Search results for: hierarchical text classification models

Authors: Yonwaba Atyosi, Moses Cho, Abel Ramoelo, Nobuhle Majozi, Cecilia Masemola, Yoliswa Mkhize

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Spectroscopy has been widely used to understand the hyperspectral remote sensing of soils. Accurate and efficient measurement of soil moisture is essential for precision agriculture. The aim of this study was to understand the spectral behavior of soil at different soil water content levels and identify the significant spectral bands for soil moisture content retrieval at field-scale. The study consisted of 60 soil samples from a maize farm, divided into four different treatments representing different moisture levels. Spectral signatures were measured for each sample in laboratory under artificial light using an Analytical Spectral Device (ASD) spectrometer, covering a wavelength range from 350 nm to 2500 nm, with a spectral resolution of 1 nm. The results showed that the absorption features at 1450 nm, 1900 nm, and 2200 nm were particularly sensitive to soil moisture content and exhibited strong correlations with the water content levels. Continuum removal was developed in the R programming language to enhance the absorption features of soil moisture and to precisely understand its spectral behavior at different water content levels. Statistical analysis using partial least squares regression (PLSR) models were performed to quantify the correlation between the spectral bands and soil moisture content. This study provides insights into the spectral behavior of soil at different water content levels and identifies the significant spectral bands for soil moisture content retrieval. The findings highlight the potential of spectroscopy for non-destructive and rapid soil moisture measurement, which can be applied to various fields such as precision agriculture, hydrology, and environmental monitoring. However, it is important to note that the spectral behavior of soil can be influenced by various factors such as soil type, texture, and organic matter content, and caution should be taken when applying the results to other soil systems. The results of this study showed a good agreement between measured and predicted values of Soil Moisture Content with high R2 and low root mean square error (RMSE) values. Model validation using independent data was satisfactory for all the studied soil samples. The results has significant implications for developing high-resolution and precise field-scale soil moisture retrieval models. These models can be used to understand the spatial and temporal variation of soil moisture content in agricultural fields, which is essential for managing irrigation and optimizing crop yield.

Keywords: soil moisture content retrieval, precision agriculture, continuum removal, remote sensing, machine learning, spectroscopy

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Authors: Noura Al Akkari, Aurélie Foucquier, Sylvain Lespinats

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Load monitoring is a management process for energy consumption towards energy savings and energy efficiency. Non Intrusive Load Monitoring (NILM) is one method of load monitoring used for disaggregation purposes. NILM is a technique for identifying individual appliances based on the analysis of the whole residence data retrieved from the main power meter of the house. Our NILM framework starts with data acquisition, followed by data preprocessing, then event detection, feature extraction, then general appliance modeling and identification at the final stage. The event detection stage is a core component of NILM process since event detection techniques lead to the extraction of appliance features. Appliance features are required for the accurate identification of the household devices. In this research work, we aim at developing a new event detection methodology with accurate load disaggregation to extract appliance features. Time-domain features extracted are used for tuning general appliance models for appliance identification and classification steps. We use unsupervised algorithms such as Dynamic Time Warping (DTW). The proposed method relies on detecting areas of operation of each residential appliance based on the power demand. Then, detecting the time at which each selected appliance changes its states. In order to fit with practical existing smart meters capabilities, we work on low sampling data with a frequency of (1/60) Hz. The data is simulated on Load Profile Generator software (LPG), which was not previously taken into consideration for NILM purposes in the literature. LPG is a numerical software that uses behaviour simulation of people inside the house to generate residential energy consumption data. The proposed event detection method targets low consumption loads that are difficult to detect. Also, it facilitates the extraction of specific features used for general appliance modeling. In addition to this, the identification process includes unsupervised techniques such as DTW. To our best knowledge, there exist few unsupervised techniques employed with low sampling data in comparison to the many supervised techniques used for such cases. We extract a power interval at which falls the operation of the selected appliance along with a time vector for the values delimiting the state transitions of the appliance. After this, appliance signatures are formed from extracted power, geometrical and statistical features. Afterwards, those formed signatures are used to tune general model types for appliances identification using unsupervised algorithms. This method is evaluated using both simulated data on LPG and real-time Reference Energy Disaggregation Dataset (REDD). For that, we compute performance metrics using confusion matrix based metrics, considering accuracy, precision, recall and error-rate. The performance analysis of our methodology is then compared with other detection techniques previously used in the literature review, such as detection techniques based on statistical variations and abrupt changes (Variance Sliding Window and Cumulative Sum).

Keywords: general appliance model, non intrusive load monitoring, events detection, unsupervised techniques;

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Authors: Athanasios Karasimos, Vasiliki Makri

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This research focuses on the design and development of the first text Corpus based on Board Game Rulebooks (BGRC) with direct application on the morphological analysis of neologisms and tendencies in word-formation processes. Corpus linguistics is a dynamic field that examines language through the lens of vast collections of texts. These corpora consist of diverse written and spoken materials, ranging from literature and newspapers to transcripts of everyday conversations. By morphologically analyzing these extensive datasets, morphologists can gain valuable insights into how language functions and evolves, as these extensive datasets can reflect the byproducts of inflection, derivation, blending, clipping, compounding, and neology. This entails scrutinizing how words are created, modified, and combined to convey meaning in a corpus of challenging, creative, and straightforward texts that include rules, examples, tutorials, and tips. Board games teach players how to strategize, consider alternatives, and think flexibly, which are critical elements in language learning. Their rulebooks reflect not only their weight (complexity) but also the language properties of each genre and subgenre of these games. Board games are a captivating realm where strategy, competition, and creativity converge. Beyond the excitement of gameplay, board games also spark the art of word creation. Word games, like Scrabble, Codenames, Bananagrams, Wordcraft, Alice in the Wordland, Once uUpona Time, challenge players to construct words from a pool of letters, thus encouraging linguistic ingenuity and vocabulary expansion. These games foster a love for language, motivating players to unearth obscure words and devise clever combinations. On the other hand, the designers and creators produce rulebooks, where they include their joy of discovering the hidden potential of language, igniting the imagination, and playing with the beauty of words, making these games a delightful fusion of linguistic exploration and leisurely amusement. In this research, more than 150 rulebooks in English from all types of modern board games, either language-independent or language-dependent, are used to create the BGRC. A representative sample of each genre (family, party, worker placement, deckbuilding, dice, and chance games, strategy, eurogames, thematic, role-playing, among others) was selected based on the score from BoardGameGeek, the size of the texts and the level of complexity (weight) of the game. A morphological model with morphological networks, multi-word expressions, and word-creation mechanics based on the complexity of the textual structure, difficulty, and board game category will be presented. In enabling the identification of patterns, trends, and variations in word formation and other morphological processes, this research aspires to make avail of this creative yet strict text genre so as to (a) give invaluable insight into morphological creativity and innovation that (re)shape the lexicon of the English language and (b) test morphological theories. Overall, it is shown that corpus linguistics empowers us to explore the intricate tapestry of language, and morphology in particular, revealing its richness, flexibility, and adaptability in the ever-evolving landscape of human expression.

Keywords: board game rulebooks, corpus design, morphological innovations, neologisms, word-formation processes

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Authors: James Jin, Weisi Xia, Runzhe Gao, Alain Vandal, Darren Svirkis, Andrew Hill

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Background: Post-haemorrhoidectomy pain is concerned by patients/clinicians. Minimizing the postoperation pain is highly interested clinically. Combinations of topical cream targeting three hypothesised post-haemorrhoidectomy pain mechanisms were developed and their effectiveness were evaluated. Specifically, a multi-centred double-blinded randomized clinical trial (RCT) was conducted in adults undergoing excisional haemorrhoidectomy. The primary analysis was conveyed on the data collected to evaluate the effectiveness of the combinations of topical cream targeting three hypothesized pain mechanisms after the operations. Methods: 192 patients were randomly allocated to 4 arms (each arm has 48 patients), and each arm was provided with pain cream 10% metronidazole (M), M and 2% diltiazem (MD), M with 4% lidocaine (ML), or MDL, respectively. Patients were instructed to apply topical treatments three times a day for 7 days, and record outcomes for 14 days after the operations. The primary outcome was VAS pain on day 4. Covariates and models were selected in the blind review stage. Multiple imputations were applied for the missingness. LMER, GLMER models together with natural splines were applied. Sandwich estimators and Wald statistics were used. P-values < 0.05 were considered as significant. Conclusions: The addition of topical lidocaine or diltiazem to metronidazole does not add any benefit. ML had significantly better pain and recovery scores than combination MDL. Multimodal topical analgesia with ML after haemorrhoidectomy could be considered for further evaluation. Further trials considering only 3 arms (M, ML, MD) might be worth exploring.

Keywords: RCT, primary analysis, multiple imputation, pain scores, haemorrhoidectomy, analgesia, lmer

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Authors: Helen Pluut, Remus Ilies, Nikos Dimotakis, Maral Darouei

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This study aims to examine recovery from work as an important daily activity with implications for workplace behavior. Building on affective events theory and the stressor-detachment model as frameworks, this paper proposes and tests a comprehensive within-individual model that uncovers the role of recovery processes at home in linking workplace demands (e.g., workload) and stressors (e.g., workplace incivility) to next-day organizational citizenship behaviors (OCBs). Our sample consisted of 126 full-time employees in a large Midwestern University. For a period of 16 working days, these employees were asked to fill out 3 electronic surveys while at work. The first survey (sent out in the morning) measured self-reported sleep quality, recovery experiences the previous day at home, and momentary effect. The second survey (sent out close to the end of the workday) measured job demands and stressors as well as OCBs, while the third survey in the evening assessed job strain. Data were analyzed using Hierarchical Linear Modeling (HLM). Results indicated that job demands and stressors at work made it difficult to unwind properly at home and have a good night’s sleep, which had repercussions for next day’s morning effect, which, in turn, influenced OCBs. It can be concluded that processes of recovery are vital to an individual’s daily effective functioning and behavior at work, but recovery may become impaired after a hard day’s work. Thus, our study sheds light on the potentially persistent nature of strain experienced as a result of work and points to the importance of recovery processes to enable individuals to avoid such cross-day spillover. Our paper will discuss this implication for theory and practice as well as potential directions for future research.

Keywords: affect, job demands, organizational citizenship behavior, recovery, strain

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Authors: Ebenezer Obaloluwa Olaniyi

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In this paper, an intelligent system has been designed to grade apple based on either its defective or healthy for production in food processing. This paper is segmented into two different phase. In the first phase, the image processing techniques were employed to extract the necessary features required in the apple. These techniques include grayscale conversion, segmentation where a threshold value is chosen to separate the foreground of the images from the background. Then edge detection was also employed to bring out the features in the images. These extracted features were then fed into the neural network in the second phase of the paper. The second phase is a classification phase where neural network employed to classify the defective apple from the healthy apple. In this phase, the network was trained with back propagation and tested with feed forward network. The recognition rate obtained from our system shows that our system is more accurate and faster as compared with previous work.

Keywords: image processing, neural network, apple, intelligent system

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Authors: Heba M. Jahin, Ali F. Bakr, Zeyad T. Elsayad

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As smart spaces can be defined as any working environment which integrates embedded computers, information appliances and multi-modal sensors to remain focused on the interaction between the users, their activity, and their behavior in the space; hence, smart space must be aware of their contexts and automatically adapt to their changing context-awareness, by interacting with their physical environment through natural and multimodal interfaces. Also, by serving the information used proactively. This paper suggests a dynamic framework through the architectural design process of the space based on the principles of computational methods and context-awareness principles to help in creating a field of changes and modifications. It generates possibilities, concerns about the physical, structural and user contexts. This framework is concerned with five main processes: gathering and analyzing data to generate smart design scenarios, parameters, and attributes; which will be transformed by coding into four types of models. Furthmore, connecting those models together in the interaction model which will represent the context-awareness system. Then, transforming that model into a virtual and ambient environment which represents the physical and real environments, to act as a linkage phase between the users and their activities taking place in that smart space . Finally, the feedback phase from users of that environment to be sure that the design of that smart space fulfill their needs. Therefore, the generated design process will help in designing smarts spaces that can be adapted and controlled to answer the users’ defined goals, needs, and activity.

Keywords: computational methods, context-awareness, design process, smart spaces

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Authors: Masoud Hassanzade Novin, Bahloul Salmani

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The process of the translation is not merely the linguistic aspects. It is also considered in the cultural framework of both the source and target text cultures. The translation process and translated texts are confronted the new aspect in 20th century which is considered mostly in the patronage framework and ideological grillwork of the target language. To have these factors scrutinized in the process of the translation both micro-element factors and macro-element factors can be taken into consideration. For the purpose of this study through a qualitative type of research based on critical discourse analysis approach, the case study of the novel “1984” written by George Orwell was chosen as the corpus of the study to have the contrastive analysis by its Persian translated texts. Results of the study revealed some distortions embedded in the target texts which were overshadowed by ideological aspect and patronage network. The outcomes of the manipulated terms were different in various categories which revealed the manipulation aspects in the texts translated.

Keywords: critical discourse analysis, ideology, patronage network, translated texts

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Authors: Sefiu Adebowale Adewumi

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Continuous improvement programme (CIP) adopts an approach to improve organizational performance with small incremental steps over time. In this approach, it is not the size of each step that is important, but the likelihood that the improvements will be ongoing. Many companies in developing nations are now complementing continuous improvement with innovation, which is the successful exploitation of new ideas. Focus area of CIP in the organization was in relation to the size of the organizations and also in relation to the generic classification of these organizations. Product quality was prevalent in the manufacturing industry while manpower training and retraining and marketing strategy were emphasized for improvement to be made in the service, transport and supply industries. However, focus on innovation in raw materials, process and methods are needed because these are the critical factors that influence product quality in the manufacturing industries.

Keywords: continuous improvement programme, developing countries, generic classfications, technological innovation

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Authors: Wanchalerm Patanacharoenwong, Panaya Sudta, Prachya Bumrungkun

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The paper focuses on the development of a system that combines Internet of Things (IoT) technologies and deep learning algorithms for anomaly detection in residential Electric Vehicle (EV) charging in smart cities. With the increasing number of EVs, ensuring efficient and reliable charging systems has become crucial. The aim of this research is to develop an integrated IoT and deep learning system for detecting anomalies in residential EV charging and enhancing EV load profiling and event detection in smart cities. This approach utilizes IoT devices equipped with infrared cameras to collect thermal images and household EV charging profiles from the database of Thailand utility, subsequently transmitting this data to a cloud database for comprehensive analysis. The methodology includes the use of advanced deep learning techniques such as Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) algorithms. IoT devices equipped with infrared cameras are used to collect thermal images and EV charging profiles. The data is transmitted to a cloud database for comprehensive analysis. The researchers also utilize feature-based Gaussian mixture models for EV load profiling and event detection. Moreover, the research findings demonstrate the effectiveness of the developed system in detecting anomalies and critical profiles in EV charging behavior. The system provides timely alarms to users regarding potential issues and categorizes the severity of detected problems based on a health index for each charging device. The system also outperforms existing models in event detection accuracy. This research contributes to the field by showcasing the potential of integrating IoT and deep learning techniques in managing residential EV charging in smart cities. The system ensures operational safety and efficiency while also promoting sustainable energy management. The data is collected using IoT devices equipped with infrared cameras and is stored in a cloud database for analysis. The collected data is then analyzed using RNN, LSTM, and feature-based Gaussian mixture models. The approach includes both EV load profiling and event detection, utilizing a feature-based Gaussian mixture model. This comprehensive method aids in identifying unique power consumption patterns among EV owners and outperforms existing models in event detection accuracy. In summary, the research concludes that integrating IoT and deep learning techniques can effectively detect anomalies in residential EV charging and enhance EV load profiling and event detection accuracy. The developed system ensures operational safety and efficiency, contributing to sustainable energy management in smart cities.

Keywords: cloud computing framework, recurrent neural networks, long short-term memory, Iot, EV charging, smart grids

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Authors: Haizhi Wu

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Sexualization brings together the interdependent experiences of prostitution and diaspora, establishing a masculine structure where a female’s body mediates the hegemony and sexuality of men from different races. Between eroticism and homesickness, writers of the Chinese diaspora develop sensual approaches to reflect on the diasporic experience and sexual frustration. Noticeably, Yu Dafu in Sinking and Yan Geling in The Lost Daughter of Happiness both take an interest in sexual encounters between an immature teen client and an erotically powerful prostitute in Japan or America, both countries considered colonizers in Chinese history. Both are utilizing the metaphor of body-space interplay to hint at the out-of-text transnational interactions, two writers, however, present distinct understandings of their bond with history and memory of the semi-colonial, semi-feudal China. Examining prostitutes’ bodies in multi-layer diasporic spaces, the central analysis of this essay works on the sexual, colonial, and historical representations of this bodily symbol and the prostitution’s engagement in negotiating with diaspora and “Chineseness”.

Keywords: Chineseness, diasporic spaces, prostitutes’ bodies, sexualization

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Authors: Rani Danavath, V. B. Narsimha

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Cloud computing is emerging as a new paradigm of large scale distributed computing. Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., three service models, and four deployment networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. This cloud model is composed of five essential characteristics models. Load balancing is one of the main challenges in cloud computing, which is required to distribute the dynamic workload across multiple nodes, to ensure that no single node is overloaded. It helps in optimal utilization of resources, enhancing the performance of the system. The goal of the load balancing is to minimize the resource consumption and carbon emission rate, that is the direct need of cloud computing. This determined the need of new metrics energy consumption and carbon emission for energy-efficiency load balancing techniques in cloud computing. Existing load balancing techniques mainly focuses on reducing overhead, services, response time and improving performance etc. In this paper we introduced a Technique for energy-efficiency, but none of the techniques have considered the energy consumption and carbon emission. Therefore, our proposed work will go towards energy – efficiency. So this energy-efficiency load balancing technique can be used to improve the performance of cloud computing by balancing the workload across all the nodes in the cloud with the minimum resource utilization, in turn, reducing energy consumption, and carbon emission to an extent, which will help to achieve green computing.

Keywords: cloud computing, distributed computing, energy efficiency, green computing, load balancing, energy consumption, carbon emission

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Authors: M. Mlhem

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Geotechnical engineers face many problematic soils upon construction and they have the choice for replacing these soils with more appropriate soils or attempting to improve the engineering properties of the soil through a suitable soil stabilization technique. Mostly, improving soils is environmental, easier and more economical than other solutions. Stabilization soils technique is applied by introducing a cementing agent or by injecting a substance to fill the pore volume. Chemical stabilizers are divided into two groups: traditional agents such as cement or lime and non-traditional agents such as polymers. This paper studies the effect of epoxy additives on the compression strength of four types of soil and then compares with the effect of cement on the compression strength for the same soils. Overall, the epoxy additives are more effective in increasing the strength for different types of soils regardless its classification. On the other hand, there was no clear relation between studied parameters liquid limit, passing No.200, unit weight and between the strength of samples for different types of soils.

Keywords: additives, clay, compression strength, epoxy, stabilization

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Authors: M. O. Adeniyi, R. T. Akinnubi

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The parameterization of turbulent heat fluxes is needed for modeling land-atmosphere interactions in Global Climate Models (GCMs). However, current GCMs still have difficulties with producing reliable turbulent heat fluxes for humid tropical regions, which may be due to inadequate parameterization of the roughness lengths for momentum (z0m) and heat (z0h) transfer. These roughness lengths are usually expressed in term of excess resistance factor (κB^(-1)), and this factor is used to account for different resistances for momentum and heat transfers. In this paper, a more appropriate excess resistance factor (〖 κB〗^(-1)) suitable for low wind speed condition was developed and incorporated into the aerodynamic resistance approach (ARA) in the GCMs. Also, the performance of various standard GCMs κB^(-1) schemes developed for high wind speed conditions were assessed. Based on the in-situ surface heat fluxes and profile measurements of wind speed and temperature from Nigeria Micrometeorological Experimental site (NIMEX), new κB^(-1) was derived through application of the Monin–Obukhov similarity theory and Brutsaert theoretical model for heat transfer. Turbulent flux parameterizations with this new formula provides better estimates of heat fluxes when compared with others estimated using existing GCMs κB^(-1) schemes. The derived κB^(-1) MBE and RMSE in the parameterized QH ranged from -1.15 to – 5.10 Wm-2 and 10.01 to 23.47 Wm-2, while that of QE ranged from - 8.02 to 6.11 Wm-2 and 14.01 to 18.11 Wm-2 respectively. The derived 〖 κB〗^(-1) gave better estimates of QH than QE during daytime. The derived 〖 κB〗^(-1)=6.66〖 Re〗_*^0.02-5.47, where Re_* is the Reynolds number. The derived κB^(-1) scheme which corrects a well documented large overestimation of turbulent heat fluxes is therefore, recommended for most regional models within the tropic where low wind speed is prevalent.

Keywords: humid, tropic, excess resistance factor, overestimation, turbulent heat fluxes

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Authors: Emma Serwaa Obobisaa, Haibo Chen

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International trade and outward foreign direct investment are important factors which are generally recognized in the economic growth and development. Though several scholars have struggled to reveal the influence of trade and outward foreign direct investment (FDI) on economic growth, most studies utilized common econometric models such as vector autoregression and aggregated the variables, which for the most part prompts, however, contradictory and mixed results. Thus, there is an exigent need for the precise study of the trade and FDI effect of economic growth while applying strong econometric models and disaggregating the variables into its separate individual variables to explicate their respective effects on economic growth. This will guarantee the provision of policies and strategies that are geared towards individual variables to ensure sustainable development and growth. This study, therefore, seeks to examine the causal effect of China-Africa trade and Outward Foreign Direct Investment on the economic growth of Africa using a robust and recent econometric approach such as system dynamics model. Our study impanels and tests an ensemble of a group of vital variables predominant in recent studies on trade-FDI-economic growth causality: Foreign direct ınvestment, international trade and economic growth. Our results showed that the system dynamics method provides accurate statistical inference regarding the direction of the causality among the variables than the conventional method such as OLS and Granger Causality predominantly used in the literature as it is more robust and provides accurate, critical values.

Keywords: economic growth, outward foreign direct investment, system dynamics model, international trade

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Authors: Adrian Kong, William Chang, Rolando Valdes, Alec Rodriguez, Roberto Miki

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The Pneumask consists of a custom snorkel-specific adapter that attaches a snorkel-port of the mask to a 3D-printed filter. This full-face snorkel mask was designed for use as personal protective equipment (PPE) during the COVID-19 pandemic when there was a widespread shortage of PPE for medical personnel. Various clinical validation tests have been conducted, including the sealing capability of the mask, filter performance, CO2 buildup, and clinical usability. However, data regarding the filter efficiencies of Pneumask and multiple filter types have not been determined. Using an experimental system, we evaluated the filtration efficiency across various masks and filters during inhalation. Eighteen combinations of respirator models (5 P100 FFRs, 4 Dolfino Masks) and filters (2091, 7093, 7093CN, BB50T) were evaluated for their exposure to airborne particles sized 0.3 - 10.0 microns using an electronic airborne particle counter. All respirator model combinations provided similar performance levels for 1.0-micron, 3.0-micron, 5.0-micron, 10.0-microns, with the greatest differences in the 0.3-micron and 0.5-micron range. All models provided expected performances against all particle sizes, with Class P100 respirators providing the highest performance levels across all particle size ranges. In conclusion, the modified snorkel mask has the potential to protect providers who care for patients with COVID-19 from increased airborne particle exposure.

Keywords: COVID-19, PPE, mask, filtration, efficiency

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Authors: Elyta Widyaningrum

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The LiDAR data acquisition has been recognizable as one of the fastest solution to provide the basis data for topographic base mapping in Indonesia. The challenges to accelerate the provision of large-scale topographic base maps as a development plan basis gives the opportunity to implement the automated scheme in the map production process. The one stop processing will also contribute to accelerate the map provision especially to conform with the Indonesian fundamental spatial data catalog derived from ISO 19110 and geospatial database integration. Thus, the automated LiDAR classification, DTM generation and feature extraction will be conducted in one GIS-software environment to form all layers of topographic base maps. The quality of automated topographic base map will be assessed and analyzed based on its completeness, correctness, contiguity, consistency and possible customization.

Keywords: automation, GIS environment, LiDAR processing, map quality

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Authors: Jiří Vágner, Dana Fialová

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The Covid-19 pandemic and its effects have triggered significant changes in travel behavior. On the contrary to a deep decline in international tourism, domestic tourism has recovered. It has not fully replaced the total volume of national tourism so far. However, from a regional point of view, and especially according to the type of destinations, regional targeting has changed significantly compared to the previous period. Urban destinations, which used to be the domain of foreign tourists, have been relatively orphaned, in contrast to destinations tied to natural attractions, which have seen seasonal increases. Even here, at a lower hierarchical geographic level, we can observe the differentiation resulting from the existing localization and infrastructure. The case study is focused on the three largest water reservoirs of the Vltava Cascade in Czechia– Lipno, Orlík, and Slapy. Based on a detailed field survey, in the periods before and during the pandemic, as well as available statistical data (Tourdata; Czech Statistical Office, Czech Cadaster and Ordnance Survey), different trends in the exploitation of these destinations with regard to existing or planned infrastructure are documented, analyzed and explained. This gives us the opportunity to discuss on concrete examples of generally known phenomena that are usually neglected in tourism: slum, brownfield, greenfield. Changes in travel behavior – especially the focus on spending leisure time individually in naturally attractive destinations – can affect the use of sites, which can be defined as a tourist or recreational slum, brownfield, but also as a tourist greenfield development. Sociocultural changes and perception of destinations by tourists and other actors represent, besides environmental changes, major trends in current tourism.

Keywords: Covid-19 pandemic, czechia, sociocultural and environmental impacts, tourist infrastructure, travel behavior, the Vltava Cascade water reservoirs

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Authors: Klary Geisler, Dalit Lev-Arey, Yael Hacohen

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It is a well-known fact that exercise has favorable effects on people's physical health, as well as mental well-being. However, as for as excessive exercise, it may likely elevate negative consequences (e.g., physical injuries, negligence of everyday responsibilities such as work, family life). Lately, there is a growing interest in exercise addiction, sometimes referred to as exercise dependence, which is defined as a craving for physical activity that results in extreme work-out sessions and generates negative physiological and psychological symptoms (e.g., withdrawal symptoms, tolerance, social conflict). Exercise addiction is considered a behavioral addiction, yet it was not included in the latest editions of the diagnostic and statistical manual of mental disorders (DSM-IV), due to lack of significant research. Specifically, there is scarce research on the relationship between exercise addiction and personality dimensions. The purpose of the current research was to examine the relationship between primary exercise addiction symptoms and the big five dimensions, perfectionism (high performance expectations and self-critical performance evaluations) and subjective affect. participants were 152 trainees on a variety of aerobic sports activities (running, cycling, swimming) that were recruited through sports groups and trainers. 88% of participants trained for at least 5 hours per week, 24% of the participants trained above 10 hours per week. To test the predictive ability of the IVs a hierarchical linear regression with forced block entry was performed. It was found that Neuroticism significantly predicted exercise addiction symptoms (20% of the variance, p<0.001), while consciousness was negatively correlated with exercise addiction symptoms (14% of variance p<0.05); both had a unique contribution. Other dimensions of the big five (agreeableness, openness and extraversion) did not have any contribution to the dependent. Moreover, maladaptive perfectionism (self-critical performance evaluations) significantly predicted exercise addiction symptoms as well (10% of the variance P < 0.05). The overall regression model explained 54% of variance.

Keywords: big five, consciousness, excessive exercise, exercise addiction, neuroticism, perfectionism, personality

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Authors: Scott M. Black, Craig Maclean, Pauline Hall Barrientos, Konstantinos Ritos, Asimina Kazakidi

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Aortic aneurysms and dissections are leading causes of death in cardiovascular disease. Both inevitably lead to hemodynamic instability without surgical intervention in the form of vascular stent-graft deployment. An accurate description of the aortic geometry and blood flow in patient-specific cases is vital for treatment planning and long-term success of such grafts, as they must generate physiological branch perfusion and in-stent hemodynamics. The aim of this study was to create patient-specific computational fluid dynamics (CFD) models through a multi-modality, multi-dimensional approach with boundary condition optimization to predict branch flow rates and in-stent hemodynamics in custom stent-graft configurations. Three-dimensional (3D) thoracoabdominal aortae were reconstructed from four-dimensional flow-magnetic resonance imaging (4D Flow-MRI) and computed tomography (CT) medical images. The former employed a novel approach to generate and enhance vessel lumen contrast via through-plane velocity at discrete, user defined cardiac time steps post-hoc. To produce patient-specific boundary conditions (BCs), the aortic geometry was reduced to a one-dimensional (1D) model. Thereafter, a zero-dimensional (0D) 3-Element Windkessel model (3EWM) was coupled to each terminal branch to represent the distal vasculature. In this coupled 0D-1D model, the 3EWM parameters were optimized to yield branch flow waveforms which are representative of the 4D Flow-MRI-derived in-vivo data. Thereafter, a 0D-3D CFD model was created, utilizing the optimized 3EWM BCs and a 4D Flow-MRI-obtained inlet velocity profile. A sensitivity analysis on the effects of stent-graft configuration and BC parameters was then undertaken using multiple stent-graft configurations and a range of distal vasculature conditions. 4D Flow-MRI granted unparalleled visualization of blood flow throughout the cardiac cycle in both the pre- and postsurgical states. Segmentation and reconstruction of healthy and stented regions from retrospective 4D Flow-MRI images also generated 3D models with geometries which were successfully validated against their CT-derived counterparts. 0D-1D coupling efficiently captured branch flow and pressure waveforms, while 0D-3D models also enabled 3D flow visualization and quantification of clinically relevant hemodynamic parameters for in-stent thrombosis and graft limb occlusion. It was apparent that changes in 3EWM BC parameters had a pronounced effect on perfusion distribution and near-wall hemodynamics. Results show that the 3EWM parameters could be iteratively changed to simulate a range of graft limb diameters and distal vasculature conditions for a given stent-graft to determine the optimal configuration prior to surgery. To conclude, this study outlined a methodology to aid in the prediction post-surgical branch perfusion and in-stent hemodynamics in patient specific cases for the implementation of custom stent-grafts.

Keywords: 4D flow-MRI, computational fluid dynamics, vascular stent-grafts, windkessel

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Authors: Kyu Chul Lee, Sung Hyun Yoo, Choon Ki Ahn, Myo Taeg Lim

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Recent experimental evidences have shown that because of a fast convergence and a nice accuracy, neural networks training via extended Kalman filter (EKF) method is widely applied. However, as to an uncertainty of the system dynamics or modeling error, the performance of the method is unreliable. In order to overcome this problem in this paper, a new finite impulse response (FIR) filter based learning algorithm is proposed to train radial basis function neural networks (RBFN) for nonlinear function approximation. Compared to the EKF training method, the proposed FIR filter training method is more robust to those environmental conditions. Furthermore, the number of centers will be considered since it affects the performance of approximation.

Keywords: extended Kalman filter, classification problem, radial basis function networks (RBFN), finite impulse response (FIR) filter

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Authors: Mohd Bahroddin Badri, Ridzuan Masri

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Despite the existence of large volume of waqf assets, it is argued that the potential of these assets not fully unleashed. There are many waqf assets especially in the form of land waqf that are idle and undeveloped mainly because of the insufficient fund and lack of investment expertise. This paper attempts to explore few cases on the innovation of waqf development in Malaysia and some countries that demonstrate synergistic collaboration between stakeholders, e.g., the government, nazir, Islamic religious councils, corporate entities and Islamic financial institutions for waqf development. This paper shows that cash waqf, corporate waqf, Build-Operate-Transfer (BOT) and Sukuk are found to be contemporary mechanisms within Islamic finance ecosystem that drive and rejuvenate the development of waqf to the next level. It further highlights few samples of waqf Sukuk that were successfully issued in selected countries. This paper also demonstrates that the benefit of waqf is beyond religious matters, which may also include education, healthcare, social care, infrastructure and corporate social responsibility (CSR) activities. This research is qualitative in nature, whereby the researcher employs descriptive method on the collected data. The researcher applies case study and library research method to collect and analyse data from journal articles, research papers, conference paper and annual reports. In a nutshell, the potential of contemporary models as demonstrated in this paper is very promising, in which the practical application of those instruments should be expanded for the rejuvenation of waqf asset.

Keywords: cash waqf, corporate waqf, Sukuk waqf, build-operate-transfer

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Authors: Pawel Twardowski, Maciej Tabaszewski, Jakub Czyżycki

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The main goal of the work was to use machine learning to predict cutting-edge wear. The research was carried out while milling hardened steel with sintered carbide cutters at various cutting speeds. During the tests, cutting-edge wear was measured, and vibration acceleration signals were also measured. Appropriate measures were determined from the vibration signals and served as input data in the machine-learning process. Two approaches were used in this work. The first one involved a two-state classification of the cutting edge - suitable and unfit for further work. In the second approach, prediction of the cutting-edge state based on vibration signals was used. The obtained research results show that the appropriate use of machine learning algorithms gives excellent results related to monitoring cutting edge during the process.

Keywords: milling of hardened steel, tool wear, vibrations, machine learning

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Authors: Estela Díaz

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This article aims to make three contributions. First, build on the literature on ethical decision-making literature by exploring factors that influence the intention of adopting veganism. Second, study the superiority of extended models of the Theory of Planned Behavior (TPB) for understanding the process involved in forming the intention of adopting veganism. Third, analyze the moderating effect of gender on TPB given that attitudes and behavior towards animals are gender-sensitive. No study, to our knowledge, has examined these questions. Veganism is not a diet but a political and moral stand that exclude, for moral reasons, the use of animals. Although there is a growing interest in studying veganism, it continues being overlooked in empirical research, especially within the domain of social psychology. TPB has been widely used to study a broad range of human behaviors, including moral issues. Nonetheless, TPB has rarely been applied to examine ethical decisions about animals and, even less, to veganism. Hence, the validity of TPB in predicting the intention of adopting veganism remains unanswered. A total of 476 non-vegan Spanish university students (55.6% female; the mean age was 23.26 years, SD= 6.1) responded to online and pencil-and-paper self-reported questionnaire based on previous studies. TPB extended models incorporated two background factors: ‘general attitudes towards humanlike-attributes ascribed to animals’ (AHA) (capacity for reason/emotions/suffer, moral consideration, and affect-towards-animals); and ‘general attitudes towards 11 uses of animals’ (AUA). SPSS 22 and SmartPLS 3.0 were used for statistical analyses. This study constructed a second-order reflective-formative model and took the multi-group analysis (MGA) approach to study gender effects. Six models of TPB (the standard and five competing) were tested. No a priori hypotheses were formulated. The results gave partial support to TPB. Attitudes (ATTV) (β = .207, p < .001), subjective norms (SNV) (β = .323, p < .001), and perceived control behavior (PCB) (β = .149, p < .001) had a significant direct effect on intentions (INTV). This model accounted for 27,9% of the variance in intention (R2Adj = .275) and had a small predictive relevance (Q2 = .261). However, findings from this study reveal that contrary to what TPB generally proposes, the effect of the background factors on intentions was not fully mediated by the proximal constructs of intentions. For instance, in the final model (Model#6), both factors had significant multiple indirect effect on INTV (β = .074, 95% C = .030, .126 [AHA:INTV]; β = .101, 95% C = .055, .155 [AUA:INTV]) and significant direct effect on INTV (β = .175, p < .001 [AHA:INTV]; β = .100, p = .003 [AUA:INTV]). Furthermore, the addition of direct paths from background factors to intentions improved the explained variance in intention (R2 = .324; R2Adj = .317) and the predictive relevance (Q2 = .300) over the base-model. This supports existing literature on the superiority of enhanced TPB models to predict ethical issues; which suggests that moral behavior may add additional complexity to decision-making. Regarding gender effect, MGA showed that gender only moderated the influence of AHA on ATTV (e.g., βWomen−βMen = .296, p < .001 [Model #6]). However, other observed gender differences (e.g. the explained variance of the model for intentions were always higher for men that for women, for instance, R2Women = .298; R2Men = .394 [Model #6]) deserve further considerations, especially for developing more effective communication strategies.

Keywords: veganism, Theory of Planned Behavior, background factors, gender moderation

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Authors: Issa M. Hweidi, Saba W. Al-Ibraheem

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This study aimed to assess the increased hospital length of stay and healthcare costs associated with SSIs among ventriculoperitoneal shunting surgery patients in Jordan. This study adopted a retrospective and nested 1:1 matched case-control design. A non-probability convenient sample of 48 VP shunt patients was recruited for the purpose of the study. The targeted groups of the study basically used to cross-match the variables investigated to minimize the risk of confounding. Information was extracted from the text of patients' electronic health records. As compared to the non-SSI group, the SSI group had an extra mean healthcare cost of $13,696.53 (p=0.001) and longer hospital length of stay (22.64 mean additional days). Furthermore, Acinetobacter baumannii and Klebsiella pneumonia were identified as being the most predominant causative agents of SSIs. The results of this study may provide baseline data for national and regional benchmarking to evaluate the quality of care provided to likewise patients. Adherence to infection control strategies and protocols considering new surveillance methods of SSIs is encouraged.

Keywords: ventriculoperitoneal shunt, health care cost, length of stay, neurosurgery, surgical site infections

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Authors: Inalegwu Stephany Akipu

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Archaeology being the study of mans past using the materials he left behind has been argued to be classified under sciences while some scholars are of the opinion that it does not deserve the status of being referred to as ‘science’. However divergent the opinions of scholars may be on the classification of Archaeology as a science or in the humanities, the discipline has no doubt, greatly aided in shaping the history of man’s past. Through the different stages that the discipline has transgressed, it has encountered some challenges. This paper therefore, attempts to highlight the need for the inclusion of branches of other disciplines when using Archaeology in reconstructing man’s history. The objective of course, is to add to the existing body of knowledge but specifically to expose the incomparable importance of archaeology as a discipline and to place it on such a high scale that it will not be regulated to the background as is done in some Nigerian Universities. The paper attempts a clarification of some conceptual terms and discusses the developmental stages of archaeology. It further describes the present state of the discipline and concludes with the disciplines that need to be imbibed in the use of Archaeology which is an evolving cultural science to obtain the aforementioned interdisciplinary approach.

Keywords: archaeology, cultural, evolution, interdisciplinary, science

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Authors: M Jeffri Arlinandes Chandra, Puwaningdyah Murti Wahyuni, Dewi Mutiara M Jeffri Arlinandes Chandra, Puwaningdyah Murti Wahyuni, Dewi Mutiara

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Indonesia is a state of the law in accordance with article 1 paragraph 3 of the Constitution of the Republic of Indonesia (1945 Constitution), namely, 'the State of Indonesia is a state of law'. The consequences of the rule of law are making the law as the main commanding officer or making the law as a basis for carrying out an action taken by the state. The types of regulations and procedures for the formation of legislation in Indonesia are contained in Law Number 12 of 2011 concerning the Formation of Legislation. Various attempts were made to make quality regulations both in the formal hierarchy and material hierarchy such as synchronization and harmonization in the formation of laws and regulations so that there is no conflict between equal and hierarchical laws, but the fact is that there are still many conflicting regulations found between one another. This can be seen clearly in the many laws and regulations that were sued to judicial institutions such as the Constitutional Court (MK) and the Supreme Court (MA). Therefore, it is necessary to have a formulation regarding the governance of the formation of laws and regulations so as to minimize the occurrence of lawsuits to the court so that positive law can be realized which can be used today and for the future (ius constituendum). The research method that will be used in this research is a combination of normative research (library research) supported by empirical data from field research so that it can formulate concepts and answer the challenges being faced. First, the structuring of laws and regulations in Indonesia must start from the inventory of laws and regulations, whether they can be classified based on the type of legislation, what are they set about, the year of manufacture, etc. so that they can be clearly traced to the regulations relating to the formation of laws and regulations. Second, the search and revocation/revocation of laws and regulations that do not exist in the state registration system. Third, the periodic evaluation system is carried out at every level of the hierarchy of laws and regulations. These steps will form an ideal model of laws and regulations in Indonesia both in terms of content and material so that the instructions can be codified and clearly inventoried so that they can be accessed by the wider community as a concrete manifestation of the principle that all people know the law (presumptio iures de iure).

Keywords: legislation, review, evaluation, reconstruction

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Authors: Modupe O. Jimoh

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Waterfalls create an ambient environment for tourism and relaxation. They are also potential sources for water supply. Owu waterfall located at Isin Local Government, Kwara state, Nigeria is the highest waterfall in the West African region, yet none of its potential usefulness has been fully exploited. Water samples were taken from two sections of the fall and were analyzed for various water quality parameters. The results obtained include pH (6.71 ± 0.1), Biochemical oxygen demand (4.2 ± 0.5 mg/l), Chemical oxygen demand (3.07 ± 0.01 mg/l), Dissolved oxygen (6.59 ± 0.6 mg/l), Turbidity (4.43 ± 0.11 NTU), Total dissolved solids (8.2 ± 0.09 mg/l), Total suspended solids (18.25 ± 0.5 mg/l), Chloride ion (0.48 ± 0.08 mg/l), Calcium ion (0.82 ± 0.02 mg/l)), Magnesium ion (0.63 ± 0.03 mg/l) and Nitrate ion (1.25 ± 0.01 mg/l). The results were compared to the World Health Organisations standard for drinking water and the Nigerian standard for drinking water. From the comparison, it can be deduced that due to the Biochemical oxygen demand value, the water is not suitable for drinking unless it undergoes treatment. However, it is suitable for other classes of water usage.

Keywords: Owu falls, waterfall, water quality, water quality parameters, water use

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Authors: Yan Huang

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Event-related potentials (ERPs) technique helps researchers to make continuous measures on the whole process of language comprehension, with an excellent temporal resolution at the level of milliseconds. The research on sentence processing has developed from the behavioral level to the neuropsychological level, which brings about a variety of sentence processing theories and models. However, the applicability of these models to L2 learners is still under debate. Therefore, the present study aims to investigate the neural mechanisms underlying English subjunctive mood processing by Chinese ESL learners. To this end, English subject clauses with subjunctive moods are used as the stimuli, all of which follow the same syntactic structure, “It is + adjective + that … + (should) do + …” Besides, in order to examine the role that language proficiency plays on L2 processing, this research deals with two groups of Chinese ESL learners (18 males and 22 females, mean age=21.68), namely, high proficiency group (Group H) and low proficiency group (Group L). Finally, the behavioral and neurophysiological data analysis reveals the following findings: 1) Syntax and semantics interact with each other on the SECOND phase (300-500ms) of sentence processing, which is partially in line with the Three-phase Sentence Model; 2) Language proficiency does affect L2 processing. Specifically, for Group H, it is the syntactic processing that plays the dominant role in sentence processing while for Group L, semantic processing also affects the syntactic parsing during the THIRD phase of sentence processing (500-700ms). Besides, Group H, compared to Group L, demonstrates a richer native-like ERPs pattern, which further demonstrates the role of language proficiency in L2 processing. Based on the research findings, this paper also provides some enlightenment for the L2 pedagogy as well as the L2 proficiency assessment.

Keywords: Chinese ESL learners, English subjunctive mood, ERPs, L2 processing

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Authors: Maropeng Maponya, Mawethu Nhlabathi

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Euphemistic expressions, as part of showing respect and ubuntu, are naturally embedded in the African Languages. These expressions are solely used to soothe the impact which dysphemistic words may have on an individual or the society at large. Conversely, the script producers of one of the well-known soap operas in South Africa, The Queen–Mzansi, seem to have turned a blind eye on that, mostly when they use dysphemistic reference to human genitals. As a result, such practice tends to deteriorate the ethicality of the African languages and the beliefs held by African society in general. They also give less meaning to the promotion of African language concepts. This paper is aimed at explaining and analyzing the impact of dysphemism on language growth, basing the argument on the fact that subtitled texts in the soap opera never reflect the actual dysphemistic sourced text uttered by the character/s. This is a clear indication that the production crew of this soap opera is aware of the impact that these utterances may have on society, yet they do not mind the characters saying them as is in African Languages whilst euphemizing them through English subtitles. The paper adopted a descriptive qualitative method with an embedded case study in it, whereby dysphemistic clips from three characters of the soap opera were selected and analyzed.

Keywords: euphemism, dysphemism, soap opera, The Queen

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