Search results for: logistics integration capabilities

Authors: Eriba Christopher Inyila, Godwin Egena Oga

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Statecraft appears to be one of the greatest cultural achievements in the history of man’s civilization. The state itself is often portrayed as the supreme community of the citizen’s collective goodness and will. However, history experience reveals that the state has often been held in captivity permanently in the hand of the political class to almost a total exclusion of the labouring class of workers, artisans and peasants. Consequently, the hallmark of the Nigerian state and society in contemporary era is state of permanent crisis characterized by poverty, unemployment and profound insecurity. A lasting solution to this state of anomie is often touted in terms of ethnic, religious and regional integration which border on non-material perception of realities. A neglected aspect of the approach to the study of recurrent problems in contemporary is the materialist conception of realties through class perspectives of the society. The cutting edge of the approach is found in the attempt to reconcile the contradiction between the productive forces and the social relation of production. In other words, the contemporary state is skewed in favour of ownership of properties/commanding height of economy predominantly in the hands of the few monopoly companies to the total exclusion of majority of Nigerian population classified as peasant, workers and artisan. The lopsided situation creates economic and social disequilibria.

Keywords: national development, class, the state, Nigeria

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Authors: Mohd Mudasir Shafi, Zafrul Hasan, Talat Saleem

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Information and communication Technology (ICT) services have been defined as a route to good governance. Introduction of ICT into Governance has given rise to the idea of e-governance which helps in enhancing transparency, generating accountability and responsiveness in the system in order to provide faster and quality service to the citizen. Advancement in ICT has provided governments all over the world to speed up the delivery of information and services to citizens and businesses and increase their participation in governance. There has been varying degree of success over the past decade into providing services to the citizens using internet and different web services. These e-government initiatives have been extensively researched. Our research is aimed at the transition from electronic government to mobile government (m-government) initiatives implementing the mobile services and concerned to understand the major factors which will aid to adoption and distribution of these services. There must be some amount of research done in the integration process between e-government and m-government. There must also be enough amount of investigation done all the factors that could affect the transition process. Such factors differ between different places and the advancement in information and technology available there. In this paper, we have discussed why mobile communication system can be used for effective e-governance and the areas where m-governance can be implemented. The paper will examine some of the reasons as well as the main opportunities for improving effective governance through mobile phones.

Keywords: e-governance, mobile phones, information technology, m-government

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Authors: Shobhit Mittal

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Headcount budgeting stands as a pivotal element in organizational financial management, extending beyond traditional budgeting to encompass strategic resource allocation for workforce-related expenses. This process is integral to maintaining financial stability and fostering a productive workforce, requiring a comprehensive analysis of factors such as market trends, business growth projections, and evolving workforce skill requirements. It demands a collaborative approach, primarily involving Human Resources (HR) and finance departments, to align workforce planning with an organization's financial capabilities and strategic objectives. The dynamic nature of headcount budgeting necessitates continuous monitoring and adjustment in response to economic fluctuations, business strategy shifts, technological advancements, and market dynamics. Its significance in talent management is also highlighted, aligning financial planning with talent acquisition and retention strategies to ensure a competitive edge in the market. The consequences of incorrect headcount budgeting are explored, showing how it can lead to financial strain, operational inefficiencies, and hindered strategic objectives. Examining case studies like IBM's strategic workforce rebalancing and Microsoft's shift for long-term success, the importance of aligning headcount budgeting with organizational goals is underscored. These examples illustrate that effective headcount budgeting transcends its role as a financial tool, emerging as a strategic element crucial for an organization's success. This necessitates continuous refinement and adaptation to align with evolving business goals and market conditions, highlighting its role as a key driver in organizational success and sustainability.

Keywords: strategic planning, fiscal budget, headcount planning, resource allocation, financial management, decision-making, operational efficiency, risk management, headcount budget

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Authors: Shazia Shinwari

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In the 21st century, South Asia is becoming one of the rising sub-regions of the world. In the whole of Asia, South Asia is going to be the center part of opportunities, development, and challenges. The increasing economy and its geopolitical importance are changing the landscape of South Asia. Despite intensifying the opportunities and development, the region is also facing the challenges of security, poverty, and conflicts. It is one of the most populated sub-regions and has many internal conflicts because of which the region remains for a long time a least developed region in the world. But now South Asia is transforming into the developing process and trying to utilize its potentials and to remove the hurdles in the way of development. South Asia is one of the distinctive regions of the world and could play an important role at the global level if the potentials of the region are properly utilized. South Asia is one of the most important regions of the world and assumed more importance after the British withdrawal from the region. Now South Asia is playing an important role in world politics due to its strategic and geographical location. That is why the importance of this region in the international political systems cannot be ignored. Day by day, changes have been taking place in the structure of the global economy, and South Asia could take advantage of these changes to advance as an economic region. For this, South Asia will need to look at its history, and that changes, particularly in the India and Pakistan relations, are necessary for the development of the South Asian region. Despite having challenges in the region, South Asia is also rising as the land of opportunities and development if the potentials of the region are properly utilized and smoothen the way for regional integration.

Keywords: challenges, development, opportunities, South Asia

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Authors: Santiago Martínez Hernández

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The establishment of the European Union signified the culmination of the supra-national power addressing economic, political, legal and humanitarian matters within and above a national territory. Human rights have taken a protagonist role as one of the pressing concerns that the EU addresses, and one of the most critical problems is that of human trafficking. This multi-billion dollar criminal business represents $31.6 per year made out of 2.5 million trafficked persons worldwide, making it one of the most crucial human rights problems in the world to address. The EU has developed strategies to tackle this issue through supra-national governance, however, how have they fared? What is the impact of its development on the issue? This paper will address the direct and indirect impact of the formation of the European Union as a supranational political and economic entity on the illicit industry of human trafficking in Europe. It attempts to analyse first, the situation of human trafficking in Europe, as an attempt to understand its importance in the region, addressing its root causes and the role of the states addressed. Second, the paper will examine the impact of the EU on human breaking down its policy-making at a supranational level, the role of the economic integration of the region, and the change of migration patterns since its inception.

Keywords: human trafficking, human rights, European union, criminal business

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Authors: Win Thandar Soe, Innocent Mpawenimana, Mathieu Di Fazio, Cécile Belleudy, Aung Ze Ya

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Intelligent electronic equipment and automation network is the brain of high-tech energy management systems in critical role of smart homes dominance. Smart home is a technology integration for greater comfort, autonomy, reduced cost, and energy saving as well. These services can be provided to home owners for managing their home appliances locally or remotely and consequently allow them to automate intelligently and responsibly their consumption by individual or collective control systems. In this study, three smart plugs are described and one of them tested on typical household appliances. This article proposes to collect the data from the wireless technology and to extract some smart data for energy management system. This smart data is to quantify for three kinds of load: intermittent load, phantom load and continuous load. Phantom load is a waste power that is one of unnoticed power of each appliance while connected or disconnected to the main. Intermittent load and continuous load take in to consideration the power and using time of home appliances. By analysing the classification of loads, this smart data will be provided to reduce the communication of wireless sensor network for energy management system.

Keywords: energy management, load profile, smart plug, wireless sensor network

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Authors: C. Senabre, S. Valero, M. Lopez, E. Velasco, M. Sanchez

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This paper focuses on an application of linear mixed models to short-term load forecasting. The challenge of this research is to improve a currently working model at the Spanish Transport System Operator, programmed by us, and based on linear autoregressive techniques and neural networks. The forecasting system currently forecasts each of the regions within the Spanish grid separately, even though the behavior of the load in each region is affected by the same factors in a similar way. A load forecasting system has been verified in this work by using the real data from a utility. In this research it has been used an integration of several regions into a linear mixed model as starting point to obtain the information from other regions. Firstly, the systems to learn general behaviors present in all regions, and secondly, it is identified individual deviation in each regions. The technique can be especially useful when modeling the effect of special days with scarce information from the past. The three most relevant regions of the system have been used to test the model, focusing on special day and improving the performance of both currently working models used as benchmark. A range of comparisons with different forecasting models has been conducted. The forecasting results demonstrate the superiority of the proposed methodology.

Keywords: short-term load forecasting, mixed effects models, neural networks, mixed effects models

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Authors: Hwei Voon Lee, N. Asikin-Mijana, Y. H. Taufiq-Yap, J. C. Juan, N. A. Rahman

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Cracking–Deoxygenation process is one of the important reaction pathways for the production of bio-fuel with desirable n-C17 hydrocarbon chain via removal of oxygen compounds. Calcium-based catalyst has attracted much attention in deoxygenation process due to its relatively high capacity in removing oxygenated compounds in the form of CO₂ and CO under decarboxylation and decarbonylation reaction, respectively. In the present study, deoxygenation of triolein was investigated using Ca(OH)₂ nanocatalyst derived from low cost natural waste shells. The Ca(OH)₂ nanocatalyst was prepared via integration techniques between surfactant treatment (anionic and non-ionic) and wet sonochemical effect. Results showed that sonochemically assisted surfactant treatment has successfully enhanced the physicochemical properties of Ca(OH)₂ nanocatalyst in terms of nanoparticle sizes (∼50 nm), high surface area(∼130 m²g⁻¹), large porosity (∼18.6 nm) and strong basic strength. The presence of superior properties from surfactant treated Ca(OH)₂ nanocatalysts rendered high deoxygenation degree, which is capable of producing high alkane and alkene selectivity in chain length of n-C17(high value of C17/(n-C17+ n-C18)ratio = 0.88). Furthermore, both Ca(OH)₂–EG and Ca(OH)₂–CTAB nanocatalysts showed high reactivity with 47.37% and 44.50%, respectively in total liquid hydrocarbon content of triolein conversion with high H/C and low O/C ratio.

Keywords: clamshell, cracking, decarboxylation-decarbonylation, hydrocarbon

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Authors: Jamie David Hopkin

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This study aims to contribute uniquely to help colleges and community learning and development institutes to help aid progression within ESOL learning. The study investigates the barriers that migrant and displaced learners face accessing further education in Scotland. The study also includes a set of recommendations both for colleges and CLD institutes to help ESOL learners in their journey to further education. The research found that integration into Scottish society is one of the biggest motivators for ESOL students to learn English. It also found that the place of gender and “gender roles” contribute to the barriers that learners face in terms of progression and learning. The study also reviews all literature related to ESOL learning in Scotland and found that there are only two main policies that support ESOL learning, and both are slightly outdated in terms of supporting progression. This study aims to help bridge the gap in knowledge around the progression from informal learning to formal education. The recommendations that are made in this study are aimed to help institutes and learners on their journey to a positive destination. The main beneficiaries of this research are current and future ESOL learners in Scotland, ESOL institutes, and TESOL professionals.

Keywords: community learning and development, English for speakers of other languages, further education, higher education TESOL, teaching English as a second language

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Authors: Munoz A. Tatiana, Solano R. Brandon, Montes C. Juan, Cierco G. Javier

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The hydrodynamic cavitation is a process in which the energy that the fluids have in the phase changes is used. From this energy, local temperatures greater than 5000 °C are obtained where thermal cracking of the fluid molecules takes place. The process applied to heavy oil affects variables such as viscosity, density, and composition, which constitutes an important improvement in the quality of crude oil. In this study, the need to design a software through mathematical integration models of mixing, cavitation, kinetics, and reactor, allows modeling changes in density, viscosity, and composition of a heavy oil crude, when the fluid passes through a hydrodynamic cavitation reactor. In order to evaluate the viability of this technique in the industry, a heavy oil of 18° API gravity, was simulated using naphtha as a hydrogen donor at concentrations of 1, 2 and 5% vol, where the simulation results showed an API gravity increase to 0.77, 1.21 and 1.93° respectively and a reduction viscosity by 9.9, 12.9 and 15.8%. The obtained results allow to have a favorable panorama on this technological development, an appropriate visualization on the generation of innovative knowledge of this technique and the technical-economic opportunity that benefits the development of the hydrocarbon sector related to heavy crude oil that includes the largest world oil production.

Keywords: hydrodynamic cavitation, thermal cracking, hydrogen donor, heavy oil upgrading, simulator

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Authors: Hamza Ouachtouk, Amine Harbi, Said Azerblou, Youssef Naimi, El Mostafa Tace

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This study delves into the structural, vibrational, magnetic, and electronic properties of La₂MMnO₆ double perovskites, where M denotes Ni, Co, and Zn. Recognized for their versatile ionic configurations within the A and B sub-lattices, double perovskite oxides have attracted considerable interest due to their extensive array of physical properties, which include multiferroic behavior, colossal magnetoresistance, and ferroelectric/piezoelectric functionalities. These materials are pivotal for energy-related technologies like solid oxide fuel cells and water-splitting catalysis, attributed to their superior oxygen ion transport and storage capabilities. This research places particular emphasis on La₂NiMnO₆ and La₂CoMnO₆, known for their distinct magnetic, electric, and multiferroic properties, and extends the investigation to La₂ZnMnO₆, synthesized via high-temperature solid-state chemistry. This addition aims to ascertain the impact of zinc substitution on these properties. Structural analysis through X-ray diffraction has confirmed a monoclinic structure within the P2₁/n space group. Comprehensive vibrational studies utilizing infrared and Raman spectroscopy, alongside additional XRD assessments, provide a detailed examination of the dynamic and electronic behaviors of these compounds. The results underscore the significant role of chemical composition in modulating their functional properties. Comparatively, this study highlights that zinc substitution notably alters the electronic and magnetic responses, which could enhance the applicability of these materials in advanced energy technologies. This expanded analysis not only reinforces our understanding of La₂MMnO₆'s physical characteristics but also highlights its potential applications in the next generation of energy solutions.

Keywords: double perovskites, structural analysis, vibrational spectroscopy, magnetic properties, electronic properties, high-temperature solid-state chemistry, La₂MMnO₆, monoclinic structure, x-ray diffraction

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Authors: Muhammad Atif, Cang Yan

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The enhancement of low-light images is a significant area of study aimed at enhancing the quality of captured images in challenging lighting environments. Recently, methods based on convolutional neural networks (CNN) have gained prominence as they offer state-of-the-art performance. However, many approaches based on CNN rely on increasing the size and complexity of the neural network. In this study, we propose an alternative method for improving low-light images using an autoencoder-based multiscale knowledge transfer model. Our method leverages the power of three autoencoders, where the encoders of the first two autoencoders are directly connected to the decoder of the third autoencoder. Additionally, the decoder of the first two autoencoders is connected to the encoder of the third autoencoder. This architecture enables effective knowledge transfer, allowing the third autoencoder to learn and benefit from the enhanced knowledge extracted by the first two autoencoders. We further integrate the proposed model into the PIX to PIX GAN framework. By integrating our proposed model as the generator in the GAN framework, we aim to produce enhanced images that not only exhibit improved visual quality but also possess a more authentic and realistic appearance. These experimental results, both qualitative and quantitative, show that our method is better than the state-of-the-art methodologies.

Keywords: low light image enhancement, deep learning, convolutional neural network, image processing

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Authors: Yuyun Wabula, B. J. Dewancker

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In the past decade, the social networking app has been growing very rapidly. Geolocation data is one of the important features of social media that can attach the user's location coordinate in the real world. This paper proposes the use of geolocation data from the Twitter social media application to gain knowledge about urban dynamics, especially on human mobility behavior. This paper aims to explore the relation between geolocation Twitter with the existence of people in the urban area. Firstly, the study will analyze the spread of people in the particular area, within the city using Twitter social media data. Secondly, we then match and categorize the existing place based on the same individuals visiting. Then, we combine the Twitter data from the tracking result and the questionnaire data to catch the Twitter user profile. To do that, we used the distribution frequency analysis to learn the visitors’ percentage. To validate the hypothesis, we compare it with the local population statistic data and land use mapping released by the city planning department of Makassar local government. The results show that there is the correlation between Twitter geolocation and questionnaire data. Thus, integration the Twitter data and survey data can reveal the profile of the social media users.

Keywords: geolocation, Twitter, distribution analysis, human mobility

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Authors: Sharad Singh, Ajay Kumar Sinha

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Coupled dampers like viscoelastic-frictional dampers for supplemental damping are a newer technique. In this paper, innovative Visco-frictional damping models have been presented and investigated. This paper attempts to couple frictional and fluid viscous dampers into a single unit of supplemental dampers. Visco-frictional damping model is developed by series and parallel coupling of frictional and fluid viscous dampers using Maxwell and Kelvin-Voigat models. The time analysis has been performed using numerical simulation on an SDOF system with varying fundamental periods, subject to a set of 12 ground motions. The simulation was performed using the direct time integration method. MATLAB programming tool was used to carry out the numerical simulation. The response behavior has been analyzed for the varying time period and added damping. This paper compares the response reduction behavior of the two modes of coupling. This paper highlights the performance efficiency of the suggested damping models. It also presents a mathematical modeling approach to visco-frictional dampers and simultaneously suggests the suitable mode of coupling between the two sub-units.

Keywords: hysteretic damping, Kelvin model, Maxwell model, parallel coupling, series coupling, viscous damping

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Authors: Emna Benmohamed, Hela Ltifi, Mounir Ben Ayed

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Bayesian Network (BN) is one of the most efficient classification methods. It is widely used in several fields (i.e., medical diagnostics, risk analysis, bioinformatics research). The BN is defined as a probabilistic graphical model that represents a formalism for reasoning under uncertainty. This classification method has a high-performance rate in the extraction of new knowledge from data. The construction of this model consists of two phases for structure learning and parameter learning. For solving this problem, the K2 algorithm is one of the representative data-driven algorithms, which is based on score and search approach. In addition, the integration of the expert's knowledge in the structure learning process allows the obtainment of the highest accuracy. In this paper, we propose a hybrid approach combining the improvement of the K2 algorithm called K2 algorithm for Parents and Children search (K2PC) and the expert-driven method for learning the structure of BN. The evaluation of the experimental results, using the well-known benchmarks, proves that our K2PC algorithm has better performance in terms of correct structure detection. The real application of our model shows its efficiency in the analysis of the phosphate laundry effluents' impact on the watershed in the Gafsa area (southwestern Tunisia).

Keywords: Bayesian network, classification, expert knowledge, structure learning, surface water analysis

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Authors: Mohsen Adabi, Mahdi Adabi, Reza Saber

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The recent advancements in nanomaterials have provided a platform to develop efficient transduction matrices for sensors. Modified electrodes allow to electrochemists to enhance the property of electrode surface and provide desired properties such as improved sensing capabilities, higher electron transfer rate and prevention of undesirable reactions competing kinetically with desired electrode process. Nanostructured electrodes including arrays of carbon nanotubes have demonstrated great potential for the development of electrochemical sensors and biosensors. The aim of this work is to evaluate the concentration of multi-walled carbon nanotubes (MWCNTs) on the conductivity of gold electrode. For this work, raw MWCNTs was functionalized and shortened. Raw and shorten MWCNTs were characterized using transfer electron microscopy (TEM). Next, 0.5, 2 and 3.5 mg of Shortened and functionalized MWCNTs were dispersed in 2 mL Dimethyl formamide (DMF) and cysteamine modified gold electrodes were incubated in the different concentrations of MWCNTs for 8 hours. Then, the immobilization of MWCNTs on cysteamine modified gold electrode was characterized by scanning electron microscopy (SEM) and the effect of MWCNT concentrations on electron transfer of modified electrodes was investigated by cyclic voltammetry (CV). The results demonstrated that CV response of ferricyanide redox at modified gold electrodes increased as concentration of MWCNTs enhanced from 0.5 to 2 mg in 2 mL DMF. This increase can be attributed to the number of MWCNTs which enhance on the surface of cysteamine modified gold electrode as the MWCNTs concentration increased whereas CV response of ferricyanide redox at modified gold electrodes did not changed significantly as the MWCNTs concentration increased from 2 to 3.5 mg in 2 mL DMF. The reason may be that amine groups of cysteamine modified gold electrodes are limited to a given number which can interact with the given number of carboxylic groups of MWCNTs and CV response of ferricyanide redox at modified gold do not enhance after amine groups of cysteamine are saturated with carboxylic groups of MWCNTs.

Keywords: carbon nanotube, cysteamine, electrochemical sensor, gold electrode

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Authors: Avani Chhajlani

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Fashion is considered to be the most destructive industry, second only to the oil rigging industry, which has a greater impact on the environment. While fashion today banks upon fast fashion to generate a higher turnover of designs and patterns in apparel and related accessories, crafts push us towards a more slow and thoughtful approach with culturally identifiably unique work and slow community-centered production. Despite this strong link between indigenous crafts and sustainability, it has not been extensively researched and explored upon. In the forthcoming years, the fashion industry will have to reinvent itself to move towards a more holistic and sustainable circular model to balance the harm already caused. And closed loops of the circular economy will help the integration of indigenous craft knowledge, which is regenerative. Though sustainability and crafts of a region go hand-in-hand, the craft still have to find its standing in the mainstream fashion world; craft practices have a strong local congruence and knowledge that has been passed down generation-to-generation through oration or written materials. This paper aims to explore ways a circular economy can be created by amalgamating fashion and craft while creating a sustainable business model and how this is slowly being created today through brands like – RaasLeela, Pero, and KaSha, to name a few.

Keywords: circular economy, fashion, India, indigenous crafts, slow fashion, sustainability, up-cycling

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Authors: Rizwan Rizwan

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This paper provides an overview of Federated Learning (FL) and its application in enhancing data security, privacy, and efficiency. FL utilizes three distinct architectures to ensure privacy is never compromised. It involves training individual edge devices and aggregating their models on a server without sharing raw data. This approach not only provides secure models without data sharing but also offers a highly efficient privacy--preserving solution with improved security and data access. Also we discusses various frameworks used in FL and its integration with machine learning, deep learning, and data mining. In order to address the challenges of multi--party collaborative modeling scenarios, a brief review FL scheme combined with an adaptive gradient descent strategy and differential privacy mechanism. The adaptive learning rate algorithm adjusts the gradient descent process to avoid issues such as model overfitting and fluctuations, thereby enhancing modeling efficiency and performance in multi-party computation scenarios. Additionally, to cater to ultra-large-scale distributed secure computing, the research introduces a differential privacy mechanism that defends against various background knowledge attacks.

Keywords: federated learning, differential privacy, gradient descent strategy, convergence, stability, threats

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Authors: Maisyatus Suadaa Irfana, Nove Eka Variant Anna, Dyah Puspitasari Sri Rahayu

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Technological developments provide convenience to all the people. Nowadays, the communication of human with the computer is done via text. With the development of technology, human and computer communications have been conducted with a voice like communication between human beings. It provides an easy facility for many people, especially those who have special needs. Voice search technology is applied in the search of book collections in the OPAC (Online Public Access Catalog), so library visitors will find it faster and easier to find books that they need. Integration with Google is needed to convert the voice into text. To optimize the time and the results of searching, Server will download all the book data that is available in the server database. Then, the data will be converted into JSON format. In addition, the incorporation of some algorithms is conducted including Decomposition (parse) in the form of array of JSON format, the index making, analyzer to the result. It aims to make the process of searching much faster than the usual searching in OPAC because the data are directly taken to the database for every search warrant. Data Update Menu is provided with the purpose to enable users perform their own data updates and get the latest data information.

Keywords: OPAC, voice, searching, faster

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Authors: Andrew Clark

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McCauley, Bassler, and Gunaratne show that integration I(d) processes as used in economics and finance do not necessarily produce stationary increments, which are required to determine causality in both the short term and the long term. This paper follows their lead and shows I(d) aluminum cash and futures log prices at daily and weekly intervals do not have stationary increments, which means prior causality studies using I(d) processes need to be re-examined. Wavelets based on undifferenced cash and futures log prices do have stationary increments and are used along with transfer entropy (versus cointegration) to measure causality. Wavelets exhibit causality at most daily time scales out to 1 year, and weekly time scales out to 1 year and more. To determine stationarity, localized stationary wavelets are used. LSWs have the benefit, versus other means of testing for stationarity, of using multiple hypothesis tests to determine stationarity. As informational flows exist between cash and futures at daily and weekly intervals, the aluminum market is efficient. Therefore, hedges used by producers and consumers of aluminum need not have a big concern in terms of the underestimation of hedge ratios. Questions about arbitrage given efficiency are addressed in the paper.

Keywords: transfer entropy, nonstationary increments, wavelets, localized stationary wavelets, localized stationary wavelets

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Authors: Nils Mueller, Gregor Herz, Erik Reichelt, Matthias Jahn

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In the context of climate change, the reduction of greenhouse gas emissions in all economic sectors is considered to be an important factor in order to meet the demands of a sustainable energy system. The steel industry as one of the large industrial CO₂ emitters is currently highly dependent on fossil resources. In order to reduce coke consumption and thereby CO₂ emissions while still being able to further utilize existing blast furnaces, the possibility of including a direct reduction process (DRP) into a fully integrated steel mill was investigated. Therefore, a blast furnace model, derived from literature data and implemented in Aspen Plus, was used to analyze the impact of DRI in the blast furnace process. Furthermore, a state-of-the-art DRP was modeled to investigate the possibility of substituting the reducing agent natural gas with hydrogen. A sensitivity analysis was carried out in order to find the boundary percentage of hydrogen as a reducing agent without penalty to the DRI quality. Lastly, the two modeled process steps were combined to form a route of producing pig iron. By varying boundary conditions of the DRP while recording the CO₂ emissions of the two process steps, the overall potential for the reduction of CO₂ emissions was estimated. Within the simulated range, a maximum reduction of CO₂ emissions of 23.5% relative to typical emissions of a blast furnace could be determined.

Keywords: blast furnace, CO₂ mitigation, DRI, hydrogen

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Authors: Shivi Agarwal, Trilok Mathur

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This paper proposes the method to measure the total factor productivity (TFP) change by credibility theory for fuzzy input and output variables. Total factor productivity change has been widely studied with crisp input and output variables, however, in some cases, input and output data of decision-making units (DMUs) can be measured with uncertainty. These data can be represented as linguistic variable characterized by fuzzy numbers. Malmquist productivity index (MPI) is widely used to estimate the TFP change by calculating the total factor productivity of a DMU for different time periods using data envelopment analysis (DEA). The fuzzy DEA (FDEA) model is solved using the credibility theory. The results of FDEA is used to measure the TFP change for fuzzy input and output variables. Finally, numerical examples are presented to illustrate the proposed method to measure the TFP change input and output variables. The suggested methodology can be utilized for performance evaluation of DMUs and help to assess the level of integration. The methodology can also apply to rank the DMUs and can find out the DMUs that are lagging behind and make recommendations as to how they can improve their performance to bring them at par with other DMUs.

Keywords: chance-constrained programming, credibility theory, data envelopment analysis, fuzzy data, Malmquist productivity index

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Authors: Marius Gavrilescu, Sabina-Adriana Floria, Florin Leon, Silvia Curteanu, Costel Anton

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Natural sciences provide a wide range of experimental data whose related problems require study and modeling beyond the capabilities of conventional methodologies. Such problems have solution spaces whose complexity and high dimensionality require correspondingly complex regression methods for proper characterization. In this context, we propose an optimization method which consists in a hybrid dual optimizer setup: a global optimizer based on a modified variant of the popular Imperialist Competitive Algorithm (ICA), and a local optimizer based on a gradient descent approach. The ICA is modified such that intermediate solution populations are more quickly and efficiently pruned of low-fitness individuals by appropriately altering the assimilation, revolution and competition phases, which, combined with an initialization strategy based on low-discrepancy sampling, allows for a more effective exploration of the corresponding solution space. Subsequently, gradient-based optimization is used locally to seek the optimal solution in the neighborhoods of the solutions found through the modified ICA. We use this combined approach to find the optimal configuration and weights of a fully-connected neural network, resulting in regression models used to characterize the process of obtained bricks using silicon-based materials. Installations in the raw ceramics industry, i.e., bricks, are characterized by significant energy consumption and large quantities of emissions. Thus, the purpose of our approach is to determine by simulation the working conditions, including the manufacturing mix recipe with the addition of different materials, to minimize the emissions represented by CO and CH4. Our approach determines regression models which perform significantly better than those found using the traditional ICA for the aforementioned problem, resulting in better convergence and a substantially lower error.

Keywords: optimization, biologically inspired algorithm, regression models, bricks, emissions

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Authors: Yimei Huang, Harvey Lui, Jianhua Zhao, Zhenguo Wu, Haishan Zeng

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Conventional laser treatment of skin diseases and cosmetic surgery is based on the principle of one-photon absorption selective photothermolysis which relies strongly on the difference in the light absorption between the therapeutic target and its surrounding tissue. However, when the difference in one-photon absorption is not sufficient, collateral damage would occur due to indiscriminate and nonspecific tissue heating. To overcome this problem, we developed a spatially selective photothermolysis method based on multiphoton absorption in which the heat generation is restricted to the focal point of a tightly focused near-infrared femtosecond laser beam aligned with the target of interest. A multimodal optical microscope with co-registered reflectance confocal imaging (RCM), two-photon fluorescence imaging (TPF), and second harmonic generation imaging (SHG) capabilities was used to perform and monitor the spatially selective photothermolysis. Skin samples excised from the shaved backs of euthanized NODSCID mice were used in this study. Treatments were performed by focusing and scaning the laser beam in the dermis with a 50µm×50µm target area. Treatment power levels of 200 mW to 400 mW and modulated pulse trains of different duration and period were experimented. Different treatment parameters achieved different degrees of spatial confinement of tissue alterations as visualized by 3-D RCM/TPF/SHG imaging. At 200 mW power level, 0.1 s pulse train duration, 4.1 s pulse train period, the tissue damage was found to be restricted precisely to the 50µm×50µm×10µm volume, where the laser focus spot had scanned through. The overlying epidermis/dermis tissue and the underneath dermis tissue were intact although there was light passing through these regions.

Keywords: multiphoton absorption photothermolysis, reflectance confocal microscopy, second harmonic generation microscopy, spatially selective photothermolysis, two-photon fluorescence microscopy

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Authors: Seun Mayowa Sunday

Abstract:

Loan prediction is one of the most significant and recognised fields of research in the banking, insurance, and the financial security industries. Some prediction systems on the market include the construction of static software. However, due to the fact that static software only operates with strictly regulated rules, they cannot aid customers beyond these limitations. Application of many machine learning (ML) techniques are required for loan prediction. Four separate machine learning models, random forest (RF), decision tree (DT), k-nearest neighbour (KNN), and logistic regression, are used to create the loan prediction model. Using the anaconda navigator and the required machine learning (ML) libraries, models are created and evaluated using the appropriate measuring metrics. From the finding, the random forest performs with the highest accuracy of 80.17% which was later implemented into the Django framework. For real-time testing, the web application is deployed on the Alibabacloud which is among the top 4 biggest cloud computing provider. Hence, to the best of our knowledge, this research will serve as the first academic paper which combines the model development and the Django framework, with the deployment into the Alibaba cloud computing application.

Keywords: k-nearest neighbor, random forest, logistic regression, decision tree, django, cloud computing, alibaba cloud

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Authors: Makarios Mosaad Thabet Ibrahim

Abstract:

the existing context paper targets to give the important position of ‘scholar voice’ and the track trainer inside the study room, which contributes to greater scholar-focused song training. The goal is to consciousness at the capabilities of the scholar voice via the tune spectrum, which has been born in the music school room, and the instructor’s methodologies and techniques used within the song classroom. The tune curriculum, the principles of pupil-centered song schooling, and the function of students and teachers as tune ambassadors have been taken into consideration the essential song parameters of scholar voice. The scholar- voice is a well worth-mentioning factor of a scholar-focused training, and all instructors have to take into account and sell its life in their lecture room. student affairs services play a critical function in contributing to the wholistic development and success of college students as they progress through their educational careers. The examine incorporates a multifaceted examination of student affairs carrier offerings among 10 personal and three public Baghdad universities. scholar affairs administrators (thirteen) have been surveyed together with over 300 students to determine university-subsidized services and pupil pride and attention. The pupil affairs service studies findings various drastically among non-public and public establishments and people that observed a country wide and international curriculum. Universities need to persist to conform to changing demographics and technological improvements to enhance students' private and academic successes, and pupil affairs services are key to preparing graduates to thrive in a diverse international world.

Keywords: college student-athletes, self-concept, use of social media training, social networking student affairs, student success, higher education, Iraq, universities, Baghdad student's voice, student-centered education, music ambassadors, music teachers

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Authors: Hsiao-ting Lin

Abstract:

This paper analyzes the history of Taiwan’s secret program to develop its nuclear weapons during the Cold War. In July 1971, US President Richard Nixon shocked the world when he announced that his national security adviser Henry Kissinger had made a secret trip to China and that he himself had accepted an invitation to travel to Beijing. This huge breakthrough in the US-PRC relationship was followed by Taipei’s loss of political legitimacy and international credibility as a result of its UN debacle in the fall that year. Confronted with the Nixon White House’s opening to the PRC, leaders in Taiwan felt being betrayed and abandoned, and they were obliged to take countermeasures for the sake of national interest and regime survival. Taipei’s endeavor to create an effective nuclear program, including the possible development of nuclear weapons capabilities, fully demonstrates the government’s resolution to pursue its own national policy, even if such a policy was guaranteed to undermine its relations with the United States. With hindsight, Taiwan’s attempt to develop its own nuclear weapons did not succeed in sabotaging the warming of US-PRC relations. Worse, it was forced to come to a full stop when, in early 1988, the US government pressured Taipei to close related facilities and programs on the island. However, Taiwan’s abortive attempt to develop its nuclear capability did influence Washington’s and Beijing’s handling of their new relationship. There did develop recognition of a common American and PRC interest in avoiding a nuclearized Taiwan. From this perspective, Beijing’s interests would best be served by allowing the island to remain under loose and relatively benign American influence. As for the top leaders on Taiwan, such a policy choice demonstrated how they perceived the shifting dynamics of international politics in the 1960s and 1970s and how they struggled to break free and pursue their own independent national policy within the rigid framework of the US-Taiwan alliance during the Cold War.

Keywords: taiwan, richard nixon, nuclear program, chiang Kai-shek, chiang ching-kuo

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Authors: Salim Yusif

Abstract:

Fiber optic technology has revolutionized telecommunications and data transmission, providing unmatched speed, bandwidth, and reliability. This paper presents the latest advancements in fiber optic technology, focusing on innovations in fiber materials, transmission techniques, and network architectures that enhance the performance of high-speed data transmission systems. Key advancements include the development of ultra-low-loss optical fibers, multi-core fibers, advanced modulation formats, and the integration of fiber optics into next-generation network architectures such as Software-Defined Networking (SDN) and Network Function Virtualization (NFV). Additionally, recent developments in fiber optic sensors are discussed, extending the utility of optical fibers beyond data transmission. Through comprehensive analysis and experimental validation, this research offers valuable insights into the future directions of fiber optic technology, highlighting its potential to drive innovation across various industries.

Keywords: fiber optics, high-speed data transmission, ultra-low-loss optical fibers, multi-core fibers, modulation formats, coherent detection, software-defined networking, network function virtualization, fiber optic sensors

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Authors: Priti Saha, Biswajit Paul

Abstract:

Rapid urbanization and industrialization have increased the demand of groundwater. However, the present era has evident an enormous level of groundwater pollution. Therefore, water quality assessment is paramount importance to evaluate its suitability for drinking, irrigation and industrial use. This study focus to evaluate the groundwater quality of an industrial city in eastern India through interdisciplinary techniques. The multi-purpose Water Quality Index (WQI) assess the suitability for drinking as well as irrigation of forty sampling locations, where 2.5% and 15% of sampling locations have excellent water quality (WQI:0-25) as well as 15% and 40% have good quality (WQI:25-50), which represents its suitability for drinking and irrigation respectively. However, the industrial water quality was assessed through Ryznar Stability Index (LSI), which affirmed that only 2.5% of sampling locations have neither corrosive nor scale forming properties (RSI: 6.2-6.8). These techniques with the integration of geographical information system (GIS) for spatial assessment indorsed its effectiveness to identify the regions where the water bodies are suitable to use for drinking, irrigation as well as industrial activities. Further, the sources of these contaminants were identified through factor analysis (FA), which revealed that both the geogenic as well as anthropogenic sources were responsible for groundwater pollution. This research demonstrates the effectiveness of statistical and GIS techniques for the analysis of environmental contaminants.

Keywords: groundwater, water quality analysis, water quality index, WQI, factor analysis, FA, spatial assessment

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Authors: Azreen Jihan Che Mohd Hashim, Rosidah Musa

Abstract:

Although 'Spiritual Intelligence' (SI) is hard to measure, it is impossible without a noble value that may affect the attitude in purchasing behavior process, so this paper aims to report on a pilot study analysis results in order to evaluate the degree of SI towards consumers’ attitude in purchasing halal cosmetics and, in turn, to reaffirm intention to purchase by using Theory Planned Behaviour (TPB). It is a descriptive cross-sectional study among the Muslim women as the subjects, working and staying in Klang valley area in Malaysia. The purpose of the study is to develop a new measurement scale to unravel and decompose the underlying dimensions of SI from the perspective of the Muslim deemed imperative. About 200 respondents of users and non-users of halal cosmetics are selected. The structure equation modeling (SEM) was conducted to examine the relationships among god, society and self, which are the dimensions of SI. A finding indicates that, in influencing attitude, those who obligate high spiritual intelligence have a good relationship with god, society and self which may influence them to purchase halal cosmetic product. This study offers important findings and implications for future research as it presents a framework on the importance of SI.

Keywords: spiritual intelligence, god, society, self, young adult Muslim female

Procedia PDF Downloads 350