Search results for: financial models

Authors: Darius Jakimavicius

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Artificial intelligence is the subject of intense debate in the international arena, identified both as a technological breakthrough and as a component of the strategic stability effect. Both the kinetic and non-kinetic development of AI and its application in the national strategies of the great powers may trigger a change in the security situation. Artificial intelligence is generally faster, more capable and more efficient than humans, and there is a temptation to transfer decision-making and control responsibilities to artificial intelligence. Artificial intelligence, which, once activated, can select and act on targets without further intervention by a human operator, blurs the boundary between human or robot (machine) warfare, or perhaps human and robot together. Artificial intelligence acts as a force multiplier that speeds up decision-making and reaction times on the battlefield. The role of humans is increasingly moving away from direct decision-making and away from command and control processes involving the use of force. It is worth noting that the autonomy and precision of AI systems make the process of strategic stability more complex. Deterrence theory is currently in a phase of development in which deterrence is undergoing further strain and crisis due to the complexity of the evolving models enabled by artificial intelligence. Based on the concept of strategic stability and deterrence theory, it is appropriate to develop further research on the development and impact of AI in order to assess AI from both a scientific and technical perspective: to capture a new niche in the scientific literature and academic terminology, to clarify the conditions for deterrence, and to identify the potential uses, impacts and possibly quantities of AI. The research problem is the impact of artificial intelligence developed by great powers on strategic stability. This thesis seeks to assess the impact of AI on strategic stability and deterrence principles, with human exclusion from the decision-making and control loop as a key axis. The interaction between AI and human actions and interests can determine fundamental changes in great powers' defense and deterrence, and the development and application of AI-based great powers strategies can lead to a change in strategic stability.

Keywords: artificial inteligence, strategic stability, deterrence theory, decision making loop

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Authors: Mustafa Al Sukar, Azzam Sleit, Abdullatif Abu-Dalhoum, Bassam Al-Kasasbeh

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Use and abuse of drugs by teens is very common and can have dangerous consequences. The drugs contribute to physical and sexual aggression such as assault or rape. Some teenagers regularly use drugs to compensate for depression, anxiety or a lack of positive social skills. Teen resort to smoking should not be minimized because it can be "gateway drugs" for other drugs (marijuana, cocaine, hallucinogens, inhalants, and heroin). The combination of teenagers' curiosity, risk taking behavior, and social pressure make it very difficult to say no. This leads most teenagers to the questions: "Will it hurt to try once?" Nowadays, technological advances are changing our lives very rapidly and adding a lot of technologies that help us to track the risk of drug abuse such as smart phones, Wireless Sensor Networks (WSNs), Internet of Things (IoT), etc. This technique may help us to early discovery of drug abuse in order to prevent an aggravation of the influence of drugs on the abuser. In this paper, we have developed a Decision Support System (DSS) for detecting the drug abuse using Artificial Neural Network (ANN); we used a Multilayer Perceptron (MLP) feed-forward neural network in developing the system. The input layer includes 50 variables while the output layer contains one neuron which indicates whether the person is a drug addict. An iterative process is used to determine the number of hidden layers and the number of neurons in each one. We used multiple experiment models that have been completed with Log-Sigmoid transfer function. Particularly, 10-fold cross validation schemes are used to access the generalization of the proposed system. The experiment results have obtained 98.42% classification accuracy for correct diagnosis in our system. The data had been taken from 184 cases in Jordan according to a set of questions compiled from Specialists, and data have been obtained through the families of drug abusers.

Keywords: drug addiction, artificial neural networks, multilayer perceptron (MLP), decision support system

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Authors: Nancy Retzlaff, Sarah J. Berkemer, Trudie Strauss

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In the last couple of decades, the advent of digitalization of any kind of data was probably one of the major advances in all fields of study. This paves the way for also analysing these data even though they might come from disciplines where there was no initial computational necessity to do so. Especially in linguistics, one can find a rather manual tradition. Still when considering studies that involve the history of language families it is hard to overlook the striking similarities to bioinformatics (phylogenetic) approaches. Alignments of words are such a fairly well studied example of an application of bioinformatics methods to historical linguistics. In this paper we will not only consider alignments of strings, i.e., words in this case, but also alignments of syntax trees of selected Indo-European languages. Based on initial, crude alignments, a sophisticated scoring model is trained on both letters and syntactic features. The aim is to gain a better understanding on which features in two languages are related, i.e., most likely to have the same root. Initially, all words in two languages are pre-aligned with a basic scoring model that primarily selects consonants and adjusts them before fitting in the vowels. Mixture models are subsequently used to filter ‘good’ alignments depending on the alignment length and the number of inserted gaps. Using these selected word alignments it is possible to perform tree alignments of the given syntax trees and consequently find sentences that correspond rather well to each other across languages. The syntax alignments are then filtered for meaningful scores—’good’ scores contain evolutionary information and are therefore used to train the sophisticated scoring model. Further iterations of alignments and training steps are performed until the scoring model saturates, i.e., barely changes anymore. A better evaluation of the trained scoring model and its function in containing evolutionary meaningful information will be given. An assessment of sentence alignment compared to possible phrase structure will also be provided. The method described here may have its flaws because of limited prior information. This, however, may offer a good starting point to study languages where only little prior knowledge is available and a detailed, unbiased study is needed.

Keywords: alignments, bioinformatics, comparative linguistics, historical linguistics, statistical methods

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Authors: Carolyn Scott, Rachel Nugent

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The agricultural industry in Ireland and worldwide is one of the most dangerous occupations with respect to occupational health and safety accidents and fatalities. Many accident causation models have been developed in safety research to understand the underlying and contributory factors that lead to the occurrence of an accident. Due to the uniqueness of the agricultural sector, current accident causation theories cannot be applied. This paper presents an accident causation model named the Irish Farm Accident Causation Model (IFACM) which has been specifically tailored to the needs of Irish farms. The IFACM is a theoretical and practical model of accident causation that arranges the causal factors into a graphic representation of originating, shaping, and contributory factors that lead to accidents when unsafe acts and conditions are created that are not rectified by control measures. Causes of farm accidents were assimilated by means of a thorough literature review and were collated to form a graphical representation of the underlying causes of a farm accident. The IFACM was validated retrospectively through case study analysis and peer review. Participants in the case study (n=10) identified causes that led to a farm accident in which they were involved. A root cause analysis was conducted to understand the contributory factors surrounding the farm accident, traced back to the ‘root cause’. Experts relevant to farm safety accident causation in the agricultural industry have peer reviewed the IFACM. The accident causation process is complex. Accident prevention requires a comprehensive understanding of this complex process because to prevent the occurrence of accidents, the causes of accidents must be known. There is little research on the key causes and contributory factors of unsafe behaviours and accidents on Irish farms. The focus of this research is to gain a deep understanding of the causality of accidents on Irish farms. The results suggest that the IFACM framework is helpful for the analysis of the causes of accidents within the agricultural industry in Ireland. The research also suggests that there may be international applicability if further research is carried out. Furthermore, significant learning can be obtained from considering the underlying causes of accidents.

Keywords: farm safety, farm accidents, accident causation, root cause analysis

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Authors: M. Vlahovic

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This paper presents a model of public finances, which combines three concepts: participatory budgeting, crowdfunding and blockchain technology. Participatory budgeting is defined as a process in which community members decide how to spend a part of community’s budget. Crowdfunding is a practice of funding a project by collecting small monetary contributions from a large number of people via an Internet platform. Blockchain technology is a distributed ledger that enables efficient and reliable transactions that are secure and transparent. In this hypothetical model, the government or authorities on local/regional level would set up a platform where they would propose public projects to citizens. Citizens would browse through projects and support or vote for those which they consider justified and necessary. In return, they would be entitled to a tax relief in the amount of their monetary contribution. Since the blockchain technology enables tracking of transactions, it can be used to mitigate corruption, money laundering and lack of transparency in public finances. Models of its application have already been created for e-voting, health records or land registries. By presenting a model of application of blockchain technology in public finances, this paper takes into consideration the potential of blockchain technology to disrupt governments and make processes more democratic, secure, transparent and efficient. The framework for this paper consists of multiple streams of research, including key concepts of direct democracy, public finance (especially the voluntary theory of public finance), information and communication technology, especially blockchain technology and crowdfunding. The framework defines rules of the game, basic conditions for the implementation of the model, benefits, potential problems and development perspectives. As an oversimplified map of a new form of public finances, the proposed model identifies primary factors, that influence the possibility of implementation of the model, and that could be tracked, measured and controlled in case of experimentation with the model.

Keywords: blockchain technology, distributed ledger, participatory budgeting, crowdfunding, direct democracy, internet platform, e-government, public finance

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Authors: Maia Kharadze, Indira Djaparidze, Maia Vanidze, Aleko Kalandia

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Modern scientific world studies chemical components and antioxidant activity of different kinds of vines according to their breed purity and location. To our knowledge, this kind of research has not been conducted in Georgia yet. The object of our research was to study Chkhaveri vine, which is included in the oldest varieties of the Black Sea basin vine. We have studied different-altitude Chkaveri grapes, juice, and wine (half dry rose-colored produced with European technologies) and their technical markers, qualitative and quantitive composition of their biologically active compounds and their antioxidant activity. We were determining the amount of phenols using Folin-Ciocalteu reagent, Flavonoids, Catechins and Anthocyanins using Spectral method and antioxidant activity using DPPH method. Several compounds were identified using –HPLC-UV-Vis, UPLC-MS methods. Six samples of Chkhaveri species– 5, 300, 360, 380, 400, 780 meter altitudes were taken and analyzed. The sample taken from 360 m altitude is distinguished by its cluster mass (383.6 grams) and high amount of sugar (20.1%). The sample taken from the five-meter altitude is distinguished by having high acidity (0.95%). Unlike other grapes varieties, such concentration of sugar and relatively low levels of citric acid ultimately leads to Chkhaveri wine individuality. Biologically active compounds of Chkhaveri were researched in 2014, 2015, 2016. The amount of total phenols in samples of 2016 fruit varies from 976.7 to 1767.0 mg/kg. Amount of Anthocians is 721.2-1630.2 mg/kg, and the amount of Flavanoids varies from 300.6 to 825.5 mg/kg. Relatively high amount of anthocyanins was found in the Chkhaveri at 780-meter altitude - 1630.2 mg/kg. Accordingly, the amount of Phenols and Flavanoids is high- 1767.9 mg/kg and 825.5 mg/kg. These characteristics are low in samples gathered from 5 meters above sea level, Anthocyanins-721.2 mg/ kg, total Phenols-976.7 mg/ kg, and Flavanoids-300.6 mg/kg. The highest amount of bioactive compounds can be found in the Chkhaveri samples of high altitudes because with rising height environment becomes harsh, the plant has to develop a better immune system using Phenolic compounds. The technology that is used for the production of wine also plays a huge role in the composition of the final product. Optimal techniques of maceration and ageing were worked out. While squeezing Chkhaveri, there are no anthocyanins in the juice. However, the amount of Anthocyanins rises during maceration. After the fermentation of dregs, the amount of anthocyanins is 55%, 521.3 gm/l, total Phenols 80% 1057.7 mg/l and Flavanoids 23.5 mg/l. Antioxidant activity of samples was also determined using the effect of 50% inhibition of the samples. All samples have high antioxidant activity. For instance, in samples at 780 meters above the sea-level antioxidant activity was 53.5%. It is relatively high compared to the sample at 5 m above sea-level with the antioxidant activity of 30.5%. Thus, there is a correlation between the amount Anthocyanins and antioxidant activity. The designated project has been fulfilled by financial support of the Georgia National Science Foundation (Grant AP/96/13, Grant 216816), Any idea in this publication is possessed by the author and may not represent the opinion of the Georgia National Science Foundation.

Keywords: antioxidants, bioactive content, wine, chkhaveri

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Authors: Priyanka Verma, Vijaya Dixit, Rishabh Bajpai

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This research paper is aimed at selecting appropriate material handling equipment among the given choices so that the automation level in material handling can be enhanced. This work is a practical case scenario of material handling systems in consumer electronic appliances manufacturing organization. The choices of material handling equipment among which the decision has to be made are Automated Guided Vehicle’s (AGV), Autonomous Mobile Robots (AMR), Overhead Conveyer’s (OC) and Battery Operated Trucks/Vehicle’s (BOT). There is a need of attaining a certain level of automation in order to reduce human interventions in the organization. This requirement of achieving certain degree of automation can be attained by material handling equipment’s mentioned above. The main motive for selecting above equipment’s for study was solely based on corporate financial strategy of investment and return obtained through that investment made in stipulated time framework. Since the low cost automation with respect to material handling devices has to be achieved hence these equipment’s were selected. Investment to be done on each unit of this equipment is less than 20 lakh rupees (INR) and the recovery period is less than that of five years. Fuzzy analytic hierarchic process (FAHP) is applied here for selecting equipment where the four choices are evaluated on basis of four major criteria’s and 13 sub criteria’s, and are prioritized on the basis of weight obtained. The FAHP used here make use of triangular fuzzy numbers (TFN). The inability of the traditional AHP in order to deal with the subjectiveness and impreciseness in the pair-wise comparison process has been improved in the FAHP. The range of values for general rating purposes for all decision making parameters is kept between 0 and 1 on the basis of expert opinions captured on shop floor. These experts were familiar with operating environment and shop floor activity control. Instead of generating exact value the FAHP generates the ranges of values to accommodate the uncertainty in decision-making process. The four major criteria’s selected for the evaluation of choices of material handling equipment’s available are materials, technical capabilities, cost and other features. The thirteen sub criteria’s listed under these following four major criteria’s are weighing capacity, load per hour, material compatibility, capital cost, operating cost and maintenance cost, speed, distance moved, space required, frequency of trips, control required, safety and reliability issues. The key finding shows that among the four major criteria selected, cost is emerged as the most important criteria and is one of the key decision making aspect on the basis of which material equipment selection is based on. While further evaluating the choices of equipment available for each sub criteria it is found that AGV scores the highest weight in most of the sub-criteria’s. On carrying out complete analysis the research shows that AGV is the best material handling equipment suiting all decision criteria’s selected in FAHP and therefore it is beneficial for the organization to carry out automated material handling in the facility using AGV’s.

Keywords: fuzzy analytic hierarchy process (FAHP), material handling equipment, subjectiveness, triangular fuzzy number (TFN)

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Authors: Biniam Seifu Debelo, Bheema Lingaiah Thamineni, Hanumesh Kumar Dasari, Ahmed Ali Dawud

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Background: One of the most frequent neurological conditions in newborns is neonatal seizures, which may indicate severe neurological dysfunction. They may be caused by a broad range of problems with the central nervous system during or after pregnancy, infections, brain injuries, and/or other health conditions. These seizures may have very subtle or very modest clinical indications because patterns like oscillatory (spike) trains begin with relatively low amplitude and gradually increase over time. This becomes very challenging and erroneous if clinical observation is the primary basis for identifying newborn seizures. Objectives: In this study, a diagnosis system using deep convolutional neural networks is proposed to determine and classify the severity level of neonatal seizures using multichannel neonatal EEG data. Methods: Clinical multichannel EEG datasets were compiled using datasets from publicly accessible online sources. Various preprocessing steps were taken, including converting 2D time series data to equivalent waveform pictures. The proposed models underwent training, and their performance was evaluated. Results: The proposed CNN was used to perform binary classification with an accuracy of 92.6%, F1-score of 92.7%, specificity of 92.8%, and precision of 92.6%. To detect newborn seizures, this model is utilized. Using the proposed CNN model, multiclassification was performed with accuracy rates of 88.6%, specificity rates of 92.18%, F1-score rates of 85.61%, and precision rates of 88.9%. A multiclassification model is used to classify the severity level of neonatal seizures. The results demonstrated that the suggested strategy can assist medical professionals in making accurate diagnoses close to healthcare institutions. Conclusion: The developed system was capable of detecting neonatal seizures and has the potential to be used as a decision-making tool in resource-limited areas with a scarcity of expert neurologists.

Keywords: CNN, multichannel EEG, neonatal seizure, severity identification

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Authors: Emejeamara Francis

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The future of potentials wind energy applications within suburban/urban areas are currently faced with various problems. These include insufficient assessment of urban wind resource, and the effectiveness of commercial gust control solutions as well as unavailability of effective and cheaper valuable tools for scoping the potentials of urban wind applications within built-up environments. In order to achieve effective assessment of the potentials of urban wind installations, an estimation of the total energy that would be available to them were effective control systems to be used, and evaluating the potential power to be generated by the wind system is required. This paper presents a methodology of predicting the power generated by a wind system operating within an urban wind resource. This method was developed by using high temporal resolution wind measurements from eight potential sites within the urban and suburban environment as inputs to a vertical axis wind turbine multiple stream tube model. A relationship between the unsteady performance coefficient obtained from the stream tube model results and turbulence intensity was demonstrated. Hence, an analytical methodology for estimating the unsteady power coefficient at a potential turbine site is proposed. This is combined with analytical models that were developed to predict the wind speed and the excess energy (EEC) available in estimating the potential power generated by wind systems at different heights within a built environment. Estimates of turbulence intensities, wind speed, EEC and turbine performance based on the current methodology allow a more complete assessment of available wind resource and potential urban wind projects. This methodology is applied to four major UK cities namely Leeds, Manchester, London and Edinburgh and the potential to map the turbine performance at different heights within a typical urban city is demonstrated.

Keywords: small-scale wind, turbine power, urban wind energy, turbulence intensity, excess energy content

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Authors: Rani Fernandez

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As global concerns regarding environmental degradation and climate change intensify, the imperative for sustainable living has never been more critical. This research delves into the role of eco-products in everyday life as a pivotal strategy for achieving sustainability. The study investigates the awareness, adoption, and impact of eco-friendly products on individual and community levels. The research employs a mixed-methods approach, combining surveys, interviews, and case studies to explore consumer perceptions, behaviours, and motivations surrounding the use of eco-products. Additionally, life cycle assessments are conducted to evaluate the environmental footprint of selected eco-products, shedding light on their tangible contributions to sustainability. The findings reveal the diverse range of eco-products available in the market, from biodegradable packaging to energy-efficient appliances, and the extent to which consumers integrate these products into their daily routines. Moreover, the research examines the challenges and opportunities associated with widespread adoption, considering factors such as cost, accessibility, and efficacy. In addition to individual consumption patterns, the study investigates the broader societal impact of eco-product integration. It explores the potential for eco-products to drive systemic change by influencing supply chains, corporate practices, and government policies. The research highlights successful case studies of communities or businesses that have effectively incorporated eco-products, providing valuable insights into scalable models for sustainability. Ultimately, this research contributes to the discourse on sustainable living by elucidating the pivotal role of eco-products in shaping environmentally conscious behaviours. By understanding the dynamics of eco-product adoption, policymakers, businesses, and individuals can collaboratively work towards a more sustainable future. The implications of this study extend beyond academia, informing practical strategies for fostering a global shift towards sustainable consumption and production.

Keywords: eco-friendly, sustainablity, environment, climate change

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Authors: Shivani Thakur, Jasmin Dominguez Cervantes, Ahmed Zabiba, Fatima Zabiba, Sandhini Agarwal, Kamalpreet Kaur, Hussein Maatouk, Shae Chand, Omar Madriz, Tiffany Huang, Saloni Bansal

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Contraceptives are an effective public health achievement, allowing for family planning and reducing the risk of sexually transmitted diseases (STDs). California’s rural Central Valley has high rates of teenage pregnancy and STDs. Factors affecting contraceptive usage here may include religious concerns, financial issues, and regional variations in the accessibility and availability of contraceptives. The increasing population and diversity of the Central Valley make the understanding of the determinants of unintended pregnancy and STDs increasingly nuanced. Patients in California’s Central Valley were surveyed at 6 surgical clinics to assess attitudes toward contraceptives. The questionnaire consisted of demographics and 14 Likert-scale statements investigating patients’ feelings regarding contraceptives. Parametric and non-parametric analysis was performed on the Likert statements. A correlation matrix for the Likert-scale statements was used to evaluate the strength of the relationship between each question. 76 patients aged 18-75 years completed the questionnaire. 90% of the participants were female, 76% Hispanic, 36% married, 44% with an income range between 30-60K, and 83% were between childbearing ages. 60% of participants stated they are currently using or had used some type of contraceptive. 25% of participants had at least one unplanned pregnancy. The most common type of contraceptives used were oral contraceptives(28%) and condoms(38%). The top reasons for patients’ contraceptive usage were: prevention of pregnancy (72%), safe sex/prevention of STDs (32%), and regulation of menstrual cycle (19%). Further analysis of Likert responses revealed that contraception usage increased due to approval of contraceptives (x̄=3.98, σ =1.02); partner approval of contraceptives (x̄=3.875, σ =1.16); and reduced anxiety about pregnancy (x̄=3.875, σ =1.23). Younger females (18-34 years old) agreed more with the statement that the cost of contraceptive supplies is too expensive than older females (35-75 years old), (x̄=3.2, σ = 1.4 vs x̄=2.8, σ =1.3, p<0.05). Younger females (44%) were also more likely to use short-acting contraceptive methods (oral and male condoms) compared to older females (64%) who use long-acting methods (implants/ intrauterine devices). 51% of Hispanic females were using some type of contraceptive. Of those Hispanic females who do not use contraceptives, 33% stated having no children, and all plan to have at least one child in the future. 35% of participants had a bachelor's degree. Those with bachelor’s degrees were more likely to use contraceptives, 58% vs 51%, p<0.05, and less likely to have unplanned pregnancy, 50% vs. 12%, p<0.01. There is increasing use and awareness among patients in rural settings concerning contraceptives. Our finding shows that younger women and women with higher educational attainment tend to have more positive attitudes towards the use of contraceptives. This work gives physicians an understanding of patients’ concerns about contraceptive methods and offers insight into culturally competent intervention programs that respect individual values.

Keywords: contraceptives, public health, rural california, women of child baring age

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Authors: Hossein Afzali

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Increasingly, decision analytic models are used to inform decisions about whether or not to publicly fund new health technologies. It is well noted that the accuracy of model predictions is strongly influenced by the appropriateness of model structuring. However, there is relatively inadequate methodological guidance surrounding this issue in guidelines developed by national funding bodies such as the Australian Pharmaceutical Benefits Advisory Committee (PBAC) and The National Institute for Health and Care Excellence (NICE) in the UK. This presentation aims to discuss issues around model structuring within decision making with a focus on (1) the need for a transparent and evidence-based model structuring process to inform the most appropriate set of structural aspects as the base case analysis; (2) the need to characterise structural uncertainty (If there exist alternative plausible structural assumptions (or judgements), there is a need to appropriately characterise the related structural uncertainty). The presentation will provide an opportunity to share ideas and experiences on how the guidelines developed by national funding bodies address the above issues and identify areas for further improvements. First, a review and analysis of the literature and guidelines developed by PBAC and NICE will be provided. Then, it will be discussed how the issues around model structuring (including structural uncertainty) are not handled and justified in a systematic way within the decision-making process, its potential impact on the quality of public funding decisions, and how it should be presented in submissions to national funding bodies. This presentation represents a contribution to the good modelling practice within the decision-making process. Although the presentation focuses on the PBAC and NICE guidelines, the discussion can be applied more widely to many other national funding bodies that use economic evaluation to inform funding decisions but do not transparently address model structuring issues e.g. the Medical Services Advisory Committee (MSAC) in Australia or the Canadian Agency for Drugs and Technologies in Health.

Keywords: decision-making process, economic evaluation, good modelling practice, structural uncertainty

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Authors: Ahmad AlAbdullah, Ali AlQallaf, Mahdi Hussain, Mohammed AlAttar, Salman Ashknani, Magdy Helal

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We study the effectiveness of the parking service provided at Kuwaiti commercial malls and explore potential problems and feasible improvements. Commercial malls are important to Kuwaitis as the entertainment and shopping centers due to the lack of other alternatives. The difficulty and relatively long times wasted in finding a parking spot at the mall are real annoyances. We applied queuing analysis to one of the major malls that offer paid-parking (1040 parking spots) in addition to free parking. Patrons of the mall usually complained of the traffic jams and delays at entering the paid parking (average delay to park exceeds 15 min for about 62% of the patrons, while average time spent in the mall is about 2.6 hours). However, the analysis showed acceptable service levels at the check-in gates of the parking garage. Detailed review of the vehicle movement at the gateways indicated that arriving and departing cars both had to share parts of the gateway to the garage, which caused the traffic jams and delays. A simple comparison we made indicated that the largest commercial mall in Kuwait does not suffer such parking issues, while other smaller, yet important malls do, including the one we studied. It was suggested that well-designed inlets and outlets of that gigantic mall permitted smooth parking despite being totally free and mall is the first choice for most people for entertainment and shopping. A simulation model is being developed for further analysis and verification. Simulation can overcome the mathematical difficulty in using non-Poisson queuing models. The simulation model is used to explore potential changes to the parking garage entrance layout. And with the inclusion of the drivers’ behavior inside the parking, effectiveness indicators can be derived to address the economic feasibility of extending the parking capacity and increasing service levels. Outcomes of the study are planned to be generalized as appropriate to other commercial malls in Kuwait

Keywords: commercial malls, parking service, queuing analysis, simulation modeling

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Authors: Songdi Li, Louise Spry, Tony Woodall

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Nowadays, Corporate Social responsibility (CSR) is becoming a buzz word, and more and more academics are putting efforts on CSR studies. It is believed that CSR could influence Corporate Reputation (CR), and they hold a favourable view that CSR leads to a positive CR. To be specific, the CSR related activities in the reputational context have been regarded as ways that associate to excellent financial performance, value creation, etc. Also, it is argued that CSR and CR are two sides of one coin; hence, to some extent, doing CSR is equal to establishing a good reputation. Still, there is no consensus of the CSR-CR relationship in the literature; thus, a systematic literature review is highly in need. This research conducts a systematic literature review with both bibliometric and content analysis. Data are selected from English language sources, and academic journal articles only, then, keyword combinations are applied to identify relevant sources. Data from Scopus and WoS are gathered for bibliometric analysis. Scopus search results were saved in RIS and CSV formats, and Web of Science (WoS) data were saved in TXT format and CSV formats in order to process data in the Bibexcel software for further analysis which later will be visualised by the software VOSviewer. Also, content analysis was applied to analyse the data clusters and the key articles. In terms of the topic of CSR-CR, this literature review with bibliometric analysis has made four achievements. First, this paper has developed a systematic study which quantitatively depicts the knowledge structure of CSR and CR by identifying terms closely related to CSR-CR (such as ‘corporate governance’) and clustering subtopics emerged in co-citation analysis. Second, content analysis is performed to acquire insight on the findings of bibliometric analysis in the discussion section. And it highlights some insightful implications for the future research agenda, for example, a psychological link between CSR-CR is identified from the result; also, emerging economies and qualitative research methods are new elements emerged in the CSR-CR big picture. Third, a multidisciplinary perspective presents through the whole bibliometric analysis mapping and co-word and co-citation analysis; hence, this work builds a structure of interdisciplinary perspective which potentially leads to an integrated conceptual framework in the future. Finally, Scopus and WoS are compared and contrasted in this paper; as a result, Scopus which has more depth and comprehensive data is suggested as a tool for future bibliometric analysis studies. Overall, this paper has fulfilled its initial purposes and contributed to the literature. To the author’s best knowledge, this paper conducted the first literature review of CSR-CR researches that applied both bibliometric analysis and content analysis; therefore, this paper achieves its methodological originality. And this dual approach brings advantages of carrying out a comprehensive and semantic exploration in the area of CSR-CR in a scientific and realistic method. Admittedly, its work might exist subjective bias in terms of search terms selection and paper selection; hence triangulation could reduce the subjective bias to some degree.

Keywords: corporate social responsibility, corporate reputation, bibliometric analysis, software program

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Authors: A. Badran, M. Hollocks, H. Markus

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Background: Common risk factors for cardiovascular disease are associated with age-related cognitive decline. There has been much interest in treating modifiable cardiovascular risk factors in the hope of reducing cognitive decline. However, there is currently no validated neuropsychological test to assess the subclinical cognitive effects of vascular risk. The Brief Memory and Executive Test (BMET) is a clinical screening tool, which was originally designed to be sensitive and specific to Vascular Cognitive Impairment (VCI), an impairment characterised by decline in frontally-mediated cognitive functions (e.g. Executive Function and Processing Speed). Objective: To cross-sectionally assess the validity of the BMET as a measure of the subclinical effects of vascular risk on cognition, in an otherwise healthy elderly cohort. Methods: Data from 346 participants (57 ± 10 years) without major neurological or psychiatric disorders were included in this study, gathered as part of a previous multicentre validation study for the BMET. Framingham Vascular Age was used as a surrogate measure of vascular risk, incorporating several established risk factors. Principal Components Analysis of the subtests was used to produce common constructs: an index for Memory and another for Executive Function/Processing Speed. Univariate General Linear models were used to relate Vascular Age to performance on Executive Function/Processing Speed and Memory subtests of the BMET, adjusting for Age, Premorbid Intelligence and Ethnicity. Results: Adverse vascular risk was associated with poorer performance on both the Memory and Executive Function/Processing Speed indices, adjusted for Age, Premorbid Intelligence and Ethnicity (p=0.011 and p<0.001, respectively). Conclusions: Performance on the BMET reflects the subclinical effects of vascular risk on cognition, in age-related cognitive decline. Vascular risk is associated with decline in both Executive Function/Processing Speed and Memory groups of subtests. Future studies are needed to explore whether treating vascular risk factors can effectively reduce age-related cognitive decline.

Keywords: age-related cognitive decline, vascular cognitive impairment, subclinical cerebrovascular disease, cognitive aging

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Authors: Wissal Ben Arfi, Lubica Hikkerova, Jean-Michel Sahut

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This study examines interfirm networks in the digital transformation era, and in particular, how tacit knowledge codification affects innovation success within digital platforms. Hence, one of the most important features of digital transformation and innovation process outcomes is the emergence of digital platforms, as an interfirm network, at the heart of open innovation. This research aims to illuminate how digital platforms influence inter-organizational innovation through virtual team interactions and knowledge sharing practices within an interfirm network. Consequently, it contributes to the respective strategic management literature on new product development (NPD), open innovation, industrial management, and its emerging interfirm networks’ management. The empirical findings show, on the one hand, that knowledge conversion may be enhanced, especially by the socialization which seems to be the most important phase as it has played a crucial role to hold the virtual team members together. On the other hand, in the process of socialization, the tacit knowledge codification is crucial because it provides the structure needed for the interfirm network actors to interact and act to reach common goals which favor the emergence of open innovation. Finally, our results offer several conditions necessary, but not always sufficient, for interfirm managers involved in NPD and innovation concerning strategies to increasingly shape interconnected and borderless markets and business collaborations. In the digital transformation era, the need for adaptive and innovative business models as well as new and flexible network forms is becoming more significant than ever. Supported by technological advancements and digital platforms, companies could benefit from increased market opportunities and creating new markets for their innovations through alliances and collaborative strategies, as a mode of reducing or eliminating uncertainty environments or entry barriers. Consequently, an efficient and well-structured interfirm network is essential to create network capabilities, to ensure tacit knowledge sharing, to enhance organizational learning and to foster open innovation success within digital platforms.

Keywords: interfirm networks, digital platform, virtual teams, open innovation, knowledge sharing

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Authors: K. R. Roopesh Bharatwaj, Avinash Maharana, Favour Tobi Aborisade, Roger Young

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Presently, there are few cases of complete automation of drones and its allied intelligence capabilities. In essence, the potential of the drone has not yet been fully utilized. This paper presents feasible methods to build an intelligent drone with smart capabilities such as self-driving, and obstacle avoidance. It does this through advanced Reinforcement Learning Techniques and performs object detection using latest advanced algorithms, which are capable of processing light weight models with fast training in real time instances. For the scope of this paper, after researching on the various algorithms and comparing them, we finally implemented the Deep-Q-Networks (DQN) algorithm in the AirSim Simulator. In future works, we plan to implement further advanced self-driving and object detection algorithms, we also plan to implement voice-based speech recognition for the entire drone operation which would provide an option of speech communication between users (People) and the drone in the time of unavoidable circumstances. Thus, making drones an interactive intelligent Robotic Voice Enabled Service Assistant. This proposed drone has a wide scope of usability and is applicable in scenarios such as Disaster management, Air Transport of essentials, Agriculture, Manufacturing, Monitoring people movements in public area, and Defense. Also discussed, is the entire drone communication based on the satellite broadband Internet technology for faster computation and seamless communication service for uninterrupted network during disasters and remote location operations. This paper will explain the feasible algorithms required to go about achieving this goal and is more of a reference paper for future researchers going down this path.

Keywords: convolution neural network, natural language processing, obstacle avoidance, satellite broadband technology, self-driving

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Authors: Nicholas C. Rose, Christopher D. Spicer

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The regeneration of damaged or diseased tissues would provide an invaluable therapeutic tool in biological research and medicine. Cells must be provided with a number of different biochemical signals in order to form mature tissue through complex signaling networks that are difficult to recreate in synthetic materials. The ability to attach and detach bioactive proteins from material in an iterative and dynamic manner would therefore present a powerful way to mimic natural biochemical signaling cascades for tissue growth. We propose to reversibly attach these bioactive proteins using ortho-boronoimine (oBI) linkages and related derivatives formed by the reaction of an ortho-boronobenzaldehyde with a nucleophilic amine derivative. To enable the use of oBIs for biomaterial modification, we have studied binding and cleavage processes with precise detail in the context of small molecule models. A panel of oBI complexes has been synthesized and screened using a novel Förster resonance energy transfer (FRET) assay, using a cyanine dye FRET pair (Cy3 and Cy5), to identify the most reactive boron-aldehyde/amine nucleophile pairs. Upon conjugation of the dyes, FRET occurs under Cy3 excitation and the resultant ratio of Cy3:Cy5 emission directly correlates to conversion. Reaction kinetics and equilibria can be accurately quantified for reactive pairs, with dissociation constants of oBI derivatives in water (KD) found to span 9-orders of magnitude (10⁻²-10⁻¹¹ M). These studies have provided us with a better understanding of oBI linkages that we hope to exploit to reversibly attach bioconjugates to materials. The long-term aim of the project is to develop a modular biomaterial platform that can be used to help combat chronic diseases such as osteoarthritis, heart disease, and chronic wounds by providing cells with potent biological stimuli for tissue engineering.

Keywords: dynamic, bioconjugation, bornoimine, rapid, physiological

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Authors: Samir Ali-arous, Mohamed Beddane, Khaled Djelouah

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This study investigated the insect diversity of olive (Olea europaea Linnaeus (Oleaceae)) groves grown in an arid climate in Algeria. In this context, several sampling methods were used within two orchards differently managed. Fifty arthropod species belonging to diverse orders and families were recorded. Hymenopteran species were quantitatively the most abundant, followed by species associated with Heteroptera, Aranea, Coleoptera and Homoptera orders. Regarding functional feeding groups, phytophagous species were dominant in the weeded and the unweeded orchard; however, higher abundance was recorded in the weeded site. Predators were ranked second, and pollinators were more frequent in the unweeded olive orchard. Two-factor Anova with repeated measures had revealed high significant effect of the weed management system, measures repetition and interaction with measurement repetition on arthropod’s abundances (P < 0.05). Likewise, generalized linear models showed that N/S ratio varied significantly between the two weed management approaches, in contrast, the remaining diversity indices including the Shannon index H’ had no significant correlation. Moreover, diversity parameters of arthropod’s communities in each agro-system highlighted multiples significant correlations (P <0.05). Rarefaction and extrapolation (R/E) sampling curves, evidenced that the survey and monitoring carried out in both sites had a optimum coverage of entomofauna present including scarce and transient species. Overall, calculated diversity and similarity indices were greater in the unweeded orchard than in the weeded orchard, demonstrating spontaneous flora's key role in entomofaunal diversity. Principal Component Analysis (PCA) has defined correlations between arthropod’s abundances and naturally occurring plants in olive orchards, including beneficials.

Keywords: Algeria, olive, insects, diversity, wild plants

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Authors: Shreya Saxena

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Background: Choledocholithiasis is a common complication of gallstone disease. Risk scoring systems exist to guide the need for further imaging or endoscopy in managing choledocholithiasis. We completed an audit to review the American Society for Gastrointestinal Endoscopy (ASGE) scoring system for prediction and management of choledocholithiasis against the current practice at a tertiary hospital to assess its utility in resource optimisation. We have now conducted a cost focused sub-analysis on patients categorized high-risk for choledocholithiasis according to the guidelines to determine any associated cost benefits. Method: Data collection from our prior audit was used to retrospectively identify thirteen patients considered high-risk for choledocholithiasis. Their ongoing management was mapped against the guidelines. Individual costs for the key investigations were obtained from our hospital financial data. Total cost for the different management pathways identified in clinical practice were calculated and compared against predicted costs associated with recommendations in the guidelines. We excluded the cost of laparoscopic cholecystectomy and considered a set figure for per day hospital admission related expenses. Results: Based on our previous audit data, we identified a77% positive predictive value for the ASGE risk stratification tool to determine patients at high-risk of choledocholithiasis. 47% (6/13) had an magnetic resonance cholangiopancreatography (MRCP) prior to endoscopic retrograde cholangiopancreatography (ERCP), whilst 53% (7/13) went straight for ERCP. The average length of stay in the hospital was 7 days, with an additional day and cost of £328.00 (£117 for ERCP) for patients awaiting an MRCP prior to ERCP. Per day hospital admission was valued at £838.69. When calculating total cost, we assumed all patients had admission bloods and ultrasound done as the gold standard. In doing an MRCP prior to ERCP, there was a 130% increase in cost incurred (£580.04 vs £252.04) per patient. When also considering hospital admission and the average length of stay, it was an additional £1166.69 per patient. We then calculated the exact costs incurred by the department, over a three-month period, for all patients, for key investigations or procedures done in the management of choledocholithiasis. This was compared to an estimate cost derived from the recommended pathways in the ASGE guidelines. Overall, 81% (£2048.45) saving was associated with following the guidelines compared to clinical practice. Conclusion: MRCP is the most expensive test associated with the diagnosis and management of choledocholithiasis. The ASGE guidelines recommend endoscopy without an MRCP in patients stratified as high-risk for choledocholithiasis. Our audit that focused on assessing the utility of the ASGE risk scoring system showed it to be relatively reliable for identifying high-risk patients. Our cost analysis has shown significant cost savings per patient and when considering the average length of stay associated with direct endoscopy rather than an additional MRCP. Part of this is also because of an increased average length of stay associated with waiting for an MRCP. The above data supports the ASGE guidelines for the management of high-risk for choledocholithiasis patients from a cost perspective. The only caveat is our small data set that may impact the validity of our average length of hospital stay figures and hence total cost calculations.

Keywords: cost-analysis, choledocholithiasis, risk stratification tool, general surgery

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Authors: Varsha Puri, Sharon Hudson, Ian Kim

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Background: Incest-related childhood sexual abuse (IRCSA) is challenging to study due to the shame and secrecy experienced by its survivors. Ramifications of IRCSA worsen when it is unidentified, and interventions are not made. IRCSA perspectives are essential for future prevention and intervention strategies. However, there is limited understanding of this population’s experiences, perspectives, and long-term struggles. To date, research for IRCSA has utilized data from treatment programs and qualitative research with cohorts of 10-20 people, much of the data is from 10-40 years prior. Methods. In June 2018, an anonymous online survey was posted to multiple social media sites (e.g., Facebook IRCSA groups) and sexual abuse resource sites. Survey responses were collected for a year. The survey collected non-identifying demographics, IRCSA experiences, and outcomes data. Results: We obtained 1310 completed surveys. Demographics of all ages, racial backgrounds, financial backgrounds, and genders were obtained; the majority identified as white (81%) and female (76%). Childhood sexual abuse (CSA) started before the age of 6 in 49% and was endured for more than one year in 84% of respondents, and 39% reported ten or more years of abuse. CSA by multiple perpetrators occurred in 58%, while 8% had ten or more perpetrators. CSA by perpetrators under 21 years old was reported by 46%. Female perpetrators were reported by 28% of respondents. Fathers were the highest reported sexual abusers at 60%, and mothers were reported at 17%. Only 16% reported that at least one of their perpetrators was prosecuted for sexual abuse of a minor. Respondents confirmed that 54% of the time, they informed an adult of the abuse; only 2% agreed that “an intervention was made by the family that protected me.” A majority reported that IRCSA has negatively impacted their intimate/sexual relationships (96%) and mental health (96%). A majority reported negative impacts on biological family relationships (88%), physical health (73%), finances (59%), educational achievement (57%), and employment (56%). When asked about suffering from addiction, 85% of respondents answered yes. Prevention strategies selected most by respondents include early school education around CSA prevention (67%), removing the statute of limitations for reporting CSA (69%), and improved laws protecting IRCSA survivors (63%). Conclusion: The data document that IRCSA can be pervasive, and the dearth of intervention and support for survivors have major lasting impacts. Survivors have a unique and valuable perspective on what interventions are needed to prevent IRCSA and support survivors; their voice has long been unheard in crafting prevention and intervention policies and services. These results thus provide an important call to action from these critical stakeholders. Pediatricians should recognize that perpetrators can be pediatric patients, women, and parents. Pediatricians can advocate for more early CSA prevention education and policy changes that remove the statute of limitations for reporting CSA.

Keywords: incest, childhood sexual abuse, incest-related childhood sexual abuse, incest survivor

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Authors: Indunil Jayatilake, Warna Karunasena

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Fiber Reinforced Polymer (FRP) composites enjoy an array of applications ranging from aerospace, marine and military to automobile, recreational and civil industry due to their outstanding properties. A structural glass fiber reinforced polymer (GFRP) composite sandwich panel made from E-glass fiber skin and a modified phenolic core has been manufactured in Australia for civil engineering applications. One of the major mechanisms of damage in FRP composites is skin-core debonding. The presence of debonding is of great concern not only because it severely affects the strength but also it modifies the dynamic characteristics of the structure, including natural frequency and vibration modes. This paper deals with the investigation of the dynamic characteristics of a GFRP beam with single and multiple debonding by finite element based numerical simulations and analyses using the STRAND7 finite element (FE) software package. Three-dimensional computer models have been developed and numerical simulations were done to assess the dynamic behavior. The FE model developed has been validated with published experimental, analytical and numerical results for fully bonded as well as debonded beams. A comparative analysis is carried out based on a comprehensive parametric investigation. It is observed that the reduction in natural frequency is more affected by single debonding than the equally sized multiple debonding regions located symmetrically to the single debonding position. Thus it is revealed that a large single debonding area leads to more damage in terms of natural frequency reduction than isolated small debonding zones of equivalent area, appearing in the GFRP beam. Furthermore, the extents of natural frequency shifts seem mode-dependent and do not seem to have a monotonous trend of increasing with the mode numbers.

Keywords: debonding, dynamic response, finite element modelling, novel FRP beams

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Authors: Suin Seo, Sung-Il Cho

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Background: The use of mobile apps for smoking cessation has grown exponentially in recent years. Yet, there were limited researches which evaluated the quality of smoking cessation apps to our knowledge. In most cases, a clinical practice guideline which is focused on clinical physician was used as an evaluation tool. Objective: The objective of this study was to develop a user-centered measure for quality of mobile smoking cessation apps. Methods: A literature search was conducted to identify articles containing explicit smoking cessation guideline for smoker published until January 2018. WHO’s guide for tobacco users to quit was adopted for evaluation tool which assesses smoker-oriented contents of smoking cessation apps. Compared to the clinical practice guideline, WHO guideline was designed for smokers (non-specialist). On the basis of existing criteria which was developed based on 2008 clinical practice guideline for Treating Tobacco Use and Dependence, evaluation tool was modified and developed by an expert panel. Results: There were five broad categories of criteria that were identified including five objective quality scales: enhancing motivation, assistance with a planning and making quit attempts, preparation for relapse, self-efficacy, connection to smoking. Enhancing motivation and assistance with planning and making quit attempts were similar to contents of clinical practice guideline, but preparation for relapse, self-efficacy and connection to smoking (environment or habit which reminds of smoking) only existed on WHO guideline. WHO guideline had more user-centered elements than clinical guideline. Especially, self-efficacy is the most important determinant of behavior change in accordance with many health behavior change models. With the WHO guideline, it is now possible to analyze the content of the app in the light of a health participant, not a provider. Conclusion: The WHO guideline evaluation tool is a simple, reliable and smoker-centered tool for assessing the quality of mobile smoking cessation apps. It can also be used to provide a checklist for the development of new high-quality smoking cessation apps.

Keywords: smoking cessation, evaluation, mobile application, WHO, guideline

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Authors: Teklay Tesfay, Gebreyesus Brhane Tesfahunegn, Abadi Berhane, Selemawit Girmay

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Adjusting the proper sowing date of a crop at a particular location with a changing climate is an essential management option to maximize crop yield. However, determining the optimum sowing date for rainfed maize production through field experimentation requires repeated trials for many years in different weather conditions and crop management. To avoid such long-term experimentation to determine the optimum sowing date, crop models such as AquaCrop are useful. Therefore, the overall objective of this study was to evaluate the performance of AquaCrop model in simulating maize productivity under varying sowing dates. A field experiment was conducted for two consecutive cropping seasons by deploying four maize seed sowing dates in a randomized complete block design with three replications. Input data required to run this model are stored as climate, crop, soil, and management files in the AquaCrop database and adjusted through the user interface. Observed data from separate field experiments was used to calibrate and validate the model. AquaCrop model was validated for its performance in simulating the green canopy and aboveground biomass of maize for the varying sowing dates based on the calibrated parameters. Results of the present study showed that there was a good agreement (an overall R2 =, Ef= d= RMSE =) between measured and simulated values of the canopy cover and biomass yields. Considering the overall values of the statistical test indicators, the performance of the model to predict maize growth and biomass yield was successful, and so this is a valuable tool help for decision-making. Hence, this calibrated and validated model is suggested to use for determining optimum maize crop sowing date for similar climate and soil conditions to the study area, instead of conducting long-term experimentation.

Keywords: AquaCrop model, calibration, validation, simulation

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Authors: Olasunkanmi Olapeju

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A large chunk of global population are not yet connected to water borne faecal management systems that rely on flush mechanisms and sewers networks that are linked with a central treatment plant. Only about 10% of sub-Saharan African countries are connected to central sewage systems. In Nigeria, majority of the population do not only depend on on-plot sanitation systems, a huge chunk do not also have access to safe and improved toilets. Apart from the organizational challenges and technical capacity, the other major factors that account for why faecal waste management is yet unimproved in developing countries are faulty planning frameworks that fail to maintain balance between urbanization dynamics and infrastructures, and misconceptions about what modern sanitation is all about. In most cases, the quest to implement developmental patterns that integrate modern sewers based sanitation systems have huge financial and political costs. Faecal waste management in poor countries largely lacks the needed political attention and budgetary prioritization. Yet, the on-plot sanitation systems being mainly relied upon the need to be managed in a manner that is sustainable and healthy, pending when development would embrace a more sustainable off-site central sewage system. This study is aimed at investigating existing strategies for managing on-plot sanitation systems’ faecal waste in Ogun state, Nigeria, with the aim of recommending sustainable sanitation management systems. The study adopted the convergent parallel variant of the mixed-mode technique, which involves the adoption of both quantitative and qualitative method of data collection. Adopting a four-level multi-stage approach, which is inclusive of all political divisions in the study area, a total of 330 questionnaires were respectively administered in the study area. Moreover, the qualitative data adopted the purposive approach in scoping down to 33 key informants. SPSS software (Version 22.0) was employed for descriptively analysis. The study shows that about 52% of households adopt the non-recovery management (NRM) means of burying their latrines with sand sludge shrinkage with chemicals such as carbides. The dominance of the non-recovery management means seriously constrains the quest for faecal resource recovery. Essentially, the management techniques adopted by households depend largely on the technology of their sanitary containments, emptying means available, the ability of households to pay for the cost of emptying, and the social acceptability of the reusability of faecal waste, which determines faecal resource recoverability. The study suggests that there is a need for municipal authorities in the study area to urgently intervene in the sanitation sector and consider it a key element of the planning process. There is a need for a comprehensive plan that would ensure a seamless transition to the adoption of a modern sanitation management system.

Keywords: faecal, management, planning, waste, sanitation, sustainability

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Authors: Antonios Paraskevas, Michael Madas

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For a university to maintain its international competitiveness in education, it is essential to recruit qualitative academic staff as it constitutes its most valuable asset. This selection demonstrates a significant role in achieving strategic objectives, particularly by emphasizing a firm commitment to the exceptional student experience and innovative teaching and learning practices of high quality. In this vein, the appropriate selection of academic staff establishes a very important factor of competitiveness, efficiency and reputation of an academic institute. Within this framework, our work demonstrates a comprehensive methodological concept that emphasizes the multi-criteria nature of the problem and how decision-makers could utilize our approach in order to proceed to the appropriate judgment. The conceptual framework introduced in this paper is built upon a hybrid neutrosophic method based on the Neutrosophic Analytical Hierarchy Process (N-AHP), which uses the theory of neutrosophy sets and is considered suitable in terms of a significant degree of ambiguity and indeterminacy observed in the decision-making process. To this end, our framework extends the N-AHP by incorporating the Neutrosophic Delphi Method (N-DM). By applying the N-DM, we can take into consideration the importance of each decision-maker and their preferences per evaluation criterion. To the best of our knowledge, the proposed model is the first which applies the Neutrosophic Delphi Method in the selection of academic staff. As a case study, it was decided to use our method for a real problem of academic personnel selection, having as the main goal to enhance the algorithm proposed in previous scholars’ work, and thus taking care of the inherent ineffectiveness which becomes apparent in traditional multi-criteria decision-making methods when dealing with situations alike. As a further result, we prove that our method demonstrates greater applicability and reliability when compared to other decision models.

Keywords: multi-criteria decision making methods, analytical hierarchy process, delphi method, personnel recruitment, neutrosophic set theory

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Authors: Jorge Luis Morales Romero, Enrique Murillo Othón

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Business to business (B2B) relationships generally go beyond a purely profit-based result, with firms seeking to maintain a relationship for many years because a breakup or getting a new supplier can be very costly. Therefore, identifying the factors which determine a successful relationship in the long term is of great interest to companies. That is why their reputation and the brand image that customers have of them are among the main factors that can achieve a successful relationship; Because of the positive effect which is driven by the client’s loyalty. Additionally, the perception that a customer may have about a brand is different when it is related to goods or to services. Thereby, they create in their minds their own brand image of it based on the past experiences they have had; Thus, a positive relationship is established between goods-related brand image, service-related brand image, and customer loyalty. The present investigation examines the boundary conditions of said relationship by testing the moderating effects of trust, commitment, and relationship value in a B2B environment. All the variables were tested independently as moderators for service-related brand image/loyalty and for goods-related brand image/loyalty, as they are assumed to be separate variables. Survey data was collected through interviews with customers that have both a product-buying relationship and a service relationship with a global B2B brand of healthcare equipment operating in the Mexican healthcare market. Interviewed respondents were either the user or the purchasing manager and/or the responsible for the equipment maintenance for the customer organization. Hence, they were appropriate informants regarding the B2B relationship with this healthcare brand. The moderation models were estimated using the PROCESS macro for the Statistical Package for the Social Sciences Software (SPSS). Results show statistical evidence that both Relationship Value and Trust are significant moderators for the service-related brand image/loyalty relation but not significant for the goods-related brand/loyalty relation. On the other hand, Commitment results in a significant moderator for the goods-related brand/loyalty relation but is not significant for the service-related brand image/loyalty relation.

Keywords: commitment, trust, relationship value, loyalty, B2B, moderator

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Authors: Balbasatu Ibrahim

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In the 19th century, Hausaland an Islamic revolution known as the Sokoto Jihad took place that led to the establishment of the Sokoto Caliphate in 1804 under the leadership of the famous Sheik Uthman Bn Fodiye. Before the Jihad movement in Hausaland (now Northern Nigeria), women were left in ignorance and were used and dumped like old kitchen utensils. The sheik and his followers did their best to actualising women’s right to education by using their female family members as role models who were highly educated and renowned scholars. After the Jihad with the establishment of an Islamic state, the women scholars initiated different strategies to teach the generality of the women. The most efficient strategy was the ‘Yantaru Movement founded by Nana Asma’u the daughter of Sheikh Uthman Bn Fodiye in collaboration with her sisters around 1840. The ‘Yantaru movement is a women’s educational movement aimed at enlightening women in rural and urban areas. The move helped in massively mobilizing women for education. In addition to town pupils, women from villages and throughout the nooks and crannies of metropolitan Sokoto participated in the movement in the search for knowledge. Thus, the birth of the ‘Yantaru system of women’s education. The ‘Yantaru operates the three-tier system at village, town and the metropolitan capital of Sokoto. ‘Yantaru functions include imparting knowledge to elderly women and young girls. Step down enlightenment program on returning home. The most effective medium of communication in the ‘Yantaru movement was through poetry where scholars composed educational poems which were memorized by the ‘Yantaru, who on return recite it to fellow women at home. Through this system, many women were educated. This paper translated and examines one of such educative poems written by the second leader of the ‘Yantaru Movement Maryam Bn Uthman Bn Fodiye in 1855.

Keywords: English, Hausa language, public enlightenment, Maryam Bint Uthman Ibn Foduye

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Authors: Ghufran Ahmed, Muhammad Osama Siddiqui, Shahbaz Siddiqui, Rauf Ahmad Shams Malick, Faisal Khan, Mubashir Khan

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In this paper, a machine learning-based approach for early prediction of diseases in cows is proposed. Different ML algos are applied to extract useful patterns from the available dataset. Technology has changed today’s world in every aspect of life. Similarly, advanced technologies have been developed in livestock and dairy farming to monitor dairy cows in various aspects. Dairy cattle monitoring is crucial as it plays a significant role in milk production around the globe. Moreover, it has become necessary for farmers to adopt the latest early prediction technologies as the food demand is increasing with population growth. This highlight the importance of state-ofthe-art technologies in analyzing how important technology is in analyzing dairy cows’ activities. It is not easy to predict the activities of a large number of cows on the farm, so, the system has made it very convenient for the farmers., as it provides all the solutions under one roof. The cattle industry’s productivity is boosted as the early diagnosis of any disease on a cattle farm is detected and hence it is treated early. It is done on behalf of the machine learning output received. The learning models are already set which interpret the data collected in a centralized system. Basically, we will run different algorithms on behalf of the data set received to analyze milk quality, and track cows’ health, location, and safety. This deep learning algorithm draws patterns from the data, which makes it easier for farmers to study any animal’s behavioral changes. With the emergence of machine learning algorithms and the Internet of Things, accurate tracking of animals is possible as the rate of error is minimized. As a result, milk productivity is increased. IoT with ML capability has given a new phase to the cattle farming industry by increasing the yield in the most cost-effective and time-saving manner.

Keywords: IoT, machine learning, health care, dairy cows

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Authors: N. Ismail, O. Thammajinda, U. Thongpanya

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Games-based learning (GBL) has become increasingly important in teaching and learning. This paper explains the first two phases (analysis and design) of a GBL development project, ending up with a prototype design based on students’ and teachers’ perceptions. The two phases are part of a full cycle GBL project aiming to help secondary school students in Thailand in their study of Comprehensive Sex Education (CSE). In the course of the study, we invited 1,152 students to complete questionnaires and interviewed 12 secondary school teachers in focus groups. This paper found that GBL can serve students in their learning about CSE, enabling them to gain understanding of their sexuality, develop skills, including critical thinking skills and interact with others (peers, teachers, etc.) in a safe environment. The objectives of this paper are to outline the development of GBL variables from the research question(s) into the developers’ flow chart, to be responsive to the GBL beneficiaries’ preferences and expectations, and to help in answering the research questions. This paper details the steps applied to generate GBL variables that can feed into a game flow chart to develop a GBL prototype. In our approach, we detailed two models: (1) Game Elements Model (GEM) and (2) Game Object Model (GOM). There are three outcomes of this research – first, to achieve the objectives and benefits of GBL in learning, game design has to start with the research question(s) and the challenges to be resolved as research outcomes. Second, aligning the educational aims with engaging GBL end users (students) within the data collection phase to inform the game prototype with the game variables is essential to address the answer/solution to the research question(s). Third, for efficient GBL to bridge the gap between pedagogy and technology and in order to answer the research questions via technology (i.e. GBL) and to minimise the isolation between the pedagogists “P” and technologist “T”, several meetings and discussions need to take place within the team.

Keywords: games-based learning, engagement, pedagogy, preferences, prototype

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