Search results for: computerized decision support systems

Authors: Wen Liu

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With the rapid progress of modern cities, the railway construction must be developing quickly in China. As a typical high-density country, shopping center on the subway should be one important factor during the process of urban development. The paper discusses the influence of the layout of shopping center on the subway, and put it in the time and space’s axis of Shanghai urban development. We use the digital technology to establish the database of relevant information. And then get the change role about shopping center on subway in Shanghaiby the Kernel density estimate. The result shows the development of shopping center on subway has a relationship with local economic strength, population size, policy support, and city construction. And the suburbanization trend of shopping center would be increasingly significant. By this case research, we could see the Kernel density estimate is an efficient analysis method on the spatial layout. It could reveal the characters of layout form of shopping center on subway in essence. And it can also be applied to the other research of space form.

Keywords: Shanghai, shopping center on the subway, layout form, Kernel density estimate

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Authors: Babak Forouraghi

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A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of the flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on the spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts, as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with an attention mechanism. In previous works on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work, with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on the presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: machine learning, classification and regression, gene circuit design, bidirectional transformers

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Authors: Neelamshobha Nirala, R. Periyasamy, Awanish Kumar

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Diabetes is a metabolic disorder and with the increase of global prevalence of diabetes, cardiovascular diseases and mortality related to diabetes has also increased. Diabetes causes the increase of arterial stiffness by elusive hormonal and metabolic abnormalities. We used photoplethysmograph (PPG), a simple non-invasive method to study the change in arterial stiffness due to diabetes. Toe PPG signals were taken from 29 diabetic subjects with mean age of (65±8.4) years and 21 non-diabetic subjects of mean age of (49±14) years. Mean duration of diabetes is 12±8 years for diabetic group. Rise-time (RT) and area under rise time (AUR) were calculated from the PPG signal of each subject and Welch’s t-test is used to find the significant difference between two groups. We obtained a significant difference of (p-value) 0.0005 and 0.03 for RT and AUR respectively between diabetic and non-diabetic subjects. Average value of RT and AUR is 0.298±0.003 msec and 14.4±4.2 arbitrary units respectively for diabetic subject compared to 0.277±0.0005 msec and 13.66±2.3 a.u respectively for non-diabetic subjects. In conclusion, this study support that arterial stiffness is increased in diabetes and can be detected early using PPG.

Keywords: area under rise-time, AUR, arterial stiffness, diabetes, photoplethysmograph, PPG, rise-time (RT)

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Authors: Ghada S. Moussa

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With the increase in population along with economic prosperity, an enormous increase in the number and types of vehicles on the roads occurred. This fact brings a growing need for efficiently yet effectively classifying vehicles into their corresponding categories, which play a crucial role in many areas of infrastructure planning and traffic management. This paper presents two vehicle-type classification approaches; 1) geometric-based and 2) appearance-based. The two classification approaches are used for two tasks: multi-class and intra-class vehicle classifications. For the evaluation purpose of the proposed classification approaches’ performance and the identification of the most effective yet efficient one, 10-fold cross-validation technique is used with a large dataset. The proposed approaches are distinguishable from previous research on vehicle classification in which: i) they consider both geometric and appearance attributes of vehicles, and ii) they perform remarkably well in both multi-class and intra-class vehicle classification. Experimental results exhibit promising potentials implementations of the proposed vehicle classification approaches into real-world applications.

Keywords: appearance attributes, geometric attributes, support vector machine, vehicle classification

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Authors: Seyed Esmail Seyedi Bariran, Khairul Salleh Mohamed Sahari

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In multi-echelon supply chain networks, optimal supplier selection significantly depends on the accuracy of suppliers’ performance prediction. Different methods of multi criteria decision making such as ANN, GA, Fuzzy, AHP, etc have been previously used to predict the supplier performance but the “black-box” characteristic of these methods is yet a major concern to be resolved. Therefore, the primary objective in this paper is to implement an artificial intelligence-based gene expression programming (GEP) model to compare the prediction accuracy with that of ANN. A full factorial design with %95 confidence interval is initially applied to determine the appropriate set of criteria for supplier performance evaluation. A test-train approach is then utilized for the ANN and GEP exclusively. The training results are used to find the optimal network architecture and the testing data will determine the prediction accuracy of each method based on measures of root mean square error (RMSE) and correlation coefficient (R2). The results of a case study conducted in Supplying Automotive Parts Co. (SAPCO) with more than 100 local and foreign supply chain members revealed that, in comparison with ANN, gene expression programming has a significant preference in predicting supplier performance by referring to the respective RMSE and R-squared values. Moreover, using GEP, a mathematical function was also derived to solve the issue of ANN black-box structure in modeling the performance prediction.

Keywords: Supplier Performance Prediction, ANN, GEP, Automotive, SAPCO

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Authors: Md. Aminul Islam, Adel Merabet, Rachid Beguenane, Hussein Ibrahim

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This paper presents a simulation and mathematical model of stand-alone solar-wind-diesel based hybrid energy system (HES). A power management system is designed for multiple energy resources in a stand-alone hybrid energy system. Both Solar photovoltaic and wind energy conversion system consists of maximum power point tracking (MPPT), voltage regulation, and basic power electronic interfaces. An additional diesel generator is included to support and improve the reliability of stand-alone system when renewable energy sources are not available. A power management strategy is introduced to distribute the generated power among resistive load banks. The frequency regulation is developed with conventional phase locked loop (PLL) system. The power management algorithm was applied in Matlab®/Simulink® to simulate the results.

Keywords: solar photovoltaic, wind energy, diesel engine, hybrid energy system, power management, frequency and voltage regulation

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Authors: Tanmay L. Joshi

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The Mental health allows children and young people to develop the resilience to cope with whatever life throws at them and grow into well-rounded, healthy adults. In urban area, many health professionals are working for the well being for younger population. There is so much of potential in rural area. However, the rural population is somehow neglected. Apart from lack of availability of basic needs like transport, electricity, telecommunication etc; the Psychological health is also overlooked in such area. There are no mental health professionals like Psychologists, counselors etc. So the researcher tries to throw some light on the mental health of Higher Secondary School going children in rural area. The current research tries to study the Mental Health (Confidence, Sociability and Neurotic Tendency) of Higher Secondary School going children. Researchers have used the tool Vyaktitva Shodhika (a personality inventory) by Dr. U. Khire (JPIP,Pune). The Sample size is 45 (N= 40, 24 boys/21 girls). The present study may provide a good support to inculcate emotional-management programs for higher secondary school going children in rural areas.

Keywords: mental health, neurotic tendency, rural area, school going children

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Authors: Amanda Abbott-Jones

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Adult students with dyslexia in higher education can receive support for their cognitive needs but may also experience negative emotion such as anxiety due to their dyslexia in connection with their studies. This paper aims to test the hypothesis that adult dyslexic learners have a higher prevalence of academic and social anxiety than their non-dyslexic peers. A quantitative approach was used to measure differences in academic and social anxiety between 102 students with a formal diagnosis of dyslexia compared to 72 students with no history of learning difficulties. Academic and social anxiety was measured in a questionnaire based on the State-Trait Anxiety Inventory. Findings showed that dyslexic students showed statistically significant higher levels of academic, but not social anxiety in comparison to the non-dyslexic sample. Dyslexic students in higher education show academic anxiety levels that are well above what is shown by students without dyslexia. The implications of this for the dyslexia practitioner is that delivery of strategies to deal with anxiety should be seen equally as important, if not more so, than interventions to deal with cognitive difficulties.

Keywords: Academic, Anxiety, Dyslexia, Quantitative

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Authors: Kwaku Damoah

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This paper presents a methodology and software application (App) designed to empower users in accessing, retrieving, and comparatively exploring data within the hierarchical network framework of the Government Finance Statistics (GFS) system. It explores the ease of navigating the GFS system and identifies the gaps filled by the new methodology and App. The GFS, embodies a complex Hierarchical Network Classification (HNC) structure, encapsulating institutional units, revenues, expenses, assets, liabilities, and economic activities. Navigating this structure demands specialized knowledge, experience, and skill, posing a significant challenge for effective analytics and fiscal policy decision-making. Many professionals encounter difficulties deciphering these classifications, hindering confident utilization of the system. This accessibility barrier obstructs a vast number of professionals, students, policymakers, and the public from leveraging the abundant data and information within the GFS. Leveraging R programming language, Data Science Analytics and Machine Learning, an efficient methodology enabling users to access, navigate, and conduct exploratory comparisons was developed. The machine learning Fiscal Analytics App (FLOWZZ) democratizes access to advanced analytics through its user-friendly interface, breaking down expertise barriers.

Keywords: data science, data wrangling, drilldown analytics, government finance statistics, hierarchical network classification, machine learning, web application.

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Authors: Shashi Mehta, Krishan Kumar Yadav

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This paper presents an overview of issues pertaining to the conservation of the natural environment and factors affecting the coexistence of the forest, wildlife and people. As forests and wildlife together create the basis for economic, cultural and recreational spaces for overall well-being and life-support systems, the adverse impacts of increasing consumerism are only too evident. The IUCN predicts extinction of 41% of all amphibians and 26% of mammals. The major causes behind this threatened extinction are Deforestation, Dysfunctional governance, Climate Change, Pollution and Cataclysmic phenomena. Thus the intrinsic relationship between natural resources and wildlife needs to be understood in totality, not only for the eco-system but for humanity at large. To demonstrate this, forest areas in the Aravalis- the oldest mountain ranges of Asia—falling in the States of Haryana and Rajasthan, have been taken up for study. The Aravalis are characterized by extreme climatic conditions and dry deciduous forest cover on intermittent scattered hills. Extending across the districts of Gurgaon, Faridabad, Mewat, Mahendergarh, Rewari and Bhiwani, these ranges - with village common land on which the entire economy of the rural settlements depends - fall in the state of Haryana. Aravali ranges with diverse fauna and flora near Alwar town of state of Rajasthan also form part of NCR. Once, rich in biodiversity, the Aravalis played an important role in the sustainable co-existence of forest and people. However, with the advent of industrialization and unregulated urbanization, these ranges are facing deforestation, degradation and denudation. The causes are twofold, i.e. the need of the poor and the greed of the rich. People living in and around the Aravalis are mainly poor and eke out a living by rearing live-stock. With shrinking commons, they depend entirely upon these hills for grazing, fuel, NTFP, medicinal plants and even drinking water. But at the same time, the pressure of indiscriminate urbanization and industrialization in these hills fulfils the demands of the rich and powerful in collusion with Government agencies. The functionaries of federal and State Governments play largely a negative role supporting commercial interests. Additionally, planting of a non- indigenous species like prosopis juliflora across the ranges has resulted in the extinction of almost all the indigenous species. The wildlife in the area is also threatened because of the lack of safe corridors and suitable habitat. In this scenario, the participatory role of different stakeholders such as NGOs, civil society and local community in the management of forests becomes crucial not only for conservation but also for the economic wellbeing of the local people. Exclusion of villagers from protection and conservation efforts - be it designing, implementing or monitoring and evaluating could prove counterproductive. A strategy needs to be evolved, wherein Government agencies be made responsible by putting relevant legislation in place along with nurturing and promoting the traditional wisdom and ethics of local communities in the protection and conservation of forests and wild life in the Aravali ranges of States of Haryana and Rajasthan of the National Capital Region, Delhi.

Keywords: deforestation, ecosystem, governance, urbanization

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Authors: Shahed Vahedi, Mohd Salmi Md Noorani

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This paper investigates cluster synchronization phenomena between community networks. We focus on the situation where a variety of dynamics occur in the clusters. In particular, we show that different synchronization states simultaneously occur between the networks. The controller is designed having an adaptive control gain, and theoretical results are derived via Lyapunov stability. Simulations on well-known dynamical systems are provided to elucidate our results.

Keywords: cluster synchronization, adaptive control, community network, simulation

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Authors: Aliyu Isah Agaie, Masrah Azrifah Azmi Murad, Nurfadhlina Mohd Sharef, Aida Mustapha

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Natural Language Interfaces typically support a restricted language and also have scopes and limitations that naïve users are unaware of, resulting in errors when the users attempt to retrieve information from ontologies. To overcome this challenge, an auto-suggest feature is introduced into the querying process where users are guided through the querying process using interactive query construction system. Guiding users to formulate their queries, while providing them with an unconstrained (or almost unconstrained) way to query the ontology results in better interpretation of the query and ultimately lead to an effective search. The approach described in this paper is unobtrusive and subtly guides the users, so that they have a choice of either selecting from the suggestion list or typing in full. The user is not coerced into accepting system suggestions and can express himself using fragments or full sentences.

Keywords: auto-suggest, expressiveness, habitability, natural language interface, query interpretation, user guidance

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Authors: D. López-Mancilla, J. M. Roblero-Villa

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Since 1990, the research on chaotic dynamics has received considerable attention, particularly in light of potential applications of this phenomenon in secure communications. Data encryption using chaotic systems was reported in the 90's as a new approach for signal encoding that differs from the conventional methods that use numerical algorithms as the encryption key. The algorithms for image encryption have received a lot of attention because of the need to find security on image transmission in real time over the internet and wireless networks. Known algorithms for image encryption, like the standard of data encryption (DES), have the drawback of low level of efficiency when the image is large. The encrypting based on chaos proposes a new and efficient way to get a fast and highly secure image encryption. In this work, a user interface for image encryption and a novel and easiest way to encrypt images using chaos are presented. The main idea is to reshape any image into a n-dimensional vector and combine it with vector extracted from a chaotic system, in such a way that the vector image can be hidden within the chaotic vector. Once this is done, an array is formed with the original dimensions of the image and turns again. An analysis of the security of encryption from the images using statistical analysis is made and is used a stage of optimization for image encryption security and, at the same time, the image can be accurately recovered. The user interface uses the algorithms designed for the encryption of images, allowing you to read an image from the hard drive or another external device. The user interface, encrypt the image allowing three modes of encryption. These modes are given by three different chaotic systems that the user can choose. Once encrypted image, is possible to observe the safety analysis and save it on the hard disk. The main results of this study show that this simple method of encryption, using the optimization stage, allows an encryption security, competitive with complicated encryption methods used in other works. In addition, the user interface allows encrypting image with chaos, and to submit it through any public communication channel, including internet.

Keywords: image encryption, chaos, secure communications, user interface

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Authors: Janki Shankar, Shu-Ping Chen

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This Canadian study explored the perspectives of recent immigrant workers regarding occupational health and safety (OHS) and workplace conditions that increase workers’ vulnerability to sustaining injury or illness. Using an interpretive research approach and semi structured qualitative interviews, 42 recent immigrant workers from a range of industries operating in two cities in a province in Canada were interviewed. A constant comparative approach was used to identify key themes across the workers’ experiences. The findings revealed that these workers have an incomplete understanding of OHS. In many workplaces, poor job training, little worker support, lack of power in the workplace, and a poor workplace safety culture make it difficult for recent immigrant workers to acquire OHS information and implement safe work practices. This study proposes workplace policies and practices that will improve worker OHS awareness and make workplaces safer for immigrant workers.

Keywords: new immigrant workers, occupational health and safety, workplace challenges, policy, practice

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Authors: Shayli Varasteh Moradi, Wayne A. Johnston, Dejan Gagoski, Kirill Alexandrov

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The demand for a rapid and more efficient technique to identify protein-protein interaction particularly in the areas of therapeutics and diagnostics development is growing. The method described here is a rapid in vitro protein-protein interaction analysis approach based on AlphaLISA technology combined with Leishmania tarentolae cell-free protein production (LTE) system. Cell-free protein synthesis allows the rapid production of recombinant proteins in a multiplexed format. Among available in vitro expression systems, LTE offers several advantages over other eukaryotic cell-free systems. It is based on a fast growing fermentable organism that is inexpensive in cultivation and lysate production. High integrity of proteins produced in this system and the ability to co-express multiple proteins makes it a desirable method for screening protein interactions. Following the translation of protein pairs in LTE system, the physical interaction between proteins of interests is analysed by AlphaLISA assay. The assay is performed using unpurified in vitro translation reaction and therefore can be readily multiplexed. This approach can be used in various research applications such as epitope mapping, antigen-antibody analysis and protein interaction network mapping. The intra-viral protein interaction network of Zika virus was studied using the developed technique. The viral proteins were co-expressed pair-wise in LTE and all possible interactions among viral proteins were tested using AlphaLISA. The assay resulted to the identification of 54 intra-viral protein-protein interactions from which 19 binary interactions were found to be novel. The presented technique provides a powerful tool for rapid analysis of protein-protein interaction with high sensitivity and throughput.

Keywords: AlphaLISA technology, cell-free protein expression, epitope mapping, Leishmania tarentolae, protein-protein interaction

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Authors: Zahzouh Zoubir

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The widespread adoption of photovoltaic panel systems for global electricity generation is a prominent trend. Algeria, demonstrating steadfast commitment to strategic development and innovative projects for harnessing solar energy, emerges as a pioneering force in the field. Heat and radiation, being fundamental factors in any solar system, are currently subject to comprehensive studies aiming to discern their genuine impact on crucial elements within photovoltaic systems. This endeavor is particularly pertinent given that solar module performance is exclusively assessed under meticulously defined Standard Test Conditions (STC). Nevertheless, when deployed outdoors, solar modules exhibit efficiencies distinct from those observed under STC due to the influence of diverse environmental factors. This discrepancy introduces ambiguity in performance determination, especially when surpassing test conditions. This article centers on the performance monitoring of an Algerian photovoltaic project, specifically the Oued El Keberite power (OKP) plant boasting a 15 megawatt capacity, situated in the town of Souk Ahras in eastern Algeria. The study elucidates the behavior of a subfield within this facility throughout the year, encompassing various conditions beyond the STC framework. To ensure the optimal efficiency of solar panels, this study integrates crucial factors, drawing on an authentic technical sheet from the measurement station of the OKP photovoltaic plant. Numerical modeling and simulation of a sub-field of the photovoltaic station were conducted using MATLAB Simulink. The findings underscore how radiation intensity and temperature, whether low or high, impact the short-circuit current, open-circuit voltage; fill factor, and overall efficiency of the photovoltaic system.

Keywords: performance monitoring, photovoltaic system, numerical modeling, radiation intensity

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Authors: B. Chen, F. Kuznik, M. Horgnies, K. Johannes, V. Morin, E. Gengembre

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More attention on renewable energy has been done after the achievement of Paris Agreement against climate change. Solar-based technology is supposed to be one of the most promising green energy technologies for residential buildings since its widely thermal usage for hot water and heating. However, the seasonal mismatch between its production and consumption makes buildings need an energy storage system to improve the efficiency of renewable energy use. Indeed, there exist already different kinds of energy storage systems using sensible or latent heat. With the consideration of energy dissipation during storage and low energy density for above two methods, thermochemical energy storage is then recommended. Recently, ettringite (3CaO∙Al₂O₃∙3CaSO₄∙32H₂O) based materials have been reported as potential thermochemical storage materials because of high energy density (~500 kWh/m³), low material cost (700 €/m³) and low storage temperature (~60-70°C), compared to reported salt hydrates like SrBr₂·6H₂O (42 k€/m³, ~80°C), LaCl₃·7H₂O (38 k€/m³, ~100°C) and MgSO₄·7H₂O (5 k€/m³, ~150°C). Therefore, they have the possibility to be largely used in building sector with being coupled to normal solar panel systems. On the other side, the lack in terms of extensive examination leads to poor knowledge on their thermal properties and limit maturity of this technology. The aim of this work is to develop a modular reactor adapting to thermal characterizations of ettringite-based material particles of different sizes. The filled materials in the reactor can be self-compacted vertically to ensure hot air or humid air goes through homogenously. Additionally, quick assembly and modification of reactor, like LEGO™ plastic blocks, make it suitable to distinct thermochemical energy storage material samples with different weights (from some grams to several kilograms). In our case, quantity of stored and released energy, best work conditions and even chemical durability of ettringite-based materials have been investigated.

Keywords: dehydration, ettringite, hydration, modular reactor, thermochemical energy storage

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Authors: Oussedik Lydia, Zaouani-Denoux Souâd

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In an economic context characterized by intense competition and the impact of new technologies, companies have a constant need to adapt to the environment and the changes imposed. This situation leads companies to take training actions to develop employees’ required skills. Further, training is considered as a strategic lever for the company's growth. Accordingly, an increasing number of companies are adopting training to ensure continuous employees qualification. Thus, the aim of this research is to understand the process of training engineering occurring in the context of a company's continuous training, which will help to identify the gaps that can hinder or promote the development of employees' knowledge and skills. The research methodology is based on a mixed-method approach. Interviews and questionnaires are implemented to collect qualitative and quantitative data. The study results can help managers to identify gaps at each stage of training design. Finally, the research findings provide important information to help design a training plan to support the development of employees' knowledge and performance.

Keywords: training engineering, training needs, training plan, competences, continuing training, perception

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Authors: Rouhallah Bagheri, Morteza Mahmoudi, Hadi Moheb-Alizadeh

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In this paper, we develop a supplier selection and order allocation multi-objective model in stochastic environment in which purchasing cost, percentage of delivered items with delay and percentage of rejected items provided by each supplier are supposed to be stochastic parameters following any arbitrary probability distribution. To do so, we use dependent chance programming (DCP) that maximizes probability of the event that total purchasing cost, total delivered items with delay and total rejected items are less than or equal to pre-determined values given by decision maker. After transforming the above mentioned stochastic multi-objective programming problem into a stochastic single objective problem using minimum deviation method, we apply a genetic algorithm to get the later single objective problem solved. The employed genetic algorithm performs a simulation process in order to calculate the stochastic objective function as its fitness function. At the end, we explore the impact of stochastic parameters on the given solution via a sensitivity analysis exploiting coefficient of variation. The results show that as stochastic parameters have greater coefficients of variation, the value of objective function in the stochastic single objective programming problem is worsened.

Keywords: dependent chance programming, genetic algorithm, minimum deviation method, order allocation, supplier selection

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Authors: Jaouadi Imen, Ben Djemaa Raoudha, Ben Abdallah Hanene

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The access to relevant information that is adapted to users’ needs, preferences and environment is a challenge in many applications running. That causes an appearance of context-aware systems. To facilitate the development of this class of applications, it is necessary that these applications share a common context meta-model. In this article, we will present our context meta-model that is defined using the OMG Meta Object facility (MOF). This meta-model is based on the analysis and synthesis of context concepts proposed in literature.

Keywords: context, meta-model, MOF, awareness system

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Authors: Khalid Almarri

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The UAE is currently developing a peaceful nuclear energy program as part of its low Carbon energy strategy to meet future energy demands. Research of nuclear energy technologies is required to support nuclear energy generation projects and maximize their performance. Research of this type will require building an operating a research reactor (RR), a costly undertaking in most circumstances. Collaboration between government and private parties through public, private partnerships (PPP) can maximize the benefits expected from the adoption of an RR project. The aim of this research is to establish the critical success factors (CSF) for developing an RR project for newcomer countries, with the UAE taken as a case study, through the utilization of public, private partnerships (PPP). The results of this study were arrived at through the use of semi-structured interviews conducted with ten experts in the field of research reactors, using grounded theory method. Underutilization was identified as the main stumbling block that impairs the success of research reactors.

Keywords: public private partnerships, research reactors, grounded theory, critical success factors

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Authors: Mohammad A. R. S. Almutairi

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This study will provide the introduction that constitutes the problem cornerstone of legal disputes of disclosure and transparency under Kuwaiti Capital market authority Law No. 7 of 2010. It also will discuss the reasons for the emergence of corporate governance and its purposes in the Capital Market Authority Law in Kuwait. In addition, it will show the legal disputes resulting from the unclear concept of disclosure and interest and will discuss the main reasons in support of the possible solution. In addition, this study will argue why the Capital Market Authority Law in Kuwait needs a clear concept and a straight structure of disclosure under section 100. This study will demonstrate why a clear disclosure is led to a better application of the law. This study will demonstrate the fairness in applying the law regarding the punishment against individual, companies and securities market. Furthermore, it will discuss added confidence between investors and the stock market with a clear concept under section 100. Finally, it will summarize arises problem and possible solution.

Keywords: corporate governors, disclosure, transparency, fairness

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Authors: Min Wei

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With the rapid development eco-tourism resources exploitation, the conflict between economy development and ecological environment is increasingly prominent. The environmental protection laws, however, are lack of necessary legal support to use market mechanism and economic means to carry out ecological compensation and promote the environmental protection. In order to protect the sustainable utilization of eco-tourism resources and the benign development of the interests of various stakeholders, protection of ecological compensation balance should be put on schedule. The main role of institutional guarantee in eco-tourism resources' value compensation mechanism is to solve the question 'how to guarantee compensation'. The evaluation of the game model in this paper reveals that interest balance of stakeholders is an important cornerstone to obtain the sustainable development. The findings result in constructing a sustainable development pattern of eco- tourism industry based on tripartite game equilibrium among government, tourism enterprises and tourists. It is important that the social, economic and ecological environment should be harmonious development during the pursuit of eco-tourism growth.

Keywords: environmental protection, ecological compensation, eco-tourism, market mechanism

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Authors: Angel Villabona-Ortíz, Candelaria Tejada-Tovar, Andrea Viera-Devoz

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Wastewater treatment is an issue of vital importance in these times where the impacts of human activities are most evident, which have become essential tasks for the normal functioning of society. However, they put entire ecosystems at risk by time destroying the possibility of sustainable development. Various conventional technologies are used to remove pollutants from water. Agroindustrial waste is the product with the potential to be used as a renewable raw material for the production of energy and chemical products, and their use is beneficial since products with added value are generated from materials that were not used before. Considering the benefits that the use of residual biomass brings, this project proposes the use of agro-industrial residues from corn crops for the production of natural adsorbents whose purpose is aimed at the remediation of contaminated water bodies with large loads of nutrients. The adsorption capacity of two biomaterials obtained from the processing of corn stalks was evaluated by batch system tests. Biochar impregnated with sulfuric acid and thermally activated was synthesized. On the other hand, the cellulose was extracted from the corn stalks and chemically modified with cetyltrimethylammonium chloride in order to quaternize the surface of the adsorbent. The adsorbents obtained were characterized by thermogravimetric analysis (TGA), scanning electron microscopy (SEM), infrared spectrometry with Fourier Transform (FTIR), analysis by Brunauer, Emmett and Teller method (BET) and X-ray Diffraction analysis ( XRD), which showed favorable characteristics for the cellulose extraction process. Higher adsorption capacities of the nutrients were obtained with the use of biochar, with phosphate being the anion with the best removal percentages. The effect of the initial adsorbate concentration was evaluated, with which it was shown that the Freundlich isotherm better describes the adsorption process in most systems. The adsorbent-phosphate / nitrate systems fit better to the Pseudo Primer Order kinetic model, while the adsorbent-sulfate systems showed a better fit to the Pseudo second-order model, which indicates that there are both physical and chemical interactions in the process. Multicomponent adsorption tests revealed that phosphate anions have a higher affinity for both adsorbents. On the other hand, the thermodynamic parameters standard enthalpy (ΔH °) and standard entropy (ΔS °) with negative results indicate the exothermic nature of the process, whereas the ascending values of standard Gibbs free energy (ΔG °). The adsorption process of anions with biocarbon and modified cellulose is spontaneous and exothermic. The use of the evaluated biomateriles is recommended for the treatment of industrial effluents contaminated with sulfate, nitrate and phosphate anions.

Keywords: adsorption, biochar, modified cellulose, corn stalks

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Authors: Saadia Izzeldin Malik

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Lack of ethics is the crisis of the 21-century. Today’s global world is filled with economic, political, environmental, media/communication, and social crises that all generated by the eroding fabric of ethics and moral values that guide human’s decisions in all aspects of live. Our global world is guided by liberal western democratic principles and liberal capitalist economic principles that define and reinforce each other. In economic terms, capitalism has turned world economic systems into one market place of ideas and products controlled by big multinational corporations that not only determine the conditions and terms of commodity production and commodity exchange between countries, but also transform the political economy of media systems around the globe. The citizen (read the consumer) today is the target of persuasion by all types of media at a time when her/his interests should be, ethically and in principle, the basic significant factor in the selection of media content. It is very important in this juncture of clashing media values –professional and commercial- and wide spread ethical lapses of media organizations and media professionals to think of a perspective to theorize these conflicting values within a broader framework of media ethics. Thus, the aim of this paper is to, epistemologically, bring to the center a perspective on media ethics as a basis for reconciliation of clashing values of the media. The paper focuses on conflicting ethical values in current media debate; namely ownership of media vs. press freedom, individual right for privacy vs. public right to know, and global western consumerism values vs. media values. The paper concludes that a framework to reconcile conflicting values of media ethics should focus on the “individual” journalist and his/her moral development as well as focus on maintaining ethical principles of the media as an institution with a primary social responsibility for the “public” it serves.

Keywords: ethics, media, journalism, social responsibility, conflicting values, global

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Authors: Monisha Isaac

Abstract:

Biotechnology is a discipline which explains the use of living organisms and systems to construct a product, or we can define it as an application or technology developed to use biological systems and organisms processes for a specific use. Particularly, it includes cells and its components use for new technologies and inventions. The tools developed can be further used in diverse fields such as agriculture, industry, research and hospitals etc. The 21^st century has seen a drastic development and advancement in biotechnology in India. Significant increase in Government of India’s outlays for biotechnology over the past decade has been observed. A sectoral break up of biotechnology-based companies in India shows that most of the companies are agriculture-based companies having interests ranging from tissue culture to biopesticides. Major attention has been given by the companies in health related activities and in environmental biotechnology. The biopharmaceutical, which comprises of vaccines, diagnostic, and recombinant products is the most reliable and largest segment of the Indian Biotech industry. India has developed its vaccine markets and supplies them to various countries. Then there are the bio-services, which mainly comprise of contract researches and manufacturing services. India has made noticeable developments in the field of bio industries including manufacturing of enzymes, biofuels and biopolymers. Biotechnology is also playing a crucial and significant role in the field of agriculture. Traditional methods have been replaced by new technologies that mainly focus on GM crops, marker assisted technologies and the use of biotechnological tools to improve the quality of fertilizers and soil. It may only be a small contributor but has shown to have huge potential for growth. Bioinformatics is a computational method which helps to store, manage, arrange and design tools to interpret the extensive data gathered through experimental trials, making it important in the design of drugs.

Keywords: biotechnology, advancement, agriculture, bio-services, bio-industries, bio-pharmaceuticals

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Authors: Yanling Li, Linying Ji, Zita Oravecz, Timothy R. Brick, Michael D. Hunter, Sy-Miin Chow

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Assessing several individuals intensively over time yields intensive longitudinal data (ILD). Even though ILD provide rich information, they also bring other data analytic challenges. One of these is the increased occurrence of missingness with increased study length, possibly under non-ignorable missingness scenarios. Multiple imputation (MI) handles missing data by creating several imputed data sets, and pooling the estimation results across imputed data sets to yield final estimates for inferential purposes. In this article, we introduce dynr.mi(), a function in the R package, Dynamic Modeling in R (dynr). The package dynr provides a suite of fast and accessible functions for estimating and visualizing the results from fitting linear and nonlinear dynamic systems models in discrete as well as continuous time. By integrating the estimation functions in dynr and the MI procedures available from the R package, Multivariate Imputation by Chained Equations (MICE), the dynr.mi() routine is designed to handle possibly non-ignorable missingness in the dependent variables and/or covariates in a user-specified dynamic systems model via MI, with convergence diagnostic check. We utilized dynr.mi() to examine, in the context of a vector autoregressive model, the relationships among individuals’ ambulatory physiological measures, and self-report affect valence and arousal. The results from MI were compared to those from listwise deletion of entries with missingness in the covariates. When we determined the number of iterations based on the convergence diagnostics available from dynr.mi(), differences in the statistical significance of the covariate parameters were observed between the listwise deletion and MI approaches. These results underscore the importance of considering diagnostic information in the implementation of MI procedures.

Keywords: dynamic modeling, missing data, mobility, multiple imputation

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Authors: Derin Ureten

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Plastic pollution does not disappear, it gets smaller and smaller through photolysis which are caused mainly by sun’s radiation, thermal oxidation, thermal degradation, and biodegradation which is the action of organisms digesting larger plastics. All plastic pollutants have exceedingly harmful effects on the environment. Together with the COVID-19 pandemic, the number of plastic products such as masks and gloves flowing into the environment has increased more than ever. However, microplastics are not the only pollutants in water, one of the most tenacious and toxic pollutants are heavy metals. Heavy metal solutions are also capable of causing varieties of health problems in organisms such as cancer, organ damage, nervous system damage, and even death. The aim of this research is to prove that microplastics can be used in wastewater treatment systems by proving that they could adsorb heavy metals in solutions. Experiment for this research will include two heavy metal solutions; one including microplastics in a heavy metal contaminated water solution, and one that just includes heavy metal solution. After being sieved, absorbance of both mediums will be measured with the help of a spectrometer. Iron (III) chloride (FeCl3) will be used as the heavy metal solution since the solution becomes darker as the presence of this substance increases. The experiment will be supported by Pure Nile Red powder in order to observe if there are any visible differences under the microscope. Pure Nile Red powder is a chemical that binds to hydrophobic materials such as plastics and lipids. If proof of adsorbance could be observed by the rates of the solutions' final absorbance rates and visuals ensured by the Pure Nile Red powder, the experiment will be conducted with different temperature levels in order to analyze the most accurate temperature level to proceed with removal of heavy metals from water. New wastewater treatment systems could be generated with the help of microplastics, for water contaminated with heavy metals.

Keywords: microplastics, heavy metal, pollution, adsorbance, wastewater treatment

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Authors: Tasaduk Musood

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In the dynamic landscape of higher education, intra-regional migration within Kashmir represents a complex interplay of influential elements. This qualitative research study aims to explore and analyze the multifaceted factors that significantly shape the patterns and motivations driving students' migration within the region. The study employed a qualitative research approach. The research is carried out with a sample of 60 participants, consisting of 30 male and 30 female students selected from various higher education institutions in the Punjab region. Through self-structured interviews and thematic analysis, the research unravels the underlying drivers, aspirations, challenges, and opportunities that underpin the phenomenon of intra-regional migration in the Kashmiri higher education landscape. The results of this study are expected to offer valuable insights for policymakers, educational institutions, and stakeholders to better understand, address, and potentially enhance the experiences and outcomes of shareholders of students engaged in intra-regional mobility within Kashmir's higher education domain. This study's findings aim to contribute significantly to the existing body of knowledge surrounding intra-regional migration within Kashmir's higher education landscape, offering a nuanced understanding of the drivers behind student mobility. Ultimately, this research endeavors to facilitate more informed and effective decision-making in addressing the evolving dynamics of intra-regional migration in Kashmir's higher education sector.

Keywords: intra-regional migration, student migration patterns, student mobility, higher education, kashmir

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Authors: Khan R. Rahaman, Quazi K. Hassan

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Global changes in climate, environment, economies, populations, governments, institutions, and cultures converge in localities. Changes at a local scale, in turn, contribute to global changes as well as being affected by them. Our hypothesis is built on a consideration that temperature does vary at local level (i.e., termed as local warming) in comparison to the predicted models at the regional and/or global scale. To date, the bulk of the research relating local places to global climate change has been top-down, from the global toward the local, concentrating on methods of impact analysis that use as a starting point climate change scenarios derived from global models, even though these have little regional or local specificity. Thus, our focus is to understand such trends over the southern Alberta, which will enable decision makers, scientists, researcher community, and local people to adapt their policies based on local level temperature variations and to act accordingly. Specific objectives in this study are: (i) to understand the local warming (temperature in particular) trend in context of temperature normal during the period 1961-2010 at point locations using meteorological data; (ii) to validate the data by using specific yearly data, and (iii) to delineate the spatial extent of the local warming trends and understanding influential factors to adopt situation by local governments. Existing data has brought the evidence of such changes and future research emphasis will be given to validate this hypothesis based on remotely sensed data (i.e. MODIS product by NASA).

Keywords: local warming, climate change, urban area, Alberta, Canada

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