Title: National Income Multipliers and Their Connections to Economic Policy effectiveness

Abstract:The study aims to derive the full multipliers of the economic variables that affect income, which are government expenditure, tax, money supply, the general level of prices, the exchange rate, and the lag of income. The reduced form of the income model was used by deriving the total expenditure equation from which the various income multipliers were derived. These multipliers are in line with macroeconomic theory in determining the effectiveness of economic policy, whether fiscal, monetary, price, income, or exchange, via the exchange rate. The study concluded that the higher the elasticities of economic variables, the higher the effectiveness of economic policy using one of the variables and vice versa. The economic state of the specific economy also affects the effectiveness of economic policy. In addition, the multipliers derived in this study facilitate the analysis of economic policy and show the extent of its effectiveness in different cases.

Title: Response and Failure of Circumferential Sharp-Notched C2700 Brass Tubes under Cyclic Bending

Abstract:This paper investigates the response and failure of circumferential sharp-notched C2700 brass tubes with four different notch depths of 0.2, 0.4, 0.6, 0.8, and 1.0 mm subjected to cyclic bending. The wall thickness is 1.5 mm for all tested tubes, and cyclic bending loads are applied until buckling failure occurs. The experimental moment-curvature relationships exhibit a stable loop from the first bending cycles. An increase in the notch depth results in the decrease of the peak bending moment. The experimental relationships between ovalization and curvature demonstrate symmetry, serrations, and a growth pattern as cycles progress, regardless of the notch depth. Regarding the curvature-number of cycles required to initiate buckling relationships, it can be observed that five notch depths correspond to five parallel straight lines when plotted on double logarithmic coordinates. Finally, this study employs the theoretical formulation proposed by Lee in 2010 to describe the aforementioned relationships. The theoretical analysis is compared with experimental data, revealing a close alignment between the two approaches.


Abstract:A smart city is a sustainable and efficient urban center that provides a high quality of life to its inhabitants through optimal management of its resources. Energy management is one of the most demanding issues within such urban centers owing to the complexity of the energy systems and their vital role. Therefore, significant attention and effort need to be dedicated to this problem. Modelling and simulation are the major tools commonly used to assess the technological and policy impacts of smart solutions, as well as to plan the best ways of shifting from current cities to smarter ones. This paper presents the design and implementation of energy management system (EMS) based on hybrid sources system containing wind turbine, Photovoltaic (PV) and battery and load, all connected to the utility grid which is used as a backup source. The objectives of this system are, primarily, to satisfy the house load power demand and, secondly, to manage the power between its different components. The performances of the proposed supervisor control is tested using MATLAB/Simulink and the implementation of system is do on a Zybo-Z7 card based on zynq FPGA device.

Title: Impact of Gas Pressure on the Adhesion Process of Cold-sprayed Titanium Dioxide layers on Unalloyed Metals

Abstract:Applying ceramic materials like TiO2 through cold spraying is acknowledged as a complex procedure. The intricacy stems from the need for feedstock particles to undergo plastic deformation to bond with the substrate during cold spraying. However, inducing such deformation in ceramics, known for their hardness and brittleness, is not straightforward. Additionally, the underlying bonding mechanism is not fully clear. This study sought to understand the effects of different substrates and gas pressures on the TiO2 application method. We experimented with TiO2 particles and metals such as copper and aluminum, exposing them to varied gas pressures to delve deeper into the dynamics of cold spraying ceramics onto metallic surfaces. We utilized sophisticated instruments like the focused ion beam and the transmission electron microscope to scrutinize the interfacial structures of TiO2 particles with pure copper (C1020) as well as pure aluminum (AA1050). The data revealed that as we adjusted the gas pressure from 0.7 to 3.0 MPa, there was a corresponding increase in the coating\'s bond strength, registering between 1.52 to 3.46 MPa for C1020 and 0.45 to 4.15 MPa for AA1050. An ultra-thin amorphous oxide layer, under 5 nm in thickness, was detected at the juncture of TiO2 with both metals. The shift in process gas pressure emerged as a pivotal element affecting the bond strength of the TiO2 layer.

Title: Identification of the spoofing in e-Learning system with the implicit face recognition

Abstract:To detect spoofing in e-Learning is of great significance in enhancing the reliability of e-learning systems and protecting the copyright of learning content. We propose a new method to detect spoofing in e-learning systems without causing inconvenience to the student\'s learning, based on the implicit face contrast in randomly selected time period during online learning. First, we show the web service model for the face recognition with message signature that can be used for the purpose of identifying learners in e-learning systems. Next, we propose a method to detect spoofing by implicit face recognition in a random time period during online learning. The application of the proposed method to the e-learning system using SOAP has shown that it can effectively detect the impostor without causing significant inconvenience to learners.

Title: Probabilistic Soil Liquefaction Assessment: A Case Study for Agartala City in Tripura in North-East India

Abstract:A sudden increase in pore water pressure causes the effective stress to decrease significantly, which in turn causes a loss of shear strength and the subsequent outcome of allowing the soil to behave as a liquid, resulting in soil liquefaction. Agartala, the capital of Tripura, is located in northeastern India, and the entire region is considered seismically active according to the seismic zoning map of India as per IS 1893:2002 (Part 1); the entire region is classified as Zone-V. Significant earthquakes have struck this region, including the 1897 Shillong and 1950 Assam earthquakes. The city is vulnerable to liquefaction due to alluvial soil and a low groundwater table. Several parameters are involved in assessing liquefaction potential in the deterministic method and have different input parameter uncertainties, resulting in inconsistent outcomes. As a result, evaluating liquefaction susceptibility requires a thorough probability approach that considers parameter uncertainty. In this work, the soil liquefaction potential of Agartala City is assessed using fuzzy logic and compared to the conventional Reliability technique using the first-order second-moment method. Soil liquefaction potential was properly calculated using both approaches for the 71 boreholes in and around Agartala city. The outcomes are shown as contour maps representing spatial variations of the probability of liquefaction at different depths. In this study, Fuzzy logic is used to model the relationships between different soil parameters, which can help better understand the soil\'s behaviour during liquefaction. This developed method can assess the vulnerability of liquefaction potential and select appropriate materials and construction processes.

Title: Improving Learners' Cognition through Designing Learning Contents with Self-feedback Structure and Advanced Interaction in Online Learning

Abstract:Developing high quality learning contents (LCs) and improving their interactions in online learning with e-learning contents is important for greater cognitive abilities of a learner. The aim of this research is to design LCs with new self-feedback structure by considering the personalized characteristics of a learner in order to ensure his greater cognitive abilities through improved interactions. A new form of LCs is developed, which learning nodes consists of knowledge units of 5-10 minutes with each unit linked to assessment and control objects. The communication interface of the learning management system (LMS) is extended for a learner to support not only learning and navigation but self-assessment and repeated learning when interacting with LCs. Experiments were performed for three years to analyse the collected achievements of 376 online learners. The results show that the self-feedback is a significant factor that gives positive influence on the learner’s cognition during the COVID-19 pandemic. The average score of participants were increased by 0.2 than before 2020.


Abstract:The purpose of this article is to propose a range of natural-based external thermal insulation (ETI) \nsystems for the vertical walls of a residential building located in the Southwest region of Algeria \n(Bechar), which represents the real case of the majority of constructions existing in the area. To \nachieve this, a combination of thermal insulation systems was realized, using natural origin materials \nsuch as wood wool, cellulose wadding, expanded cork, hemp fiber, and sheep wool. The evaluation \nof energy consumption (heating and air conditioning) was carried out using a dynamic thermal \nsimulator \"TRNSYS\". In order to establish a precise estimate of the savings achieved and the payback \nperiod on investment, a techno-economic study was conducted for all the tested systems. The results \nobtained show a considerable efficiency of the proposed natural-based systems compared to \nsynthetic-based system for the thermal insulation of vertical walls, allowing significant energy \nsavings in the form of annual benefits while improving the energy performance of the studied building \nas well as the quality of life of its occupants.

Title: Improving thermal comfort of residential building based on Recycling materials in arid and hot regions. Case studies of South of Algeria

Abstract:the building envelope can reduce heating and cooling consumption, if it is well thermally insulated from the outside. To do this, it is necessary to use eco-friendly materials, such as recycled materials, which could control the environmental impact. The objective of this work is not only to design sustainable designs for hot and arid climates, but also to have new thermal insulation systems based on recycled materials and fibers. In this regard, the systems studied were fixed to a simple concrete block wall, under cladding (dry process). The results showed the important role of insulation with recycled materials such as wood fiber from the outside. These results make it possible to evaluate the potential impact of ETIs based on recycled and natural materials in extreme conditions, highlighting the interest in maintaining summer comfort. It�s concluded that the use of recycled material can be enable to improving consumption energy. Also, the technical-economic analysis can be revealed, the technical feasibility of the systems studied and the economic impact of natural and recycled insulating materials compared to conventional polystyrene insulation.

Title: Hand Gesture Classification through Time Frequency Images with One-to-One, All-to-One, and Cross-Validation Approaches.

Abstract:Surface electromyographic (sEMG) signals are a non-invasive method for acquiring signals that play a fundamental role in the monitoring of prosthetic devices by providing information about human motor functions. This leads to the need for accurate classification of sEMG signals, despite variations in signal stationarity, the presence of sensor noise, differences between the muscles involved, and the peculiarities of each patient. This study focuses on the classification of hand grip postures using sEMG signals acquired from amputee patients. Special emphasis is placed on the use of the time-frequency domain for feature extraction, using the spectral analysis of the reduced-time Fourier transform (STFT).To carry out this task, a classification model based on a convolutional neural network (CNN) is used. The classification method is adjusted, trained, and evaluated through three experiments. The first, called "One to One", yields accuracy percentages of 90.84%, 91.05%, and 91.13% for spectrograms of 32x32, 64x64, and 128x128 in size, respectively. In the second validation, called "All by One", an accuracy of 62.28% is achieved for spectrograms of 32x32 pixels. Finally, in the last K-fold cross-validation validation, an average accuracy of 86.73%, 86.77%, and 87.97% is obtained for spectrograms of 32x32, 64x64, and 128x128 in size, respectively.