Search results for: importance of SPC supplier selection criteria

Authors: Raghunath Arnab

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The two-phase sampling which is also known as double sampling was introduced in 1938. In two-phase sampling, samples are selected in phases. In the first phase, a relatively large sample of size is selected by some suitable sampling design and only information on the auxiliary variable is collected. During the second phase, a sample of size is selected either from, the sample selected in the first phase or from the entire population by using a suitable sampling design and information regarding the study and auxiliary variable is collected. Evidently, two phase sampling is useful if the auxiliary information is relatively easy and cheaper to collect than the study variable as well as if the strength of the relationship between the variables and is high. If the sample is selected in more than two phases, the resulting sampling design is called a multi-phase sampling. In this article we will consider how one can use data collected at the first phase sampling at the stages of estimation of the parameter, stratification, selection of sample and their combinations in the second phase in a unified setup applicable to any sampling design and wider classes of estimators. The problem of the estimation of variance will also be considered. The variance of estimator is essential for estimating precision of the survey estimates, calculation of confidence intervals, determination of the optimal sample sizes and for testing of hypotheses amongst others. Although, the variance is a non-negative quantity but its estimators may not be non-negative. If the estimator of variance is negative, then it cannot be used for estimation of confidence intervals, testing of hypothesis or measure of sampling error. The non-negativity properties of the variance estimators will also be studied in details.

Keywords: auxiliary information, two-phase sampling, varying probability sampling, unbiased estimators

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Authors: Agholor Deborah Ewere, Emmanuel Ade, Seriki Idowu

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The role women entrepreneur plays to combat unemployment should not be underestimated, especially in countries with growing unemployment rates such as South Africa. Women entrepreneurs contribute significantly to economic development in South Africa, but their contribution has not been adequately studied and developed. Hence, the study identified business strategies adopted by women entrepreneurs to sustain growth and development of entrepreneurship. Survey research design approach was adopted and convenience sampling method was used for sample selection. The structured questionnaire was used to elicit information from the respondents. The findings revealed some of the operational challenges women entrepreneur faced to include lack of finance, marketing skills and planning and also showed that the strategies adopted by women entrepreneurs have a positive effect on the success of small businesses. It was recommended among others that the women entrepreneurs should take some time to study the nature of challenges other women have faced in business and possibly provide solutions to such issues before starting their own business. It was however concluded that unless the operational challenges named above are resolved, the role of women entrepreneurs in the developing nations will continue to experience deprived economic growth, development and display substandard competitiveness.

Keywords: business, entrepreneurs, small, strategies, success, women

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Authors: Elisa Pautasso, Matteo Castagno, Michele Osella

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In the last decade, the emergence of new social needs as an effect of the economic crisis has stimulated the flourishing of business endeavours characterised by explicit social goals. Social start-ups, social enterprises or Corporate Social Responsibility operations carried out by traditional companies are quintessential examples in this regard. This paper analyses these kinds of initiatives in order to discover the main characteristics of social business models and to provide insights to social entrepreneurs for developing or improving their strategies. The research is conducted through the integration of literature review and case study analysis and, thanks to the recognition of the importance of both profits and social impacts as the key success factors for a social business model, proposes a framework for identifying indicators suitable for measuring the social impacts generated.

Keywords: business model, case study, impacts, social business

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Authors: R. Gharari, N. Kojouri, R. Hosseini Aghdam, E. Alibeigi, B. Salmasian

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In this research, the WWER1000/V446 (a PWR Russian type reactor) is chosen as the case study. It is assumed that radioactive materials that release into the environment are more than allowable limit due to a complete failure of the ventilation system (reactor stack). In the following, the HOTSPOT and the RASCAL computational codes have been used and coupled with a developed program using MATLAB software to evaluate Total effective dose equivalent (TEDE) and cancer risk according to the BEIR equations for various human organs. In addition, effects of the containment spray system and climate conditions on the TEDE have been investigated. According to the obtained results, there is an inverse correlation between the received dose and the wind speed; the amount of the TEDE for wind speed 2 m/s and is more than wind speed for 14 m/s during the class A of the climate (2.168 and 0.444 mSv, respectively). Also, containment spray system can effect and reduce the amount of the fission products and TEDE. Furthermore, the probability of the cancer risk for women is more than men, and for children is more than adults. In addition, a specific emergency zonal planning is proposed. Results are promising in which the site selection of the WWER1000/V446 were considered safe for the public in this situation.

Keywords: TEDE, total effective dose equivalent, RASCAL and HOTSPOT codes, BEIR equations, cancer risk

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Authors: Joseph Osafo, Winifred Asare-Doku, Charity Akotia

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Decriminalizing suicide is one of the major goals of suicide prevention worldwide. In Ghana, suicide is legally prescribed and there is a wide-spread societal condemnation of the act, the survivor and families share the stigma. Evidence and advocacy continue to mount towards pressuring the government, the legal fraternity and lawmakers to consider decriminalizing the act. However, within this discourse, the views of families of attempt survivors are absent. The purpose of this study was to explore from relatives of suicide attempters their reactions towards the criminality of suicide attempt in the country. A total of 10 relatives of suicide attempters were interviewed using a semi-structured interview guide. Thematic analysis was used to analyze the data. We found that there were divergent views from families on decriminalizing suicide. We generated two major themes; Out-group bias versus In-group bias. Half of the participants opined that suicide attempt should not be decriminalized and others advocated for help and mental health care for victims of the suicide attempt. It was generally observed that although all 10 participants were cognizant that suicide attempt is a crime in Ghana, they preferred their relatives were spared from prosecution. The findings indicate incongruity, especially when participants want their relatives to avoid jail term but want the law that criminalizes suicide to remain. Findings are explained using the Fundamental Attribution Error and the concept of Kin selection. Implications for public education on decriminalization and advocacy are addressed.

Keywords: decriminalization, families, Ghana suicide, suicide attempt

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Authors: A. Lefebre, M. Willekens, K. Debackere

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Since the 1990s, patent applications have been booming, especially in the field of telecommunications. However, this increase in patent filings has been associated with an (alleged) decrease in patent quality. The plethora of low-quality patents devalues the high-quality ones, thus weakening the incentives for inventors to patent inventions. Despite the rich literature on strategic patenting, previous research has neglected to emphasize the importance of patent portfolio management and its impact on patent quality. In this paper, we compare related patent portfolios vs. nonrelated patents and investigate whether the patent quality and innovativeness differ between the two types. In the analyses, patent quality is proxied by five individual proxies (number of inventors, claims, renewal years, designated states, and grant lag), and these proxies are then aggregated into a quality index. Innovativeness is proxied by two measures: the originality and radicalness index. Results suggest that related patent portfolios have, on average, a lower patent quality compared to nonrelated patents, thus suggesting that firms use them for strategic purposes rather than for the extended protection they could offer. Even upon testing the individual proxies as a dependent variable, we find evidence that related patent portfolios are of lower quality compared to nonrelated patents, although not all results show significant coefficients. Furthermore, these proxies provide evidence of the importance of adding fixed effects to the model. Since prior research has found that these proxies are inherently flawed and never fully capture the concept of patent quality, we have chosen to run the analyses with individual proxies as supplementary analyses; however, we stick with the comprehensive index as our main model. This ensures that the results are not dependent upon one certain proxy but allows for multiple views of the concept. The presence of divisional applications might be linked to the level of innovativeness of the underlying invention. It could be the case that the parent application is so important that firms are going through the administrative burden of filing for divisional applications to ensure the protection of the invention and the preemption of competition. However, it could also be the case that the preempting is a result of divisional applications being used strategically as a backup plan and prolonging strategy, thus negatively impacting the innovation in the portfolio. Upon testing the level of novelty and innovation in the related patent portfolios by means of the originality and radicalness index, we find evidence for a significant negative association with related patent portfolios. The minimum innovation that has been brought on by the patents in the related patent portfolio is lower compared to the minimum innovation that can be found in nonrelated portfolios, providing evidence for the second argument.

Keywords: patent portfolio management, patent quality, related patent portfolios, strategic patenting

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Authors: Olga Blasco-Blasco, Vicente Liern

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The development of tourism since the mid-20th century has raised problems of overcrowding, indiscriminate construction in seaside areas and gentrification. Increasingly, the World Tourism Organisation and public institutions are promoting policies that encourage sustainability. From the perspective of sustainability, three types of tourism can be established: traditional tourism, sustainable tourism and sustainable impact tourism. Measuring sustainability is complex due to its multiple dimensions of different relative importance and diversity in nature. In order to try to answer this problem and to identify the benefits of applying policies that promote sustainable tourism, a decision-making analysis will be carried out through the application of a multicriteria analysis method. The proposal is applied to hotel reservations and to the evaluation and management of tourism sustainability in the Spanish Autonomous Communities.

Keywords: sustainable tourism, multicriteria analysis, flexible optimization, composite indicators

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Authors: Koel Chakraborty

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This paper critically examines the role of ‘disclosure and visibility’ of sexual minorities in a heteronormative organizational setting. The paper wishes to comment on the importance of promoting ‘visibility’ as an important catalyst in increasing the efficacy of outreach programs as part of diversity management practices as well as increasing the efficacy of teams. The aim of the research is to assess the pitfalls of not bringing ‘one’s authentic or whole self’ to work. In doing so, it will address whether Inclusive Leadership at the top propels employees to come out. The paper finally discusses and recommends strategies that could be helpful toward attaining and improving the visibility factor at a cross-functional level. This is a qualitative research with interviews and surveys conducted in inclusive workplace environments across various private sector companies in India.

Keywords: LGBT, diversity, organisation, leadership

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Authors: Nahashon Mwirigi

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The management of HIV/AIDS is a global challenge, demanding precise tools to predict disease progression and guide tailored treatment. CD4 cell count dynamics, a crucial immune function indicator, play an essential role in understanding HIV/AIDS progression and enhancing patient care through effective modeling. While several models assess disease progression, existing methods often fall short in capturing the complex, non-linear nature of HIV/AIDS, especially across diverse demographics. A need exists for models that balance predictive accuracy with clinical applicability, enabling individualized care strategies based on patient-specific progression rates. This study utilizes patient data from Kenyatta National Hospital (2003–2014) to model HIV/AIDS progression across six CD4-defined states. The Exponential, 2-Parameter Weibull, and 3-Parameter Weibull models are employed to analyze failure rates and explore progression patterns by age and gender. Model selection is based on Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) to identify models best representing disease progression variability across demographic groups. The 3-Parameter Weibull model emerges as the most effective, accurately capturing HIV/AIDS progression dynamics, particularly by incorporating delayed progression effects. This model reflects age and gender-specific variations, offering refined insights into patient trajectories and facilitating targeted interventions. One key finding is that older patients progress more slowly through CD4-defined stages, with a delayed onset of advanced stages. This suggests that older patients may benefit from extended monitoring intervals, allowing providers to optimize resources while maintaining consistent care. Recognizing slower progression in this demographic helps clinicians reduce unnecessary interventions, prioritizing care for faster-progressing groups. Gender-based analysis reveals that female patients exhibit more consistent progression, while male patients show greater variability. This highlights the need for gender-specific treatment approaches, as men may require more frequent assessments and adaptive treatment plans to address their variable progression. Tailoring treatment by gender can improve outcomes by addressing distinct risk patterns in each group. The model’s ability to account for both accelerated and delayed progression equips clinicians with a robust tool for estimating the duration of each disease stage. This supports individualized treatment planning, allowing clinicians to optimize antiretroviral therapy (ART) regimens based on demographic factors and expected disease trajectories. Aligning ART timing with specific progression patterns can enhance treatment efficacy and adherence. The model also has significant implications for healthcare systems, as its predictive accuracy enables proactive patient management, reducing the frequency of advanced-stage complications. For resource limited providers, this capability facilitates strategic intervention timing, ensuring that high-risk patients receive timely care while resources are allocated efficiently. Anticipating progression stages enhances both patient care and resource management, reinforcing the model’s value in supporting sustainable HIV/AIDS healthcare strategies. This study underscores the importance of models that capture the complexities of HIV/AIDS progression, offering insights to guide personalized, data-informed care. The 3-Parameter Weibull model’s ability to accurately reflect delayed progression and demographic risk variations presents a valuable tool for clinicians, supporting the development of targeted interventions and resource optimization in HIV/AIDS management.

Keywords: HIV/AIDS progression, 3-parameter Weibull model, CD4 cell count stages, antiretroviral therapy, demographic-specific modeling

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Authors: Ramin Vafadary, Maryam Khanbaghi

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Forecasting electricity load is important for various purposes like planning, operation, and control. Forecasts can save operating and maintenance costs, increase the reliability of power supply and delivery systems, and correct decisions for future development. This paper compares various time series methods to forecast 24 hours ahead of electricity load. The methods considered are the Holt-Winters smoothing, SARIMA Modeling, LSTM Network, Fbprophet, and Tensorflow probability. The performance of each method is evaluated by using the forecasting accuracy criteria, namely, the mean absolute error and root mean square error. The National Renewable Energy Laboratory (NREL) residential energy consumption data is used to train the models. The results of this study show that the SARIMA model is superior to the others for 24 hours ahead forecasts. Furthermore, a Bagging technique is used to make the predictions more robust. The obtained results show that by Bagging multiple time-series forecasts, we can improve the robustness of the models for 24 hours ahead of electricity load forecasting.

Keywords: bagging, Fbprophet, Holt-Winters, LSTM, load forecast, SARIMA, TensorFlow probability, time series

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Authors: S. H. Atef, N. H. Mahmoud, S. Abdrahman, A. Fattoh

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Background: The aim of the study is to assess the diagnostic value of fibrotest and hyaluronic acid in discriminate between insignificant and significant fibrosis. Also, to find out if these parameters could replace liver biopsy which is currently used for selection of chronic hepatitis C patients eligible for antiviral therapy. Study design: This study was conducted on 52 patients with HCV RNA detected by polymerase chain reaction (PCR) who had undergone liver biopsy and attending the internal medicine clinic at Ain Shams University Hospital. Liver fibrosis was evaluated according to the METAVIR scoring system on a scale of F0 to F4. Biochemical markers assessed were: alpha-2 macroglobulin (α2-MG), apolipoprotein A1 (Apo-A1), haptoglobin, gamma-glutamyl transferase (GGT), total bilirubin (TB) and hyaluronic acid (HA). The fibrotest score was computed after adjusting for age and gender. Predictive values and ROC curves were used to assess the accuracy of fibrotest and HA results. Results: For fibrotest, the observed area under curve for the discrimination between minimal or no fibrosis (F0-F1) and significant fibrosis (F2-F4) was 0.6736 for cutoff value 0.19 with sensitivity of 84.2% and specificity of 85.7%. For HA, the sensitivity was 89.5% and specificity was 85.7% and area under curve was 0.540 at the best cutoff value 71 mg/dL. Multi-use of both parameters, HA at 71 mg/dL with fibrotest score at 0.22 give a sensitivity 89.5%, specificity 100 and efficacy 92.3% (AUC 0.895). Conclusion: The use of both fibrotest score and HA could be as alternative to biopsy in most patients with chronic hepaitis C putting in consideration some limitations of the proposed markers in evaluating liver fibrosis.

Keywords: fibrotest, liver fibrosis, HCV RNA, biochemical markers

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Authors: Reemiah Alotaibi, Muthu Ramachandran, Ah-Lian Kor, Amin Hosseinian-Far

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In the past decade, developers of Web 2.0 technologies have shown increasing interest in the topic of e-government. There has been a rapid growth in social media technology because of its significant role in backing up some essential social needs. Its importance and power is derived from its capacity to support two-way communication. Governments are curious to get engaged in these websites, hoping to benefit from the new forms of communication and interaction offered by such technology. Greater participation by the public can be viewed as a chief indicator of effective government communication. Yet, the level of public participation in government 2.0 is not quite satisfactory. In general, it is still at the early stage in most developing countries, including Saudi Arabia. Although it is a fact that Saudi people are among the most active in using social media, the number of people who use social media to communicate with the public institutions is not high. Furthermore, most of the governmental organisations are not using social media tools to communicate with the public. They use these platforms to disseminate information. Our study focuses on the factors affecting citizens’ adoption of social media in Saudi Arabia. Our research question is: what are the factors affecting Saudi citizens’ use of social media to communicate with the government? To answer this research question, the research aims to validate the UTAUT model for examining social media tools from the citizen perspective. An amendment will be proposed to fit the adoption of social media platforms as a communication channel in government by using a developed conceptual model which integrates constructs from the UTAUT model and others external variables based on the literature review. The set of potential factors that affect these citizens' decisions to adopt social media to communicate with their government has been identified as perceived encouragement, trust and cultural influence. The connection between the above-mentioned constructs from the basis for the research hypothesis will be examined in the light of a quantitative methodology. Data collection will be performed through a survey targeting a number of Saudi citizens who are social media users. The data collected from the primary survey will later be analysed by using statistical methods. The outcomes of this research project are argued to have potential contributions to the fields of social media and e-Government adoption, both on the theoretical and practical levels. It is believed that this research project is the first of its type that attempts to identify the factors that affect citizens’ adoption of social media to communicate with the government. The importance of identifying these factors stems from the potential use of them to enhance the government’s implementation of social media and help in making more accurate decisions and strategies based on comprehending the most important factors that affect citizens’ decisions.

Keywords: social media, adoption, citizen, UTAUT model

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Authors: Zohreh Hajiha

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Culture affects the ability of the organization in expressing and achieving the goals. Organizational culture influences the selection of instruments applied in the management of organizations. All the instruments applied in organizations to control, promote and create innovations are influenced by organizational culture. This research studies organizational culture based on the cultural model of Muijen and its relationship with applying management accounting innovations in Iranian listed firms. Management accounting innovations of this study include activity-based costing, activity-based management, balanced scorecard, target costing, standard costing, quality costing, Kaizen costing and dimensions of organizational culture include support orientation, innovation orientation, rules orientation and goal orientation. 105 questionnaires were sent to financial executives of production companies and 73 questionnaires were returned. The findings show that there is a significant difference between organizational culture of firms that have applied management accounting innovations and those which have used these innovations less. Also, dimensions of support orientation and culture goal orientation are the highest in groups that apply management accounting innovations. The findings suggest that proper organization culture could promote the use od management accounting tools in Iranian firms.

Keywords: organizational culture, innovation, management accounting, muijen model

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Authors: Muhammad Saqlain, Poom Kumam

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Language being an abstract system and creative act, is quite complicated as its meaning varies depending on the context. The context is determined by the empirical knowledge of a person, which is derived from observation and experience. About further subdivided attributes, the decision-making challenges may entail quantitative and qualitative factors. However, because there is no norm for putting a numerical value on language, existing approaches cannot carry out the operations of linguistic knowledge. The assigning of mathematical values (fuzzy, intuitionistic, and neutrosophic) to any decision-making problem; without considering any rule of linguistic knowledge is ambiguous and inaccurate. Thus, this paper aims to provide a generic model for these issues. This paper provides the linguistic set structure of the fuzzy hypersoft set (FLHSS) to solve decision-making issues. We have proposed the definition some basic operations like AND, NOT, OR, AND, compliment, negation, etc., along with Topology and examples, and properties. Secondly, the operational laws for the fuzzy linguistic hypersoft set have been proposed to deal with the decision-making issues. Implementing proposed aggregate operators and operational laws can be used to convert linguistic quantifiers into numerical values. This will increase the accuracy and precision of the fuzzy hypersoft set structure to deal with decision-making issues.

Keywords: linguistic quantifiers, aggregate operators, multi-criteria decision making (mcdm)., fuzzy topology

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Authors: Alexey Abilov

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The article highlights the experience of training master's and doctoral students at Satbayev University by preparing their course works for disciplines "Principles of Sustainable Architecture", "Energy Efficiency in Urban planning", "Urban planning analysis, "Social foundations of Architecture". The purpose of these works is the acquisition by students of practical skills necessary in their future professional activities, which are achieved through comprehensive assessment of individual sections of the Almaty urban environment. The methodology of student’s researches carried out under the guidance of the author of this publication is based on an expert assessment of the territory through its full-scale survey, analysis of project documents and statistical data, as well as on a social assessment of the territory based on the results of a questionnaire survey of residents. A comprehensive qualitative and quantitative assessment of the selected sites according to the criteria of the quality of the living environment also allows to formulate specific recommendations for designers who carry out a pre-project analysis of the city territory in the process of preparing draft master plans and detailed planning projects.

Keywords: urban environment, expert/social assessment of the territory, questionnaire survey, comprehensive approach

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Authors: Solomon Weldegebriel Gebrelibanos

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Water is one of the most important substances in human life that can give a human liberality with its cost and availability. Water comes from rainfall and runoff and reaches the ground as runoff that is stored in a river, ponds, and big water bodies, including sea and ocean and the remaining water portion is infiltrated into the ground to store in the aquifer. Water can serve human beings in various ways, including irrigation, water supply, hydropower and soon. Water supply is the main pillar of the water service to the human being. Water supply distribution in Addis Ababa arises from Legedadi, Akakai, and Gefersa. The objective of the study is to measure the performance of the water supply distribution in Addis Ababa city. The water supply distribution model is developed by computer-aided design software. The model can analyze the operational change, loss of water, and performance of the network. The two design criteria that have been employed to analyze the network system are velocity and pressure. The result shows that the customers are using the water at high pressure with low demand. The water distribution system is older than the expected service life with more leakage. Hence the study recommended that fixing Pressure valves and new distribution facilities can resolve the performance of the water supply system

Keywords: distribution, model, pressure, velocity

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Authors: Abbas Nesayan

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Background: In recent years, autism has been under consideration in public and research area. Autistic children have dysfunction in communication, socialization, repetitive and stereotyped behaviors. In addition, they clinically suffer from difficulty in attention, challenge with familiar behaviors and sensory processing problems. Several variables are linked to sensory processing problems in autism, one of these variables is working memory. Working memory is part of the executive function which provides the necessary ability to completing multiple stages tasks. Method: This study has categorized in correlational research methods. After determining of entry criteria, according to purposive sampling method, 50 children were selected. Dunn’s sensory profile school companion was used for assessment of sensory processing patterns; behavioral rating inventory of executive functions was used (BRIEF) for assessment of working memory. Pearson correlation coefficient and linear regression were used for data analyzing. Results: The results showed the significant relationship between sensory processing patterns (low registration, sensory seeking, sensory sensitivity and sensory avoiding) with working memory in autistic children. Conclusion: According to the findings, there is the significant relationship between the patterns of sensory processing and working memory. So, in order to improve the working memory could be used some interventions based on the sensory processing.

Keywords: sensory processing patterns, working memory, autism, autistic children

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Authors: Asma Ameur, Dhafer Malouche

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Hotel competitiveness research is an essential phase of the marketing strategy for any hotel. Certainly, knowing the hotels' competitors helps the hotelier to grasp its position in the market and the citizen to make the right choice in picking a hotel. Thus, competitiveness is an important indicator that can be influenced by various factors. In fact, the issue of competitiveness, this ability to cope with competition, remains a difficult and complex concept to define and to exploit. Therefore, the purpose of this article is to make an exploratory study to calculate a competitiveness indicator for hotels. Further on, this paper makes it possible to determine the criteria of direct or indirect effect on the image and the perception of a hotel. The actual research is used to look into the right model for hotel ‘competitiveness. For this reason, we exploit different theoretical contributions in the field of machine learning. Thus, we use some statistical techniques such as the Principal Component Analysis (PCA) to reduce the dimensions, as well as other techniques of statistical modeling. This paper presents a survey covering of the techniques and methods in hotel competitiveness research. Furthermore, this study allows us to deduct the significant variables that influence the determination of hotel’s competitors. Lastly, the discussed experiences in this article found that the hotel competitors are influenced by several factors with different rates.

Keywords: competitiveness, e-reputation, hotels' competitors, online hotel’ review, principal component analysis, statistical modeling

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Authors: Mohsin Sadaqat, Hilal Anwar Butt

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Following the stock selection guidelines provided by the Sharia Board (SB), we segregate the firms listed at Pakistan Stock Exchange (PSX) into Sharia Compliant (SC) and Non-Sharia Compliant (NSC) stocks. Subsequently, we form portfolios within each group based on market capitalization and volatility. The purpose is to analyze and compare the performance of these two groups as the SC stocks have lesser diversification opportunities due to SB restrictions. Using data ranging from January 2004 until June 2016, our results indicate that in most of the cases the risk-adjusted returns (alphas) for the returns differential between SC and NCS firms are positive. In addition, the SC firms in comparison to their counterparts in PSX provides excess returns that are hedged against the market, size, and value-based systematic risks factors. Overall, these results reconcile with one prevailing notion that the SC stocks that have lower financial leverage and higher investment in real assets are lesser exposed to market-based risks. Further, the SC firms that are more capitalized and less volatile, perform better than lower capitalized and higher volatile SC and NSC firms. To sum up our results, we do not find any substantial evidence for opportunity loss due to limited diversification opportunities in case of SC firms. To optimally utilize scarce resources, investors should consider SC firms as a candidate in portfolio construction.

Keywords: diversification, performance, sharia compliant stocks, risk adjusted returns

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Authors: Oluwafunmibi Omotayo Fasanya, Augustine Kena Adjei

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To develop a machine learning model to predict diabetes (DM) prevalence in the U.S. population using demographic characteristics, physical indicators, and lifestyle habits, and to analyze how these factors contribute to the likelihood of diabetes. We analyzed data from 23,546 participants aged 20 and older, who were non-pregnant, from the 2009-2018 National Health and Nutrition Examination Survey (NHANES). The dataset included key demographic (age, sex, ethnicity), physical (BMI, leg length, total cholesterol [TCHOL], fasting plasma glucose), and lifestyle indicators (smoking habits). A weighted sample was used to account for NHANES survey design features such as stratification and clustering. A classification machine learning model was trained to predict diabetes status. The target variable was binary (diabetes or non-diabetes) based on fasting plasma glucose measurements. The following models were evaluated: Logistic Regression (baseline), Random Forest Classifier, Gradient Boosting Machine (GBM), Support Vector Machine (SVM). Model performance was assessed using accuracy, F1-score, AUC-ROC, and precision-recall metrics. Feature importance was analyzed using SHAP values to interpret the contributions of variables such as age, BMI, ethnicity, and smoking status. The Gradient Boosting Machine (GBM) model outperformed other classifiers with an AUC-ROC score of 0.85. Feature importance analysis revealed the following key predictors: Age: The most significant predictor, with diabetes prevalence increasing with age, peaking around the 60s for males and 70s for females. BMI: Higher BMI was strongly associated with a higher risk of diabetes. Ethnicity: Black participants had the highest predicted prevalence of diabetes (14.6%), followed by Mexican-Americans (13.5%) and Whites (10.6%). TCHOL: Diabetics had lower total cholesterol levels, particularly among White participants (mean decline of 23.6 mg/dL). Smoking: Smoking showed a slight increase in diabetes risk among Whites (0.2%) but had a limited effect in other ethnic groups. Using machine learning models, we identified key demographic, physical, and lifestyle predictors of diabetes in the U.S. population. The results confirm that diabetes prevalence varies significantly across age, BMI, and ethnic groups, with lifestyle factors such as smoking contributing differently by ethnicity. These findings provide a basis for more targeted public health interventions and resource allocation for diabetes management.

Keywords: diabetes, NHANES, random forest, gradient boosting machine, support vector machine

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Authors: Mahmut Yildirim

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This paper proposed the bidirectional long short-term memory (Bi-LSTM) network-aided deep learning (DL)-based signal detection for Orthogonal frequency division multiplexing with all index modulation (OFDM-AIM), namely Bi-DeepAIM. OFDM-AIM is developed to increase the spectral efficiency of OFDM with index modulation (OFDM-IM), a promising multi-carrier technique for communication systems beyond 5G. In this paper, due to its strong classification ability, Bi-LSTM is considered an alternative to the maximum likelihood (ML) algorithm, which is used for signal detection in the classical OFDM-AIM scheme. The performance of the Bi-DeepAIM is compared with LSTM network-aided DL-based OFDM-AIM (DeepAIM) and classic OFDM-AIM that uses (ML)-based signal detection via BER performance and computational time criteria. Simulation results show that Bi-DeepAIM obtains better bit error rate (BER) performance than DeepAIM and lower computation time in signal detection than ML-AIM.

Keywords: bidirectional long short-term memory, deep learning, maximum likelihood, OFDM with all index modulation, signal detection

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Authors: Guenther Schuh, Christina Koenig, Nico Schoen, Markus Wellensiek

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Identification and selection of appropriate product and manufacturing technologies are key factors for competitiveness and market success of technology-based companies. Therefore many companies perform technology intelligence (TI) activities to ensure the identification of evolving technologies at the right time. Technology monitoring is one of the three base activities of TI, besides scanning and scouting. As the technological progress is accelerating, more and more technologies are being developed. Against the background of limited resources it is therefore necessary to focus TI activities. In this paper, we propose a concept for defining appropriate search fields for technology monitoring. This limitation of search space leads to more concentrated monitoring activities. The concept will be introduced and demonstrated through an anonymized case study conducted within an industry project at the Fraunhofer Institute for Production Technology. The described concept provides a customized monitoring approach, which is suitable for use in technology-oriented companies especially those that have not yet defined an explicit technology strategy. It is shown in this paper that the definition of search fields and search tasks are suitable methods to define topics of interest and thus to direct monitoring activities. Current as well as planned product, production and material technologies as well as existing skills, capabilities and resources form the basis of the described derivation of relevant search areas. To further improve the concept of technology monitoring the proposed concept should be extended during future research e.g. by the definition of relevant monitoring parameters.

Keywords: monitoring radar, search field, technology intelligence, technology monitoring

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Authors: Steven G. Sclan

Abstract:

Background: Since December 2019, the world has been afflicted by the spread of the Severe Acute Respiratory Syndrome-Corona Virus-2 (SARS-CoV-2), which is responsible for the condition referred to as Covid-19. The illness has had a cataclysmic impact on the political, social, economic, and overall well-being of the population of the entire globe. While Covid-19 has had a substantial universal fatality impact, it may have an even greater effect on the socioeconomic, medical well-being, and healthcare planning for remaining societies. Significance: As these numbers illustrate, many more persons survive the infection than die from it, and many of those patients have noted ongoing, persistent symptoms after successfully enduring the acute phase of the illness. Recognition and understanding of these symptoms are crucial for developing and arranging efficacious models of care for all patients (whether or not having been hospitalized) surviving acute covid illness and plagued by post-acute symptoms. Furthermore, regarding Covid infection in children (< 18 y/o), although it may be that Covid “+” children are not major vectors of infective transmission, it now appears that many more children than initially thought are carrying the virus without accompanying obvious symptomatic expression. It seems reasonable to wonder whether viral effects occur in children – those children who are Covid “+” and now asymptomatic – and if, over time, they might also experience similar symptoms. An even more significant question is whether Covid “+” asymptomatic children might manifest increased multiple health problems as they grow – i.e., developmental complications (e.g., physical/medical, metabolic, neurobehavioral, etc.) – in comparison to children who had been consistently Covid “ - ” during the pandemic. Topics Addressed and Theoretical Importance: This review is important because of the description of both quantitative and qualitative methods for clinical and biomedical research. Topics reviewed will consider the importance of well-designed, comprehensive (i.e., quantitative and qualitative methods) longitudinal studies of Post Covid-19 symptoms in both adults and children. Also reviewed will be general characteristics of longitudinal studies and a presentation of a model for a proposed study. Also discussed will be the benefit of longitudinal studies for the development of efficacious interventions and for the establishment of cogent, practical, and efficacious community healthcare service planning for post-acute covid patients. Conclusion: Results of multi-dimensional, longitudinal studies will have important theoretical implications. These studies will help to improve our understanding of the pathophysiology of long COVID and will aid in the identification of potential targets for treatment. Such studies can also provide valuable insights into the long-term impact of COVID-19 on public health and socioeconomics.

Keywords: COVID-19, post-COVID-19, long COVID, longitudinal research, quantitative research, qualitative research

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Authors: Hyeon-Kyo Lim, Tong-il Jang, Yong-Hee Lee

Abstract:

As for any nuclear power plant, human error is one of the most dreaded factors that may result in unexpected accidents. Thus, for accident prevention, it is quite indispensable to analyze and to manage the influence of any factor which may raise the possibility of human errors. Among lots factors, stress has been reported to have significant influence on human performance. Stress level of a person may fluctuate over time. To handle the possibility over time, robust stress management program is required, especially in nuclear power plants. Therefore, to overcome the possibility of human errors, this study aimed to develop a stress management program as a part of Fitness-for-Duty (FFD) Program for the workers in nuclear power plants. The meaning of FFD might be somewhat different by research objectives, appropriate definition of FFD was accomplished in this study with special reference to human error prevention, and diverse stress factors were elicited for management of human error susceptibility. In addition, with consideration of conventional FFD management programs, appropriate tests and interventions were introduced over the whole employment cycle including selection and screening of workers, job allocation, job rotation, and disemployment as well as Employee-Assistance-Program (EAP). The results showed that most tools mainly concentrated their weights on common organizational factors such as Demands, Supports, and Relationships in sequence, which were referred as major stress factors.

Keywords: human error, accident prevention, work performance, stress, fatigue

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Authors: Adewale O. Ogunde, Emmanuel O. Ajibade

Abstract:

The task of selecting a few elective courses from a variety of available elective courses has been a difficult one for many students over the years. In many higher institutions, guidance and counselors or level advisers are usually employed to assist the students in picking the right choice of courses. In reality, these counselors and advisers are most times overloaded with too many students to attend to, and sometimes they do not have enough time for the students. Most times, the academic strength of the student based on past results are not considered in the new choice of electives. Recommender systems implement advanced data analysis techniques to help users find the items of their interest by producing a predicted likeliness score or a list of top recommended items for a given active user. Therefore, in this work, a collaborative filtering-based recommender system that will dynamically recommend elective courses to undergraduate students based on their past grades in related courses was developed. This approach employed the use of the k-nearest neighbor algorithm to discover hidden relationships between the related courses passed by students in the past and the currently available elective courses. Real students’ results dataset was used to build and test the recommendation model. The developed system will not only improve the academic performance of students, but it will also help reduce the workload on the level advisers and school counselors.

Keywords: collaborative filtering, elective courses, k-nearest neighbor algorithm, recommender systems

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Authors: Ranjana Dani

Abstract:

Brand communication narratives in India has evolved today to reflect the vibrant and intriguing tone of voice inspired by a rich cultural heritage while addressing the culturally alert attitude of the contemporary global Indian. Brands are strongly associated with the organization's values, vision, and mission and portray this through specific ‘look and feel’ and ‘tone of voice’. It is within the brand’s visual language that COLOUR has evolved to become a most powerful weapon in the designer’s arsenal. Color is big business in Brand Design! A brand is a ‘collection of perceptions’, meaningful brand connect is about striving to occupy head and heart space in consumers. The persona of the young Indian reflects a deep attachment to cultural roots as seen through the characteristic of ‘Indie Pride,’ blended with the ambitious, aspirational traits of a modern ‘global citizen’.Studies on ‘Color Perceptions’ indicate a trend that amplifies this, and hence brands reflect a GLOCAL palette, a Global and Local Blend. This paper establishes this through case studies that expand the inspirations, selection processes, and use of innovative color palettes crafted by some dynamic brand designers. This throws light on the role of color as it generates visual impact and recall for successful brands.

Keywords: colour palettes, brand design and business, cultural context, colour perceptions, glocal, contemporaneity

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Authors: Amir Andria Gad Shehata

Abstract:

Minimizing the inventory cost, optimizing the inventory quantities, and increasing system operational availability are the main motivations to enhance forecasting demand of spare parts in a major power utility company in Medina. This paper reports in an effort made to optimize the orders quantities of spare parts by improving the method of forecasting the demand. The study focuses on equipment that has frequent spare parts purchase orders with uncertain demand. The pattern of the demand considers a lumpy pattern which makes conventional forecasting methods less effective. A comparison was made by benchmarking various methods of forecasting based on experts’ criteria to select the most suitable method for the case study. Three actual data sets were used to make the forecast in this case study. Two neural networks (NN) approaches were utilized and compared, namely long short-term memory (LSTM) and multilayer perceptron (MLP). The results as expected, showed that the NN models gave better results than traditional forecasting method (judgmental method). In addition, the LSTM model had a higher predictive accuracy than the MLP model.

Keywords: spare part, spare part inventory, inventory model, optimization, maintenanceneural network, LSTM, MLP, forecasting demand, inventory management

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Authors: Robin Lok-Wang Ma

Abstract:

The Center/Unit for Industry Engagement and Collaboration, as well as Internship, play a significant role at university. In general, the Center serves as the official interface between the industry and the School or Department to cultivate students’ early exposure to professional experience. The missions of the Center are not limited to provide a communication channel and collaborative platform for the industries and the university but also to assist students to build up their career paths early while still in the university. In recent years, a cooperative education experience (commonly known as a co-op) has been strongly advocated for students to make the school-to-work transition. The nature of the co-op program is not only consistent with the internships/final year design projects, but it is also more industrial-oriented with academic support from faculty at the university. The purpose of this paper is to describe an approach to how cooperative education experience can be integrated into Engineering Curriculum. It provides a mutual understanding and exchange of ideas for the approach between the university and the industry. A suggested format in terms of timeline, duration, selection of candidates, students, and companies’ expectations for the co-op program is described. Also, feedbacks from employers/industries show that a longer-term co-op program is well suited for students compared with a short-term internship. To this end, it provides a new insight into collaboration and/or partnership between the university and the industries to prepare professional work-ready graduates.

Keywords: cooperative education, industry, engagement, collaboration

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Authors: Samrina Jafrin, Till Talaulicar

Abstract:

This study investigates stakeholder perceptions of environmental, social, and governance (ESG) reporting patterns and their effectiveness in enhancing trust and transparency. Utilizing a multi-method approach, including experimental research and systematic literature review, insights are gathered from investors, employees, customers, suppliers, managers, and community members. The findings reveal diverse stakeholder expectations and perceptions and emphasize the importance of effective ESG reporting strategies in building credibility and trust. This research contributes to the academic discourse on corporate sustainability reporting and provides practical recommendations for optimizing ESG reporting practices.

Keywords: ESG reporting, stakeholder perceptions, corporate sustainability, transparency, trust

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Authors: Siddhant Yadav, Rylea Ranum, Hannah Alberts, Abdul Kalaiger, Brent Bauer, Ryan Hurt, Ann Vincent, Loren Toussaint, Sanjeev Nanda

Abstract:

Background and significance: Fibromyalgia (FM) is a chronic pain disorder also characterized by chronic fatigue, morning stiffness, sleep, and cognitive symptoms, psychological disturbances (anxiety, depression), and is comorbid with multiple medical and psychiatric conditions. It has an incidence of 2-4% in the general population and is reported more commonly in women. Oxidative stress and inflammation are thought to contribute to pain in patients with FM, and the adoption of an antioxidant/anti-inflammatory diet has been suggested as a modality to alleviate symptoms. The aim of this systematic review was to evaluate the efficacy of specialized diets (ketogenic, gluten free, Mediterranean, and low carbohydrate) in improving FM symptoms. Methodology: A comprehensive search of the following databases from inception to July 15th, 2021, was conducted: Ovid MEDLINE and Epub ahead of print, in-process and other non-indexed citations and daily, Ovid Embase, Ovid EBM reviews, Cochrane central register of controlled trials, EBSCO host CINAHL with full text, Elsevier Scopus, website and citation index, web of science emerging sources citation and clinicaltrials.gov. We included randomized controlled trials, non-randomized experimental studies, cross-sectional studies, cohort studies, case series, and case reports in adults with fibromyalgia. The risk of bias was assessed with the Agency for Health Care Research and Quality designed, specific recommended criteria (AHRQ). Results: Thirteen studies were eligible for inclusion. This included a total of 761 participants. Twelve out of the 13 studies reported improvement in widespread body pain, joint stiffness, sleeping pattern, mood, and gastrointestinal symptoms, and one study reported no changes in symptomatology in patients with FM on specialized diets. None of the studies showed the worsening of symptoms associated with a specific diet. Most of the patient population was female, with the mean age at which fibromyalgia was diagnosed being 48.12 years. Improvement in symptoms was reported by the patient's adhering to a gluten-free diet, raw vegan diet, tryptophan- and magnesium-enriched Mediterranean diet, aspartame- and msg- elimination diet, and specifically a Khorasan wheat diet. Risk of bias assessment noted that 6 studies had a low risk of bias (5 clinical trials and 1 case series), four studies had a moderate risk of bias, and 3 had a high risk of bias. In many of the studies, the allocation of treatment (diets) was not adequately concealed, and the researchers did not rule out any potential impact from a concurrent intervention or an unintended exposure that might have biased the results. On the other hand, there was a low risk of attrition bias in all the trials; all were conducted with an intention-to-treat, and the inclusion/exclusion criteria, exposures/interventions, and primary outcomes were valid, reliable, and implemented consistently across all study participants. Concluding statement: Patients with fibromyalgia who followed specialized diets experienced a variable degree of improvement in their widespread body pain. Improvement was also seen in stiffness, fatigue, moods, sleeping patterns, and gastrointestinal symptoms. Additionally, the majority of the patients also reported improvement in overall quality of life.

Keywords: fibromyalgia, specialized diet, vegan, gluten free, Mediterranean, systematic review

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