Efficiency Analyses of Higher Education in Taiwan: Implications to Higher Education Crisis

This study applies nonparametric DEA to analyze Taiwan’s 46 comprehensive and 73 technical universities from 2012 to 2017. The inter-category comparison of efficient universities percentage reveals that, on the whole, private universities outperform public universities in the same category. In addition, comprehensive universities outperform technical universities. However, the trend analyses confirm that facing the challenge of the higher education crisis, performance improvement is much more urgent for PriCU, PubTECH and PriTECH than for PubCU, especially for PriTECH. The crisis in higher education has hit private universities harder than public ones, and technical universities harder than comprehensive ones, and is worsening fast. Moreover, for PubCU, PubTECH, and PriTECH to better their overall operational efficiency, facilitating management efficiency or innovating teaching and research are equally crucial with optimizing operational scale. Conversely, for PriCU, they should, first of all, put more emphasis on scale efficiency improvement to boom their efficiencies. In terms of scale efficiency, it is required to together consider pure technical efficiency and scale return, and thus seems no merger combinations can better their efficiencies and simultaneously solve their urgent crisis. That thus suggests PriCU, PubTECH, and PriTECH should take other ways, such as to raise income from outputs other than tuition fees, rather than a merger, to reduce the shock as could as possible and thus improve their scale efficiency. Finally, the robustness test suggests consolidated estimation is a more objective and fair evaluation of university efficiency.

State of Emergency in Turkey (July 2016 – July 2018): A Case of Utilization of Law as a Political Instrument

In this study, we will aim to analyze how the period of the state of emergency in Turkey lead to gaps in law and the formation of areas in which there was a complete lack of supervision. The state of emergency that was proclaimed following the coup attempt of July 15, 2016, continued until July 18, 2018, that is to say, 2 years, without taking into account whether the initial circumstances persisted. As part of this work, we claim that the state of emergency provided the executive power with important tools for governing, which it took constant use. We can highlight how the concern for security at the center of the basic considerations of the people in a city was exploited as a foundation by the military power in Turkey to interfere in the political, legal and social spheres. The constitutions of 1924, 1961 and 1982 entrusted the army with the role of protector of the integrity of the state. This became an instrument at the hands of the military to legitimize their interventions in the name of public security. Its interventions in the political field are indeed politically motivated. The constitution, the legislative and regulatory systems are modified and monopolized by the military power that dominates the legislative, regulatory and judicial power, leading to a state of exception. With the political convulsions over a decade, the government was able to usurp the instrument called the state of exception. In particular, the decree-laws of the state of emergency, which the executive makes frequent and generally abusive use, became instruments in the hands of the government to take measures that it wishes to escape from the rules and the pre-established control mechanisms. Thus the struggle against the political opposition becomes more unbalanced and destructive. To this must also be added the ineffectiveness of ex-post controls and domestic remedies. This research allows us to stress how a legal concept such as "the state of emergency" can be politically exploited to make it a legal weapon that continues to produce victims.

A Comparison Study of the Animation Industries between China and Japan

Taking Japanese and Chinese animation industry as research objects with a detailed analysis and comparison of the industrial models and status quo in two countries, this study fully reveals the development mechanism and internal and external situations of the industry. It is believed that the Japanese animation industry's continuous pursuit of low-cost production models, virtuous recycling mechanisms, and active expansion of overseas markets are valuable experiences; whereas China needs to strengthen national and local support for animation and emphasis on the protection of the copyright. The targeted and forward-looking suggestions and conclusions proposed in this study provides not only an insight into the animation industry but also inspirations for development in the animation industry around the world through an analysis of experiences and shortcomings.

Public Participation Regarding Heritage Preservation in Former Communist Countries: The Case of Tobacco City in Plovdiv, Bulgaria

In times of rapid globalization, the significance of cultural and architectural heritage is rising, as it is a key element to define the identity of a place, a city, even a country. Its preservation, conservation, and revitalization are everyone’s responsibility, and the public is growing more aware of that fact. The citizens are looking for a way to actively participate in the decision-making in projects regarding heritage sites. Public involvement in the planning process is not a new phenomenon, especially in Western countries. However, countries, such as the former communist states of Eastern Europe, have been less studied. Based on established theories, this paper analyses the level of citizens’ inclusion in projects regarding heritage preservation, using the example of the Tobacco City in Plovdiv, Bulgaria. As this case is exemplary for Bulgaria, it illustrates the current condition of public participation country-wise. At the same time, considering the former communist states have had a similar socio-economic and political development in the past several decades, it is possible to apply the conclusions to most of these countries with only slight variations.

Image Haze Removal Using Scene Depth Based Spatially Varying Atmospheric Light in Haar Lifting Wavelet Domain

This paper presents a method for single image dehazing based on dark channel prior (DCP). The property that the intensity of the dark channel gives an approximate thickness of the haze is used to estimate the transmission and atmospheric light. Instead of constant atmospheric light, the proposed method employs scene depth to estimate spatially varying atmospheric light as it truly occurs in nature. Haze imaging model together with the soft matting method has been used in this work to produce high quality haze free image. Experimental results demonstrate that the proposed approach produces better results than the classic DCP approach as color fidelity and contrast of haze free image are improved and no over-saturation in the sky region is observed. Further, lifting Haar wavelet transform is employed to reduce overall execution time by a factor of two to three as compared to the conventional approach.

Modeling Engagement with Multimodal Multisensor Data: The Continuous Performance Test as an Objective Tool to Track Flow

Engagement is one of the most important factors in determining successful outcomes and deep learning in students. Existing approaches to detect student engagement involve periodic human observations that are subject to inter-rater reliability. Our solution uses real-time multimodal multisensor data labeled by objective performance outcomes to infer the engagement of students. The study involves four students with a combined diagnosis of cerebral palsy and a learning disability who took part in a 3-month trial over 59 sessions. Multimodal multisensor data were collected while they participated in a continuous performance test. Eye gaze, electroencephalogram, body pose, and interaction data were used to create a model of student engagement through objective labeling from the continuous performance test outcomes. In order to achieve this, a type of continuous performance test is introduced, the Seek-X type. Nine features were extracted including high-level handpicked compound features. Using leave-one-out cross-validation, a series of different machine learning approaches were evaluated. Overall, the random forest classification approach achieved the best classification results. Using random forest, 93.3% classification for engagement and 42.9% accuracy for disengagement were achieved. We compared these results to outcomes from different models: AdaBoost, decision tree, k-Nearest Neighbor, naïve Bayes, neural network, and support vector machine. We showed that using a multisensor approach achieved higher accuracy than using features from any reduced set of sensors. We found that using high-level handpicked features can improve the classification accuracy in every sensor mode. Our approach is robust to both sensor fallout and occlusions. The single most important sensor feature to the classification of engagement and distraction was shown to be eye gaze. It has been shown that we can accurately predict the level of engagement of students with learning disabilities in a real-time approach that is not subject to inter-rater reliability, human observation or reliant on a single mode of sensor input. This will help teachers design interventions for a heterogeneous group of students, where teachers cannot possibly attend to each of their individual needs. Our approach can be used to identify those with the greatest learning challenges so that all students are supported to reach their full potential.

Eco-Design of Multifunctional System Based on a Shape Memory Polymer and ZnO Nanoparticles for Sportswear

Since the beginning of the 20th century, sportswear has a major contribution to the impact of fashion on our lives. Nowadays, the embracing of sportswear fashion/looks is undoubtedly noticeable, as the modern consumer searches for high comfort and linear aesthetics for its clothes. This compromise lead to the arise of the athleisure trend. Athleisure surges as a new style area that combines both wearability and fashion sense, differentiated from the archetypal sportswear, usually associated to “gym clothes”. Additionally, the possibility to functionalize and implement new technologies have shifted and progressively empowers the connection between the concepts of physical activities practice and well-being, allowing clothing to be more interactive and responsive with its surroundings. In this study, a design inspired in retro and urban lifestyle was envisioned, engineering textile structures that can respond to external stimuli. These structures are enhanced to be responsive to heat, water vapor and humidity, integrating shape memory polymers (SMP) to improve the breathability and heat-responsive behavior of the textiles and zinc oxide nanoparticles (ZnO NPs) to heighten the surface hydrophobic properties. The best results for hydrophobic exhibited superhydrophobic behavior with water contact angle (WAC) of more than 150 degrees. For the breathability and heat-response properties, SMP-coated samples showed an increase in water vapour permeability values of about 50% when compared with non SMP-coated samples. These innovative technological approaches were endorsed to design innovative clothing, in line with circular economy and eco-design principles, by assigning a substantial degree of mutability and versatility to the clothing. The development of a coat and shirt, in which different parts can be purchased separately to create multiple products, aims to combine the technicality of both the fabrics used and the making of the garments. This concept translates itself into a real constructive mechanism through the symbiosis of high-tech functionalities and the timeless design that follows the athleisure aesthetics.

Characterizing the Geometry of Envy Human Behaviour Using Game Theory Model with Two Types of Homogeneous Players

An envy behavioral game theoretical model with two types of homogeneous players is considered in this paper. The strategy space of each type of players is a discrete set with only two alternatives. The preferences of each type of players is given by a discrete utility function. All envy strategies that form Nash equilibria and the corresponding envy Nash domains for each type of players have been characterized. We use geometry to construct two dimensional envy tilings where the horizontal axis reflects the preference for players of type one, while the vertical axis reflects the preference for the players of type two. The influence of the envy behavior parameters on the Cartesian position of the equilibria has been studied, and in each envy tiling we determine the envy Nash equilibria. We observe that there are 1024 combinatorial classes of envy tilings generated from envy chromosomes: 256 of them are being structurally stable while 768 are with bifurcation. Finally, some conditions for the disparate envy Nash equilibria are stated.

Normal and Peaberry Coffee Beans Classification from Green Coffee Bean Images Using Convolutional Neural Networks and Support Vector Machine

The aim of this study is to develop a system which can identify and sort peaberries automatically at low cost for coffee producers in developing countries. In this paper, the focus is on the classification of peaberries and normal coffee beans using image processing and machine learning techniques. The peaberry is not bad and not a normal bean. The peaberry is born in an only single seed, relatively round seed from a coffee cherry instead of the usual flat-sided pair of beans. It has another value and flavor. To make the taste of the coffee better, it is necessary to separate the peaberry and normal bean before green coffee beans roasting. Otherwise, the taste of total beans will be mixed, and it will be bad. In roaster procedure time, all the beans shape, size, and weight must be unique; otherwise, the larger bean will take more time for roasting inside. The peaberry has a different size and different shape even though they have the same weight as normal beans. The peaberry roasts slower than other normal beans. Therefore, neither technique provides a good option to select the peaberries. Defect beans, e.g., sour, broken, black, and fade bean, are easy to check and pick up manually by hand. On the other hand, the peaberry pick up is very difficult even for trained specialists because the shape and color of the peaberry are similar to normal beans. In this study, we use image processing and machine learning techniques to discriminate the normal and peaberry bean as a part of the sorting system. As the first step, we applied Deep Convolutional Neural Networks (CNN) and Support Vector Machine (SVM) as machine learning techniques to discriminate the peaberry and normal bean. As a result, better performance was obtained with CNN than with SVM for the discrimination of the peaberry. The trained artificial neural network with high performance CPU and GPU in this work will be simply installed into the inexpensive and low in calculation Raspberry Pi system. We assume that this system will be used in under developed countries. The study evaluates and compares the feasibility of the methods in terms of accuracy of classification and processing speed.

A Robust Optimization Method for Service Quality Improvement in Health Care Systems under Budget Uncertainty

With the development of business competition, it is important for healthcare providers to improve their service qualities. In order to improve service quality of a clinic, four important dimensions are defined: tangibles, responsiveness, empathy, and reliability. Moreover, there are several service stages in hospitals such as financial screening and examination. One of the most challenging limitations for improving service quality is budget which impressively affects the service quality. In this paper, we present an approach to address budget uncertainty and provide guidelines for service resource allocation. In this paper, a service quality improvement approach is proposed which can be adopted to multistage service processes to improve service quality, while controlling the costs. A multi-objective function based on the importance of each area and dimension is defined to link operational variables to service quality dimensions. The results demonstrate that our approach is not ultra-conservative and it shows the actual condition very well. Moreover, it is shown that different strategies can affect the number of employees in different stages.

Designing of a Non-Zero Dispersion Shifted Fiber with Ultra-High Birefringence and High Non-Linearity

Photonic Crystal Fiber (PCF) uses are no longer limited to telecommunication only rather it is now used for many sensors-based fiber optics application, medical science, space application and so on. In this paper, the authors have proposed a microstructure PCF that is designed by using Finite Element Method (FEM) based software. Besides designing, authors have discussed the necessity of the characteristics that it poses for some specified applications because it is not possible to have all good characteristics from a single PCF. Proposed PCF shows the property of ultra-high birefringence (0.0262 at 1550 nm) which is more useful for sensor based on fiber optics. The non-linearity of this fiber is 50.86 w-1km-1 at 1550 nm wavelength which is very high to guide the light through the core tightly. For Perfectly Matched Boundary Layer (PML), 0.6 μm diameter is taken. This design will offer the characteristics of Nonzero-Dispersion-Shifted Fiber (NZ-DSF) for 450 nm waveband. Since it is a software-based design and no practical evaluation has made, 2% tolerance is checked and the authors have found very small variation of the characteristics.

Public Financial Management in Ghana: A Move beyond Reforms to Consolidation and Sustainability

Ghana’s Public Financial Management reforms have been going on for some two decades now (1997/98 to 2017/18). Given this long period of reforms, Ghana in 2019 is putting together both a Public Financial Management (PFM) strategy and a Ghana Integrated Financial Management Information System (GIFMIS) strategy for the next 5-years (2020-2024). The primary aim of these dual strategies is assisting the country in moving beyond reforms to consolidation and sustainability. In this paper we, first, examined the evolution of Ghana’s PFM reforms. We, secondly, reviewed the legal and institutional reforms undertaken to strengthen the country’s key PFM institutions. Thirdly, we summarized the strengths and weaknesses identified by the 2018 Public Expenditure and Financial Accountability (PEFA) assessment of Ghana’s PFM system relating to its macro-fiscal framework, budget preparation and approval, budget execution, accounting and fiscal reporting as well as external scrutiny and audit. We, finally, considered what the country should be doing to achieve its intended goal of PFM consolidation and sustainability. Using a qualitative method of review and analysis of existing documents, we, through this paper, brought to the fore the lessons that could be learnt by other developing countries from Ghana’s PFM reforms experiences. These lessons included the need to: (a) undergird any PFM reform with a comprehensive PFM reform strategy; (b) undertake a legal and institutional reforms of the key PFM institutions; (c) assess the strengths and weaknesses of those reforms using PFM performance evaluation tools such as PEFA framework; and (d) move beyond reforms to consolidation and sustainability.

Controlling of Multi-Level Inverter under Shading Conditions Using Artificial Neural Network

This paper describes the effects of photovoltaic voltage changes on Multi-level inverter (MLI) due to solar irradiation variations, and methods to overcome these changes. The irradiation variation affects the generated voltage, which in turn varies the switching angles required to turn-on the inverter power switches in order to obtain minimum harmonic content in the output voltage profile. Genetic Algorithm (GA) is used to solve harmonics elimination equations of eleven level inverters with equal and non-equal dc sources. After that artificial neural network (ANN) algorithm is proposed to generate appropriate set of switching angles for MLI at any level of input dc sources voltage causing minimization of the total harmonic distortion (THD) to an acceptable limit. MATLAB/Simulink platform is used as a simulation tool and Fast Fourier Transform (FFT) analyses are carried out for output voltage profile to verify the reliability and accuracy of the applied technique for controlling the MLI harmonic distortion. According to the simulation results, the obtained THD for equal dc source is 9.38%, while for variable or unequal dc sources it varies between 10.26% and 12.93% as the input dc voltage varies between 4.47V nd 11.43V respectively. The proposed ANN algorithm provides satisfied simulation results that match with results obtained by alternative algorithms.

Uplink Throughput Prediction in Cellular Mobile Networks

The current and future cellular mobile communication networks generate enormous amounts of data. Networks have become extremely complex with extensive space of parameters, features and counters. These networks are unmanageable with legacy methods and an enhanced design and optimization approach is necessary that is increasingly reliant on machine learning. This paper proposes that machine learning as a viable approach for uplink throughput prediction. LTE radio metric, such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), and Signal to Noise Ratio (SNR) are used to train models to estimate expected uplink throughput. The prediction accuracy with high determination coefficient of 91.2% is obtained from measurements collected with a simple smartphone application.

Urban Development from the Perspective of Lou Gang Polder System: Taihu Lake, Huzhou as an Example

Lou Gang world irrigation project heritage in Taihu Lake is a systematic irrigation project integrating water conservancy, ecology and culture. Through the methods of historical documents and field investigation, this paper deeply analyzes the formation history, connotation and value of Lou Gang polder system: Lou Gang heritage, describes in detail the relationship between Lou Gang polder system in Taihu Lake and the development and evolution of Huzhou City, and initially explores the protection and Utilization Strategies of Lou Gang water conservancy cultural heritage resources in Taihu Lake from the current situation.

Mistranslation in Cross Cultural Communication: A Discourse Analysis on Former President Bush’s Speech in 2001

The differences in languages play a big role in cross-cultural communication. If meanings are not translated accurately, the risk can be crucial not only on an interpersonal level, but also on the international and political levels. The use of metaphorical language by politicians can cause great confusion, often leading to statements being misconstrued. In these situations, it is the translators who struggle to put forward the intended meaning with clarity and this makes translation an important field to study and analyze when it comes to cross-cultural communication. Owing to the growing importance of language and the power of translation in politics, this research analyzes part of President Bush’s speech in 2001 in which he used the word “Crusade” which caused his statement to be misconstrued. The research uses a discourse analysis of cross-cultural communication literature which provides answers supported by historical, linguistic, and communicative perspectives. The first finding indicates that the word ‘crusade’ carries different meaning and significance in the narratives of the Western world when compared to the Middle East. The second one is that, linguistically, maintaining cultural meanings through translation is quite difficult and challenging. Third, when it comes to the cross-cultural communication perspective, the common and frequent usage of literal translation is a sign of poor strategies being followed in translation training. Based on the example of Bush’s speech, this paper hopes to highlight the weak practices in translation in cross-cultural communication which are still commonly used across the world. Translation studies have to take issues such as this seriously and attempt to find a solution. In every language, there are words and phrases that have cultural, historical and social meanings that are woven into the language. Literal translation is not the solution for this problem because that strategy is unable to convey these meanings in the target language.

Research on Reservoir Lithology Prediction Based on Residual Neural Network and Squeeze-and- Excitation Neural Network

Conventional reservoir prediction methods ar not sufficient to explore the implicit relation between seismic attributes, and thus data utilization is low. In order to improve the predictive classification accuracy of reservoir lithology, this paper proposes a deep learning lithology prediction method based on ResNet (Residual Neural Network) and SENet (Squeeze-and-Excitation Neural Network). The neural network model is built and trained by using seismic attribute data and lithology data of Shengli oilfield, and the nonlinear mapping relationship between seismic attribute and lithology marker is established. The experimental results show that this method can significantly improve the classification effect of reservoir lithology, and the classification accuracy is close to 70%. This study can effectively predict the lithology of undrilled area and provide support for exploration and development.

Energy Recovery Potential from Food Waste and Yard Waste in New York and Montréal

Landfilling of organic waste is still the predominant waste management method in the USA and Canada. Strategic plans for waste diversion from landfills are needed to increase material recovery and energy generation from waste. In this paper, we carried out a statistical survey on waste flow in the two cities New York and Montréal and estimated the energy recovery potential for each case. Data collection and analysis of the organic waste (food waste, yard waste, etc.), paper and cardboard, metal, glass, plastic, carton, textile, electronic products and other materials were done based on the reports published by the Department of Sanitation in New York and Service de l'Environnement in Montréal. In order to calculate the gas generation potential of organic waste, Buswell equation was used in which the molar mass of the elements was calculated based on their atomic weight and the amount of organic waste in New York and Montréal. Also, the higher and lower calorific value of the organic waste (solid base) and biogas (gas base) were calculated. According to the results, only 19% (598 kt) and 45% (415 kt) of New York and Montréal waste were diverted from landfills in 2017, respectively. The biogas generation potential of the generated food waste and yard waste amounted to 631 million m3 in New York and 173 million m3 in Montréal. The higher and lower calorific value of food waste were 3482 and 2792 GWh in New York and 441 and 354 GWh in Montréal, respectively. In case of yard waste, they were 816 and 681 GWh in New York and 636 and 531 GWh in Montréal, respectively. Considering the higher calorific value, this amount would mean a contribution of around 2.5% energy in these cities.

Virtual Container Yard: Assessing the Perceived Impact of Legal Implications to Container Carriers

Virtual Container Yard (VCY) is a modern concept that helps to reduce the empty container repositioning cost of carriers. The concept of VCY is based on container interchange between shipping lines. Although this mechanism has been theoretically accepted by the shipping community as a feasible solution, it has not yet achieved the necessary momentum among container shipping lines (CSL). This paper investigates whether there is any legal influence on this industry myopia about the VCY. It is believed that this is the first publication that focuses on the legal aspects of container exchange between carriers. Not much literature on this subject is available. This study establishes with statistical evidence that there is a phobia prevailing in the shipping industry that exchanging containers with other carriers may lead to various legal implications. The complexity of exchange is two faceted. CSLs assume that offering a container to another carrier (obviously, a competitor in terms of commercial context) or using a container offered by another carrier may lead to undue legal implications. This research reveals that this fear is reflected through four types of perceived components, namely: shipping associate; warehouse associate; network associate; and trading associate. These components carry eighteen subcomponents that comprehensively cover the entire process of a container shipment. The statistical explanation has been supported through regression analysis; INCO terms were used to illustrate the shipping process.

Validation and Projections for Solar Radiation up to 2100: HadGEM2-AO Global Circulation Model

The objective of this work is to evaluate the results of solar radiation projections between 2006 and 2013 for the state of Rio Grande do Sul, Brazil. The projections are provided by the General Circulation Models (MCGs) belonging to the Coupled Model Intercomparison Phase 5 (CMIP5). In all, the results of the simulation of six models are evaluated, compared to monthly data, measured by a network of thirteen meteorological stations of the National Meteorological Institute (INMET). The performance of the models is evaluated by the Nash coefficient and the Bias. The results are presented in the form of tables, graphs and spatialization maps. The ACCESS1-0 RCP 4.5 model presented the best results for the solar radiation simulations, for the most optimistic scenario, in much of the state. The efficiency coefficients (CEF) were between 0.95 and 0.98. In the most pessimistic scenario, HADGen2-AO RCP 8.5 had the best accuracy among the analyzed models, presenting coefficients of efficiency between 0.94 and 0.98. From this validation, solar radiation projection maps were elaborated, indicating a seasonal increase of this climatic variable in some regions of the Brazilian territory, mainly in the spring.