PENGARUH KEJELASAN SASARAN ANGGARAN DAN PARTISIPASI ANGGARAN TEHADAP KINERJA ORGANISASI DENGAN GAYA KEPEMIMPINAN SEBAGAI VARIABEL PEMODERASI (STUDI PADA KELEMBAGAAN DAN UKM DI UST)

This study aims to test whether the clarity of budget targets and budget participation in institutions and Student Activity Units of the Sarjanawiyata Tamansiswa University Yogyakarta have an effect on organizational performance with leadership style as a moderating variable. The study took a sample of students who were active in the Student Activity Unit at the Sarjanawiyata Tamansiswa University, Yogyakarta. The technique used in sampling is carried out with a non-probability or non-random approach using convenience sampling. Data collection was carried out by spreading the google form link through the Instagram and Whatsapp applications to institutional members and the Student Activity Unit (UKM). The number of questionnaires processed is 100 questionnaires. Data were analyzed using path analysis. The results showed that the clarity of budget targets had no effect on organizational performance. Budget participation has an effect on organizational performance. Leadership style cannot strengthen the influence of clarity of budget objectives on organizational performance. Leadership style cannot strengthen the influence of budget participation on organizational performance. Keywords: Clarity of budget targets; Budget Participation; Organizational Performance; Leadership Style

An Analytical Optimisation Framework for Airport Terminal Capacity Expansion

This article considers how to allocate additional physical resources within airport terminals. An optimization model was developed to determine where additional resources should be placed to minimise passenger waiting times. The objective function is stochastic and can only be evaluated using discrete event simulation. As this model is stochastic and nonlinear, a Simulated Annealing (SA) metaheuristic was implemented and tested. The SA algorithm repeatedly perturbs a resource allocation solution using one of two methods. The first method is creating new solution randomly in each iteration, and the second method is local search that is mimicked by any move of the current solution of x solution chosen randomly in its neighborhood. Numerical testing shows that the random approach is best, and solutions that are 12.11% better can be obtained.

Entrepreneurial Orientation and Firm Performance: Evidence from Argentina

This document aims to study the role played by the five dimensions of entrepreneurial orientation on corporate performance. To test our hypotheses, we used a sample of companies headquartered in Argentina. To collect the data, we used a questionnaire that was sent by e-mail to the owner and/or manager of the companies. At the end of the survey, 214 Argentine companies (21.4% of the sample) completed the questionnaire. The sampling was carried out with a stratified random approach to improve the efficiency of the estimates and ensure the representativeness of the extracted sample. To assess the reliability of the results, quantitative statistical tools were used. The analysis results show that not all variables have a significant influence on performance. In particular, three dimensions of the EO (innovation, proactivity, and risk) have a significant and positive influence on the performance of companies. Conversely, competitive aggressiveness and autonomy do not have a significant impact on performance or they are not relevant.

Active feature acquisition on data streams under feature drift

Traditional active learning tries to identify instances for which the acquisition of the label increases model performance under budget constraints. Less research has been devoted to the task of actively acquiring feature values, whereupon both the instance and the feature must be selected intelligently and even less to a scenario where the instances arrive in a stream with feature drift. We propose an active feature acquisition strategy for data streams with feature drift, as well as an active feature acquisition evaluation framework. We also implement a baseline that chooses features randomly and compare the random approach against eight different methods in a scenario where we can acquire at most one feature at the time per instance and where all features are considered to cost the same. Our initial experiments on 9 different data sets, with 7 different degrees of missing features and 8 different budgets show that our developed methods outperform the random acquisition on 7 data sets and have a comparable performance on the remaining two.

Out of Pocket Payment by Inpatients After Health Sector Evolution Plan and Its Effecting Factors: A Report of Iran

Background: The health transformation plan (HTP) was implemented in April 2014 in university hospitals to provide equitable access to healthcare, improve the quality of care, and protect patients against high costs of hospitals. Objectives: The present study aimed to investigate out of pocket (OOP) payment by inpatients after the health sector evolution plan (HSEP) and its effective factors in hospitals affiliated with Iran University of Medical Science. Methods: In this study, descriptive and cross-sectional research design was utilized. 277 patients at 5 hospitals affiliated with Iran University of Medical Sciences were selected via simple random approach. Checklists and hospital bills were used to collect data. Then the data were analyzed by SPSS 19.0. Results: The results indicated that OOP was 18.71% of the total hospitals expenditure. There was a significant relationship among insurance status, location, and OOP (P < 0.05). Conclusions: The OOP rate of hospitalized patients was not in accordance with the goal set in the HSEP. Thus, policymakers and managers should take serious measures to decrease out-of-pocket payments.

Fitness-Orientated Mutation Operators in Genetic Algorithms

Genetic Algorithms are the most popular metaheuristics used in search-based program solving. They search for a solution by repeating the following operators: selection, crossover, and mutation. By going through several generations of these operators, a solution is reached. The total number of generations depends on the reproduction of offspring. Of the reproduction operators, the mutation operator tends to be chosen with a random approach because the concept of mutation is from the natural evolution cycle. But the effectiveness of genetic algorithms should be monitored, especially in software testing. The effectiveness is represented by the total number of generations, which corresponds to the speed of solution acquisition. This work focuses on mutation as a factor in reducing the total number of generations and devises two contrasting ways to define mutation operators. One is fitness-positive, and the other is fitness-negative. The fitness-negative definition thus appears to fit more aptly. This work determines which of these two methods of mutation achieves the higher effectiveness through conducting a controlled experiment. The result shows that the fitness-positive method takes a smaller number of generations than the fitness-negative method.

Multiparameter control modeling of electrical signal in a medium voltage network by Markov random approach

In this paper, the electrical signals coupled to the fields present in a medium voltage network are analyzed by the randomMarkov approach. This approach with the contribution of the “Yakam Matrix” is studied to establish the quantitative approximationsof the current I and the voltage V in non-steady state conditions in order to efficiently deduct the error percent between theexperimental and the simulated results. Also, the aim was to determine the functional constant with infinite duration through multivariablestabilization in commandability and controllability process. The development of the transition and observability matrices ofthe electrical signals behavior to establish the initialization’s system of Dirichlet is presented where the vector  by the hidden Markovapproach revealed to be almost stable. The multiparameter analysis in non-steady state conditions is conducted to show the maximumprobability of the injected signals. The comparison of the experimental results with the simulation is presented with a 4% errorobtained by using MATLAB. Since the function current I(t) remains in (0  I  20)A conditions in case of phase disconnection.However, the application of the Markov random approach in electrical networks control modeling still require further studies andclarifications.

Resource Sharing for Granted & Grant-free Demands in 5G for Non-orthogonal Multiple Access

In the present days we observed a drastic change in the usage of mobile internet as well as advancements in Internet of things. With this advancements in mobile communications as well as IOT, the present generation mobile communication i.e. 4G technology is considered to be not sufficient to reach to the needs of common people, therefore the upcoming generation 5G needs in a frame way to face to ultra huge network capacity & massive wireless connectivity. A major hopeful technology which has the capacity for enabling different user equipments, sharing interweaving wireless resources in 5G is named as Non Orthogonal multiple Access (NOMA) technology, where most of the industrialists & academicians are doing research in recent years To establish good Quality of Service (QoS) & also to obtain low access latency as well as overhead signaling NOMA must compulsorily support two kinds of approaches: i) Scheduling approach ii)Random approach. The major challenge we observe in these two kinds of approach is how efficiently we obtain simultaneous support. Here we are proposing an approach for combining the granted & grant free demands which works on the principle of allowing the approaches to share the same resources simultaneously. We are proposing heuristic resource algorithm which improve capacity of network & user connectivity of NOMA in 5G networking.

Resource Sharing for Granted & Grant-free Demands in 5G for Non-orthogonal Multiple Access

In the present days we observed a drastic change in the usage of mobile internet as well as advancements in Internet of things. With this advancements in mobile communications as well as IOT, the present generation mobile communication i.e. 4G technology is considered to be not sufficient to reach to the needs of common people, therefore the upcoming generation 5G needs in a frame way to face to ultra huge network capacity & massive wireless connectivity. A major hopeful technology which has the capacity for enabling different user equipments, sharing interweaving wireless resources in 5G is named as Non Orthogonal multiple Access (NOMA) technology, where most of the industrialists & academicians are doing research in recent years To establish good Quality of Service (QoS) & also to obtain low access latency as well as overhead signaling NOMA must compulsorily support two kinds of approaches: i) Scheduling approach ii)Random approach. The major challenge we observe in these two kinds of approach is how efficiently we obtain simultaneous support. Here we are proposing an approach for combining the granted & grant free demands which works on the principle of allowing the approaches to share the same resources simultaneously. We are proposing heuristic resource algorithm which improve capacity of network & user connectivity of NOMA in 5G networking