Search results for: diversity and business performance

Authors: Mehdi Asgarkhani

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Today, investment on Information Technology (IT) solutions in most organizations is the largest component of capital expenditure. As capital investment on IT continues to grow, IT managers and strategists are expected to develop and put in practice effective decision making models (frameworks) that improve decision-making processes for the use of IT in organizations and optimize the investment on IT solutions. To be exact, there is an expectation that organizations not only maximize the benefits of adopting IT solutions but also avoid the many pitfalls that are associated with rapid introduction of technological change. Different organizations depending on size, complexity of solutions required and processes used for financial management and budgeting may use different techniques for managing strategic investment on IT solutions. Decision making processes for strategic use of IT within organizations are often referred to as IT Governance (or Corporate IT Governance). This paper examines IT governance - as a tool for best practice in decision making about IT strategies. Discussions in this paper represent phase I of a project which was initiated to investigate trends in strategic decision making on IT strategies. Phase I is concerned mainly with review of literature and a number of case studies, establishing that the practice of IT governance, depending on the complexity of IT solutions, organization's size and organization's stage of maturity, varies significantly – from informal approaches to sophisticated formal frameworks.

Keywords: IT governance, corporate governance, IT governance frameworks, IT governance components, aligning IT with business strategies

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Authors: Jonathan Sohn

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Deep neural networks (DNNs) have shown state-of-the-art performance for many applications, including computer vision, natural language processing, and speech recognition. Recently, adversarial attacks have been studied in the context of deep neural networks, which aim to alter the results of deep neural networks by modifying the inputs slightly. For example, an adversarial attack on a DNN used for object detection can cause the DNN to miss certain objects. As a result, the reliability of DNNs is undermined by their lack of robustness against adversarial attacks, raising concerns about their use in safety-critical applications such as autonomous driving. In this paper, we focus on studying the adversarial attacks and defenses on DNNs for image classification. There are two types of adversarial attacks studied which are fast gradient sign method (FGSM) attack and projected gradient descent (PGD) attack. A DNN forms decision boundaries that separate the input images into different categories. The adversarial attack slightly alters the image to move over the decision boundary, causing the DNN to misclassify the image. FGSM attack obtains the gradient with respect to the image and updates the image once based on the gradients to cross the decision boundary. PGD attack, instead of taking one big step, repeatedly modifies the input image with multiple small steps. There is also another type of attack called the target attack. This adversarial attack is designed to make the machine classify an image to a class chosen by the attacker. We can defend against adversarial attacks by incorporating adversarial examples in training. Specifically, instead of training the neural network with clean examples, we can explicitly let the neural network learn from the adversarial examples. In our experiments, the digit recognition accuracy on the MNIST dataset drops from 97.81% to 39.50% and 34.01% when the DNN is attacked by FGSM and PGD attacks, respectively. If we utilize FGSM training as a defense method, the classification accuracy greatly improves from 39.50% to 92.31% for FGSM attacks and from 34.01% to 75.63% for PGD attacks. To further improve the classification accuracy under adversarial attacks, we can also use a stronger PGD training method. PGD training improves the accuracy by 2.7% under FGSM attacks and 18.4% under PGD attacks over FGSM training. It is worth mentioning that both FGSM and PGD training do not affect the accuracy of clean images. In summary, we find that PGD attacks can greatly degrade the performance of DNNs, and PGD training is a very effective way to defend against such attacks. PGD attacks and defence are overall significantly more effective than FGSM methods.

Keywords: deep neural network, adversarial attack, adversarial defense, adversarial machine learning

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Authors: Nabilah Filzah Mohd Radzuan, Zalinda Othman, Azuraliza Abu Bakar, Abdul Razak Hamdan

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Uncertain data is believed to be an important issue in building up a prediction model. The main objective in the time series uncertainty analysis is to formulate uncertain data in order to gain knowledge and fit low dimensional model prior to a prediction task. This paper discusses the performance of a number of techniques in dealing with uncertain data specifically those which solve uncertain data condition by minimizing the loss of compression properties.

Keywords: compression properties, uncertainty, uncertain time series, mining technique, weather prediction

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Authors: Eylem Güzel, Mustafa Gülen

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Historical structures are the most important symbols of a country that link the past with the future. In order to transfer them in their present conditions to the next generations, maintaining these historical structures are one of our main tasks. Seismic performance of historical structures damaged by the earthquake effects can be enhanced by repair and retrofitting applications. However, repair and retrofitting applications of historical structures are more complicated compared with the traditional structures. For this reason, they need much more attention in repair and retrofitting applications to preserve the spirit of historical structures. In this study, the present condition of selected historical structures built up in Van city that has a very rich historical heritage is given and the necessity of repair and retrofitting applications of historical structures are debated in detail.

Keywords: historical structures, repair, retrofitting, Van city

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Authors: Enhui Wang, Qingzhu Ou, Yan Tang, Xiaodong Guo

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As one of most popular polyanionic compounds in lithium-ion cathode materials, Li3V2(PO4)3 has always suffered from the low rate capability especially during 3~4.8V, which is considered to be related with the ion diffusion resistance and structural transformation during the Li+ de/intercalation. Here, as the change of cut-off voltages, cycling numbers and current densities, the process of SEI interfacial film’s formation-growing- destruction-repair on the surface of the cathode, the structural transformation during the charge and discharge, the de/intercalation kinetics reflected by the electrochemical impedance and the diffusion coefficient, have been investigated in detail. Current density, cycle numbers and cut-off voltage impacting on interfacial film and structure was studied specifically. Firstly, the matching between electrolyte and material was investigated, it turned out that the batteries with high voltage electrolyte showed the best electrochemical performance and high voltage electrolyte would be the best electrolyte. Secondly, AC impedance technology was used to study the changes of interface impedance and lithium ion diffusion coefficient, the results showed that current density, cycle numbers and cut-off voltage influenced the interfacial film together and the one who changed the interfacial properties most was the key factor. Scanning electron microscopy (SEM) analysis confirmed that the attenuation of discharge specific capacity was associated with the destruction and repair process of the SEI film. Thirdly, the X-ray diffraction was used to study the changes of structure, which was also impacted by current density, cycle numbers and cut-off voltage. The results indicated that the cell volume of Li3V2 (PO4 )3 increased as the current density increased; cycle numbers merely influenced the structure of material; the cell volume decreased first and moved back gradually after two Li-ion had been deintercalated as the charging cut-off voltage increased, and increased as the intercalation number of Li-ion increased during the discharging process. Then, the results which studied the changes of interface impedance and lithium ion diffusion coefficient turned out that the interface impedance and lithium ion diffusion coefficient increased when the cut-off voltage passed the voltage platforms and decreased when the cut-off voltage was between voltage platforms. Finally, three-electrode system was first adopted to test the activation energy of the system, the results indicated that the activation energy of the three-electrode system (22.385 KJ /mol) was much smaller than that of two-electrode system (40.064 KJ /mol).

Keywords: cut-off voltage, de/intercalation kinetics, solid electrolyte interphase film, structural transformation

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Authors: Amal E. Ahmed, Levent Trabzon

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Due to the low concentration of the analytes in biological samples, the use of Biological Microelectromechanical System (Bio-MEMS) biosensors for biomolecules detection results in a minuscule output signal that is not good enough for practical applications. In response to this, a need has arisen for an optimized biosensor capable of giving high output signal in response the detection of few analytes in the sample; the ultimate goal is being able to convert the attachment of a single biomolecule into a measurable quantity. For this purpose, MEMS microcantilevers based biosensors emerged as a promising sensing solution because it is simple, cheap, very sensitive and more importantly does not need analytes optical labeling (Label-free). Among the different microcantilever transducing techniques, piezoresistive based microcantilever biosensors became more prominent because it works well in liquid environments and has an integrated readout system. However, the design of piezoresistive microcantilevers is not a straightforward problem due to coupling between the design parameters, constraints, process conditions, and performance. It was found that the parameters that can be optimized to enhance the sensitivity of Piezoresistive microcantilever-based sensors are: cantilever dimensions, cantilever material, cantilever shape, piezoresistor material, piezoresistor doping level, piezoresistor dimensions, piezoresistor position, Stress Concentration Region's (SCR) shape and position. After a systematic analyzation of the effect of each design and process parameters on the sensitivity, a step-wise optimization approach was developed in which almost all these parameters were variated one at each step while fixing the others to get the maximum possible sensitivity at the end. At each step, the goal was to optimize the parameter in a way that it maximizes and concentrates the stress in the piezoresistor region for the same applied force thus get the higher sensitivity. Using this approach, an optimized sensor that has 73.5x times higher electrical sensitivity (ΔR⁄R) than the starting sensor was obtained. In addition to that, this piezoresistive microcantilever biosensor it is more sensitive than the other similar sensors previously reported in the open literature. The mechanical sensitivity of the final senior is -1.5×10-8 Ω/Ω ⁄pN; which means that for each 1pN (10-10 g) biomolecules attach to this biosensor; the piezoresistor resistivity will decrease by 1.5×10-8 Ω. Throughout this work COMSOL Multiphysics 5.0, a commercial Finite Element Analysis (FEA) tool, has been used to simulate the sensor performance.

Keywords: biosensor, microcantilever, piezoresistive, stress concentration region (SCR)

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Authors: T. Vamsee Kiran, A. Gopi

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The undesired torque and flux ripple may occur in conventional direct torque control (DTC) induction motor drive. DTC can improve the system performance at low speeds by continuously tuning the regulator by adjusting the Kp, Ki values. In this differential evolution (DE) is proposed to adjust the parameters (Kp, Ki) of the speed controller in order to minimize torque ripple, flux ripple, and stator current distortion.The DE based PI controller has resulted is maintaining a constant speed of the motor irrespective of the load torque fluctuations.

Keywords: differential evolution, direct torque control, PI controller

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Authors: Natalie Rinfret, Francine Tougas, Ann Beaton

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Conventions No. 100 and 111 of the International Labor Organization, passed in 1951 and 1958 respectively, established the principles of equal pay for men and women for work of equal value and freedom from discrimination in employment. Governments of different countries followed suit. For example, in 1964, the Civil Rights Act was passed in the United States and in 1972, Canada ratified Convention 100. Thus, laws were enacted and programs were implemented to combat discrimination in the workplace and, over time, more than 90% of the member countries of the International Labour Organization have ratified these conventions by implementing programs such as employment equity in Canada aimed at groups recognized as being discriminated against in the labor market, including women. Although legislation has been in place for several decades, employment discrimination has not gone away. In this study, we pay particular attention to the hidden side of the effects of employment discrimination. This is the emergence of subtle forms of discrimination that often fly under the radar but nevertheless, have adverse effects on the attitudes and behaviors of members of targeted groups. Researchers have identified two forms of racial and gender bias. On the one hand, there are traditional prejudices referring to beliefs about the inferiority and innate differences of women and racial minorities compared to White men. They have the effect of confining these two groups to job categories suited to their perceived limited abilities and can result in degrading, if not violent and hateful, language and actions. On the other hand, more subtle prejudices are more suited to current social norms. However, this subtlety harbors a conflict between values of equality and remnants of negative beliefs and feelings toward women and racial minorities. Our literature review also takes into account an overlooked part of the groups targeted by the programs in place, senior workers, and highlights the quantifiable and observable effects of prejudice and discriminatory behaviors in employment. The study proposes a hybrid model of interventions, taking into account the organizational system (employment equity practices), discriminatory attitudes and behaviors, and the type of leadership to be advocated. This hybrid model includes, in the first instance, the implementation of initiatives aimed at both promoting employment equity and combating discrimination and, in the second instance, the establishment of practices that foster inclusion, the full and complete participation of all, including seniors, in the mission of their organization.

Keywords: employment discrimination, gender bias, the hybrid model of interventions, senior workers

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Authors: Fateme Mazbanpoor, Sayed Mohammad Amiri

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In this article, we will examine the Persian words in Quran and study the reasons of their presence in this holy book. Writers of this paper extracted about 70 Persian words of Quran by referring to resources. (Alalfaz ol Moarab ol Farsieh Edishir, Almoarabol Javalighi, Almahzab va Etghan Seuti; Vocabulary involved in Quran Arthur Jeffry;, and etc…), some of these words are: ‘Abarigh, ‘Estabragh’,’Barzakh’, ‘Din’,’Zamharir, ‘Sondos’ ‘Sejil’,’ Namaregh’, ‘Fil’ etc. These Persian words have entered Arabic and finally entered Quran in two ways: 1) directly from Persian language, 2) via other languages. The first way: because of the Iranian dominance on Hira, Yemen, whole Oman and Bahrein land in Sasanian period, there were political, religious, linguistic, literary, and trade ties between these Arab territories causing the impact of Persian on Arabic; giving way to many Persian-loan words into Arabic in this period of time. The second way: Since the geographical and business conditions of the areas were dominated by Iran, Hejaz had lots of deals and trades with Mesopotamia and Yemen. On the other hand, Arabic language which was relatively a young language at that time, used to be impressed by Semitic languages in order to expand its vocabulary (Syrian and Aramaic were influenced by the languages of Iran). Consequently, due to the long relationship between Iranian and Arabs, some of the Persian words have taken longer ways through Aramaic and Syrian to find their way into Quran.

Keywords: Quran, Persian word, Arabic language, Persian

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Authors: Z. Abdessemed, N. Messaâdia, M. Houhamdi

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The PAH (Polycyclic Aromatic Hydrocarbons) represent a persistent source of pollution for oil field soils. Their degradation, essentially dominated by the aerobic bacterial and fungal flora, exhibits certain aspects for remediation of these soils microbial oxygenases have, as their substrates, a large range of PAH. The variety and the performance of these enzymes allow the initiation of the biodegradation of any PAH through many different metabolic pathways. These pathways are very important for the recycling of the PAH in the biosphere, where substances supposed indigestible by living organisms are rapidly transformed into simples compounds, directly assimilated by the intermediate metabolism of other microorganisms.

Keywords: polycyclic aromatic hydrocarbons, microbial oxygenases, biodegradation, metabolic pathways

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Authors: Berker Bayazit, Gulgun Kayakutlu

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The World Energy Outlook shows that energy markets will substantially change within a few forthcoming decades. First, determined action plans according to COP21 and aim of CO₂ emission reduction have already impact on policies of countries. Secondly, swiftly changed technological developments in the field of renewable energy will be influential upon medium and long-term energy generation and consumption behaviors of countries. Furthermore, share of electricity on global energy consumption is to be expected as high as 40 percent in 2040. Electrical vehicles, heat pumps, new electronical devices and digital improvements will be outstanding technologies and innovations will be the testimony of the market modifications. In order to meet highly increasing electricity demand caused by technologies, countries have to make new investments in the field of electricity production, transmission and distribution. Specifically, electricity generation mix becomes vital for both prevention of CO₂ emission and reduction of power prices. Majority of the research and development investments are made in the field of electricity generation. Hence, the prime source diversity and source planning of electricity generation are crucial for improving the wealth of citizen life. Approaches considering the CO₂ emission and total cost of generation, are necessary but not sufficient to evaluate and construct the product mix. On the other hand, employment and positive contribution to macroeconomic values are important factors that have to be taken into consideration. This study aims to constitute new investments in renewable energies (solar, wind, geothermal, biogas and hydropower) between 2018-2023 under 4 different goals. Therefore, a multi-objective programming model is proposed to optimize the goals of minimizing the CO₂ emission, investment amount and electricity sales price while maximizing the total employment and positive contribution to current deficit. In order to avoid the user preference among the goals, Dinkelbach’s algorithm and Guzel’s approach have been combined. The achievements are discussed with comparison to the current policies. Our study shows that new policies like huge capacity allotment might be discussible although obligation for local production is positive. The improvements in grid infrastructure and re-design support for the biogas and geothermal can be recommended.

Keywords: energy generation policies, multi-objective linear programming, portfolio planning, renewable energy

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Authors: Tanzeel Ur Rehman Khan, Franz Josef Behr, Phillip Davis

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Open source geospatial certifications are needed in geospatial technology education and industry sector. In parallel with proprietary software, free and open source software solutions become important in geospatial technology research and play an important role for the growth of the geospatial industry. ESRI, GISCI (GIS Certification Institute), ASPRS (American Society of Photogrammetry and remote sensing), and Meta spatial are offering certifications on proprietary and open source software. These are portfolio and competency based certifications depending on GIS Body of Knowledge (Bok). The analysis of these certification approaches might lead to the discovery of some gaps in them and will open a new way to develop certifications related to the geospatial open source (OS). This new certification will investigate the different geospatial competencies according to open source tools that help to identify geospatial professionals and strengthen the geospatial academic content. The goal of this research is to introduce a geospatial certification model based on geospatial technology competency model (GTCM).The developed certification will not only incorporate the importance of geospatial education and production of the geospatial competency-based workforce in universities and companies (private or public) as well as describe open source solutions with tools and technology. Job analysis, market analysis, survey analysis of this certification opens a new horizon for business as well.

Keywords: geospatial certification, open source, geospatial technology competency model, geoscience

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Authors: Rajesh Karki, Safal Bhattarai, Saket Adhikari

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Reliable and economic operation of power systems are becoming extremely challenging with large scale integration of renewable energy sources due to the intermittency and uncertainty associated with renewable power generation. It is, therefore, important to make a quantitative risk assessment and explore the potential resources to mitigate such risks. Probabilistic models for different energy storage systems (ESS), such as the flywheel energy storage system (FESS) and the compressed air energy storage (CAES) incorporating specific charge/discharge performance and failure characteristics suitable for probabilistic risk assessment in power system operation and planning are presented in this paper. The proposed methodology used in FESS modelling offers flexibility to accommodate different configurations of plant topology. It is perceived that CAES has a high potential for grid-scale application, and a hybrid approach is proposed, which embeds a Monte-Carlo simulation (MCS) method in an analytical technique to develop a suitable reliability model of the CAES. The proposed ESS models are applied to a test system to investigate the economic and reliability benefits of the energy storage technologies in system operation and planning, as well as to assess their contributions in facilitating wind integration during different operating scenarios. A comparative study considering various storage system topologies are also presented. The impacts of failure rates of the critical components of ESS on the expected state of charge (SOC) and the performance of the different types of ESS during operation are illustrated with selected studies on the test system. The paper also applies the proposed models on the test system to investigate the economic and reliability benefits of the different ESS technologies and to evaluate their contributions in facilitating wind integration during different operating scenarios and system configurations. The conclusions drawn from the study results provide valuable information to help policymakers, system planners, and operators in arriving at effective and efficient policies, investment decisions, and operating strategies for planning and operation of power systems with large penetrations of renewable energy sources.

Keywords: flywheel energy storage, compressed air energy storage, power system reliability, renewable energy, system planning, system operation

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Authors: Pranav Gunhal., Krish Jhurani

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This study tackles the significant computational challenge of predicting excited state dynamics in organic photovoltaic (OPV) materials—a pivotal factor in the performance of solar energy solutions. Time-dependent density functional theory (TDDFT), though effective, is computationally prohibitive for larger and more complex molecules. As a solution, the research explores the application of transformer neural networks, a type of artificial intelligence (AI) model known for its superior performance in natural language processing, to predict excited state dynamics in OPV materials. The methodology involves a two-fold process. First, the transformer model is trained on an extensive dataset comprising over 10,000 TDDFT calculations of excited state dynamics from a diverse set of OPV materials. Each training example includes a molecular structure and the corresponding TDDFT-calculated excited state lifetimes and key electronic transitions. Second, the trained model is tested on a separate set of molecules, and its predictions are rigorously compared to independent TDDFT calculations. The results indicate a remarkable degree of predictive accuracy. Specifically, for a test set of 1,000 OPV materials, the transformer model predicted excited state lifetimes with a mean absolute error of 0.15 picoseconds, a negligible deviation from TDDFT-calculated values. The model also correctly identified key electronic transitions contributing to the excited state dynamics in 92% of the test cases, signifying a substantial concordance with the results obtained via conventional quantum chemistry calculations. The practical integration of the transformer model with existing quantum chemistry software was also realized, demonstrating its potential as a powerful tool in the arsenal of materials scientists and chemists. The implementation of this AI model is estimated to reduce the computational cost of predicting excited state dynamics by two orders of magnitude compared to conventional TDDFT calculations. The successful utilization of transformer neural networks to accurately predict excited state dynamics provides an efficient computational pathway for the accelerated discovery and design of new OPV materials, potentially catalyzing advancements in the realm of sustainable energy solutions.

Keywords: transformer neural networks, organic photovoltaic materials, excited state dynamics, time-dependent density functional theory, predictive modeling

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Authors: Amir Farouk Ahmed Ali Hussin

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Social media, such as Facebook, LinkedIn and Ex-Twitter have experienced exponential growth and a remarkable adoption rate in recent years. They give fantastic means of online social interactions and communications with family, friends, and colleagues from around the corner or across the globe, and they have become an important part of daily digital interactions for more than one and a half billion users around the world. The personal information sharing practices that social network providers encourage have led to their success as innovative social interaction platforms. Moreover, these practices have outcome in concerns with respect to privacy and security from different stakeholders. Guiding these privacy and security concerns in social networks is a must for these networks to be sustainable. Real security and privacy tools may not be enough to address existing concerns. Some points should be followed to protect users from the existing risks. In this research, we have checked the various privacy and security issues and concerns pertaining to social media. However, we have classified these privacy and security issues and presented a thorough discussion of the effects of these issues and concerns on the future of the social networks. In addition, we have presented a set of points as precaution measures that users can consider to address these issues.

Keywords: international legal, consultation mix, legal research, small and medium-sized enterprises, strategic International law, strategy alignment, house of laws, deployment, production strategy, legal strategy, business strategy

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Authors: Tim Nedyalkov

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A business decision to move to the cloud brings fundamental changes in how an organization develops and delivers its Information Technology solutions. The accelerated pace of digital transformation across businesses and government agencies increases the reliance on cloud-based services. They are collecting, managing, and retaining large amounts of data in cloud environments makes information security and data privacy protection essential. It becomes even more important to understand what key factors drive successful cloud adoption following the commencement of the Privacy Amendment Notifiable Data Breaches (NDB) Act 2017 in Australia as the regulatory changes impact many organizations and industries. This quantitative correlational research investigated the governance, risk management, and compliance factors contributing to cloud security success. The factors influence the adoption of cloud computing within an organizational context after the commencement of the NDB scheme. The results and findings demonstrated that corporate information security policies, data storage location, management understanding of data governance responsibilities, and regular compliance assessments are the factors influencing cloud computing adoption. The research has implications for organizations, future researchers, practitioners, policymakers, and cloud computing providers to meet the rapidly changing regulatory and compliance requirements.

Keywords: cloud compliance, cloud security, data governance, privacy protection

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Authors: Thiago Fabrizio Gavilano Farje, Marcelo Patricio Herrera Malpartida

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This study examines the influence of artificial intelligence (AI) on the work efficiency of administrative employees in the financial sector of Metropolitan Lima, Peru, during the year 2024. Focusing on the relationship between AI implementation and work efficiency, it addresses specific variables such as decision-making, motivation, and employee productivity. To accomplish the analysis between AI and work efficiency within the financial sector of Metropolitan Lima, it is necessary to evaluate how AI optimizes time in administrative tasks, examine how AI impacts the agility of the process of making decisions, and investigate the influence of AI on the satisfaction and motivation of employees. The research adopts a correlational and explanatory approach, designed to establish and understand the connections between AI and work efficiency. A survey design adapted from an OECD study is used, applying questionnaires to a representative sample of administrative workers in the financial sector who incorporate AI into their functions. The target population includes administrative workers in the financial sector of Metropolitan Lima, estimated at 73,097 employees based on data from the Censo Nacional de Empresas y Establecimientos and studies by the BCRP. The sample, selected through simple random sampling, comprises 246 workers.

Keywords: business management, artificial intelligence, decision making, labor efficiency, financial sector

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Authors: Mrinal Kanti Bhowmik, Shawli Bardhan Jr., Debotosh Bhattacharjee

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Human skin containing temperature value more than absolute zero, discharges infrared radiation related to the frequency of the body temperature. The difference in infrared radiation from the skin surface reflects the abnormality present in human body. Considering the difference, detection and forecasting the temperature variation of the skin surface is the main objective of using Medical Infrared Thermography(MIT) as a diagnostic tool for pain detection. Medical Infrared Thermography(MIT) is a non-invasive imaging technique that records and monitors the temperature flow in the body by receiving the infrared radiated from the skin and represent it through thermogram. The intensity of the thermogram measures the inflammation from the skin surface related to pain in human body. Analysis of thermograms provides automated anomaly detection associated with suspicious pain regions by following several image processing steps. The paper represents a rigorous study based survey related to the processing and analysis of thermograms based on the previous works published in the area of infrared thermal imaging for detecting inflammatory pain diseases like arthritis, spondylosis, shoulder impingement, etc. The study also explores the performance analysis of thermogram processing accompanied by thermogram acquisition protocols, thermography camera specification and the types of pain detected by thermography in summarized tabular format. The tabular format provides a clear structural vision of the past works. The major contribution of the paper introduces a new thermogram acquisition standard associated with inflammatory pain detection in human body to enhance the performance rate. The FLIR T650sc infrared camera with high sensitivity and resolution is adopted to increase the accuracy of thermogram acquisition and analysis. The survey of previous research work highlights that intensity distribution based comparison of comparable and symmetric region of interest and their statistical analysis assigns adequate result in case of identifying and detecting physiological disorder related to inflammatory diseases.

Keywords: acquisition protocol, inflammatory pain detection, medical infrared thermography (MIT), statistical analysis

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Authors: Taba Tath

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Arunachal Pradesh, located in the easternmost part of India, is known for its natural beauty and diverse tribal lifestyles. The state has the highest species richness and biological diversity among Northeast states in terms of flora, fauna, and tribal traditions and culture. The protection of nature and culture is a practice that is widely used by governments or nongovernmental organizations seeking to preserve the scenic beauty of landscapes and their natural resources in spaces that stand out for their natural and cultural value and have not been heavily impacted by human activity. The whole of Arunachal Pradesh comes under the purview of special permits such as the Inner Line Permit (ILP) and Protected Area Permit (PAP) for domestic and foreign travellers, respectively. Due to politically vibrant areas and naturally fragile in nature, the state needs to be protected, but at the same time, the demand for tourism activities is increasing gradually due to its unique blend of nature and socio-cultural richness. There are 13 protected areas in the state which is unexplored, and there are no tourism activities in these protected areas except for Namdapha National Park. Out of 13 protected areas, the Pakke Wildlife Sanctuary is one of the well-managed protected areas located near the Assam-Arunachal border, approximately 40km away from Tezpur town, Assam. The state has great potential for wildlife and nature-based tourism development, which can also indirectly support wildlife and nature-based livelihood options for the local inhabitants living in the peripheral of the sanctuary area due to its high richness in terms of flora and fauna. To promote the richness of the state, boost tourism, and the economic, social and environmental development of the area and local communities, a proper tourism management practice and framework are very much required. The research paper has made an attempt to study the role of stakeholders in preserving and promoting the Protected Areas for tourism development in a sustainable way. This is both a primary and secondary study conducted with field visits, interaction, questionnaire and observation with the various stakeholders and also conducted with the Government reports, magazines and other published sources available. Furthermore, this study will be relevant to all stakeholders for having knowledge and processes for promoting tourism in Protected Areas in a sustainable way. The results will provide relevant information and process for the management and promotion of the protected Areas and to strengthen the sustainable tourism activities in these areas.

Keywords: protected area, inner line permit, protected area permit, management, government, nongovernmental organization, stakeholders, sustainable, natural resources

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Authors: Sadeq Al Yaari, Muhammad Alkhunayn, Sajedah Al Yaari, Adham Al Yaari, Ayman Al Yaari, Montaha Al Yaari, Ayah Al Yaari, Fatehi Eissa

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Dysgraphia is a neurological disorder of written expression that impairs writing ability and fine motor skills, resulting primarily in problems relating not only to handwriting but also to writing coherence and cohesion. We investigate the properties of smart writing technology to highlight some unique features of the effects they cause on the academic performance of pupils with dysgraphia. In Amis, dysgraphics undergo writing problems to express their ideas due to ordinary writing aids, as the default strategy. The Amis data suggests a possible connection between available writing aids and pupils’ writing improvement; therefore, texts’ expression and comprehension. A group of thirteen dysgraphic pupils were placed in a regular classroom of primary school, with twenty-one pupils being recruited in the study as a control group. To ensure validity, reliability and accountability to the research, both groups studied writing courses for two semesters, of which the first was equipped with smart writing aids while the second took place in an ordinary classroom. Two pre-tests were undertaken at the beginning of the first two semesters, and two post-tests were administered at the end of both semesters. Tests examined pupils’ ability to write coherent, cohesive and expressive texts. The dysgraphic group received the treatment of a writing course in the first semester in classes with smart technology and produced significantly greater increases in writing expression than in an ordinary classroom, and their performance was better than that of the control group in the second semester. The current study concludes that using smart teaching aids is a ‘MUST’, both for teaching and learning dysgraphia. Furthermore, it is demonstrated that for young dysgraphia, expressive tasks are more challenging than coherent and cohesive tasks. The study, therefore, supports the literature suggesting a role for smart educational aids in writing and that smart writing techniques may be an efficient addition to regular educational practices, notably in special educational institutions and speech-language therapeutic facilities. However, further research is needed to prompt the adults with dysgraphia more often than is done to the older adults without dysgraphia in order to get them to finish the other productive and/or written skills tasks.

Keywords: smart technology, writing aids, pupils with dysgraphia, hands’ movement

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Authors: V. M. Levshakov, N. A. Steshenkova, N. A. Nosyrev

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Application of hulls processing technologies, based on high-concentrated energy sources (laser and plasma technologies), allow improve shipbuilding production. It is typical for high-speed vessels construction using steel and aluminum alloys with high precision hulls required. Report describes high-performance technologies for plasma welding (using direct current of reversed polarity), laser, and hybrid laser-arc welding of hulls structures developed by JSC “SSTC”.

Keywords: flat sections, hybrid laser-arc welding, plasma welding, plasmatron

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Authors: L. Alejandro Cárdenas, Fernando Herrera, David Nova, Juan Ballesteros

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This paper presents a methodology to optimize the maintenance of grid-connected photovoltaic systems, considering the cleaning and module replacement periods based on an asset management strategy. The methodology is based on the analysis of the energy production of the PV plant, the energy feed-in tariff, and the cost of cleaning and replacement of the PV modules, with the overall revenue received being the optimization variable. The methodology is evaluated as a case study of a 5.6 kWp solar PV plant located on the Bogotá campus of the Universidad Nacional de Colombia. The asset management strategy implemented consists of assessing the PV modules through visual inspection, energy performance analysis, pollution, and degradation. Within the visual inspection of the plant, the general condition of the modules and the structure is assessed, identifying dust deposition, visible fractures, and water accumulation on the bottom. The energy performance analysis is performed with the energy production reported by the monitoring systems and compared with the values estimated in the simulation. The pollution analysis is performed using the soiling rate due to dust accumulation, which can be modelled by a black box with an exponential function dependent on historical pollution values. The pollution rate is calculated with data collected from the energy generated during two years in a photovoltaic plant on the campus of the National University of Colombia. Additionally, the alternative of assessing the temperature degradation of the PV modules is evaluated by estimating the cell temperature with parameters such as ambient temperature and wind speed. The medium-term energy decrease of the PV modules is assessed with the asset management strategy by calculating the health index to determine the replacement period of the modules due to degradation. This study proposes a tool for decision making related to the maintenance of photovoltaic systems. The above, projecting the increase in the installation of solar photovoltaic systems in power systems associated with the commitments made in the Paris Agreement for the reduction of CO2 emissions. In the Colombian context, it is estimated that by 2030, 12% of the installed power capacity will be solar PV.

Keywords: asset management, PV module, optimization, maintenance

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Authors: Tai Chen, Caihuan Tian, Xiuxia Ren, Jingqi Xue, Xiuxin Zhang

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The herbaceous peony has become increasingly popular worldwide in recent years, especially as a cut flower with great economic value. However, peony has a very short vase life, only 3-5 d usually, which seriously affects its commodity value. In this study, we used the cut peony (Paeonia lactiflora cv. Sarah) as a material and found that melatonin treatment significantly improved its postharvest performance. In the control group, its vase life was 4.8 d, accompanied by petal dropping at last; melatonin treatment (40 μM) increased this time to 6.9 d without petal dropping at the end. Further study showed that melatonin treatment significantly increased the activity of antioxidant enzymes as well as reduced sugar content in petals, whereas the starch content in petals decreased. These results indicated that melatonin treatment may delay the oxidation reaction caused by aging, which also provides extra energy for maintaining flowering. Through full-length transcriptome sequencing, a total of 2819 differentially expressed genes (DEGs) between control and melatonin treatment groups were identified. KEGG enrichment analysis showed that these DEGs were mainly involved in three pathways, including melatonin synthesis, starch and sucrose conversion, and plant disease resistance. After the RT-qPCR verification, we identified three DEGs, named PlBAM3, PlWRKY22 and PlTIP1, and they should play major roles in melatonin-improved postharvest performance. One possible reason is that PlBAM3 caused maltose production (by starch degradation), maintained the proline biosynthesis, and then alleviated oxidative stress. Another reason is that both PlBAM3 and PlWRKY22 are key drought resistance regulators, which have the ability to alleviate osmotic stress and improve water absorption, which may also help to improve the postharvest quality of cut peony. In addition, PlTIP1 is involved in the sugar signal pathway, indicating sugar may also as a signal substance during this process. Our work may give new ideas for developing new ways to prolong the vase life of cut peony and improve its commodity value eventually.

Keywords: cut peony, melatonin, vase life, oxidation reaction, energy supply, differentially expressed genes

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Authors: Natalia Carolina Encalada Castillo

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As part of an intended radical policy change compared to former administrations in Ecuador, the transformation of the institutionality of international cooperation during the period of President Rafael Correa was considered as a key element for the construction of the state of 'Good Living'. This intention led to several regulatory changes in the reception of cooperation for development, and even the departure of some foreign cooperation agencies. Moreover, Ecuador launched the initiative to become a donor of cooperation towards other developing countries through the ‘South-South Cooperation’ approach. All these changes were institutionalized through the Ecuadorian System of International Cooperation as a new framework to establish rules and policies that guarantee a sovereign management of foreign aid. Therefore, this research project has been guided by two questions: What were the factors that motivated the transformation of the institutionality of international cooperation in Ecuador from 2007 to 2017? and, what were the implications of this transformation in terms of the international role of the country? This paper seeks to answer these questions through Role Theory within a Constructivist meta-theoretical perspective, considering that in this case, changes at the institutional level in the field of cooperation, responded not only to material motivations but also to interests built on the basis of a specific state identity. The latter was only possible to affirm through specific roles such as ‘sovereign recipient of cooperation’ as well as ‘donor of international cooperation’. However, the performance of these roles was problematic as they were not easily accepted by the other actors in the international arena or in the domestic level. In terms of methodology, these dynamics are analyzed in a qualitative way mainly through interpretive analysis of the discourse of high-level decision-makers from Ecuador and other cooperation actors. Complementary to this, document-based research of relevant information as well as interviews have been conducted. Finally, it is concluded that even if material factors such as infrastructure needs, trade and investment interests, as well as reinforcement of state control and monitoring of cooperation flows, motivated the institutional transformation of international cooperation in Ecuador; the essential basis of these changes was the search for a new identity for the country to be projected in the international arena. This identity started to be built but continues to be unstable. Therefore, it is important to potentiate the achievements of the new international cooperation policies, and review their weaknesses, so that non-reimbursable cooperation funds received as well as ‘South-South cooperation’ actions, contribute effectively to national objectives.

Keywords: Ecuador, international cooperation, Role Theory, state identity

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Authors: Sourabh Jain, S. S. Jain

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Intelligent transportation system (ITS) is the application of technologies for developing a user–friendly transportation system to extend the safety and efficiency of urban transportation systems in developing countries. These systems involve vehicles, drivers, passengers, road operators, managers of transport services; all interacting with each other and the surroundings to boost the security and capacity of road systems. The goal of urban corridor management using ITS in road transport is to achieve improvements in mobility, safety, and the productivity of the transportation system within the available facilities through the integrated application of advanced monitoring, communications, computer, display, and control process technologies, both in the vehicle and on the road. Intelligent transportation system is a product of the revolution in information and communications technologies that is the hallmark of the digital age. The basic ITS technology is oriented on three main directions: communications, information, integration. Information acquisition (collection), processing, integration, and sorting are the basic activities of ITS. In the paper, attempts have been made to present the endeavor that was made to interpret and evaluate the performance of the 27.4 Km long study corridor having eight intersections and four flyovers. The corridor consisting of six lanes as well as eight lanes divided road network. Two categories of data have been collected such as traffic data (traffic volume, spot speed, delay) and road characteristics data (no. of lanes, lane width, bus stops, mid-block sections, intersections, flyovers). The instruments used for collecting the data were video camera, stop watch, radar gun, and mobile GPS (GPS tracker lite). From the analysis, the performance interpretations incorporated were the identification of peak and off-peak hours, congestion and level of service (LOS) at midblock sections and delay followed by plotting the speed contours. The paper proposed the urban corridor management strategies based on sensors integrated into both vehicles and on the roads that those have to be efficiently executable, cost-effective, and familiar to road users. It will be useful to reduce congestion, fuel consumption, and pollution so as to provide comfort, safety, and efficiency to the users.

Keywords: ITS strategies, congestion, planning, mobility, safety

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Authors: Si-Gwan Kim

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Small-size and low-power sensors with sensing, signal processing and wireless communication capabilities is suitable for the wireless sensor networks. Due to the limited resources and battery constraints, complex routing algorithms used for the ad-hoc networks cannot be employed in sensor networks. In this paper, we propose node-disjoint multi-path hexagon-based routing algorithms in wireless sensor networks. We suggest the details of the algorithm and compare it with other works. Simulation results show that the proposed scheme achieves better performance in terms of efficiency and message delivery ratio.

Keywords: clustering, multi-path, routing protocol, sensor network

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Authors: Kimuli Ismail, Michael Lubwama, John Baptist Kirabira, Adam Sebbit

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This study develops 4 energy scenarios for Greater Kampala Metropolitan Area (GKMA). GKMA is Uganda’s capital with a population of 4.1million and a GDP growth rate of 5.8 with a nonsustainable energy management system. The study uses TIMES-VEDA to examine the energy impacts of business as usual (BAU), Kabejja, Carbon-Tax, and Lutta scenarios in commercial, industrial, transportation, residential, agricultural, and electricity generation activities. BAU is the baseline scenario with limited CO2 emissions restrictions against which Kabejja with 20% CO2 emissions restriction, a carbon tax of $100/ton imposed in 2050 for Carbon-Tax scenario, and Lutta with 95% CO2 emissions restriction is made. The analysis suggests that if the current policy trends continue as BAU, consumption would increase from 139.6PJ to 497.42PJ and CO2 emissions will increase from 4.6mtns to 7mtns. However, consumption would decrease by 2.3% in Kabejja, 3.4% in Carbon-Tax, and 3.3 % in Lutta compared to BAU. The CO2 emissions would decrease by 8.57% in Kabejja, 55.14% in Carbon-Tax, and 60% in Lutta compared to BAU. Sustainability is achievable when low-carbon electricity is increased by 53.68% in the EMS, and setting up an electrified Kampala metro. The study recommends Lutta as the sustainable pathway to a lowcarbon 2050.

Keywords: Sustainability, Scenario Plannnig, Times-Veda Modelling, Energy Policy Development

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Authors: Kaewkarn Phuangsombat, Arthit Phuangsombat, Anupun Terdwongworakul

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Hard seeds will not grow and can cause mold in sprouting process. Thus, the hard seeds need to be separated from the normal seeds. Near infrared hyperspectral imaging in a range of 900 to 1700 nm was implemented to develop a model by partial least squares discriminant analysis to discriminate the hard seeds from the normal seeds. The orientation of the seeds was also studied to compare the performance of the models. The model based on hilum-up orientation achieved the best result giving the coefficient of determination of 0.98, and root mean square error of prediction of 0.07 with classification accuracy was equal to 100%.

Keywords: mung bean, near infrared, germinatability, hard seed

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Authors: Mohammad Alhajeri

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This paper reports a computational fluid dynamics (CFD) investigation of cylindrical filter. Silicon carbide cylindrical filter elements have proven to be an effective mean of removing particulates to levels exceeding the new source performance standard. The CFD code is used here to understand the deposition process and the factors that affect the particles distribution over the filter element surface. Different approach cross flow velocity to filter face velocity ratios and different face velocities (ranging from 2 to 5 cm/s) are used in this study. Particles in the diameter range 1 to 100 microns are tracked through the domain. The radius of convergence (or the critical trajectory) is compared and plotted as a function of many parameters.

Keywords: filtration, CFD, CCF, hot gas filtration

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Authors: Khaled A. Alsaif, Mosaad A. Foda

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In the following article, we present the dynamic simulation of an unmanned aerial vehicle with main fuel engine in the middle to carry most of the weight. This configuration will increase the flight time of the vehicle for a given payload size as opposed to the traditional quad rotor, where only DC motors are used. A parametric study to investigate the effect of the propellers ratio (main rotor propeller diameter to secondary rotor propeller diameter), the angle of incidence of the main rotor and the twist angle of the main rotor blades on selected performance criteria is presented.

Keywords: unmanned aerial vehicle (UAV), quadrotor, petrol quadcopter, flying robot

Procedia PDF Downloads 436