Search results for: diurnal temperature cycle model

Authors: Iyad A. A. Abusahloub

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This research aimed to measure the level of perception and application of Integrated Talent Management according to IBM standards, by the upper and middle categories in Palestinian government institutions in Gaza, using a descriptive-analytical method. Using a questionnaire based on the standards of the IBM Institute for Business Value, the researcher added a second section to measure the perception of integrated talent management, the sample was 248 managers. The SPSS package was used for statistical analysis. The results showed that government institutions in Gaza apply Integrated Talent Management according to IBM standards at a medium degree did not exceed 59.8%, there is weakness in the perception of integrated talent management at the level of 53.6%, and there is a strong correlation between (Integrated Talent Management) and (the perception of the integrated talent management) amounted to 92.9%, and 88.9% of the change in the perception of the integrated talent management is by (motivate and develop, deploy and manage, connect and enable, and transform and sustain) talents, and 11.1% is by other factors. Conclusion: This study concluded that the integrated talent management model presented by IBM with its six dimensions is an effective model to reach your awareness and understanding of talent management, especially that it must rely on at least four basic dimensions out of the six dimensions: 1- Stimulating and developing talent. 2- Organizing and managing talent. 3- Connecting with talent and empowering it. 4- Succession and sustainability of talent. Therefore, this study recommends the adoption of the integrated talent management model provided by IBM to any organization across the world, regardless of its specialization or size, to reach talent sustainability.

Keywords: HR, talent, talent management, IBM

Procedia PDF Downloads 73

Authors: E. Karacabey, Ş. G. Özçelik, M. S. Turan, C. Baltacıoğlu, E. Küçüköner

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Main concern about deep-fat-fried food materials is their high final oil contents absorbed during frying process and/or after cooling period, since diet including high content of oil is accepted unhealthy by consumers. Different methods have been evaluated to decrease oil content of fried food stuffs. One promising method is partially drying of food material before frying. In the present study it was aimed to control and decrease the final oil content of zucchini slices by means of partial drying and to optimize process conditions. Conventional oven drying was used to decrease moisture content of zucchini slices at a certain extent. Process performance in terms of oil uptake was evaluated by comparing oil content of predried and then fried zucchini slices with those determined for directly fried ones. For predrying and frying processes, oven temperature and weight loss and frying oil temperature and time pairs were controlled variables, respectively. Zucchini slices were also directly fried for sensory evaluations revealing preferred properties of final product in terms of surface color, moisture content, texture and taste. These properties of directly fried zucchini slices taking the highest score at the end of sensory evaluation were determined and used as targets in optimization procedure. Response surface methodology was used for process optimization. The properties, determined after sensory evaluation, were selected as targets; meanwhile oil content was aimed to be minimized. Results indicated that final oil content of zucchini slices could be reduced from 58% to 46% by controlling conditions of predrying and frying processes. As a result, it was suggested that predrying could be one choose to reduce oil content of fried zucchini slices for health diet. This project (113R015) has been supported by TUBITAK.

Keywords: health process, optimization, response surface methodology, oil uptake, conventional oven

Procedia PDF Downloads 358

Authors: Lokes Parvatha Kumaran S., Sakthi Jay Mahenthar C., Sathyaprakash P., Jayakumar V., Shobanadevi A.

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With the evolution of technology, the need to solve complex computational problems like machine learning and deep learning has shot up. But even the most powerful classical supercomputers find it difficult to execute these tasks. With the recent development of quantum computing, researchers and tech-giants strive for new quantum circuits for machine learning tasks, as present works on Quantum Machine Learning (QML) ensure less memory consumption and reduced model parameters. But it is strenuous to simulate classical deep learning models on existing quantum computing platforms due to the inflexibility of deep quantum circuits. As a consequence, it is essential to design viable quantum algorithms for QML for noisy intermediate-scale quantum (NISQ) devices. The proposed work aims to explore Variational Quantum Circuits (VQC) for Deep Reinforcement Learning by remodeling the experience replay and target network into a representation of VQC. In addition, to reduce the number of model parameters, quantum information encoding schemes are used to achieve better results than the classical neural networks. VQCs are employed to approximate the deep Q-value function for decision-making and policy-selection reinforcement learning with experience replay and the target network.

Keywords: quantum computing, quantum machine learning, variational quantum circuit, deep reinforcement learning, quantum information encoding scheme

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Authors: Bauta J., Raynaud C., Vaca-Medina G., Simon V., Roully A., Vandenbossche V.

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Sargassum is a brown algae, originally found in the Sargasso Sea, located in the Caribbean region and the Gulf of Mexico. The flow of Sargassum is becoming a critical environmental problem all over the Caribbean islands particularly. In Guadeloupe alone, around 80,000 tons of seaweed are stranded during the season. Since the appearance of the first waves of Sargassum algae, several measures have been taken to collect them to keep the beaches clean. Nevertheless, 90% of the collected algae are currently stored without recovery. The lack of research initiative demands a more in-depth exploration of Sargassum algae chemistry, targeted towards added value applications and their development. In this context, the aim of the study was to develop a biorefinery process to valorize Sargassum as a source of bioactive natural substances and as raw material to produce biomaterials simultaneously. The technology used was the twin-screw extrusion, which allows to achieve continuously in the same machine different unit fractionation operations. After the identification of the molecules of interest in Sargassum algae, different operating conditions of thermo-mechanical treatment were applied in a twin-screw extruder. The nature of the solvent, the configuration of the extruder, the screw profile, and the temperature profile were studied in order to fractionate the algal biomass and to allow the recovery of a bioactive liquid fraction of interest and a solid residue suitable for the production of biomaterials. Each bioactive liquid fraction was characterized and strategic ways of adding value were proposed. In parallel, the possibility of using the solid residue to produce biomaterials was studied by setting up Dynamic Vapour Sorption (DVS) and basic Pressure-Volume-Temperature (PVT) analyses. The solid residue was molded by compression cooking. The obtained materials were finally characterized mechanically. The results obtained were very comforting and gave some perspectives to find an interesting valorization for the Sargassum algae.

Keywords: seaweeds, twin-screw extrusion, fractionation, bioactive compounds, biomaterials, biomass

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Authors: Kunihisa Kakumoto

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This technical paper is for the prototype of solar energy utilization for finding sustainable conditions. This model has been simulated under the climate conditions in Japan. At the beginning of the study, the solar model house was built up on site. And the concerned data was collected in this model house for several years. On the basis of these collected data, the concept on the solar community was built up. For the finding sustainable conditions, the amount of the solar energy generation and its reduction of carbon dioxide and the reduction of carbon dioxide by the green planting and the amount of carbon dioxide according to the normal daily life in the solar community and the amount of the necessary water for the daily life in the solar community and the amount of the water supply by the rainfall on-site were calculated. These all values were taken into consideration. The relations between each calculated result are shown in the expression of inequality. This solar community and its consideration for finding sustainable conditions can be one prototype to do the feasibility study for our life in the future

Keywords: carbon dioxide, green planting, smart city, solar community, sustainable condition, water activity

Procedia PDF Downloads 271

Authors: Li-Ching Chen

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The case-control design has been widely applied in clinical and epidemiological studies to investigate the association between risk factors and a given disease. The retrospective design can be easily implemented and is more economical over prospective studies. To adjust effects for confounding factors, methods such as stratification at the design stage and may be adopted. When some major confounding factors are difficult to be quantified, a matching design provides an opportunity for researchers to control the confounding effects. The matching effects can be parameterized by the intercepts of logistic models and the conditional logistic regression analysis is then adopted. This study demonstrates an information-matrix-based goodness-of-fit statistic to test the validity of the logistic regression model for matched case-control data. The asymptotic null distribution of this proposed test statistic is inferred. It needs neither to employ a simulation to evaluate its critical values nor to partition covariate space. The asymptotic power of this test statistic is also derived. The performance of the proposed method is assessed through simulation studies. An example of the real data set is applied to illustrate the implementation of the proposed method as well.

Keywords: conditional logistic model, goodness-of-fit, information matrix, matched case-control studies

Procedia PDF Downloads 277

Authors: Betty Makena, Tsegaye Tadesse, Mark Svoboda

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Global warming has intensified the frequency and intensity of extreme climate disasters and led to unpredictable weather conditions. Consequently, rapid shifts between drought and floods, known as Drought-Flood Abrupt Alteration (DFAA), have become increasingly common. DFAA results in superimposed impacts of drought and floods within a short period, exacerbating the effects of the floods or drought event. Current disaster management plans often overlook DFAA events, as they primarily focus on either floods or drought. Therefore, effectively identifying DFAA events is crucial for developing effective mitigation strategies. This study aims to identify historical DFAA events in Kenya using the Long Cycle Drought-Flood Abrupt Alteration Index (LDFAI). The research will analyze the spatial distribution, temporal variation, and intensity of DFAA events from 1990 to 2023, as well as their socio-economic impacts. Understanding these events is important to develop more effective strategies to address the impacts of DFAA events. Findings from this study will inform decision making to develop coping strategies to mitigate the adverse effects of DFAA in Kenya.

Keywords: abrupt, alteration, drought, floods

Procedia PDF Downloads 56

Authors: Abhit Kumar

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The world is full of master slave Telemanipulator where the doctor’s masters the console and the surgical arm perform the operations, i.e. these robots are passive robots, what the world needs to focus is that in use of these passive robots we are acquiring doctors for operating these console hence the utilization of the concept of robotics is still not fully utilized ,hence the focus should be on active robots, Auto Surgical-Emissive Hand use the similar concept of active robotics where this anthropomorphic hand focuses on the autonomous surgical, emissive and scanning operation, enabled with the vision of 3 way emission of Laser Beam/-5°C < ICY Steam < 5°C/ TIC embedded in palm of the anthropomorphic hand and structured in a form of 3 way disc. Fingers of AS-EH (Auto Surgical-Emissive Hand) as called, will have tactile, force, pressure sensor rooted to it so that the mechanical mechanism of force, pressure and physical presence on the external subject can be maintained, conversely our main focus is on the concept of “emission” the question arises how all the 3 non related methods will work together that to merged in a single programmed hand, all the 3 methods will be utilized according to the need of the external subject, the laser if considered will be emitted via a pin sized outlet, this radiation is channelized via a thin channel which further connect to the palm of the surgical hand internally leading to the pin sized outlet, here the laser is used to emit radiation enough to cut open the skin for removal of metal scrap or any other foreign material while the patient is in under anesthesia, keeping the complexity of the operation very low, at the same time the TIC fitted with accurate temperature compensator will be providing us the real time feed of the surgery in the form of heat image, this gives us the chance to analyze the level, also ATC will help us to determine the elevated body temperature while the operation is being proceeded, the thermal imaging camera in rooted internally in the AS-EH while also being connected to the real time software externally to provide us live feedback. The ICY steam will provide the cooling effect before and after the operation, however for more utilization of this concept we can understand the working of simple procedure in which If a finger remain in icy water for a long time it freezes the blood flow stops and the portion become numb and isolated hence even if you try to pinch it will not provide any sensation as the nerve impulse did not coordinated with the brain hence sensory receptor did not got active which means no sense of touch was observed utilizing the same concept we can use the icy stem to be emitted via a pin sized hole on the area of concern ,temperature below 273K which will frost the area after which operation can be done, this steam can also be use to desensitized the pain while the operation in under process. The mathematical calculation, algorithm, programming of working and movement of this hand will be installed in the system prior to the procedure, since this AS-EH is a programmable hand it comes with the limitation hence this AS-EH robot will perform surgical process of low complexity only.

Keywords: active robots, algorithm, emission, icy steam, TIC, laser

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Authors: Nahia H. Sassine, Frédéric-Victor Donzé, Arnaud Bruch, Barthélemy Harthong

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Thermal Energy Storage (TES) systems are central elements of various types of power plants operated using renewable energy sources. Packed bed TES can be considered as a cost–effective solution in concentrated solar power plants (CSP). Such a device is made up of a tank filled with a granular bed through which heat-transfer fluid circulates. However, in such devices, the tank might be subjected to catastrophic failure induced by a mechanical phenomenon known as thermal ratcheting. Thermal stresses are accumulated during cycles of loading and unloading until the failure happens. For instance, when rocks are used as storage material, the tank wall expands more than the solid medium during charge process, a gap is created between the rocks and tank walls and the filler material settles down to fill it. During discharge, the tank contracts against the bed, resulting in thermal stresses that may exceed the wall tank yield stress and generate plastic deformation. This phenomenon is repeated over the cycles and the tank will be slowly ratcheted outward until it fails. This paper aims at studying the evolution of tank wall stresses over granular bed thermal cycles, taking into account both thermal and mechanical loads, with a numerical model based on the discrete element method (DEM). Simulations were performed to study two different thermal configurations: (i) the tank is heated homogeneously along its height or (ii) with a vertical gradient of temperature. Then, the resulting loading stresses applied on the tank are compared as well the response of the internal granular material. Besides the study of the influence of different thermal configurations on the storage tank response, other parameters are varied, such as the internal angle of friction of the granular material, the dispersion of particles diameters as well as the tank’s dimensions. Then, their influences on the kinematics of the granular bed submitted to thermal cycles are highlighted.

Keywords: discrete element method (DEM), thermal cycles, thermal energy storage, thermocline

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Authors: Jacques Lamarche, Juhani Dickinson

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This paper introduces a computational model of a Grammar as Logic of Labeling (GLL), where the lexical primitives of morphosyntax are phonological matrixes, the form of words, understood as labels that apply to realities (or targets) assumed to be outside of grammar altogether. The hypothesis is that even though a lexical label relates to its target arbitrarily, this label in a complex (constituent) label is part of a labeling pattern which, depending on its value (i.e., N, V, Adj, etc.), imposes language-specific restrictions on what it targets outside of grammar (in the world/semantics or in cognitive knowledge). Lexical forms categorized as nouns, verbs, adjectives, etc., are effectively targets of labeling patterns in use. The paper illustrates GLL through a computer model of basic patterns in English NPs. A constituent label is a binary object that encodes: i) alignment of input forms so that labels occurring at different points in time are understood as applying at once; ii) endocentric structuring - every grammatical constituent has a head label that determines the target of the constituent, and a limiter label (the non-head) that restricts this target. The N or A values are restricted to limiter label, the two differing in terms of alignment with a head. Consider the head initial DP ‘the dog’: the label ‘dog’ gets an N value because it is a limiter that is evenly aligned with the head ‘the’, restricting application of the DP. Adapting a traditional analysis of ‘the’ to GLL – apply label to something familiar – the DP targets and identifies one reality familiar to participants by applying to it the label ‘dog’ (singular). Consider next the DP ‘the large dog’: ‘large dog’ is nominal by even alignment with ‘the’, as before, and since ‘dog’ is the head of (head final) ‘large dog’, it is also nominal. The label ‘large’, however, is adjectival by narrow alignment with the head ‘dog’: it doesn’t target the head but targets a property of what dog applies to (a property or value of attribute). In other words, the internal composition of constituents determines that a form targets a property or a reality: ‘large’ and ‘dog’ happen to be valid targets to realize this constituent. In the presentation, the computer model of the analysis derives the 8 possible sequences of grammatical values with three labels after the determiner (the x y z): 1- D [ N [ N N ]]; 2- D [ A [ N N ] ]; 3- D [ N [ A N ] ]; 4- D [ A [ A N ] ]; 5- D [ [ N N ] N ]; 5- D [ [ A N ] N ]; 6- D [ [ N A ] N ] 7- [ [ N A ] N ] 8- D [ [ Adv A ] N ]. This approach that suggests that a computer model of these grammatical patterns could be used to construct ontologies/knowledge using speakers’ judgments about the validity of lexical meaning in grammatical patterns.

Keywords: syntactic theory, computational linguistics, logic and grammar, semantics, knowledge and grammar

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Authors: Bandar Alahmadi, Manohar Mareboyana, Lethia Jackson

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Today, there are many applications that are using computer vision models, such as face recognition, image classification, and object detection. The accuracy of these models is very important for the performance of these applications. One challenge that facing the computer vision models is the adversarial examples attack. In computer vision, the adversarial example is an image that is intentionally designed to cause the machine learning model to misclassify it. One of very well-known method that is used to attack the Convolution Neural Network (CNN) is Fast Gradient Sign Method (FGSM). The goal of this method is to find the perturbation that can fool the CNN using the gradient of the cost function of CNN. In this paper, we introduce a novel model that can attack Regional-Convolution Neural Network (R-CNN) that use FGSM. We first extract the regions that are detected by R-CNN, and then we resize these regions into the size of regular images. Then, we find the best perturbation of the regions that can fool CNN using FGSM. Next, we add the resulted perturbation to the attacked region to get a new region image that looks similar to the original image to human eyes. Finally, we placed the regions back to the original image and test the R-CNN with the attacked images. Our model could drop the accuracy of the R-CNN when we tested with Pascal VOC 2012 dataset.

Keywords: adversarial examples, attack, computer vision, image processing

Procedia PDF Downloads 178

Authors: Raheb Mirzanamadi, João Patrício

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Asphalt rubber (AR) was initially developed in Sweden in the 1960s by replacing crumb rubber (CR) as aggregates in asphalt pavement. The AR produced by this method had better mechanical properties than conventional asphalt pavement but was very expensive. Since then, different technologies and methods have been developed to use CR in asphalt pavements, including blending CR with bitumen at a high temperature in the mixture, called the wet method, and blending CR with bitumen in the refinery, called the terminal blending method. In 2006, the wet method was imported from the USA to Sweden to evaluate the potential of using AR on Swedish roads. 154 km AR roads were constructed by the wet method in Sweden. The evaluation showed that the AR had, in most cases, better mechanical performance than conventional asphalt pavements. However, the terrible smoke and smell led the Swedish Transport Administration (STA) to stop using AR in Sweden. Today, there are few focuses on AR, despite its good mechanical properties and environmental aspects. Hence, there is a need to study the drives and barriers of using AR mixture in Sweden. The aims of this paper are: (i) to study drivers and barriers of using AR pavements in Sweden and (ii) to discover knowledge gaps for further research in this area. The study was done using a literature review and completed by interviews with experts, including three researchers from Swedish National Road and Transport Research Institute (VTI) and two experts from STA. The results showed that AR can be an alternative not only for conventional asphalt pavement but also for polymer modified asphalt (PMA) due to the same mechanical properties but the lower cost for production. New technologies such as terminal blending and using warm mix asphalt (WMA) methods can lead to reducing the energy and temperature during production processes. From this study, it is found that there is not enough experience and knowledge about AR in Sweden, and more research is needed, including the lifespan of AR, mechanical properties of AR using new technologies, and the impact of AR on spreading and leaching substances into nature. More studies can lead to standardization of using AR in Sweden, a potential solution for the use of end-of-life tyres, with better mechanical properties and lower costs, in comparison with conventional asphalt pavements and PMA.

Keywords: asphalt rubber, crumb rubber, terminal blending method, wet method

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Authors: P. Selyshchev

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We consider fluctuations of defects density taking into account their interaction. Stochastic field of displacement generation rate gives random defect distribution. We determinate statistical characteristics (mean and dispersion) of random field of point defect distribution as function of defect generation parameters, temperature and properties of irradiated crystal.

Keywords: irradiation, primary defects, interaction, fluctuations

Procedia PDF Downloads 328

Authors: Ritsuko Kawasaki, Takeshi Hiromatsu

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Management is required to understand all information security risks within an organization, and to make decisions on which information security risks should be treated in what level by allocating how much amount of cost. However, such decision-making is not usually easy, because various measures for risk treatment must be selected with the suitable application levels. In addition, some measures may have objectives conflicting with each other. It also makes the selection difficult. Therefore, this paper provides a model which supports the selection of measures by applying multi-objective analysis to find an optimal solution. Additionally, a list of measures is also provided to make the selection easier and more effective without any leakage of measures.

Keywords: information security risk treatment, selection of risk measures, risk acceptance, multi-objective optimization

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Authors: Godwin Chigozie Okpara, William Chimee Nwaoha

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The paper set out to stress on how financial inclusion index could be calculated and also investigated the impact of inclusive finance on inclusive growth in an emerging economy. In the light of these objectives, chi-wins method was used to calculate indexes of financial inclusion while co-integration and error correction model were used for evaluation of the impact of financial inclusion on inclusive growth. The result of the analysis revealed that financial inclusion while having a long-run relationship with GDP growth is an insignificant function of the growth of the economy. The speed of adjustment is correctly signed and significant. On the basis of these results, the researchers called for tireless efforts of government and banking sector in promoting financial inclusion in developing countries.

Keywords: chi-wins index, co-integration, error correction model, financial inclusion

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Authors: Kyaw Zin Htut

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In this article, the synthesis of the efficiency of intelligent diagnostic system in the aircraft measuring devices is described. The technology developments of the diagnostic system are considered based on the model errors of the gyro instruments, which are used to measure the parameters of the aircraft. The synthesis of the diagnostic intelligent system is considered on the example of the problem of assessment and forecasting errors of the gyroscope devices on the onboard aircraft. The result of the system is to detect of faults of the aircraft measuring devices as well as the analysis of the measuring equipment to improve the efficiency of its work.

Keywords: diagnostic, dynamic system, errors of gyro instruments, model errors, assessment, prognosis

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Authors: N. Ouslimani, T. Abadlia, M. Fadel

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This work focused on the elimination of acid textile dye (red bermacide acid dye BN-CL-200), widely used for dyeing wool and polyamide fibers, by adsorption on a natural material, wood sawdust, in the static mode by keeping under continuous stirring, a specific mass of the adsorbent, with a dye solution of known concentration. The influence of various parameters is studied like the influence of particle size, mass, pH and time. The best results were obtained with 0.4 mm grain size, mass of 3g, Temperature of 20 °C, pH 2 and Time contact of 120 min.

Keywords: acid dye, environment, wood sawdust, wastewater

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Authors: Chiao-Chen Chang, Yang-Chieh Chin

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Social media has created a change in the way the network community is clustered, especially from the location of the community, from the original virtual space to the intertwined network, and thus the communication between people will change from face to face communication to social media-based communication model. However, social media users who have had a fixed engagement may have an intention to switch to another service provider because of the emergence of new forms of social media. For example, some of Facebook or Twitter users switched to Instagram in 2014 because of social media messages or image overloads, and users may seek simpler and instant social media to become their main social networking tool. This study explores the impact of system features overload, information overload, social monitoring concerns, problematic use and privacy concerns as the antecedents on social media fatigue, dissatisfaction, and alternative attractiveness; further influence social media switching. This study also uses the online questionnaire survey method to recover the sample data, and then confirm the factor analysis, path analysis, model fit analysis and mediating analysis with the structural equation model (SEM). Research findings demonstrated that there were significant effects on multiple paths. Based on the research findings, this study puts forward the implications of theory and practice.

Keywords: social media, switching, social media fatigue, alternative attractiveness

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Authors: Dharell B. Siano, Wendy C. Mateo, Victorino T. Taylan, Francisco D. Cuaresma

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Biofuel is one of the renewable energy sources adapted by the Philippine government in order to lessen the dependency on foreign fuel and to reduce carbon dioxide emissions. Rain tree pods were seen to be a promising source of bioethanol since it contains significant amount of fermentable sugars. The study was conducted to establish the complete procedure in processing rain tree pods for village level hydrous bioethanol production. Production processes were done for village level hydrous bioethanol production from collection, drying, storage, shredding, dilution, extraction, fermentation, and distillation. The feedstock was sundried, and moisture content was determined at a range of 20% to 26% prior to storage. Dilution ratio was 1:1.25 (1 kg of pods = 1.25 L of water) and after extraction process yielded a sugar concentration of 22 ⁰Bx to 24 ⁰Bx. The dilution period was three hours. After three hours of diluting the samples, the juice was extracted using extractor with a capacity of 64.10 L/hour. 150 L of rain tree pods juice was extracted and subjected to fermentation process using a village level anaerobic bioreactor. Fermentation with yeast (Saccharomyces cerevisiae) can fasten up the process, thus producing more ethanol at a shorter period of time; however, without yeast fermentation, it also produces ethanol at lower volume with slower fermentation process. Distillation of 150 L of fermented broth was done for six hours at 85 °C to 95 °C temperature (feedstock) and 74 °C to 95 °C temperature of the column head (vapor state of ethanol). The highest volume of ethanol recovered was established at with yeast fermentation at five-day duration with a value of 14.89 L and lowest actual ethanol content was found at without yeast fermentation at three-day duration having a value of 11.63 L. In general, the results suggested that rain tree pods had a very good potential as feedstock for bioethanol production. Fermentation of rain tree pods juice can be done with yeast and without yeast.

Keywords: fermentation, hydrous bioethanol, fermentation, rain tree pods, village level

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Authors: Shanawaz Patil, Mohamed Haneef, K. S. Narayanaswamy

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In the recent years, aluminum metal matrix composites were most widely used, which are finding wide applications in various field such as automobile, aerospace defense etc., due to their outstanding mechanical properties like low density, light weight, exceptional high levels of strength, stiffness, wear resistance, high temperature resistance, low coefficient of thermal expansion and good formability. In the present work, an effort is made to study the effect of heat treatment on mechanical properties of aluminum 7075 alloy reinforced with constant weight percentage of naturally occurring mineral beryl and varying weight percentage of graphene. The hybrid composites are developed with 0.5 wt. %, 1wt.%, 1.5 wt.% and 2 wt.% of graphene and 6 wt.% of beryl  by stir casting liquid metallurgy route. The cast specimens of unreinforced aluminum alloy and hybrid composite samples were prepared for heat treatment process and subjected to solutionizing treatment (T6) at a temperature of 490±5 ^oC for 8 hours in a muffle furnace followed by quenching in boiling water. The microstructure analysis of as cast and heat treated hybrid composite specimens are examined by scanning electron microscope (SEM). The tensile test and hardness test of unreinforced aluminum alloy and hybrid composites are examined. The wear behavior is examined by pin-on disc apparatus. The results of as cast specimens and heat treated specimens were compared. The heat treated Al7075-Beryl-Graphene hybrid composite had better properties and significantly improved the ultimate tensile strength, hardness and reduced wear loss when compared to aluminum alloy and  as cast hybrid composites.

Keywords: beryl, graphene, heat treatment, mechanical properties

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Authors: Kartikey Gupta

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Global warming and environmental degradation are at their peak today, with the years after 2000A.D. giving way to 15 hottest years in terms of average temperatures. In India, much of the standard temperature measuring equipment are located in ‘developed’ urban areas, hence showing us an incomplete picture in terms of the climate across many rural areas, which comprises most of the landmass. This study showcases data studied by the author since 3 years at Vatsalya’s Children’s village, in outskirts of Jaipur, Rajasthan, India; in the midst of semi-arid topography, where consistently huge temperature differences of up to 15.8 degrees Celsius from local Jaipur weather only 30 kilometers away, are stunning yet scary at the same time, encouraging analysis of where the natural climatic pattern is heading due to rapid unrestricted urbanization. Record-breaking data presented in this project enforces the need to discuss causes and recovery techniques. This research further explores how and to what extent we are causing phenomenal disturbances in the natural meteorological pattern by urban growth. Detailed data observations using a standardized ambient weather station at study site and comparing it with closest airport weather data, evaluating the patterns and differences, show striking differences in temperatures, wind patterns and even rainfall quantity, especially during high-pressure zone days. Winter-time lows dip to 8 degrees below freezing with heavy frost and ice, while only 30 kms away minimum figures barely touch single-digit temperatures. Human activity is having an unprecedented effect on climatic patterns in record-breaking trends, which is a warning of what may follow in the next 15-25 years for the next generation living in cities, and a serious exploration into possible solutions is a must.

Keywords: climate change, meteorology, urban heat island, urbanization

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Authors: Fatima Sohail, Faizan Iftikhar

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This paper studies the relationship between digital finance, renewable energy, and the economic development of Pakistan and least developed countries from 2000 to 2022. The paper used panel analysis and generalized method of moments Arellano-Bond approaches. The findings show that under the growth model, renewable energy (RE) has a strong and favorable link with fixed broadband and mobile subscribers. However, FB and MD have a strong but negative association with the uptake of renewable energy (RE) in the average and simple model. This paper provides valuable insights for policymakers, investors of the digital economy.

Keywords: digital finance, renewable energy, economic development, mobile subscription, fixed broadband

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Authors: Farhad Alizadeh, Alireza Faregh Gharamaleki, Mojtaba Jalilzadeh, Houshang Gholami, Ali Akhoundzadeh

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This study presented hybrid pre-processing approach along with a conceptual model to enhance the accuracy of river discharge prediction. In order to achieve this goal, Ensemble Empirical Mode Decomposition algorithm (EEMD), Discrete Wavelet Transform (DWT) and Mutual Information (MI) were employed as a hybrid pre-processing approach conjugated to Least Square Support Vector Machine (LSSVM). A conceptual strategy namely multi-station model was developed to forecast the Souris River discharge more accurately. The strategy used herein was capable of covering uncertainties and complexities of river discharge modeling. DWT and EEMD was coupled, and the feature selection was performed for decomposed sub-series using MI to be employed in multi-station model. In the proposed feature selection method, some useless sub-series were omitted to achieve better performance. Results approved efficiency of the proposed DWT-EEMD-MI approach to improve accuracy of multi-station modeling strategies.

Keywords: river stage-discharge process, LSSVM, discrete wavelet transform, Ensemble Empirical Decomposition Mode, multi-station modeling

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Authors: G. Nampa, M. Ndlovu

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Mutualistic relationships amongst organisms drive diversity in terrestrial ecosystems. Yet, few mutual associations have been documented in the semi-arid savannas of Africa. The levels and benefits of association between Carissa bispinosa, a medium-sized evergreen thorny shrub, and Trinervitermes trinervoides, an ecosystem engineer termite species, were studied at a semi-arid savanna setting in Nylsvley nature reserve, South Africa. It was hypothesized that there would be a close plant-insect association since termite mounds provide nutrients for plant growth and, in return, the thorny shrubs protect mounds from predation and also provide a temperature buffer. Comparative plant and mounds measurements were taken from associated and isolated occurrences seasonally. Soil particle size, macro- and micronutrients were also evaluated from mounds and the adjacent topsoil matrix General Additive Mixed Models were used to assess internal mound temperatures in relation to prevailing ambient and plant shade temperatures. Findings revealed that plants growing on mounds were significantly taller with a wider canopy and remained greener in the dry season with more fruits. On the other hand, termite mounds under plants were less prone to be damaged by aardvarks and pangolins and had a significantly wider diameter than exposed mounds. All soil macronutrients except for calcium and phosphorous were enriched in mounds relative to the matrix. Only Manganese was enriched in mounds while the other micronutrients (Cu, Fe, Zn and B) were not. Termite mounds under plants maintained a better constant and higher mean internal temperature during winter compared to exposed mounds. To our best knowledge, the study has revealed a previously undocumented survival mechanism that termites use to escape extreme temperatures and predation in semi-arid savannas.

Keywords: mound, mutualism, soil nutrients, termites, thermoregulation

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Authors: Yemane Hailu Fissuh, Zhongzhan Zhang

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In biomedical researches and randomized clinical trials, the most commonly interested outcomes are time-to-event so-called survival data. The importance of robust models in this context is to compare the effect of randomly controlled experimental groups that have a sense of causality. Causal estimation is the scientific concept of comparing the pragmatic effect of treatments conditional to the given covariates rather than assessing the simple association of response and predictors. Hence, the causal effect based semiparametric transformation model was proposed to estimate the effect of treatment with the presence of possibly time-varying covariates. Due to its high flexibility and robustness, the semiparametric transformation model which shall be applied in this paper has been given much more attention for estimation of a causal effect in modeling left-truncated and right censored survival data. Despite its wide applications and popularity in estimating unknown parameters, the maximum likelihood estimation technique is quite complex and burdensome in estimating unknown parameters and unspecified transformation function in the presence of possibly time-varying covariates. Thus, to ease the complexity we proposed the modified estimating equations. After intuitive estimation procedures, the consistency and asymptotic properties of the estimators were derived and the characteristics of the estimators in the finite sample performance of the proposed model were illustrated via simulation studies and Stanford heart transplant real data example. To sum up the study, the bias of covariates was adjusted via estimating the density function for truncation variable which was also incorporated in the model as a covariate in order to relax the independence assumption of failure time and truncation time. Moreover, the expectation-maximization (EM) algorithm was described for the estimation of iterative unknown parameters and unspecified transformation function. In addition, the causal effect was derived by the ratio of the cumulative hazard function of active and passive experiments after adjusting for bias raised in the model due to the truncation variable.

Keywords: causal estimation, EM algorithm, semiparametric transformation models, time-to-event outcomes, time-varying covariate

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Authors: Brindusa Balanuca, Raluca Stan, Cristina Ott, Matei Raicopol

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The current study aims to develop anti corrosive coatings using vegetable oil (VO)-based polymers. Due to their chemical versatility, reduced costs and more important, higher hydrophobicity, VO’s are great candidates in the field of anti-corrosive materials. Lignin (Ln) derivatives were also used in this research study in order to achieve performant hydrophobic anti-corrosion layers. Methods Through a rational functionalization pathway, the selected VO (linseed oil) is converted to more reactive monomer – methacrylate linseed oil (noted MLO). The synthesized MLO cover the metals surface in a thin layer and through different polymerization techniques (using visible radiation or temperature, respectively) and well-established reaction conditions, is converted to a hydrophobic coating capable to protect the metals against corrosive factors. In order to increase the anti-corrosion protection, lignin (Ln) was selected to be used together with MLO macromonomer. Thus, super hydrophobic protective coatings will be formulated. Results The selected synthetic strategy to convert the VO in more reactive compounds – MLO – has led to a functionalization degree of greater than 80%. The obtained monomers were characterized through NMR and FT-IR by monitoring the characteristic signals after each synthesis step. Using H-NMR data, the functionalization degrees were established. VO-based and also VO-Ln anti corrosion formulations were both photochemical and thermal polymerized in specific reaction conditions (initiators, temperature range, reaction time) and were tested as anticorrosive coatings. Complete and advances characterization of the synthesized materials will be presented in terms of thermal, mechanical and morphological properties. The anticorrosive properties were also evaluated and will be presented. Conclusions Through the design strategy briefly presented, new composite materials for metal corrosion protection were successfully developed, using natural derivatives: vegetable oils and lignin, respectively.

Keywords: anticorrosion protection, hydrophobe layers, lignin, methacrylates, vegetable oil

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Authors: Shuo Liu

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In Chinese text classification tasks, redundant words and phrases can interfere with the formation of extracted and analyzed text information, leading to a decrease in the accuracy of the classification model. To reduce irrelevant elements, extract and utilize text content information more efficiently and improve the accuracy of text classification models. In this paper, the text in the corpus is first extracted using the TextRank algorithm for abstraction, the words in the abstract are used as nodes to construct a text graph, and then the graph attention network (GAT) is used to complete the task of classifying the text. Testing on a Chinese dataset from the network, the classification accuracy was improved over the direct method of generating graph structures using text.

Keywords: Chinese natural language processing, text classification, abstract extraction, graph attention network

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Authors: Veronica S. Moertini, Niko Ibrahim, Verliyantina

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As market intermediary firms, e-commerce transaction broker firms need to strongly collaborate with suppliers in order to develop brands seek by customers. Developing suitable electronic Supplier Relationship Management (e-SRM) system is the solution to the need. In this paper, we propose our concept of e-SRM for transaction brokers owned by small medium enterprises (SMEs), which includes the integrated e-SRM and e-CRM architecture, the e-SRM applications with their functions. We then discuss the customization and implementation of the proposed e-SRM model in a specific transaction broker selling hotel rooms, which owned by an SME, KlikHotel.com. The implementation of the e-SRM in KlikHotel.com has been successfully boosting the number of suppliers (hotel members) and hotel room sales.

Keywords: e-CRM, e-SRM, SME, transaction broker

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Authors: Dhruvit S. Berawala, Jann R. Ursin, Obrad Slijepcevic

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Shale gas is one of the most rapidly growing forms of natural gas. Unconventional natural gas deposits are difficult to characterize overall, but in general are often lower in resource concentration and dispersed over large areas. Moreover, gas is densely packed into the matrix through adsorption which accounts for large volume of gas reserves. Gas production from tight shale deposits are made possible by extensive and deep well fracturing which contacts large fractions of the formation. The conventional reservoir modelling and production forecasting methods, which rely on fluid-flow processes dominated by viscous forces, have proved to be very pessimistic and inaccurate. This paper presents a new approach to forecast shale gas production by detailed modeling of gas desorption, diffusion and non-linear flow mechanisms in combination with statistical representation of these processes. The representation of the model involves a cube as a porous media where free gas is present and a sphere (SiC: Sphere in Cube model) inside it where gas is adsorbed on to the kerogen or organic matter. Further, the sphere is considered consisting of many layers of adsorbed gas in an onion-like structure. With pressure decline, the gas desorbs first from the outer most layer of sphere causing decrease in its molecular concentration. The new available surface area and change in concentration triggers the diffusion of gas from kerogen. The process continues until all the gas present internally diffuses out of the kerogen, gets adsorbs onto available surface area and then desorbs into the nanopores and micro-fractures in the cube. Each SiC idealizes a gas pathway and is characterized by sphere diameter and length of the cube. The diameter allows to model gas storage, diffusion and desorption; the cube length takes into account the pathway for flow in nanopores and micro-fractures. Many of these representative but general cells of the reservoir are put together and linked to a well or hydraulic fracture. The paper quantitatively describes these processes as well as clarifies the geological conditions under which a successful shale gas production could be expected. A numerical model has been derived which is then compiled on FORTRAN to develop a simulator for the production of shale gas by considering the spheres as a source term in each of the grid blocks. By applying SiC to field data, we demonstrate that the model provides an effective way to quickly access gas production rates from shale formations. We also examine the effect of model input properties on gas production.

Keywords: adsorption, diffusion, non-linear flow, shale gas production

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Authors: Majid Rezayi, Sh. Shahaboddin, HNM E. Mahmud, A. Yadollah, A. Saeid, A. Yatimah

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In this study, the adaptive neuro-fuzzy inference system (ANFIS) was applied to obtain the membrane composition model affecting the potential response of our reported polymeric PVC sensor for determining the titanium (III) ions. The performance statistics of the artificial neural network (ANN) and linear regression models for potential slope prediction of membrane composition of titanium (III) ion selective electrode were compared with ANFIS technique. The results show that the ANFIS model can be used as a practical tool for obtaining the Nerntian slope of the proposed sensor in this study.

Keywords: adaptive neuro fuzzy inference, PVC sensor, titanium (III) ions, Nerntian slope

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