Search results for: syntactic units

Authors: Rahmat Irawan, Mundhir Hanifsyam Harahap, Andar Ristabet Hesda

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As a public sector organization in Indonesia, Directorate General of State Asset Management (DGSAM) which is a unit under the Ministry of Finance of The Republic of Indonesia, has many constraints in managing its employees. While private organizations are able to conduct a human resource management as the best practice, DGSAM is limited by many regulations, especially about punishment and lay off policy for under-performance employees. Therefore, since 2015, DGSAM tries to implement a new and uncommon approach considering employees’ preference to encourage the motivation and performance of employees. DGSAM’s employees may propose the job places, and DGSAM considers them in deciding employees deployment. This study tries to determine the impact of preference-based approach toward employees’ satisfaction and organizational performance. This study uses quantitative approaches by regression analysis to measure the impact of deployment toward satisfaction of deployed employees and performance change of related units in DGSAM. The result of this study shows that preference-based approach significantly improves employees’ satisfaction and performance of related units as well. Based on the results of this study, it can be suggested that the approach is able to be implemented in the wider scope of the Ministry of Finance of The Republic of Indonesia and whole public sector organization in Indonesia. However, this study only focuses on short term measurement, so it is suggested to do further study to analyze the long-term impact.

Keywords: employee deployment, employee satisfaction, human resource management, organizational performance, preference-based approach

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Authors: S. Alansary, M. Nagi

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This paper presents an approach of conducting semantic annotation of Arabic corpus using the Universal Networking Language (UNL) framework. UNL is intended to be a promising strategy for providing a large collection of semantically annotated texts with formal, deep semantics rather than shallow. The result would constitute a semantic resource (semantic graphs) that is editable and that integrates various phenomena, including predicate-argument structure, scope, tense, thematic roles and rhetorical relations, into a single semantic formalism for knowledge representation. The paper will also present the Interactive Analysis​ tool for automatic semantic annotation (IAN). In addition, the cornerstone of the proposed methodology which are the disambiguation and transformation rules, will be presented. Semantic annotation using UNL has been applied to a corpus of 20,000 Arabic sentences representing the most frequent structures in the Arabic Wikipedia. The representation, at different linguistic levels was illustrated starting from the morphological level passing through the syntactic level till the semantic representation is reached. The output has been evaluated using the F-measure. It is 90% accurate. This demonstrates how powerful the formal environment is, as it enables intelligent text processing and search.

Keywords: semantic analysis, semantic annotation, Arabic, universal networking language

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Authors: R. Güçlü, E. Küçüksakarya

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Word association (WA) gives the broadest information on how knowledge is structured in the human mind. Cognitive linguistics, psycholinguistics, and applied linguistics are the disciplines that consider WA tests as substantial in gaining insights into the very nature of the human cognitive system and semantic knowledge. In this study, Berlin and Kay’s basic 11 color terms (1969) are presented as the stimuli words to a total number of 300 Turkish university students. The responses are analyzed according to Fitzpatrick’s model (2007), including four categories, namely meaning-based responses, position-based responses, form-based responses, and erratic responses. In line with the findings, the responses to free association tests are expected to give much information about Turkish university students’ psychological structuring of vocabulary, especially morpho-syntactic and semantic relationships among words. To conclude, theoretical and practical implications are discussed to make an in-depth evaluation of how associations of basic color terms are represented in the mental lexicon of Turkish university students.

Keywords: color term, gender, mental lexicon, word association task

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Authors: Emad A. Mohammed

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The concept of hydraulic flow units (HFU) has been used for decades in the petroleum industry to improve the prediction of permeability. This concept is strongly related to the flow zone indicator (FZI) which is a function of the reservoir rock quality index (RQI). Both indices are based on reservoir porosity and permeability of core samples. It is assumed that core samples with similar FZI values belong to the same HFU. Thus, after dividing the porosity-permeability data based on the HFU, transformations can be done in order to estimate the permeability from the porosity. The conventional practice is to use the power law transformation using conventional HFU where percentage of error is considerably high. In this paper, neural network technique is employed as a soft computing transformation method to predict permeability instead of power law method to avoid higher percentage of error. This technique is based on HFU identification where Amaefule et al. (1993) method is utilized. In this regard, Kozeny and Carman (K–C) model, and modified K–C model by Hasan and Hossain (2011) are employed. A comparison is made between the two transformation techniques for the two porosity-permeability models. Results show that the modified K-C model helps in getting better results with lower percentage of error in predicting permeability. The results also show that the use of artificial intelligence techniques give more accurate prediction than power law method. This study was conducted on a heterogeneous complex carbonate reservoir in Oman. Data were collected from seven wells to obtain the permeability correlations for the whole field. The findings of this study will help in getting better estimation of permeability of a complex reservoir.

Keywords: permeability, hydraulic flow units, artificial intelligence, correlation

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Authors: Adam Y. Sulaiman, Gerard I.Obasi, Roma Chang, Hussein Sayed Moghaieb, Ming J. Huang, Neil J. Hewitt

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Residential air-conditioning units are essential for quality indoor comfort in hot climate countries. Nevertheless, because of their non-renewable energy sources and the contribution of ecologically unfriendly working fluids, these units are a major source of CO2 emissions in these countries. The utilisation of sustainable technologies nowadays is essential to reduce the adverse effects of CO2 emissions by replacing conventional technologies. This paper investigates the feasibility of running an off-grid solar-powered air-conditioning bed unit using three low GWP refrigerants (R32, R290, and R600a) to supersede conventional refrigerants.A prototype air conditioning unit was built to supply cold air to a canopy that was connected to it. The assembled unit was designed to distribute cold air to a canopy connected to it. This system is powered by two 400 W photovoltaic panels, with battery storage supplying power to the unit at night-time. Engineering Equation Solver (EES) software is used to mathematically model the vapor compression cycle (VCC) and predict the unit's energetic and exergetic performance. The TRNSYS software was used to simulate the electricity storage performance of the batteries, whereas the IES-VE was used to determine the amount of solar energy required to power the unit. The article provides an analytical design guideline, as well as a comprehensible process system. Combining a renewable energy source to power an AC based-VCC provides an excellent solution to the real problems of high-energy consumption in warm-climate countries.

Keywords: air-conditioning, refrigerants, PV panel, energy storages, VCC, exergy

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Authors: Steven D. P Moore

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A novel method referred to asKýklos(Ky) dimensional geometry is proposed as an entity specific core geometric dimensional measurement system. Ky geometric measures can constructscaled multi-dimensionalmodels using regular and irregular sets in IRn. This entity specific-derived geometric measurement system shares similar fractal methods in which a ‘fractal transformation operator’ is applied to a set S to produce a union of N copies. The Kýklos’ inputs use 1D geometry as a core measure. One-dimensional inputs include the radius interval of a circle/sphere or the semiminor/semimajor axes intervals of an ellipse or spheroid. These geometric inputs have finite values that can be measured by SI distance units. The outputs for each interval are divided and subdivided 1D subcomponents with a union equal to the interval geometry/length. Setting a limit of subdivision iterations creates a finite value for each 1Dsubcomponent. The uniqueness of this method is captured by allowing the simplest 1D inputs to define entity specific subclass geometric core measurements that can also be used to derive length measures. Current methodologies for celestial based measurement of time, as defined within SI units, fits within this methodology, thus combining spatial and temporal features into geometric core measures. The novel Ky method discussed here offers geometric measures to construct scaled multi-dimensional structures, even models. Ky classes proposed for consideration include celestial even subatomic. The application of this offers incredible possibilities, for example, geometric architecture that can represent scaled celestial models that incorporates planets (spheroids) and celestial motion (elliptical orbits).

Keywords: Kyklos, geometry, measurement, celestial, dimension

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Authors: Ramūnas Antanaitis, Lina Anskienė, Robertas Stoškus

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This study was conducted during 2021.05.01 – 2021.08.31 at the Lithuanian University of health sciences and one Lithuanian dairy farm with 500 dairy cows (55.911381565736, 21.881321760608195). Average calving – 50 cows per month. Cows (n=20) in the treatment group (TG) were fed with feed supplement Optipartum C+ 200 (Enzymes: Alfa- Amylase 57 Units; Beta-Glucanase 107 Units) from 21 days before calving till 30 days after calving with feeding rate 200g/cow/day. Cows in the control group (CG) were fed a feed ration without feed supplement. Measurements started from 6 days before calving and continued till 21 days after calving. The following indicators were registered: with the RumiWatch System: Rumination time; Eating time; Drinking time; Rumination chews; Eating chews; Drinking gulps; Bolus; Chews per minute; Chews per bolus. With SmaXtec system - the temperature, pH of the contents of cows' reticulorumens and cows' activity. According to our results, we found that feeding of cows, from 21 days before calving to 30 days after calving, with a feed supplement with alfa- amylase and beta-glucanase (Optipartum C+ 200) (with dose 200g/cow/day) can produce an increase in: 9% rumination time and eating time, 19% drinking time, 11% rumination chews, 16% eating chews,13% number of boluses per rumination, 5% chews per minute and 16% chews per bolus. We found 1.28 % lower reiticulorumen pH and 0.64% lower reticulorumen temperature in cows fed with the supplement compared with control group cows. Also, cows feeding with enzymes were 8.80% more active.

Keywords: Alfa-Amylase, Beta-Glucanase, cows, in-line, sensors

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Authors: Imoh Philip

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Basà language is classified as belonging to Kainji family, under the sub-phylum Western-Kainji known as Rubasa (Basa Benue) (Croizier & Blench, 1992:32). Basà is an under-described language spoken in the North-Central Nigeria. The language is characterized by subject-verb-object (henceforth SVO) as its canonical word order. Data for this work is sourced from the researcher’s native intuition of the language corroborated with a careful observation of native speakers. This paper investigates the syntactic derivational strategy of information-structure encoding in Basà language. It emphasizes on a negative operator, as a strategy for focusing a constituent or clause that follows it and negativizes a whole proposition. For items that are not nouns, they have to undergo an obligatory nominalization process, either by affixation, modification or conversion before they are moved to the pre verbal position for these operations. The study discovers and provides evidence of the fact showing that deferent constituents in the sentence such as the subject, direct, indirect object, genitive, verb phrase, prepositional phrase, clause and idiophone, etc. can be focused with the same negativizing operator. The process is characterized by focusing the pre verbal NP constituent alone, whereas the whole proposition is negated. The study can stimulate similar study or be replicated in other languages.

Keywords: negation, focus, Basà, nominalization

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Authors: Shraddha Jain Sharma, Ratnalata Gupta

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Predicting stock movements in the financial market is both difficult and rewarding. Analysts and academics are increasingly using advanced approaches such as machine learning techniques to anticipate stock price patterns, thanks to the expanding capacity of computing and the recent advent of graphics processing units and tensor processing units. Stock market prediction is a type of time series prediction that is incredibly difficult to do since stock prices are influenced by a variety of financial, socioeconomic, and political factors. Furthermore, even minor mistakes in stock market price forecasts can result in significant losses for companies that employ the findings of stock market price prediction for financial analysis and investment. Soft computing techniques are increasingly being employed for stock market prediction due to their better accuracy than traditional statistical methodologies. The proposed research looks at the need for soft computing techniques in stock market prediction, the numerous soft computing approaches that are important to the field, past work in the area with their prominent features, and the significant problems or issue domain that the area involves. For constructing a predictive model, the major focus is on neural networks and fuzzy logic. The stock market is extremely unpredictable, and it is unquestionably tough to correctly predict based on certain characteristics. This study provides a complete overview of the numerous strategies investigated for high accuracy prediction, with a focus on the most important characteristics.

Keywords: stock market prediction, artificial intelligence, artificial neural networks, fuzzy logic, accuracy, deep learning, machine learning, stock price, trading volume

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Authors: Imen Elleuch, Wael Ouarda, Gargouri Bilel

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We proposes in this paper a Deep Learning based approach to classify text in order to enrich an Arabic ontology based on the objects classes of Gaston Gross. Those object classes are defined by taking into account the syntactic and semantic features of the treated language. Thus, our proposed approach is a hybrid one. In fact, it is based on the one hand on the object classes that represents a knowledge based-approach on classification of text and in the other hand it uses the deep learning approach that use the word embedding-based-approach to classify text. We have applied our proposed approach on a corpus constructed from an Arabic dictionary. The obtained semantic classification of text will enrich the Arabic objects classes ontology. In fact, new classes can be added to the ontology or an expansion of the features that characterizes each object class can be updated. The obtained results are compared to a similar work that treats the same object with a classical linguistic approach for the semantic classification of text. This comparison highlight our hybrid proposed approach that can be ameliorated by broaden the dataset used in the deep learning process.

Keywords: deep-learning approach, object-classes, semantic classification, Arabic

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Authors: Sufia Maroof

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This empirical study investigated the web-translations of five Pakistani public offices (FPSC, FIA, HEC, USB, and Ministry of Finance) offering Urdu tab as an option to access information on their official websites. Triangulation of quantitative and qualitative research design informed the researcher of the semantic, lexical and syntactic caveats in these translations. The study hypothesized that majority of the Pakistani population is oblivious of the Supreme Court’s amendments in language policy concerning national and official language; hence, Urdu web-translations of the public departments have not been accessed effectively. Firstly, the researcher conducted an online survey, comprising of two sections, close ended and short answer based questions. Secondly, the researcher compiled corpus of the five selected websites in a tabular form to compare the data. Thirdly, the administrators of the departments had been contacted regarding the methods of translation and the expertise of the personnel involved. The corpus was assessed for TQA after examining the lexical, semantic, syntactical and technical alignment inaccuracies and imperfections. The study suggests the public offices to invest in their Urdu webs by either hiring expert translators or engaging expertise of a translation agency for this project to offer quality translation to public.

Keywords: machine translations, public offices, Urdu translations, websites

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Authors: Jakob Renko, Deja Praprotnik, Kristina Martinovič, Igor Karnjuš

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Introduction: Catheter-related bloodstream infections are a major burden for healthcare and patients. Although infections of this type cannot be completely avoided, they can be reduced by taking preventive measures. The aim of this study is to review and analyze the existing literature on preventive interventions to prevent central venous catheters (CVC) infections. Methods: A systematic literature review was carried out. The international databases CINAHL, Medline, PubMed, and Web of Science were searched using the search strategy: "catheter-related infections" AND "intensive care units" AND "prevention" AND "central venous catheter." Articles that met the inclusion and exclusion criteria were included in the study. The literature search flow is illustrated by the PRISMA diagram. The descriptive research method was used to analyze the data. Results: Out of 554 search results, 22 surveys were included in the final analysis. We identified seven relevant preventive measures to prevent CVC infections: washing the whole body with chlorhexidine gluconate (CHG) solution, disinfecting the CVC entry site with CHG solution, use of CHG or silver dressings, alcohol protective caps, CVC care education, selecting appropriate catheter and multicomponent care bundles. Discussion and conclusions: Both single interventions and multicomponent care bundles have been shown to be currently effective measures to prevent CVC infections in adult patients in the ICU. None of the measures identified stood out in terms of their effectiveness. Prevention work to reduce CVC infections in the ICU is a complex process that requires the simultaneous consideration of several factors.

Keywords: central venous access, critically ill patients, hospital-acquired complications, prevention

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Authors: Ludovic Fabre, Paola Melani, Patrick Lemaire

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The goal of this study was to test whether and how emotions influence drone operators in estimation skills. The empirical study was run in the context of numerical estimation. Participants saw a two-digit number together with a collection of cars. They had to indicate whether the stimuli collection was larger or smaller than the number. The two-digit numbers ranged from 12 to 27, and collections included 3-36 cars. The presentation of the collections was dynamic (each car moved 30 deg. per second on the right). Half the collections were smaller collections (including fewer than 20 cars), and the other collections were larger collections (i.e., more than 20 cars). Splits between the number of cars in a collection and the two-digit number were either small (± 1 or 2 units; e.g., the collection included 17 cars and the two-digit number was 19) or larger (± 8 or 9 units; e.g., 17 cars and '9'). Half the collections included more items (and half fewer items) than the number indicated by the two-digit number. Before and after each trial, participants saw an image inducing negative emotions (e.g., mutilations) or neutral emotions (e.g., candle) selected from International Affective Picture System (IAPS). At the end of each trial, participants had to say if the second picture was the same as or different from the first. Results showed different effects of emotions on RTs and percent errors. Participants’ performance was modulated by emotions. They were slower on negative trials compared to the neutral trials, especially on the most difficult items. They errored more on small-split than on large-split problems. Moreover, participants highly overestimated the number of cars when in a negative emotional state. These findings suggest that emotions influence numerical estimation, that effects of emotion in estimation interact with stimuli characteristics. They have important implications for understanding the role of emotions on estimation skills, and more generally, on how emotions influence cognition.

Keywords: drone operators, emotion, numerical estimation, arithmetic

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Authors: Kriangkrai Vathanalaoha

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Misery generates fear and anxiety in readers through its intense plot associated with the unpredictable emotional states of the nurse, Annie Wilkes. At the same time, she mentally and physically abuses the novelist victim, Paul Sheldon. The suspense is not only at the story level, where the violent expressions are used but also at the discourse level, where the linguistic structures may intentionally cause the reader to view language as disturbing performative. This performativity could be reflected through linguistic choices where the writer triggers a new imaginative world through experiential metafunction and schema disruption. This study explores striking excerpts from the fiction through mind style and transitivity analysis to demonstrate how the horrific experience contrasts when the protagonist and the antagonist converse extensively. The results reveal that stylistic deviation can be found at the syntactic levels, where the intensity of emotions can be apparent when the protagonist is verbally abused. In addition, transitivity can flesh out how the protagonist is expressed chiefly through the internalized process, whereas the antagonist is eminent with the externalized process. The findings suggest that the application of cognitive stylistics, such as mind style and transitivity analysis, could contribute to the mental representation of horrific reality.

Keywords: horror, mind style, misery, stylistics, transitivity

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Authors: Atour Taghipour

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In the real world each manufacturing company is an independent business unit. These business units are linked to each other through upstream and downstream linkages. The management of these linkages is called coordination which, could be considered as a difficult engineering task. The degree of difficulty of coordination depends on the type and the nature of information exchanged between partners as well as the structure of relationship from mutual to the network structure. The literature of manufacturing systems comprises a wide range of varieties of methods and approaches of coordination. In fact, two main streams of research can be distinguished: central coordination versus decentralized coordination. In the centralized systems a high degree of information exchanges is required. The high degree of information exchanges sometimes leads to difficulties when independent members do not want to share information. In order to address these difficulties, decentralized approaches of coordination of operations planning decisions based on some minimal information sharing have been proposed in many academic disciplines. This paper first proposes a framework of analysis in order to analyze the proposed approaches in the literature, based on this framework which includes the similarities between approaches we categorize the existing approaches. This classification can be used as a research map for future researches. The result of our paper highlights several opportunities for future research. First, it is proposed to develop more dynamic and stochastic mechanisms of planning coordination of manufacturing units. Second, in order to exploit the complementarities of approaches proposed by diverse science discipline, we propose to integrate the techniques of coordination. Finally, based on our approach we proposed to develop coordination standards to guaranty both the complementarity of these approaches as well as the freedom of companies to adopt any planning tools.

Keywords: network coordination, manufacturing, operations planning, supply chain

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Authors: Ashwag O. Maghraby, Nida N. Khan, Hosnia A. Ahmed, Ghufran N. Brohi, Hind F. Assouli, Jawaher S. Melibari

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The Arabic language is one of the most important languages. Learning it is so important for many people around the world because of its religious and economic importance and the real challenge lies in practicing it without grammatical or syntactical mistakes. This research focused on detecting and correcting the syntactic mistakes of Arabic syntax according to their position in the sentence and focused on two of the main syntactical rules in Arabic: Dual and Plural. It analyzes each sentence in the text, using Stanford CoreNLP morphological analyzer and machine-learning approach in order to detect the syntactical mistakes and then correct it. A prototype of the proposed system was implemented and evaluated. It uses support vector machine (SVM) algorithm to detect Arabic grammatical errors and correct them using the rule-based approach. The prototype system has a far accuracy 81%. In general, it shows a set of useful grammatical suggestions that the user may forget about while writing due to lack of familiarity with grammar or as a result of the speed of writing such as alerting the user when using a plural term to indicate one person.

Keywords: Arabic language acquisition and learning, natural language processing, morphological analyzer, part-of-speech

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Authors: Nabin Prasad Joshi

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A new variant of the coronavirus family found in the Wuhan city market of China is causing serious harm to human beings. After the WHO decided COVID-19 was a pandemic situation, everyone started to measure the prevention of infectious diseases according to WHO guidelines. It includes social distancing, isolation, quarantine, lockdown, sanitation, and masking, respectively. During this time, the researcher has observed the difficulties of cultivating the new normal in people in Nepal. People have perceived the single coronavirus differently; common populations and frontline workers have different perceptions of coronavirus. The researcher started to measure the psychosocial impact of the COVID-19 pandemic on frontline workers and general populations in Kathmandu valley. The total number of sample units for this research is 82; it includes 52 general populations and 30 frontline workers. These sample units are selected through convenient sampling and purposive sampling, respectively. This research is based on descriptive and exploratory design. DASS-21 of the Nepali version is a comprehensive data collection tool for depression, anxiety, and stress measurement in this research, and simultaneously the psychosocial checklist, key-informant interview, and case study have been done. Quantitative data are analyzed with the help of excel, and qualitative data are through thematic analysis. The study has shown that the occurrence of psychosocial issues among frontline workers is greater than in general populations. It is found that the informants with higher education status have greater psychosocial issues in comparison to low education status. In the context of a pandemic, family/friends’ support can function as a protective factor when at adequate levels.

Keywords: anxiety, depression, isolation, lockdown

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Authors: Lamia Bouzgarrou, Amira Omrane, Naima Bouatay, Chaima Harrathi, Samia Machroughl, Ahmed Mhalla

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Background and Aims: Professionals of health care sector are exposed to psychosocial constraints like stress, harassment, violence, which can lead to many mental health problems such as, depression, addictive behavior, and burn-out. Moreover, it’s well established that caregivers affected to intensive care units are more likely to experience such constraints and mental health problems. For these caregivers, the mental health state may affect care quality and patient’s safety. This study aims either to identify occupational psychosocial constraints and their mental health consequences among paramedical and medical caregivers affected to intensive units in Tunisian public hospital. Methods: An exhaustive three months cross-sectional study conducted among medical and paramedical staffs of intensive care units in three Tunisian university hospitals. After informed consent collection, we evaluated work-related stress, workplace harassment, depression, anxious troubles, addictive behavior, and self-esteems through an anonymous self-completed inquiry form. Five validated questionnaires and scales were included in this form: Karasek's Job Content Questionnaire, Negative Acts Questionnaire, Rosenberg, Beck depression inventory and Hamilton Anxiety scale. Results: We included 129 intensive unit caregivers; with a mean age of 36.1 ± 1.1 years and a sex ratio of 0.58. Among these caregivers, 30% were specialist or under-specialization doctors. The average seniority in the intensive care was 6.1 ± 1.2 (extremes=1 to 40 years). Atypical working schedules were noted among 36.7% of the subjects with an imposed choice in 52.4% of cases. During the last 12 months preceding the survey, 51.7% of care workers were absent from work because of a health problem with stops exceeding 15 days in 11.7%. Job strain was objective among 15% of caregivers and 38.33% of them were victims of moral harassment. A low or very low self-esteem was noted among 40% of respondents. Moreover, active smoking was reported by 20% subjects, alcohol consumption by 13.3% and psychotropic substance use by 1.7% of them. According to Beck inventory and Hamilton Anxiety scale, we concluded that 61.7% of intensive care providers were depressed, with 'severe' depression in 13.3% of cases and 49.9% of them present anxious disorders. Multivariate analysis objective that, job strain was correlated with young age (p=0.005) and shorter work seniority (p=0.001). Workplace and moral harassment was more prevalent among females (p=0.009), under-specialization doctor (p=0.021), those affected to atypical schedules (p=0.008). Concerning depression, it was more prevalent among staff in job strain situation (p = 0.004), among smokers caregivers (p = 0.048), and those with no leisure activity (p < 0.001). Anxious disorders were positively correlated to chronic diseases history (p = 0.001) and work-bullying exposure (p = 0.004). Conclusions: Our findings reflected a high frequency of caregivers who are under stress at work and those who are victims of moral harassment. These health professionals were at increased risk for developing psychiatric illness such depressive and anxious disorders and addictive behavior. Our results suggest the necessity of preventive strategies of occupational psychosocial constraints in order to preserve professional’s mental health and maximize patient safety and quality of care.

Keywords: health care sector, intensive care units, mental health, psychosocial constraints

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Authors: Sima Majnooni

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This paper discusses the Green Climate Fund's environmental and social management framework (GCF). The environmental and social management framework ensures the accredited entity considers the GCF's accreditation standards and effectively implements each of the GCF-funded projects. The GCF requires all accredited entities to meet basic transparency and accountability standards as well as environmental and social safeguards (ESMS). In doing so, the accredited entity sets up different independent units. One of these units is called the Grievance Mechanism. When allegations of environmental and social harms are raised in association with GCF-funded activities, affected parties can contact the entity’s grievance unit. One of the most challenging things about the accredited entity's grievance unit is the lack of available information and resources on the entities' websites. Many AEs have anti-corruption or anti-money laundering unit, but they do not have the environmental and social unit for affected people. This paper will argue the effectiveness of environmental and social grievance mechanisms of AEs by using a qualitative approach to indicate how many of AEs have a poor or an effective GRM. Some ESMSs seem highly effective. On the other hand, other mechanisms lack basic requirements such as a clear, transparent, uniform procedure and a definitive timetable. We have looked at each AE mechanism not only in light of how the website goes into detail regarding the process of grievance mechanism but also in light of their risk category. Many mechanisms appear inadequate for the lower level risk category entities (C) and, even surprisingly, for many higher-risk categories (A). We found; in most cases, the grievance mechanism of AEs seems vague.

Keywords: grievance mechanism, vague environmental and social policies, green climate fund, international climate finance, lower and higher risk category

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Authors: Tahmidul Islam

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Propensity Score Matching (PSM) technique has been widely used for estimating causal effect of treatment in observational studies. One major step of implementing PSM is estimating the propensity score (PS). Logistic regression model with additive linear terms of covariates is most used technique in many studies. Logistics regression model is also used with cubic splines for retaining flexibility in the model. However, choosing the functional form of the logistic regression model has been a question since the effectiveness of PSM depends on how accurately the PS been estimated. In many situations, the linearity assumption of linear logistic regression may not hold and non-linear relation between the logit and the covariates may be appropriate. One can estimate PS using machine learning techniques such as random forest, neural network etc for more accuracy in non-linear situation. In this study, an attempt has been made to compare the efficacy of Generalized Additive Model (GAM) in various linear and non-linear settings and compare its performance with usual logistic regression. GAM is a non-parametric technique where functional form of the covariates can be unspecified and a flexible regression model can be fitted. In this study various simple and complex models have been considered for treatment under several situations (small/large sample, low/high number of treatment units) and examined which method leads to more covariate balance in the matched dataset. It is found that logistic regression model is impressively robust against inclusion quadratic and interaction terms and reduces mean difference in treatment and control set equally efficiently as GAM does. GAM provided no significantly better covariate balance than logistic regression in both simple and complex models. The analysis also suggests that larger proportion of controls than treatment units leads to better balance for both of the methods.

Keywords: accuracy, covariate balances, generalized additive model, logistic regression, non-linearity, propensity score matching

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Authors: Alaa Alateeqi, Sara Aldhulaiee, Sara Alibraheem, Noura Alsaleh

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For the past few decades or so, Kuwait's local food industry has grown remarkably due to increase in demand for processed or semi processed food products in the market. It is important that the ever increasing food manufacturing/processing units maintain the required quality standards as per regional and to some extent international quality requirements. It has been realized that all Kuwait food manufacturing units should understand and follow the international standard practices, and moreover a set of guidelines must be set for quality assurance such that any new business in this area is aware of the minimum requirements. The current study has been undertaken to identify the gaps in Kuwait food industries in following the Good Manufacturing Practices (GMP) in terms of quality planning, control and quality assurance. GMP refers to Good Manufacturing Practices, which are a set of rules, laws or regulations that certify producing products within quality standards and ensuring that it is safe, pure and effective. The present study therefore reports about a ‘case study’ in a reputed food manufacturing unit in Kuwait; starting from assessment of the current practices followed by diagnosis, report of the diagnosis and road map and corrective measures for GMP implementation in the unit. The case study has also been able to identify the best practices and establish a benchmarking data for other companies to follow, through measuring the selected company's quality, policies, products and strategies and compare it with the established benchmarking data. A set of questionnaires and assessment mechanism has been established for companies to identify their ‘benchmarking score’ in relation to the number of non-conformities and conformities with the GMP standard requirements.

Keywords: good manufacturing practices, GMP, benchmarking, Kuwait Food Industries, food quality

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Authors: Anes Enakoa, Yawei Liang

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Question Answering (QA) system is one of the most important and demanding tasks in the field of Natural Language Processing (NLP). In QA systems, the answer generation task generates a list of candidate answers to the user's question, in which only one answer is correct. Answer selection is one of the main components of the QA, which is concerned with selecting the best answer choice from the candidate answers suggested by the system. However, the selection process can be very challenging especially in Arabic due to its particularities. To address this challenge, an approach is proposed to answer questions with multiple answer choices for Arabic QA systems based on Textual Entailment (TE) recognition. The developed approach employs a Support Vector Machine that considers lexical, semantic and syntactic features in order to recognize the entailment between the generated hypotheses (H) and the text (T). A set of experiments has been conducted for performance evaluation and the overall performance of the proposed method reached an accuracy of 67.5% with C@1 score of 80.46%. The obtained results are promising and demonstrate that the proposed method is effective for TE recognition task.

Keywords: information retrieval, machine learning, natural language processing, question answering, textual entailment

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Authors: ShuHui Yang, ChingChing Lu

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Measuring event-related potentials (ERPs) has been fundamental to our understanding of how people process language. One specific ERP component, a P600, has been hypothesized to be associated with syntactic reanalysis processes. We, however, propose that the P600 is not restricted to reanalysis processes, but is the index of the structural pattern processing. To investigate the structural pattern processing, we utilized the effects of stimulus degradation in structural priming. To put it another way, there was no P600 effect if the structure of the prime was the same with the structure of the target. Otherwise, there would be a P600 effect if the structure were different between the prime and the target. In the experiment, twenty-two participants were presented with four sentences of Tang poetry. All of the first two sentences, being prime, were conducted with SVO+VP. The last two sentences, being the target, were divided into three types. Type one of the targets was SVO+VP. Type two of the targets was SVO+VPVP. Type three of the targets was VP+VP. The result showed that both of the targets, SVO+VPVP and VP+VP, elicited positive-going brainwave, a P600 effect, at 600~900ms time window. Furthermore, the P600 component was lager for the target’ VP+VP’ than the target’ SVO+VPVP’. That meant the more dissimilar the structure was, the lager the P600 effect we got. These results indicate that P600 was the index of the structure processing, and it would affect the P600 effect intensity with the degrees of structural heterogeneity.

Keywords: ERPs, P600, structural pattern, structural priming, Tang poetry

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Authors: E. Mendoza, D. Jackson-Maldonado, G. Avecilla-Ramírez, A. Mondaca

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Assessing language proficiency is a major issue in psycholinguistic research. There are multiple tools that measure language dominance and language proficiency in hearing bilinguals, however, this is not the case for Deaf bilinguals. Specifically, there are few, if not none, assessment tools useful in the description of the multilingual abilities of Mexican Deaf signers. Because of this, the linguistic characteristics of Mexican Deaf population have been poorly described. This paper attempts to explain the necessary changes done in order to adapt the Bilingual Language Profile (BLP) to Mexican Sign Language (LSM) and written/oral Spanish. BLP is a Self-Evaluation tool that has been adapted and translated to several oral languages, but not to sign languages. Lexical, syntactic, cultural, and structural changes were applied to the BLP. 35 Mexican Deaf signers participated in a pilot study. All of them were enrolled in Higher Education programs. BLP was presented online in written Spanish via Google Forms. No additional information in LSM was provided. Results show great heterogeneity as it is expected of Deaf populations and BLP seems to be a useful tool to create a bilingual profile of the Mexican Deaf population. This is a first attempt to adapt a widely tested tool in bilingualism research to sign language. Further modifications need to be done.

Keywords: deaf bilinguals, assessment tools, bilingual language profile, mexican sign language

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Authors: John Hardy

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The expansion of special operations forces (SOF) in the twenty-first century is often discussed in terms of the size and disposition of SOF units. Research regarding the number SOF personnel, the equipment SOF units procure, and the variety of roles and mission that SOF fulfill in contemporary conflicts paints a fascinating picture of changing expectations for the use of force. A strong indicator of the changing nature of SOF in contemporary conflicts is the fusion of strike and intelligence functions in the SOF in many countries. What were once more distinct roles on the kind of battlefield generally associated with the concept of conventional warfare have become intermingled in the era of persistent conflict which SOF face. This study presents a historical analysis of the co-evolution of the intelligence and direct action functions carried out by SOF in counterterrorism, counterinsurgency, and training and mentoring missions between 2004 and 2016. The study focuses primarily on innovation in the US military and the diffusion of key concepts to US allies first, and then more broadly afterward. The findings show that there were three key phases of evolution throughout the period of study, each coinciding with a process of innovation and doctrinal adaptation. The first phase was characterized by the fusion of intelligence at the tactical and operational levels. The second phase was characterized by the industrial counterterrorism campaigns used by US SOF against irregular enemies in Iraq and Afghanistan. The third phase was characterized by increasing forward collection of actionable intelligence by SOF force elements in the course of direct action raids. The evolution of strike and intelligence functions in SOF operations between 2004 and 2016 was significantly influenced by reciprocity. Intelligence fusion led to more effective targeting, which then increased intelligence collection. Strike and intelligence functions were then enhanced by greater emphasis on intelligence exploitation during operations, which further increased the effectiveness of both strike and intelligence operations.

Keywords: counterinsurgency, counterterrorism, intelligence, irregular warfare, military operations, special operations forces

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Authors: Behnoush Moghiminia, Jesus Anaya Diaz

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The current study attempts to present the relationship between the structure development and Patkaneh as one of the Iranian geometric patterns and parametric algorithms by introducing two practical methods. While having a structural function, Patkaneh is also used as an ornamental element. It can be helpful in the scientific and practical review of Patkaneh. The current study aims to use Patkaneh as a parametric form generator based on the algorithm. The current paper attempts to express how can a more complete algorithm of this covering be obtained based on the parametric study and analysis of a sample of a Patkaneh and also investigate the relationship between the development of the geometrical pattern of Patkaneh as a structural-decorative element of Iranian architecture and digital design. In this regard, to achieve the research purposes, researchers investigated the oldest type of Patkaneh in the architecture history of Iran, such as the Northern Entrance Patkaneh of Oshtorjan Jame’ Mosque. An accurate investigation was done on the history of the background to answer the questions. Then, by investigating the structural behavior of Patkaneh, the decorative or structural-decorative role of Patkaneh was investigated to eliminate the ambiguity. Then, the geometrical structure of Patkaneh was analyzed by introducing two practical methods. The first method is based on the constituent units of Patkaneh (Square and diamond) and investigating the interactive relationships between them in 2D and 3D. This method is appropriate for cases where there are rational and regular geometrical relationships. The second method is based on the separation of the floors and the investigation of their interrelation. It is practical when the constituent units are not geometrically regular and have numerous diversity. Finally, the parametric form algorithm of these methods was codified.

Keywords: geometric properties, parametric design, Patkaneh, structural analysis

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Authors: Mads Kirk Larsen

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Strict air pollution control is today high on the agenda world-wide. By reducing the particular emission, not only the mg/Nm3 will be reduced – also parts of mercury and other hazardous matters attached to the particles will be reduced. Furthermore, it is possible to catch the fine particles (PM2.5). For particulate control, the precipitators are still the preferred choice and much efforts have been done to improve the efficiencies. Many ESP’s have seen electrical upgrading by changing the traditional 1 phase power system into either 3 phase or SMPS (High Frequency) units. However, there exist a 4th type of power supply – the pulse type. This is unfortunately widely unknown, but may be of great benefit to power plants. The FLSmidth type is called COROMAX® and it is a high voltage pulse generator for precipitators using a semiconductor switch operating at medium potential. The generated high voltage pulses have rated amplitude of 80 kV and duration of 75 μs and are superimposed on a variable base voltage of 60 kV rated voltage. Hereby, achieving a peak voltage of 140 kV. COROMAX® has the ability to increase the voltage beyond the natural spark limit inside the precipitator. Voltage levels may often be twice as high after installation of COROMAX®. Hereby also the migration velocity increases and thereby the efficiency. As the collection efficiency is proportional to the voltage peak and mean values, this also increases the collection efficiency of the fine particles where test has shown 80% removal of particles less than 0.07 micron. Another great advantage is the indifference to back-corona. Simultaneously with emission reduction, the power consumption will also be reduced. Another great advantage of the COROMAX® system is that the emission can be improved without the need to change the internal parts or enlarge the ESP. Recently, more than 150 units have been installed in China, where emissions have been reduced to ultra-low levels.

Keywords: eleectrostatic precipitator, high resistivity dust, micropulse energization, particulate removal

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Authors: Hoa Thi Hoang, Stephan Sass, Michael U. Kumke

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Concanavalin A (conA) is a protein has been widely used in sensor system based on its specific binding to α-D-Glucose or α-D-Manose. For glucose sensor using conA, either fluoresence based techniques with intensity based or lifetime based are used. In this research, liposomes made from phospholipids were used as a biomimetic membrane system. In a first step, novel building blocks containing perylene labeled glucose units were added to the system and used to decorate the surface of the liposomes. Upon the binding between rhodamine labeled con A to the glucose units at the biomimetic membrane surface, a Förster resonance energy transfer system can be formed which combines unique fluorescence properties of perylene (e.g., high fluorescence quantum yield, no triplet formation) and its high hydrophobicity for efficient anchoring in membranes to form a novel probe for the investigation of sugar-driven binding reactions at biomimetic surfaces. Two glucose-labeled perylene derivatives were synthesized with different spacer length between the perylene and glucose unit in order to probe the binding of conA. The binding interaction was fully characterized by using high-end fluorescence techniques. Steady-state and time-resolved fluorescence techniques (e.g., fluorescence depolarization) in combination with single-molecule fluorescence spectroscopy techniques (fluorescence correlation spectroscopy, FCS) were used to monitor the interaction with conA. Base on the fluorescence depolarization, the rotational correlation times and the alteration in the diffusion coefficient (determined by FCS) the binding of the conA to the liposomes carrying the probe was studied. Moreover, single pair FRET experiments using pulsed interleaved excitation are used to characterize in detail the binding of conA to the liposome on a single molecule level avoiding averaging out effects.

Keywords: concanavalin A, FRET, sensor, biomimetic membrane

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Authors: Rifat Tabassoom

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Recently multistoried housing projects are accelerating in the capital of Bangladesh- Dhaka, to house its massive population. Insufficient background research leads to a building design trend where a single unit is designed and then multiplied all through the buildings. Therefore, although having identical designs, all the units cannot perform evenly considering daylight, which also alters their household activities. This paper aims to understand if a single unit can be an optimum solution regarding daylight for a selected housing project.

Keywords: daylight, orientation, performance, simulations

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Authors: Christoph Opperer

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The rapid urbanization of modern societies and the need for sustainable urban development demand innovative solutions that meet both individual and collective needs while addressing environmental concerns. To address these challenges, this paper presents a study that explores the potential of spatial and energetic/ecological optimization to enhance the performance of urban settlements, focusing on both architectural and urban scales. The study focuses on the application of biological principles and self-organization processes in urban planning and design, aiming to achieve a balance between ecological performance, architectural quality, and individual living conditions. The research adopts a case study approach, focusing on a 10-hectare brownfield site in the south of Vienna. The site is surrounded by a small-scale built environment as an appropriate starting point for the research and design process. However, the selected urban form is not a prerequisite for the proposed design methodology, as the findings can be applied to various urban forms and densities. The methodology used in this research involves dividing the overall building mass and program into individual small housing units. A computational model has been developed to optimize the distribution of these units, considering factors such as solar exposure/radiation, views, privacy, proximity to sources of disturbance (such as noise), and minimal internal circulation areas. The model also ensures that existing vegetation and buildings on the site are preserved and incorporated into the optimization and design process. The model allows for simultaneous optimization at two scales, architectural and urban design, which have traditionally been addressed sequentially. This holistic design approach leads to individual and collective benefits, resulting in urban environments that foster a balance between ecology and architectural quality. The results of the optimization process demonstrate a seemingly random distribution of housing units that, in fact, is a densified hybrid between traditional garden settlements and allotment settlements. This urban typology is selected due to its compatibility with the surrounding urban context, although the presented methodology can be extended to other forms of urban development and density levels. The benefits of this approach are threefold. First, it allows for the determination of ideal housing distribution that optimizes solar radiation for each building density level, essentially extending the concept of sustainable building to the urban scale. Second, the method enhances living quality by considering the orientation and positioning of individual functions within each housing unit, achieving optimal views and privacy. Third, the algorithm's flexibility and robustness facilitate the efficient implementation of urban development with various stakeholders, architects, and construction companies without compromising its performance. The core of the research is the application of global and local optimization strategies to create efficient design solutions. By considering both, the performance of individual units and the collective performance of the urban aggregation, we ensure an optimal balance between private and communal benefits. By promoting a holistic understanding of urban ecology and integrating advanced optimization strategies, our methodology offers a sustainable and efficient solution to the challenges of modern urbanization.

Keywords: sustainable development, self-organization, ecological performance, solar radiation and exposure, daylight, visibility, accessibility, spatial distribution, local and global optimization

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