Miracle-dz/UniFAR-FTUs huggingface dataset:
Linking career success motives and career boundaries to repatriates’ turnover intentions: A case study

Abstract This study’s goal is to understand repatriates’ personal experiences about their career success motives in the years following an international assignment and how that may prompt turnover intentions. The case study comprises data from 8 Portuguese companies belonging to different industries. Overall, we interviewed 42 repatriates and 17 human resource organizational representatives. Building on career success literature, this study’s findings show that these repatriates’ main career–pull motives to stay with the organization are related to (1) Recognition and Affection, (2) Financial and Employment Security, (3) Developmental Career Opportunities, (4) and, lastly, Career Advancement. By comparison, these repatriates’ career–push motives to leave pertain to (1) the Lack of Developmental Career Opportunities, (2) Financial and Employment Insecurity, and (3) Recognition and Affection Breach. Furthermore, the findings shed new light on the role played by contextual-structural career boundaries as a mitigating factor in repatriates’ turnover intentions. Overall, we add a new contribution to the literature on career success and repatriation by showing that Affective career success motives (both Intra-Inter-Personal) are, on the whole, more important than Achievement career success motives in these repatriates’ turnover intentions.
Association between work in deforested, compared to forested, areas and human heat strain: an experimental study in a rural tropical environment

Background. With climate change, adverse human health effects caused by heat exposure are of increasing public health concern. Forests provide beneficial ecosystem services for human health, including local cooling. Few studies have assessed the relationship between deforestation and heat-related health effects in tropical, rural populations. We sought to determine whether deforested compared to forested landscapes are associated with increased physiological heat strain in a rural, tropical environment. Methods. We analyzed data from 363 healthy adult participants from ten villages who participated in a two-by-two factorial, randomized study in East Kalimantan, Indonesia from 10/1/17 to 11/6/17. Using simple randomization, field staff allocated participants equally to different conditions to conduct a 90 min outdoor activity, representative of typical work. Core body temperature (CBT) was estimated at each minute during the activity using a validated algorithm from baseline oral temperatures and sequential heart rate data, measured using chest band monitors. We used linear regression models, clustered by village and with a sandwich variance estimator, to assess the association between deforested versus forested conditions and the number of minutes each participant spent above an estimated CBT threshold of 38.5 °C. Results. Compared to those in the forested condition (n = 172), participants in the deforested condition (n = 159) spent an average of 3.08 (95% confidence interval (CI) 0.57, 5.60) additional minutes with an estimated CBT exceeding 38.5 °C, after adjustment for age, sex, body mass index, and experiment start time, with a larger difference among those who began the experiment after 12 noon (5.17 [95% CI 2.20, 8.15]). Conclusions. In this experimental study in a tropical, rural setting, activity in a deforested versus a forested setting was associated with increased objectively measured heat strain. Longer durations of hyperthermia can increase the risk of serious health outcomes. Land use decisions should consider the implications of deforestation on local heat exposure and health as well as on forest services, including carbon storage functions that impact climate change mitigation.
Shaping the New Europe: Interest Representation in the European Union

Title, Acknowledgments, Contents, List of Tables, Figures and Appendices, List of Abbreviations Introduction 1 1. The Quest for Legitimacy in the European Union 2. Concepts of Representation 3. Partial Organisations, Democracy, and Representation 4. Institutional Representation in the European Union 5. European Interest Group Representation 5 31 59 92 183 Conclusion 229 Bibliography 235 Appendices 247 Zusammenfassung 257
Providing Static Timing Anlaysis Support for an ARM7 Processor Platform

KANG, SANG YEOL. Providing Static Timing Analysis Support for an ARM7 Processor Platform. (Under the direction of Professor Alexander G. Dean). Scratchpad memory provides faster speed but smaller capacity than other memories do in embedded systems. It provides a visibly heterogeneous memory hierarchy rather than abstracting it as cache memory does. Unlike cache memory, program code and data can be allocated into the scratchpad memory as desired. This enables optimizing the performance in real-time embedded systems. Static timing analysis helps the optimization processes by providing microscopic information of the application program’s timing information. Based on the WCET and BCET estimated by static timing analysis, the techniques using scratchpad memory may be enhanced. This study aims to provide a method of static timing analysis for an ARM processor platform (ARM7TDMI). Basic analysis is performed relying on well-known program analysis graphs such as control flow graphs, call graphs, depth-first search trees, and post-dominance trees. During this basic analysis, loops and unstructured code are also identified, which make static timing analysis more difficult. A control dependence analysis is a convenient way to analyze the WCET and BCET, since it represents the hierarchical control structure of a program. By traversal of the control dependence graph, the WCET and BCET are estimated. To confirm the feasibility of this study, a real target system and its development environment tool chains are developed and an existing application is ported. In addition, the static timing analysis framework of this study is implemented by the tool named ARMSAT. Experiments are performed in these all environments. The experimental results show that the actual execution times are bounded by the calculated analytical WCET and BCET bounds, although there are a few factors which interfere with computing the analytical
Sociological Approach to Eradication Corruption in Indonesia (Alternative to Imprisonment)

Punishment of corruption not quite put in the context of law enforcement, leading to sanctions of imprisonment. Reality shows more than 600 state officials have been convicted of corruption but the rate has no effect at all to prevent the corruption. If no breakthrough is the law, the state can be called a defeat and to its knees at the foot of criminals. As a result, Indonesia can be called a heaven for criminals country. As a rule of law, law enforcement must be done in a holistic and integrated. Thus the imprisonment should also be offset by imposing sanction corrupt social order to be cured/deterrent. Make criminals real deterrent is not an easy step, but in need of understanding and synergy between the law enforcement community on the one hand with the other hand to continue to spread the spirit of corruption eradication in all social strata. The imposition of sanctions of imprisonment must also be followed by removal of political rights, especially the right to have occupied political positions both in government agencies and representatives (DPR). Sanctioning the disenfranchisement of political rights for a time after undergoing convict prison, is a powerful tool and a non-penal nature to combat corruption.
Semi-supervision and Active Relevance Feedback Algorithm for Content-Based Image Retrieval

To improve the efficiency of relevance feedback in image retrieval,a novel active learning algorithm SVMpr based on relevance probability is proposed in the paper.And combined with a semi-supervision learning, the framework of image retrieval based on semi-supervision and active learning is designed.In the process of relevance feedback, firstly, the labeled samples are trained by TSVM,secondly according to active learning algorithm in this paper,the k image samples from the unlabeled images are selected into the user which is added label and more helpful for useful sam-ples.Experimental result shows that the algorithm is better than traditional one,which is in improving significantly the efficiency and convergent rate of machine learning.
S-LOOK: A Preemptive Disk Scheduling Algorithm for Offline and Online Environments

We consider the problem of disk scheduling to enhance disk performance. We introduce a new algorithm (S- LOOK) for offline optimal performance, in terms of total seek time, and test it in online situations using a preemptive approach. In addition, we build a simulator for disk requests generation (DiskSims) to experimentally test our proposed algorithm and provide a comprehensive comparison with popular disk scheduling algorithms. Experimental results demonstrate that our algorithms achieve promising behavior. Кеу words - scheduling algorithms, scheduling simulator.
Field Programmable Gate Array Implementation of 14 bit Sigma-Delta Analog to Digital Converter

This paper the design and FPGA implementation of a delta sigma A/D convertor. The proposed converter has been designed using Xilinx system generator tool, which reduces the design cycle by directly generating efficient VHDL code. The VHDL code has been implemented on a Spartan 3E xc3s100e-4vq100 FPGA using ISE 12.4 tool.
Are We Innovative? Increasing Perceptions of Nonprofit Innovation Through Leadership, Inclusion, and Commitment

Innovation is particularly important for the sustainability, functioning, and improvement of public and nonprofit organizations. Researchers have called for the examination of how leaders can foster innovation in the nonprofit context. This study examined whether climate for inclusion and affective commitment were key mechanisms by which transformational leadership increased perceptions of innovation in a diverse nonprofit health care organization. Data were collected at three points in 6-month intervals from a U.S. nonprofit hospital. Longitudinal multilevel path analysis revealed transformational leaders increase perceptions of nonprofit innovation through helping every organizational member feel valued as an important member of the group and appreciated for their unique personal characteristics (fostering a climate for inclusion). Inclusion increases organizational members’ emotional attachment to the organization (affective commitment), which then enhances favorable perceptions of innovation wherein members feel comfortable sharing their ideas and perspectives with one another (critical to workplace innovation).
Impacto do reconhecimento de instrumentos financeiros mensurados a valor justo sobre a volatilidade do resultado

Visando verificar se o reconhecimento de instrumentos financeiros mensurados a valor justo no resultado levou a uma maior volatilidade dos lucros contábeis, adotou-se testes estatísticos que analisaram a diferença entre as variâncias dos lucros líquidos que consideram instrumentos financeiros avaliados a valor justo e a custo histórico amortizado, no período entre 2010 e 2016, das empresas brasileiras de capital aberto não financeiras e Bancos com maior Presença em Bolsa. Após analisar o efeito sobre o lucro líquido dos ganhos e perdas não realizados de instrumentos financeiros, constatou-se uma tendência a suavização, tanto para as empresas não-financeiras quanto para os Bancos, e não de aumento da volatilidade como argumentado pelos críticos a adoção do valor justo. Essa tendência pode apresentar um impacto positivo na avaliação dessas empresas pelo mercado de capitais e por credores, já que apresentam uma preferência por lucros consistentes ao longo do tempo, devido a sua aversão ao risco.
SUPPLY CHAIN INTEGRATION UNDER VENDOR MANAGED INVENTORY MODE OF OPERATION CONSIDERING STOCKOUT

This paper formulates a two-echelon single-vendor multi-buyer supply chain model assuming unsatisfied demand at the vendor to be backordered. The vendor and buyers apply Vendor Managed Inventory (VMI) mode of operation. The vendor gives the product to the buyers. The operational parameters are sales quantity, sales price and maximum number of stockouts for each buyer at the vendor’s location. Channel profit of the supply chain and contract price between the vendor and buyers are determined based on the operational parameters. In order to find out the optimal values of the parameters, a mathematical model is formulated. Two heuristics are proposed to solve the addressed problem. Some numerical problems are provided and each problem is solved utilizing the heuristics. We have also solved the sample problems utilizing LINGO optimization solver in order to evaluate the performance of the proposed algorithms.
Legal reasoning: the methods of balancing : proceedings of the Special Workshop “Legal reasoning: the methods of balancing" held at the 24th World Congress of the International Association for Philosophy of Law and Social Philosophy (IVR), Beijing, 2009

Balancing is an indispensable instrument of legal reasoning, both with respect to the interpretation and application of basic and human rights and to numerous other fields of law. However, the objectivity, rationality, and legitimacy of this method are now being contested. It is criticised as irrational and arbitrary, a threat to legal certainty, and an illegitimate interference of courts with the political sphere. The contributions in this volume are devoted to an examination of these issues. Some of them discuss the structure of balancing and offer advanced theoretical analyses. A main focus is Robert Alexy's "weight formula". Other issues are the problem of rationality of balancing and its legitimacy in judicial decision-making, in particular regarding the application of the principle of proportionality in constitutional and European Community law.
Genetic Based Qos Task Scheduling In Cloud -Upgrade Genetic Algorithm

Cloud computing has been emerged as a new service model in computing world and giving lot of interest to the researchers to find its benefits. Task scheduling is a major conflict in cloud environment and genetic algorithms are one of the optimization techniques to solve that problem. Virtual machine’s processing elements are important criteria to solve a scheduling problem. In proposed algorithm called upgraded Genetic algorithm, initial population is sorted according to the number of processing elements of each virtual machines. Proposed algorithm is compared with MGA in terms of cost and with MACO in terms of make span. Experiment results shows upgrade genetic algorithm gives better efficiency in term of cost and make span.
Die Grundsätze ordnungsmäßiger Modellierung und ihre Einbettung in ein Vorgehensmodell zur Erstellung betrieblicher Informationsmodelle

Mit den Grundsätzen ordnungsmäßiger Modellierung (GOM) ist ein methodischer Ordnungsrahmen entwickelt und über die letzten Jahre validiert worden, der die Erstellung von Informationsmodellen in bezug auf Klarheit, Konsistenzsicherung und Qualität unterstützt. Die Anwendbarkeit der Grundsätze ordnungsmäßiger Modellierung wird dadurch noch weiter erhöht, daß sie in ein Vorgehensmodell eingebunden werden, das einen Vorschlag unterbreitet, in welchen Schritten ein Modellierungsprojekt voranschreiten muß und welche Maßnahmen, die diesen Grundsätzen zugeordnet werden können, zu welchem Zeitpunkt beachtet werden müssen. Damit liegt ein geschlossenes Rahmenkonzept vor, das insbesondere bei großen Modellierungsprojekten eine wesentliche Unterstützung bei der Modellerstellung bietet. In dem Beitrag werden die sechs Grundsätze ordnungsmäßiger Modellierung – Grundsatz der Richtigkeit, Grundsatz der Relevanz, Grundsatz der Wirtschaftlichkeit, Grundsatz der Klarheit, Grundsatz der Vergleichbarkeit und Grundsatz des systematischen Aufbaues vorgestellt. Daraus werden Maßnahmen abgeleitet, z. B. Entwicklung eines strukturierenden Ordnungsrahmens, Vermeidung von sich schneidenden Linien im Layout von Informationsmodellen, Prüfung des Modells gegen ein Metamodell, Einhaltung von Namenskonventionen, Verwendung geeigneter Konnektoren in ereignisgesteuerten Prozeßketten für Build-Timeund Run-Time-Komponenten, Verwendung konsistenter Hierarchieebenen etc. Schließlich wird ein Vorgehensmodell entwickelt, das die Schritte zur Erstellung von betrieblichen Informationsmodellen vorgibt: Zieldefinition, Konstruktion des Ordnungsrahmens, Modellierung der Struktur, Konsolidierung und Komplettierung, Umsetzung und Prozeßanalyse. Interdependenzen zwischen Grundsätzen, Maßnahmen und Vorgehensmodell werden thematisiert. Ein EDV-System zur Unterstützung der Modellerstellung unter Zuhilfenahme der Grundsätze ordnungsmäßiger Modellierung, der „GOM-Advisor“ hilft, diese Interdependenzen sichtbar zu machen.
Simulation Research of Fault-Tolerant Control Based on Adaptive Mind Evoltionary Algorithm

Mind evolutionary computation(MEC) is a novel intelligent computing algorithm.It can effectively avoid some essential drawbacks of genetic algorithm(GA), but yet there exists disadvantage of slow evolution speed in MEC.In order to increase the evolution speed of MEC, an adaptive mind-evolutionary algorithm(AMEA) was proposed via introducing three adaptive factors.An adaptive mind-evolutionary fault-tolerant control(AMEFTC) system, which could reconfigure the control law on-line, was constructed based on AMEA, and this fault-tolerant control system could guarantee normal static and dynamic characteristics of system when faults occurred within the system.Feasibility and effectiveness of the above fault-tolerant strategies were demonstrated by simulation examples.
CoPrivacy:A Collaborative Location Privacy-Preserving Method without Cloaking Region

Serious location privacy problems arise with extensive application of location-based services.Nowadays,location k-anonymity is the one of the most popular location privacy-preserving methods,it requires a trusted third party as an anonymity server which is proved to be the performance bottleneck and aim point of attacks.In addition,it complicates the query processing by requiring an anonymity region instead of a point.This paper proposes a collaborative location privacy-preserving method without anonymity server and cloaking region.Anonymity groups are formed through user's collaboration,members in the group regard density center as their locations when requiring for LBS,and acquire kNN results incrementally from the service provider.At last,group members get the precise results through computing distances between their locations and the kNN results.The proposed method achieves k-anonymity without cloaking region,the efficiency of anonymity is improved,and query processing is simplified.Extensive experimental results show advantages of the proposed method.
An Application of Genetic Algorithm for Extraction and Evaluation of Effectiveness of Paths for Testing from Activity Diagram

Software testing is the process of validation and verification of the software product which in turn deliver the reliable and quality oriented software product to users. For this, an effective software testing process is required to generate effective test cases, which demand an effort, time and cost. In many software development organizations, the cost of testing can account for more than 40% of the total development cost for a software system. This necessity has increased the demand for techniques that can generate test data effectively as well as at low cost. This paper proposed an application of Genetic Algorithm (GA) for extraction of paths to be tested from UML Activity diagram and evaluation of its effectiveness. Activity diagram is transformed to activity flow graph and then assigning weights on it. On the weighted activity flow graph, GA operators will be applied to get path that must be tested first with the suitable test case.
A 12-bit 1-MS/s 26-μW SAR ADC for Sensor Applications

Abstract This chapter presents an energy-efficient 12-bit 1-MS/s successive approximation register analog-to-digital converter (ADC) for sensor applications. A programmable dynamic comparator is proposed to suppress static current and maintain good linearity. A hybrid charge redistribution digital-to-analog converter is proposed to decrease the total capacitance, which would reduce the power consumption of the input and reference buffers. In the proposed ADC, its total input capacitance is only 700 fF, which greatly reduces the total power consumption of the analog frontend circuits. The 12-bit ADC is fabricated using 0.18-μm complementary metal-oxidesemiconductor technology, and it consumes only 26 μW from a 1 V supply at 1-MS/s. The measured signal-to-noise-and-distortion ratio (SNDR) and spurious-free dynamic range (SFDR) are 60.1 and 72.6 dB, respectively. The measured effective number of bits (ENOB) for a 100 kHz input frequency is 9.7 bits. At the Nyquist input frequency, the measured SNDR and SFDR are 59.7 and 71 dB, respectively. The ENOB is maintained at 9.6 bits and the figure-of-merit is 33.5 fJ/conversion-step.
An Empirical Study On Interest Rate Towards International Markets

Interest rate is one of the fiscal factors that is used to regulate the monetary policy of a country. The main objective of the study is to know about the interest rate prevailing with countries and to analyze about impact of interest rate towards international currency pairs. For this purpose the currencies of five countries were taken and they were compared with the interest rate to know about the impact. The conclusion that the interest rate changes has an impact towards the market in mid and long term basis with all the currencies taken for the study.
Data Aided ML Symbol Timing Estimation for MIMO Systems Using a Polyphase Filterbank

This paper derives the maximum likelihood (ML) symbol timing estimator for a frequency nonselective multiple-input, multiple output (MIMO) channel assuming linear modulation and known data and known channel gains. The non-frequency selective fading assumption means the multipath delay spread is small so that the symbol time delay is the same across all receive antennas. Both a closed-loop and an approximate open-loop architecture are demonstrated. The open-loop or “batch” estimator is based on a polyphase filterbank implementation of the derivative matched filter.
Effectively Metamorphic Testing Based on Program Path Analysis

Metamorphic testing is very practical and effective for programs with oracle problems.Much research has been done in this field.Based upon existed methods of metamorphic testing and program path-analysis,the authors first present a set of metamorphic testing criteria for the test with binary metamorphic relations.These criteria define the adequacy of metamorphic test suites at several different levels.Then,three new testing algorithms are given to generate test suites that could satisfy the criteria above.Finally,these algorithms' performances are fully proved with the technique of mutation analysis.The experiment results show that testing effects are greatly decided by the selection of metamorphic relations and testing criteria,and the algorithm APCEMST could detect faults quickly and exactly with fewer test cases than traditional method.
Blind Detection of High Frequency FH Signals Based on Image Segmentation and Template Matching

In this paper,an algorithm is proposed for blind detection of High Frequency FH Signals based on Image Segmentation and Template Matching.The algorithm takes the time-frequency spectrograph of practical signal STFT as an ordinary image,utilizes image segmentation to remove the background noise,and implements the blind detection of FH signal by template matching.Experimental results show that the algorithm can effectively remove the complex background noise coming from the practical High Frequency channel with smaller computational complexity,thus making engineering implementation easier.