referring to the problem of true-fake warhead recognition in missile early warning satellite system,a new algorithm of warhead target recognition for decision-making system is established. By use of some infrared attributes as characteristic parameter of warhead target recognition, such as temperature change rate, thermal capacity difference, radiant intensity, gray characteristic and infrared movement characteristic, information fusion based on the Analytic Hierarchy Process (AHP) algorithm of multiple attribute decision making is applied. Furthermore, fuzzy dynamic method is applied to construct the attribute importance estimation matrix, and the problem of the attribute weights being changed with time is efficiently solved. The true warhead is recognized by the result of fusion and ranking. The simulation results show that this target recognition algorithm is trusty and practical.
Study on Rule-based Data Protection System Using Blockchain in P2P Distributed Networks

The blockchain is new revolutionary paradigm for the world, but the privacy and confidentiality are still issues. This study is focused on the technical securities to provide a blockchain service on a foundation of trust. We suggested the rule-based data protection system that is to provide authorize rules used in mechanism, to control an access users without intermediaries on the blockchain. We have developed a scenario of an application a smart contract based on the suggested system and simulated it
Design and Analysis of SAFER Block Cipher

The general structure of SAFER block ciphers adopts SP network. It's design has some original features. In this paper, the design technique of SAFER block cipher is analyzed. Along the process of improvement of it's designers, we give a description of and attack on their confusion layer, diffusion layer and key schedule algorithm. In the end, some problems about SAFER design are proposed, and will be studied later.
Teacher motivation in stricto sensu postgraduation: an analysis based on self-determination theory,

The objective of this research was to analyze the motivational factors that lead accounting sciences professors to teach on stricto sensu postgraduate courses, based on self-determination theory. Research on motivation in education in the area of accounting sciences mostly concerns student motivation. Thus, there are few studies related to teacher motivation, especially in the area of accounting sciences and in stricto sensu postgraduate programs. Teacher motivation is directly linked to the teaching-learning process and student motivation, so it is important to identify what motivates these teachers and, given this, to act in a way that the motivation, or lack of it, will not interfere with the quality of teaching. The importance of teachers in the quality of education is indisputable and inevitably relates to the motivation to remain in the teaching career, taking both personal and professional aspects into account. The Work Tasks Motivation Scale for Teachers was applied and answered by 108 professors from the 33 stricto sensu postgraduate programs in the area of accounting sciences. The data were analyzed in an aggregated way, using descriptive statistics and Wilcoxon-Mann-Whitney and chi-squared tests, with the purpose of assessing the relationship between levels of motivation and age group, time teaching, and time teaching in the stricto sensu postgraduate course. Most of the professors analyzed are extrinsically motivated via identified regulation; however this is less related to access to financial resources and more linked to the prestige that teaching on the stricto sensu postgraduate course brings. Also, the overall mean of the dimensions of intrinsic and extrinsic motivation was shown to be higher for teachers of the female gender and who work in private institutions.
Aligning observed and modeled behavior

Aligning Observed and Modeled Behavior The availability of process models and event logs is rapidly increasing as more and more business processes are supported by IT. On the one hand, most organizations make substantial efforts to document their processes, while on the other hand, these processes leave footprints in their information systems. Although it is possible to extract event logs from today’s systems, the relation between event logs and process models is often identified using heuristics that may yield misleading insights. In this thesis, techniques to align event logs and process models are explored. Based on the obtained alignments, various analysis techniques are developed. The techniques are evaluated against both artificial and real-life process models and event logs. A memory-efficient technique to compute alignments between event logs and process models has been developed. Given an event log and a process model, low-level deviations, i.e., observed activities that are not allowed according to the model and the other way around, are explicitly identified. The technique can also be used to identify high-level deviations such as swapped and replaced activities. Our technique is applied to problems occurring in different domains. Unlike earlier approaches, alignment-based conformance checking techniques are shown to be robust against peculiarities of process models, such as duplicate and invisible tasks. Alignmentbased conformance metrics, such as fitness and precision, are shown to be more intuitive and can deal with multiple level of noise in event logs. Various visualizations of alignments provide powerful diagnostics to identify the context of frequently occurring deviations between process executions and prescribed process models. Applying data mining techniques to alignments yields root causes of deviations between the observed behavior in an event log and the modeled behavior in a process model. Alignments also improve the robustness of performance measurements based on event logs and process models, even if the logs are deviating from the models. From a computational point of view, computing alignments is extremely expensive. However, the obtained results indicate that alignments not only provide a theoretically solid basis for analysis based on both models and process executions, but are also able to handle problems of real-life complexity.
Music Generation from Statistical Models of Harmony

This article investigates the problem of sampling from statistical models of music, motivated by the fact that music generated by random walk is generally atypical in style and of vastly inferior quality compared with pieces in the corpus. Specifically, we employ a multiple viewpoint system of four-part harmony, in conjunction with a small set of general rules of harmony, to evaluate an improved iterative random walk technique which efficiently finds low cross-entropy (high probability) solutions. By first using standard iterative random walk, we show that a range of very high cross-entropy harmonizations is generated. Furthermore, we demonstrate a relationship between cross-entropy and the number of rule violations; that is, there are fewer violations at lower cross-entropy. Motivated by this result, the application of an improved sampling technique was used to produce solutions of very low cross-entropy, confirming that the correlation between cross-entropy and rule violations extends into the low cross-entropy region. Various diversity measures, such as the number of non-diatonic notes per 100 melody notes, also exhibit trends with respect to cross-entropy. These findings are likely to influence future research involving the generation of samples from statistical models, in the realm of music and beyond.
On Methodology for Verification, Validation and Uncertainty Quantification in Power Electronic Converters Modeling

This thesis provides insight into quantitative accuracy assessment of the modeling and simulation of power electronic converters. Verification, Validation, and Uncertainty quantification (VV&UQ) provides a means to quantify the disagreement between computational simulation results and experimental results in order to have quantitative comparisons instead of qualitative comparisons. Due to the broad applications of modeling and simulation in power electronics, VV&UQ is used to evaluate the credibility of modeling and simulation results. The topic of VV&UQ needs to be studied exclusively for power electronic converters. To carry out this work, the formal procedure for VV&UQ of power electronic converters is presented. The definition of the fundamental words in the proposed framework is also provided. The accuracy of the switching model of a three-phase Voltage Source Inverter (VSI) is quantitatively assessed following the proposed procedure. Accordingly, this thesis describes the hardware design and development of the switching model of the three-phase VSI.
State feedback controller for distributed systems with non-deterministic time delays

Physical distribution of modules of a closed loop control system, i.e., sensor, controller and actuator over a communication network, is the state of the art in the modern motion control industry. The gains are to reduce system wiring, ease of fault diagnosis, maintenance etc. Inserting a communication network to connect the sensor to controller and controller to actuator, makes the analysis and controller design complicated. Because the ideal centralized assumptions such as synchronized sensor and/or controller signal availability, non-delayed sensing and actuation are no longer valid. The network induced delays in communicating through a shared medium like standard Ethernet are hardly ever constant. The time varying non-deterministic nature of the delays, depending on their magnitudes compared to the time constants, can destabilize or at least degrade a system whose non-networked closed loop version is highly stable and well performing. This paper addresses the network induced delay problem by using time-stamps of the data packets in real-time computation of a full-state feedback controller. Performance of the method is verified using a test rig comprising a Brushless DC motor, whose speed control loop is closed via a standard Ethernet network. Further, the experimental results of the suggested method are compared with the performance of standard controller designs for systems with time delays.
Application and Comparison of Industrial Control Configuration Software

The development course of configuration software is presented, and a detailed comparison between several kinds of domestic and foreign configuration software is given. The different kinds of configuration software are analyzed in respect of function, script language, open structure, database and price, etc. Finally a typical application case based on application of configuration software development is illustrated.
Climate Finance, Carbon Market Mechanisms and Finance 'Blending' As Instruments to Support NDC Achievement Under the Paris Agreement

This paper considers the impacts of"finance blending"whereby climate finance is added to international carbon markets for offset trading. The paper first discusses climate finance and the carbon market as free-standing finance solutions by high-income countries to increase mitigation in low-income countries. Climate finance solutions have advantages for high-income countries due to their greater flexibility and general efficiency. A favorable aspect of well-functioning offset markets is that all participating countries face a similar and robust carbon price. With finance blending and"all attribution to the carbon market,"the market equilibrium is inefficient, as mitigation is excessive in low-income countries and too low in high-income countries. Instead, mitigation outcomes in the offset market should be attributed to the two finance types in proportion to their finance shares provided to the low-income countries through this market. When climate finance is added to the carbon market, the ambition level for emissions reductions for donor countries should be raised equivalently; otherwise, the added climate finance leads to no increase in global mitigation. When low-income country market participants have limited access to credit markets, climate finance can increase mitigation by supplying the capital required to implement efficient mitigation projects.
Job shop scheduling problem based on particle swarm optimization

Considering the conventional algorithms' low efficiency of searching for optimizing in job shop scheduling problems,the job shop scheduling solution is presented based on particle swarm optimization algorithm.In this paper,the basic theory of particle swarm optimization is described,also,the coding and selection of parameters as well as the decoding of PSO are studied.It uses the maximum flow time which being minimized to evaluate performance of the algorithm,and applies it to solve a typical scheduling problem.The simulation results show that PSO applied in solving job-shop scheduling is very effective.
Design of Energy-Efficient Many-Core MIMD GALS Processor Arrays in the 1000-Processor Era

As transistor sizes continue to scale, more transistors are able to be used in a fixed die size. The recent trend for general purpose processing units is to use the increased number of transistors from process technology scaling to add more processing cores on a single die. At a certain point, it becomes untenable to continue to add more cores with traditional architectures and communication systems, which necessitates a fundamental change in architectures to facilitate these cores. This paradigm shift requires new energyefficient, high-performance algorithms and hardware designs tailored for many-core processor arrays, as they provide different challenges than a single or multi-core chip. With such large arrays of processors, communication, both between processors and to memories, becomes a limiting factor, requiring algorithms to work with these limitations as well as on-chip interconnect networks to make communication possible. This dissertation offers three different novel methods to perform a high throughput energy-efficient database sort data records using a fine-grained many-core processor array. When measured against sorts created to fairly compare results, the most energy efficient first-phase many-core sort requires over 83× lower energy than a quick sort performed on an Intel laptop-class processor and over 105× lower energy than a radix sort running on an Nvidia GPU. In addition, the highest first-phase throughput many-core sort is over 10× faster than the quick sort and over 14× faster than the radix sort. Both phases of an entire 10 GB external sort require 6.9× lower energy×time (energy delay product, EDP) than the quick sort and over 13× lower energy×time than the radix sort. The proposed sorts are easily programmed and scalable to any sized 2D mesh processor array while giving a large energy savings without penalizing performance. The dissertation presents the developed physical design flow and design methodology for creating a digital chip in the 1000-processor era. A number of design considerations are discussed, including module design, power grid design, power gate system design, physical DVFS requirements, communication, and chip level layout.
Credit Variance Risk Premiums

This paper studies variance risk premiums in the credit market. Using a novel data set of swaptions quotes on the CDX North America Investment Grade index, we find that returns of credit variance swaps are negative and economically large. Shorting variance swaps yields an annualized Sharpe ratio of almost six, eclipsing its counterpart in fixed income or equity markets. The returns remain highly statistically significant when accounting for transaction costs, cannot be explained by established risk-factors, and hold for various investment horizons. We also dissect the overall variance risk premium into payer and receiver variance risk premiums. We find that exposure to both parts is priced. However, the returns for payer variance, associated with bad economic states, are roughly twice as high in absolute terms.
Cognitive Flexibility and Pro–Environmental Behaviour: A Multimethod Approach

While cognitive flexibility has been hypothesized to relate to adaptive, long–term–oriented behaviour, empirical support for such a relationship is scarce. In the present article, we examine the role of cognitive flexibility as a correlate of long–term–oriented behaviour in the domain of environmental conservation. In a first study (N = 143), we explored potential associations between multiple self–report scales and performance–based measures of cognitive flexibility and pro–environmental behaviour. Based on its results, we conducted a pre–registered confirmatory study (N = 264) focusing on the most promising correlations found in our exploratory study. This study generated conclusive support for a positive medium–sized correlation between cognitive flexibility and pro–environmental behaviour. Exploratory hierarchical regression analyses further revealed that cognitive flexibility accounted for a small portion of variance in pro–environmental behaviour above and beyond the Big Five. While appearing robust on the level of self–reports, the relationship between cognitive flexibility and pro–environmental behaviour did not reliably extend to the level of performance tasks, possibly because of their relatively specific scope. These results illustrate the contribution of cognitive flexibility to understanding individual differences in long–term–oriented, pro–environmental behaviour. © 2019 European Association of Personality Psychology
The Limits of Meritocracy

We show that too much meritocracy, modeled as accuracy of performance ranking in contests, can be a bad thing: in contests with homogeneous agents, it reduces output and is Pareto inefficient. In contests with sufficiently heterogeneous agents, discouragement and complacency effects further reduce the benefits of meritocracy. Perfect meritocracy may be optimal only for intermediate levels of heterogeneity.