Search results for: key performance indicators

Authors: M. E. Marwan, A. R. Madar, N. Fuad

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Mobile learning (m-learning) is a new method in teaching and learning process which combines technology of mobile device with learning materials. It can enhance student's engagement in learning activities and facilitate them to access the learning materials at anytime and anywhere. In Kolej Poly-Tech Mara (KPTM), this method is seen as an important effort in teaching practice and to improve student learning performance. The aim of this paper is to discuss the development of m-learning application called Mobile EEF Learning System (MEEFLS) to be implemented for Electric and Electronic Fundamentals course using Flash, XML (Extensible Markup Language) and J2ME (Java 2 micro edition). System Development Life Cycle (SDLC) was used as an application development approach. It has three modules in this application such as notes or course material, exercises and video. MEELFS development is seen as a tool or a pilot test for m-learning in KPTM.

Keywords: flash, mobile device, mobile learning, teaching and learning, SDLC, XML

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Authors: K. Hema Shankari, R. Thirumalaiselvi, N. V. Balasubramanian

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The present paper addresses to the research in the area of regression testing with emphasis on automated tools as well as prioritization of test cases. The uniqueness of regression testing and its cyclic nature is pointed out. The difference in approach between industry, with business model as basis, and academia, with focus on data mining, is highlighted. Test Metrics are discussed as a prelude to our formula for prioritization; a case study is further discussed to illustrate this methodology. An industrial case study is also described in the paper, where the number of test cases is so large that they have to be grouped as Test Suites. In such situations, a genetic algorithm proposed by us can be used to reconfigure these Test Suites in each cycle of regression testing. The comparison is made between a proprietary tool and an open source tool using the above-mentioned metrics. Our approach is clarified through several tables.

Keywords: APFD metric, genetic algorithm, regression testing, RFT tool, test case prioritization, selenium tool

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Authors: Kehinde K. Agbele, Kehinde Daniel Aruleba, Eniafe F. Ayetiran

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When using Information Retrieval Systems (IRS), users often present search queries made of ad-hoc keywords. It is then up to the IRS to obtain a precise representation of the user’s information need and the context of the information. This paper investigates optimization of IRS to individual information needs in order of relevance. The study addressed development of algorithms that optimize the ranking of documents retrieved from IRS. This study discusses and describes a Document Ranking Optimization (DROPT) algorithm for information retrieval (IR) in an Internet-based or designated databases environment. Conversely, as the volume of information available online and in designated databases is growing continuously, ranking algorithms can play a major role in the context of search results. In this paper, a DROPT technique for documents retrieved from a corpus is developed with respect to document index keywords and the query vectors. This is based on calculating the weight (

Keywords: information retrieval, document relevance, performance measures, personalization

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Authors: Nadia Hammouda, K. Belmokre

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Organic coatings are widely employed in the corrosion protection of most metal surfaces, particularly steel. They provide a barrier against corrosive species present in the environment, due to their high resistance to oxygen, water and ions transport. This study focuses on the evaluation of corrosion protection performance of epoxy paint on the carbon steel surface in sea water by Electrochemical Impedance Spectroscopy (EIS). The electrochemical behavior of painted surface was estimated by EIS parameters that contained paint film resistance, paint film capacitance and double layer capacitance. On the basis of calculation using EIS spectrums it was observed that pore resistance (Rpore) decreased with the appearance of doubled layer capacitance (Cdl) due to the electrolyte penetration through the film. This was further confirmed by the decrease of diffusion resistance (Rd) which was also the indicator of the deterioration of paint film protectiveness.

Keywords: epoxy paints, carbon steel, electrochemical impedance spectroscopy, corrosion mechanisms, sea water

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Authors: Syed Abdul Rehman Khan

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In today’s world, information sharing plays a vital role in successful operations of supply chain; and boost to the profitability of the organizations (end-to-end supply chains). Many researches have been completed over the role of information sharing in supply chain. In this research article, we will investigate the ‘how information sharing can boost profitability & productivity of the organization; for this purpose, we have developed one conceptual model and check to that model through collected data from companies. We sent questionnaire to 369 companies; and will filled form received from 172 firms and the response rate was almost 47%. For the data analysis, we have used Regression in (SPSS software) In the research findings, our all hypothesis has been accepted significantly and due to the information sharing between suppliers and manufacturers ‘quality of material and timely delivery’ increase and also ‘collaboration & trust’ will become more stronger and these all factors will lead to the company’s profitability directly and in-directly. But unfortunately, companies could not avail the all fruitful benefits of information sharing due to the fear of ‘compromise confidentiality or leakage of information’.

Keywords: collaboration, information sharing, risk factor, timely delivery

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Authors: Mohamad H. Atyeh, Ahmad Khaldi

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The main objective of this research is to measure the relationship between the Kuwait stock Exchange (KSE) index and its two marketing sectors after the new market classification. The findings of this research are important for Public economic policy makers as they need to know if the new system (new classification) is efficient and to what level, to monitor the markets and intervene with appropriate measures. The data used are the daily index of the whole Kuwaiti market and the daily closing price, number of deals and volume of shares traded of two marketing sectors (consumer goods and consumer services) for the period from the 13th of May 2012 till the 12th of December 2016. The results indicate a positive direct impact of the closing price, volume and deals indexes of the consumer goods and the consumer services companies on the overall KSE index, volume and deals of the Kuwaiti stock market (KSE).

Keywords: correlation, market capitalization, Kuwait Stock Exchange (KSE), marketing sectors, stock performance

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Authors: Victoriano Valencia García, Luis Usero Aragonés, Eugenio J. Fernández Vicente

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Nowadays, the successful implementation of ICTs is vital for almost any kind of organization. Good governance and ICT management are essential for delivering value, managing technological risks, managing resources and performance measurement. In addition, outsourcing is a strategic IT service solution which complements IT services provided internally in organizations. This paper proposes the measurement tools of a new holistic maturity model based on standards ISO/IEC 20000 and ISO/IEC 38500, and the frameworks and best practices of ITIL and COBIT, with a specific focus on IT outsourcing. These measurement tools allow independent validation and practical application in the field of higher education, using a questionnaire, metrics tables, and continuous improvement plan tables as part of the measurement process. Guidelines and standards are proposed in the model for facilitating adaptation to universities and achieving excellence in the outsourcing of IT services.

Keywords: IT governance, IT management, IT services, outsourcing, maturity model, measurement tools

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Authors: Jiaqi Huang, Yuheng Wang

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Premises selection, the task of selecting a set of axioms for proving a given conjecture, is a major bottleneck in automated theorem proving. An array of deep-learning-based methods has been established for premises selection, but a perfect performance remains challenging. Our study examines the inaccuracy of deep neural networks in premises selection. Through training network models using encoded conjecture and axiom pairs from the Mizar Mathematical Library, two potential biases are found: the network models classify more premises as necessary than unnecessary, referred to as the ‘positive bias’, and the network models perform better in proving conjectures that paired with more axioms, referred to as ‘length bias’. The ‘positive bias’ and ‘length bias’ discovered could inform the limitation of existing deep neural networks.

Keywords: automated theorem proving, premises selection, deep learning, interpreting deep learning

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Authors: Rahma Tibigui, Ikram Hadj Said, Rachid Belkada, Dalila Hammoutene

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The vulnerability of industrial facilities is highly concerned with multiple risks from corrosion. The commonly adopted solution is based on the use of organic inhibitors, which are gradually being replaced by environmentally friendly organic inhibitors. In our work, we carried out a quantum chemical study based on the Density Functional Theory (DFT) method at the B3LYP/6-311G (d,p) level of theory. The inhibitory performance of a derivative of the tetrazole molecule has been investigated and reported as a carbon steel-friendly corrosion inhibitor in hydrochloric acid (HCl) medium. The relationship is likely to exist between the molecular structure of this compound as well as its various global reactivity descriptors, and its corrosion inhibition efficiency, which was examined and then discussed. The results show low values of ΔE, which represent strong adsorption of the inhibitor on the steel surface. Moreover, the flat adsorption orientation confirmed the great ability to donate (accept) electrons to (from) steel, fabricating an anchored barrier to prevent steel from corrosion.

Keywords: eco-friendly, corrosion inhibitors, tetrazole, DFT

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Authors: Laura O’Halloran, Zhipeng Cao, Clare M. Kelly, Hugh Garavan, Robert Whelan

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Reaction time (RT) variability on cognitive tasks provides the index of the efficiency of executive control processes (e.g. attention and inhibitory control) and is considered to be a hallmark of clinical disorders, such as attention-deficit disorder (ADHD). Increased RT variability is associated with structural and functional brain differences in children and adults with various clinical disorders, as well as poorer task performance accuracy. Furthermore, the strength of functional connectivity across various brain networks, such as the negative relationship between the task-negative default mode network and task-positive attentional networks, has been found to reflect differences in RT variability. Although RT variability may provide an index of attentional efficiency, as well as being a useful indicator of neurological impairment, the brain substrates associated with RT variability remain relatively poorly defined, particularly in a healthy sample. Method: Firstly, we used the intra-individual coefficient of variation (ICV) as an index of RT variability from “Go” responses on the Stop Signal Task. We then examined the functional and structural neural correlates of ICV in a large sample of 14-year old healthy adolescents (n=1719). Of these, a subset had elevated symptoms of ADHD (n=80) and was compared to a matched non-symptomatic control group (n=80). The relationship between brain activity during successful and unsuccessful inhibitions and gray matter volume were compared with the ICV. A mediation analysis was conducted to examine if specific brain regions mediated the relationship between ADHD symptoms and ICV. Lastly, we looked at functional connectivity across various brain networks and quantified both positive and negative correlations during “Go” responses on the Stop Signal Task. Results: The brain data revealed that higher ICV was associated with increased structural and functional brain activation in the precentral gyrus in the whole sample and in adolescents with ADHD symptoms. Lower ICV was associated with lower activation in the anterior cingulate cortex (ACC) and medial frontal gyrus in the whole sample and in the control group. Furthermore, our results indicated that activation in the precentral gyrus (Broadman Area 4) mediated the relationship between ADHD symptoms and behavioural ICV. Conclusion: This is the first study first to investigate the functional and structural correlates of ICV collectively in a large adolescent sample. Our findings demonstrate a concurrent increase in brain structure and function within task-active prefrontal networks as a function of increased RT variability. Furthermore, structural and functional brain activation patterns in the ACC, and medial frontal gyrus plays a role-optimizing top-down control in order to maintain task performance. Our results also evidenced clear differences in brain morphometry between adolescents with symptoms of ADHD but without clinical diagnosis and typically developing controls. Our findings shed light on specific functional and structural brain regions that are implicated in ICV and yield insights into effective cognitive control in healthy individuals and in clinical groups.

Keywords: ADHD, fMRI, reaction-time variability, default mode, functional connectivity

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Authors: Abderrahmane Khiat, Moussa Benaissa

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Due to the increasing number of sources of information available on the web and their distribution and heterogeneity, ontology alignment became a very important and inevitable problem to ensure semantic interoperability. Instance-based ontology alignment is based on the comparison of the extensions of concepts; and represents a very promising technique to find semantic correspondences between entities of different ontologies. In practice, two situations may arise: ontologies that share many common instances and ontologies that share few or do not share common instances. In this paper, we describe an approach to manage the latter case. This approach exploits the reasoning on ontologies in order to create a corpus of common instances. We show that it is theoretically powerful because it is based on description logics and very useful in practice. We present the experimental results obtained by running our approach on ontologies of OAEI 2012 benchmark test. The results show the performance of our approach.

Keywords: description logic inference, instance-based ontology alignment, semantic interoperability, semantic web

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Authors: Inas Kamel, Noor Z. Habib

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Utilizing construction and demolition wastes in hotmix asphalt (HMA) pavement construction can reduce the adverse environmental effect of its inadequate disposal and reduce the pressure of extracting and processing mineral aggregates (MA). This study aims to examine the viability of replacing MA by recycled construction and demolition waste aggregates (RCDWA) in the wearing course of asphaltic concrete (AC) pavements without compromising its loadbearing capacity. The Marshall Method was used to evaluate the performance of AC wearing course specimens by replacing MA by 10%, 20% and 30% RCDWA. Grade 60/70 bitumen was used in the range 3.0-5.5%, with 05% increments, to generate the optimum bitumen content (OBC). From the volumetric analysis and test property curves, the mixture containing 20% RCDWA was chosen as the preferred mix at 5.1% OBC. It possessed a 10% increase in Marshall Stability compared to the reference specimen, containing 100% MA, and a 6% increase in Marshall flow.

Keywords: aggregate, asphaltic concrete, Marshall method, optimum bitumen content, recycled construction and demolition waste

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Authors: Ebrahim Ghanbari, Mohammad Reza Nematollahi

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Integrating deterministic and probabilistic safety assessment (IDPSA) is one of the most commonly used issues in the field of safety analysis of power plant accident. It has also been recognized today that the role of human error in creating these accidents is not less than systemic errors, so the human interference and system errors in fault and event sequences are necessary. The integration of these analytical topics will be reflected in the frequency of core damage and also the study of the use of water resources in an accident such as the loss of all electrical power of the plant. In this regard, the SBO accident was simulated for the pressurized water reactor in the deterministic analysis issue, and by analyzing the operator's behavior in controlling the accident, the results of the combination of deterministic and probabilistic assessment were identified. The results showed that the best performance of the plant operator would reduce the risk of an accident by 10%, as well as a decrease of 6.82 liters/second of the water sources of the plant.

Keywords: IDPSA, human error, SBO, risk

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Authors: S. Jahangir, S. H. I. Jaffery, M. Khan, Z. Zareef, A. Yar, A. Mubashir, S. Butt, L. Ali

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In this work, drilling responses and behavior of MMC was investigated in Al-Mg2Si composites. For the purpose Al-15% wt. Mg2Si, was selected from the hypereutectic region of Al- Mg2Si phase diagram. Based on hardness and tensile strength, drill bit of appropriate material and morphology was selected. The performance of different drill bits of different morphology and material was studied and analysed using experimental data. For theoretical calculations of axial thrust force and required power calculation, material factor “K” was obtained from different data charts and at the same time cutting forces (drilling forces) were practically obtained using a Peizo electric force dynamometer. These results show the role of reinforcement particles on the machinability of MMCs and provide a useful guide for a better control and optimized drilling parameters for the drilling process. Furthermore, in this work, comparison of MMC with non -reinforced Aluminum Alloy regarding drilling operation was also studied.

Keywords: drilling, metal matrix composite (MMC), cutting forces, thrust force

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Authors: Hamid Reza Mahdipoor, Mehdi Bahrami, Mohammad Bodaghi, Seyed Ali Akbar Mansoori

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Nowadays, with stricter limitations to reduce emissions, considerable penalties are imposed if pollution limits are exceeded. Therefore, refineries, along with focusing on improving the quality of their products, are also focused on producing products with the least environmental impact. The duty of the sulfur recovery unit (SRU) is to convert H₂S gas coming from the upstream units to elemental sulfur and minimize the burning of sulfur compounds to SO₂. The Claus process is a common process for converting H₂S to sulfur, including a reaction furnace followed by catalytic reactors and sulfur condensers. In addition to a Claus section, SRUs usually consist of a tail gas treatment (TGT) section to decrease the concentration of SO₂ in the flue gas below the emission limits. To operate an SRU properly, the flow rate of combustion air to the reaction furnace must be adjusted so that the Claus reaction is performed according to stoichiometry. Accurate control of the air demand leads to an optimum recovery of sulfur during the flow and composition fluctuations in the acid gas feed. Therefore, the major control system in the SRU is the air demand control loop, which includes a feed-forward control system based on predetermined feed flow rates and a feed-back control system based on the signal from the tail gas online analyzer. The use of online analyzers requires compliance with the installation and operation instructions. Unfortunately, most of these analyzers in Iran are out of service for different reasons, like the low importance of environmental issues and a lack of access to after-sales services due to sanctions. In this paper, an SRU in Iran was simulated and calibrated using industrial experimental data. Afterward, the effect of the malfunction of the online analyzer on the performance of SRU was investigated using the calibrated simulation. The results showed that an increase in the SO₂ concentration in the tail gas led to an increase in the temperature of the reduction reactor in the TGT section. This increase in temperature caused the failure of TGT and increased the concentration of SO₂ from 750 ppm to 35,000 ppm. In addition, the lack of a control system for the adjustment of the combustion air caused further increases in SO₂ emissions. In some processes, the major variable cannot be controlled directly due to difficulty in measurement or a long delay in the sampling system. In these cases, a secondary variable, which can be measured more easily, is considered to be controlled. With the correct selection of this variable, the main variable is also controlled along with the secondary variable. This strategy for controlling a process system is referred to as inferential control" and is considered in this paper. Therefore, a sensitivity analysis was performed to investigate the sensitivity of other measurable parameters to input disturbances. The results revealed that the output temperature of the first Claus reactor could be used for inferential control of the combustion air. Applying this method to the operation led to maximizing the sulfur recovery in the Claus section.

Keywords: sulfur recovery, online analyzer, inferential control, SO₂ emission

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Authors: Manal Osman

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Sprinkler irrigation system became more popular to reduce water consumption and increase irrigation efficiency. The water distribution uniformity plays an important role in the performance of the sprinkler irrigation system. The use of low operating pressure instead of high operating pressure can be achieved many benefits including energy and water saving. An experimental study was performed to investigate the water distribution uniformity of the solid-set sprinkler irrigation system under low operating pressure. Different low operating pressures (62, 82, 102 and 122 kPa) were selected. The range of operating pressure was lower than the recommended in the previous studies to investigate the effect of low pressure on the water distribution uniformity. Different nozzle diameters (4, 5, 6 and 7 mm) were used. The outdoor single sprinkler test was performed. The water distribution of single sprinkler, the coefficients of uniformity such as coefficient of uniformity (CU), distribution uniformity of low quarter (DUlq), distribution uniformity of low half (DUlh), coefficient of variation (CV) and the distribution characteristics like rotation speed, throw radius and overlapping distance are presented in this paper.

Keywords: low operating pressure, sprinkler irrigation system, water distribution uniformity

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Authors: Josip Vasilj, Petar Sarajcev, Damir Jakus

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One of the major difficulties introduced with wind power penetration is the inherent uncertainty in production originating from uncertain wind conditions. This uncertainty impacts many different aspects of power system operation, especially the balancing power requirements. For this reason, in power system development planing, it is necessary to evaluate the potential uncertainty in future wind power generation. For this purpose, simulation models are required, reproducing the performance of wind power forecasts. This paper presents a wind power forecast error simulation models which are based on the stochastic process simulation. Proposed models capture the most important statistical parameters recognized in wind power forecast error time series. Furthermore, two distinct models are presented based on data availability. First model uses wind speed measurements on potential or existing wind power plant locations, while the seconds model uses statistical distribution of wind speeds.

Keywords: wind power, uncertainty, stochastic process, Monte Carlo simulation

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Authors: Veronika Přivřelová

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Well-designed composite steel and concrete structures highlight the good material properties and lower the deficiencies of steel and concrete, in particular they make use of high tensile strength of steel and high stiffness of concrete. The most common composite steel and concrete structure is a simply supported beam, which concrete slab transferring the slab load to a beam is connected to the steel cross-section. The aim of this paper is to find the most adequate numerical model of a simply supported composite beam with the cross-sectional and material parameters based on the results of a processed parametric study and numerical analysis. The paper also evaluates the suitability of using compact concrete with the lightweight aggregates for composite steel and concrete beams. The most adequate numerical model will be used in the resent future to compare the results of laboratory tests.

Keywords: composite beams, high-performance concrete, high-strength steel, lightweight concrete slab, modeling

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Authors: Kriangkrai Maneerat, Chutima Prommak

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Indoor wireless localization systems have played an important role to enhance context-aware services. Determining the position of mobile objects in complex indoor environments, such as those in multi-floor buildings, is very challenging problems. This paper presents an effective floor estimation algorithm, which can accurately determine the floor where mobile objects located. The proposed algorithm is based on the confidence interval of the summation of online Received Signal Strength (RSS) obtained from the IEEE 802.15.4 Wireless Sensor Networks (WSN). We compare the performance of the proposed algorithm with those of other floor estimation algorithms in literature by conducting a real implementation of WSN in our facility. The experimental results and analysis showed that the proposed floor estimation algorithm outperformed the other algorithms and provided highest percentage of floor accuracy up to 100% with 95-percent confidence interval.

Keywords: floor estimation algorithm, floor determination, multi-floor building, indoor wireless systems

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Authors: Qiang Fu, Abu Saleh

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Research studies are highly fragmented when an innovation management framework is being discussed. With the aim to identify an innovation management framework/assessment tool suitable for small & medium enterprises (SMEs) in the service industry, this researcher critically reviewed existing innovation management frameworks and assessment models/tools and discovered a number of literature gaps. It is established that existing literature lacks generally agreed innovation management dimensions, commonly accepted knowledge creation through empirical studies on innovation management in SMEs, effective innovation management performance measurements, and studies on innovation management in the service industry, in particular in retail SMEs. As such, there is a dire need to develop an appropriate firm-level innovation management framework suitable for SMEs in the service industry for a future research project and further study. In addition, this researcher also discussed the significance of establishing such an innovation management framework.

Keywords: innovation management, innovation management framework, innovation management assessment tools, SMEs, service industry

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Authors: Elison Eduardo Jardim Bierhals, Claudineia Brazil, Rafael Haag, Elton Rossini

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This work aims to validate and make the projections of solar energy for the Brazilian period from 2025 to 2100. As the plants designed by the HadGEM2-AO (Global Hadley Model 2 - Atmosphere) General Circulation Model UK Met Office Hadley Center, belonging to Phase 5 of the Intercomparison of Coupled Models (CMIP5). The simulation results of the model are compared with monthly data from 2006 to 2013, measured by a network of meteorological sections of the National Institute of Meteorology (INMET). The performance of HadGEM2-AO is evaluated by the efficiency coefficient (CEF) and bias. The results are shown in the table of maps and maps. HadGEM2-AO, in the most pessimistic scenario, RCP 8.5 had a very good accuracy, presenting efficiency coefficients between 0.94 and 0.98, the perfect setting being Solar radiation, which indicates a horizontal trend, is a climatic alternative for some regions of the Brazilian scenario, especially in spring.

Keywords: climate change, projections, solar radiation, scenarios climate change

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Authors: Yao-Hong Tsai

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This paper presents an efficient fusion algorithm for iris images to generate stable feature for recognition in unconstrained environment. Recently, iris recognition systems are focused on real scenarios in our daily life without the subject’s cooperation. Under large variation in the environment, the objective of this paper is to combine information from multiple images of the same iris. The result of image fusion is a new image which is more stable for further iris recognition than each original noise iris image. A wavelet-based approach for multi-resolution image fusion is applied in the fusion process. The detection of the iris image is based on Adaboost algorithm and then local binary pattern (LBP) histogram is then applied to texture classification with the weighting scheme. Experiment showed that the generated features from the proposed fusion algorithm can improve the performance for verification system through iris recognition.

Keywords: image fusion, iris recognition, local binary pattern, wavelet

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Authors: Viriyavudh Sim, Woo Young Jung

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The failure of roof cladding mostly occurs due to the failing of the connection between claddings and purlins, which is the pull-out of the screw connecting the two parts when the pull-out load, i.e. typhoon, is higher than the resistance of the connection screw. As typhoon disasters in Korea are constantly on the rise, probability risk assessment (PRA) has become a vital tool to evaluate the performance of civil structures. In this study, we attempted to determine the fragility of roof cladding with the screw connection. Experimental study was performed to evaluate the pull-out resistance of screw joints between honeycomb panels and back frames. Subsequently, by means of Monte Carlo Simulation method, probability of failure for these types of roof cladding was determined. The results that the failure of roof cladding was depends on their location on the roof, for example, the edge most panel has the highest probability of failure.

Keywords: Monte Carlo Simulation, roof cladding, screw pull-out strength, wind fragility

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Authors: Sadia Nasrin Tisha, Mushfika Sharmin Rahman, Javier Orduz

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Machine learning is applied in a variety of fields throughout the world. The healthcare sector has benefited enormously from it. One of the most effective approaches for predicting human heart diseases is to use machine learning applications to classify data and predict the outcome as a classification. However, with the rapid advancement of quantum technology, quantum computing has emerged as a potential game-changer for many applications. Quantum algorithms have the potential to execute substantially faster than their classical equivalents, which can lead to significant improvements in computational performance and efficiency. In this study, we applied quantum machine learning concepts to predict coronary heart diseases from text data. We experimented thrice with three different features; and three feature sets. The data set consisted of 100 data points. We pursue to do a comparative analysis of the two approaches, highlighting the potential benefits of quantum machine learning for predicting heart diseases.

Keywords: quantum machine learning, SVM, QSVM, matrix product state

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Authors: Mladen Dragičević, Mirjana Pejić Bach, Vanja Šimičević

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The purpose of this paper is to develop models that would enable predicting student success. These models could improve allocation of students among colleges and optimize the newly introduced model of government subsidies for higher education. For the purpose of collecting data, an anonymous survey was carried out in the last year of undergraduate degree student population using random sampling method. Decision trees were created of which two have been chosen that were most successful in predicting student success based on two criteria: Grade Point Average (GPA) and time that a student needs to finish the undergraduate program (time-to-degree). Decision trees have been shown as a good method of classification student success and they could be even more improved by increasing survey sample and developing specialized decision trees for each type of college. These types of methods have a big potential for use in decision support systems.

Keywords: data mining, knowledge discovery in databases, prediction models, student success

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Authors: M. Shoukath Ali, Rajendra Prasad Singh

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Game Theory approaches and their application in improving the performance of Wireless Sensor Networks (WSNs) are discussed in this paper. The mathematical modeling and analysis of WSNs may have low success rate due to the complexity of topology, modeling, link quality, etc. However, Game Theory is a field, which can efficiently use to analyze the WSNs. Game Theory is related to applied mathematics that describes and analyzes interactive decision situations. Game theory has the ability to model independent, individual decision makers whose actions affect the surrounding decision makers. The outcome of complex interactions among rational entities can be predicted by a set of analytical tools. However, the rationality demands a stringent observance to a strategy based on measured of perceived results. Researchers are adopting game theory approaches to model and analyze leading wireless communication networking issues, which includes QoS, power control, resource sharing, etc.

Keywords: wireless sensor network, game theory, cooperative game theory, non-cooperative game theory

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Authors: Gaurav Malik, Satyendra Mourya, Jyoti Jaiswal, Ramesh Chandra

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The attractive and multifunctional properties of ZnO make it a promising material for the fabrication of highly sensitive and selective efficient gas sensors at room temperature. This presented article focuses on the development of highly selective and sensitive H₂ gas sensor based on the Pd-Pt decorated ZnO framework and its sensing mechanisms. The gas sensing performance of sputter made Pd-Pt/ZnO electrode on anodized porous silicon (PSi) substrate toward H₂ gas is studied under low detection limit (2–500 ppm) of H₂ in the air. The chemiresistive sensor demonstrated sublimate selectivity, good sensing response, and fast response/recovery time with excellent stability towards H₂ at low temperature operation under ambient environment. The elaborate selective measurement of Pd-Pt/ZnO/PSi structure was performed towards different oxidizing and reducing gases. This structure exhibited advance and reversible response to H₂ gas, which revealed that the acquired architecture with ZnO framework is a promising candidate for H₂ gas sensor.

Keywords: sputtering, porous silicon, ZnO framework, XPS spectra, gas sensor

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Authors: Fahed Alrshoudi

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Saudi Arabia is ranked the third of the largest suppliers of Dates worldwide (about 28.5 million palm trees), producing more than 2 million tons of dates yearly. These trees produce large quantity of dates palm seeds (DPS) which can be considered literally as a waste. The date seeds are stiff, therefore, it is possible to utilize DPS as coarse aggregates in lightweight concrete for certain structural applications and to participate at reusing the waste. The use of DPS as coarse aggregate in concrete can be an alternative choice as a partial replacement of the stone aggregates (SA). This paper reports the influence of partially replaced stone aggregates with DPS on the hardened properties of concrete performance. Based on the experimental results, the DPS has the potential use as an acceptable alternative aggregates in producing structural lightweight concrete members, instead of stone aggregates.

Keywords: compressive strength, tensile Strength, date palm seeds, aggregate

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Authors: Shahin Mirshekari, Mohammadreza Moradi, Hossein Jafari, Mehdi Jafari, Mohammad Ensaf

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This research employs Gaussian Process Regression (GPR) with an ensemble kernel, integrating Exponential Squared, Revised Matern, and Rational Quadratic kernels to analyze pharmaceutical sales data. Bayesian optimization was used to identify optimal kernel weights: 0.76 for Exponential Squared, 0.21 for Revised Matern, and 0.13 for Rational Quadratic. The ensemble kernel demonstrated superior performance in predictive accuracy, achieving an R² score near 1.0, and significantly lower values in MSE, MAE, and RMSE. These findings highlight the efficacy of ensemble kernels in GPR for predictive analytics in complex pharmaceutical sales datasets.

Keywords: Gaussian process regression, ensemble kernels, bayesian optimization, pharmaceutical sales analysis, time series forecasting, data analysis

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Authors: Brenden M. Shutt, Lubjana Beshaj, Paul L. Goethals, Ambrose Kam

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Communication security is of particular interest to military data networks. A relatively novel approach to network security is blockchain, a cryptographically secured distribution ledger with a decentralized consensus mechanism for data transaction processing. Recent advances in blockchain technology have proposed new techniques for both data validation and trust management, as well as different frameworks for managing dataflow. The purpose of this work is to test the feasibility of different blockchain architectures as applied to military command and control networks. Various architectures are tested through discrete-event simulation and the feasibility is determined based upon a blockchain design’s ability to maintain long-term stable performance at industry standards of throughput, network latency, and security. This work proposes a consortium blockchain architecture with a computationally inexpensive consensus mechanism, one that leverages a Proof-of-Identity (PoI) concept and a reputation management mechanism.

Keywords: blockchain, consensus mechanism, discrete-event simulation, fog computing

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