Search results for: machine performance

Authors: Jiaqi Dong, Qing-Hua Qin, Yi Xiao

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Some of the most fundamental challenges of elastic metamaterials (EMMs) optimization can be attributed to the high consumption of computational power resulted from finite element analysis (FEA) simulations that render the optimization process inefficient. Furthermore, due to the inherent mesh dependence of FEA, minuscule geometry features, which often emerge during the later stages of optimization, induce very fine elements, resulting in enormously high time consumption, particularly when repetitive solutions are needed for computing the objective function. In this study, a surrogate modelling algorithm is developed to reduce computational time in structural optimization of EMMs. The surrogate model is constructed based on a multilayer feedforward artificial neural network (ANN) architecture, trained with prepopulated eigenfrequency data prepopulated from FEA simulation and optimized through regime selection with genetic algorithm (GA) to improve its accuracy in predicting the location and width of the primary elastic band gap. With the optimized ANN surrogate at the core, a Nelder-Mead (NM) algorithm is established and its performance inspected in comparison to the FEA solution. The ANNNM model shows remarkable accuracy in predicting the band gap width and a reduction of time consumption by 47%.

Keywords: artificial neural network, machine learning, mechanical metamaterials, Nelder-Mead optimization

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Authors: Hanlin Liu, Hua Li, Yintan AI

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Network performance prediction (NPP) is essential for the management and optimization of software-defined networking (SDN) and contributes to improving the quality of service (QoS) in SDN to meet the requirements of users. Although current deep learning-based methods can achieve high effectiveness, they still suffer from some problems, such as difficulty in capturing global information of the network, inefficiency in modeling end-to-end network performance, and inadequate graph feature extraction. To cope with these issues, our proposed Graphormer-based architecture for NPP leverages the powerful graph representation ability of Graphormer to effectively model the graph structure data, and a node-edge transformation algorithm is designed to transfer the feature extraction object from nodes to edges, thereby effectively extracting the end-to-end performance characteristics of the network. Moreover, routing oriented centrality measure coefficient for nodes and edges is proposed respectively to assess their importance and influence within the graph. Based on this coefficient, an enhanced feature extraction method and an advanced centrality encoding strategy are derived to fully extract the structural information of the graph. Experimental results on three public datasets demonstrate that the proposed GraphNPP architecture can achieve state-of-the-art results compared to current NPP methods.

Keywords: software-defined networking, network performance prediction, Graphormer, graph neural network

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Authors: Mohsen Azarmjoo, Navid Sharifi, Zahra Alikhani Koopaei

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This article aims to conserve energy and optimize the performance of solar water heaters using modern modeling systems. In this study, a large-scale solar water heater is modeled using an AVR microcontroller, which is a digital processor from the AVR microcontroller family. This mechatronic system will be used to analyze the performance and design of solar collectors, with the ultimate goal of improving the efficiency of the system being used. The findings of this research provide insights into optimizing the performance of solar water heaters. By manipulating the arrangement of solar panels and controlling the water flow through them using the AVR microcontroller, researchers can identify the optimal configurations and operational protocols to achieve the desired temperature and flow conditions. These findings can contribute to the development of more efficient and sustainable heating and cooling systems. This article investigates the optimization of solar water heater performance. It examines the impact of solar panel layout on system efficiency and explores methods of controlling water flow to achieve the desired temperature and flow conditions. The results of this research contribute to the development of more sustainable heating and cooling systems that rely on renewable energy sources.

Keywords: energy conservation, solar water heaters, solar cooling, simulation, mechatronics

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Authors: Azar Baghtaghi

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Financial risk management is critically important as it enables companies to maintain stability and profitability amidst market fluctuations and unexpected events. It involves the precise identification of risks that could impact investments, assets, and potential revenues. By implementing effective risk management strategies, companies can insure themselves against adverse market changes and prevent potential losses. In today's era, where markets are highly complex and influenced by various factors such as macroeconomic policies, exchange rate fluctuations, and natural disasters, the need for meticulous planning to cope with these uncertainties is more pronounced. Ultimately, financial risk management means being prepared for the future and the ability to sustain business in changing environments. A company capable of managing its risks not only achieves sustainable profitability but also gains the confidence of shareholders, investors, and business partners, enhancing its competitive position in the market. In this article, the types of financial risk and risk management strategies for improving financial performance were investigated. By identifying the risks stated in this article and their evaluation techniques, it is possible to improve the organization's financial performance.

Keywords: strategy, risk, risk management, financial performance

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Authors: Mary David, Denis Basila

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This study assessed the Impact of Board Composition on the Performance of Listed Deposit Money Banks in Nigeria. A sample of ten (10) deposit money banks formed the sample of this study. Board size, gender diversity, and board independence were used as the independent variables, and firm size as a control variable, whiles the bank performance was proxy with Tobin’s Q (TQ) as the dependent variable. Secondary data was collected from secondary source through the annual report and account of the banks and was analyzed through the support of STATA 14 versions. Descriptive statistics, correlation matrix, and OLS multiple regression model were adopted for the study. Breusch and pagan lagrangian multiplier test for random effect was conducted. The findings of the study reveal that board size has positive and significant impact on Tobin’s Q, gender diversity has positive and significant impact on Tobin’s Q, while board independent had a negative and nonsignificant influence on the Tobin’s Q, Similarly, firm size was found to have a negative and nonsignificant impact on Tobin’s Q of the study banks. This study recommended that policy makers, stakeholders, and corporate managers of deposit money banks of Nigeria and related industries are encouraged to adopt board sizes and gender diversity that impact positively on bank performance.

Keywords: board composition, performance, deposit money banks, nigeria

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Authors: P. K. Guha Thakurta, Shouvik Roy, Bhawana Raj

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A congestion control scheme in mobile networks is proposed in this paper through a verification based model. The model proposed in this work is represented through performance metric like buffer Occupancy, latency and packet loss rate. Based on pre-defined values, each of the metric is introduced in terms of three different states. A Markov chain based model for the proposed work is introduced to monitor the occurrence of the corresponding state transitions. Thus, the estimation of the network status is obtained in terms of performance metric. In addition, the improved performance of our proposed model over existing works is shown with experimental results.

Keywords: congestion, mobile networks, buffer, delay, call drop, markov chain

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Authors: Agus Sahri, Cahya Putra Dinata, Faishal Andhi Rokhman

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Intersection is a critical area on a highway which is a place of conflict points and congestion due to the meeting of two or more roads. Conflicts that occur at the intersection include diverging, merging, weaving, and crossing. To deal with these conflicts, a crossing control system is needed, at a plot of intersection there are two control systems namely signal intersections and non-signalized intersections. The control system at a plot of intersection can affect the intersection performance. In Indonesia there are still many intersections with poor intersection performance. In analyzing the parameters to measure the performance of a plot of intersection in Indonesia, it is guided by the 1997 Indonesian Road Capacity Manual. For this reason, this study aims to develop laboratory diagnostics at plot intersections to analyze parameters that can affect the performance of an intersection. The research method used is research and development. The laboratory diagnosis includes anamnesis, differential diagnosis, inspection, diagnosis, prognosis, specimens, analysis and sample data analysts. It is expected that this research can encourage the development and application of laboratory diagnostics at a plot of intersection in Indonesia so that intersections can function optimally.

Keywords: intersection, the laboratory diagnostic, control systems, Indonesia

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Authors: Medya Fathi

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When public transportation projects were delivered through design-bid-build and later design-build, governments found a serious issue: inadequate funding. With population growth, governments began to develop new arrangements in which the private sectors were involved to cut the financial burden. This arrangement, known as Public-Private Partnership (PPP), has its own risks; however, performance outputs can motivate or discourage its use. On top of such output's list are time and budget, which can be affected by the type of project delivery methods. Project completion within or ahead of schedule as well as within or under budget is among any owner’s objectives. With a higher application of PPP in the highway industry in the US and insufficient PPP research, the current study addresses the schedule and cost performance of PPP highway projects and determines which one outperforms the other. To meet this objective, after collecting performance data of all PPP projects, schedule growth and cost growth are calculated, and finally, statistical analysis is conducted to evaluate the PPP performance. The results and conclusions will be provided. This study can assist practitioners in applying PPP for transportation projects by showing its ability to save time and/or cost.

Keywords: cost, delivery method, highway, public-private partnership, schedule, transportation

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Authors: D. Vidhyaprakash, A. Elango

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In real-time applications, wheeled mobile robots are increasingly used and operated in extreme and diverse conditions traversing challenging surfaces such as a pitted, uneven terrain, natural flat, smooth terrain, as well as wet and dry surfaces. In order to accomplish such tasks, it is critical that the motion control functions without wheel slip and odometry error during the navigation of the two-wheeled mobile robot (WMR). Wheel slip and odometry error are disrupting factors on overall WMR performance in the form of deviation from desired trajectory, navigation, travel time and budgeted energy consumption. The wheeled mobile robot’s ability to operate at peak performance on various work surfaces without wheel slippage and odometry error is directly connected to four main parameters, which are the range of payload distribution, speed, wheel diameter, and wheel width. This paper analyses the effects of those parameters on overall performance and is concerned with determining the ideal range of parameters for optimum performance.

Keywords: wheeled mobile robot, terrain, wheel slippage, odometryerror, trajectory

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Authors: Azeddine Ghodbane, David Bensoussan, Maher Hammami

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An innovative approach for controlling unstable and invertible systems has demonstrated superior performance compared to conventional controllers. It has been successfully applied to a levitation system and drone control. Simulations have yielded satisfactory performances when applied to a satellite antenna controller. This design method, based on sensitivity analysis, has also been extended to handle multivariable unstable and invertible systems that exhibit dominant diagonal characteristics at high frequencies, enabling decentralized control. Furthermore, this control method has been expanded to the realm of adaptive control. In this study, we introduce an alternative adaptive architecture that enhances both time and frequency performance, helpfully mitigating the effects of disturbances from the input plant and external disturbances affecting the output. To facilitate superior performance in both the time and frequency domains, we have developed user-friendly interactive design methods using the GeoGebra platform.

Keywords: control theory, decentralized control, sensitivity theory, input-output stability theory, robust multivariable feedback control design

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Authors: Carmel Khrisna Wong Moreno, Dinah M. Espina

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The increasing price of feed ingredients has prompted farmers to seek feasible feed alternatives like the utilization of locally-grown protein-rich feedstuff which is cheaper but gives a positive result in poultry production. Trichanthera gigantea, a fodder tree which is an excellent alternative as feed ingredient in the Philippines has now gained popularity as feed supplement. This study was conducted to determine the growth and laying performance of commercial hens fed with varying levels of Trichanthera gigantea leaf meal. The incorporation of Trichanthera gigantea leaf meal at 5%, 10%, and 15% into the diet of commercial hens did not affect the growth and laying performance. Results of the study revealed that the weight gain of the birds fed with Trichanthera gigantea supplemented diets was not significantly different with the control (100% commercial layer mash). The voluntary feed intake, feed conversion ratio, weekly average egg weight and egg production of the commercial hens fed with T. gigantea leaf meal supplemented diets were not significantly different from the control. Results of the study showed that the supplementation of Trichanthera gigantea leaf meal of up to 15% into the diets of commercial hens is highly acceptable since it does not affect the growth and laying performance of the birds. In addition, it would mean a 15% savings in production cost from commercial feeds.

Keywords: egg production, growth, laying performance, trichanthera gigantea (nees)

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Authors: Viacheslav Shkuratskyy, Aminu Bello Usman, Michael O’Dea, Saifur Rahman Sabuj

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This paper examines relationships between solar activity and earthquakes; it applied machine learning techniques: K-nearest neighbour, support vector regression, random forest regression, and long short-term memory network. Data from the SILSO World Data Center, the NOAA National Center, the GOES satellite, NASA OMNIWeb, and the United States Geological Survey were used for the experiment. The 23rd and 24th solar cycles, daily sunspot number, solar wind velocity, proton density, and proton temperature were all included in the dataset. The study also examined sunspots, solar wind, and solar flares, which all reflect solar activity and earthquake frequency distribution by magnitude and depth. The findings showed that the long short-term memory network model predicts earthquakes more correctly than the other models applied in the study, and solar activity is more likely to affect earthquakes of lower magnitude and shallow depth than earthquakes of magnitude 5.5 or larger with intermediate depth and deep depth.

Keywords: k-nearest neighbour, support vector regression, random forest regression, long short-term memory network, earthquakes, solar activity, sunspot number, solar wind, solar flares

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Authors: Reuben Kinyuru Njuguna, Martin Mabuya Njuguna

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Digital platforms, such as The Internet, and the advent of digital marketing strategies, have led to many changes in the marketing of goods and services. These have resulted in improved service quality, enhanced customer relations, productivity gains, marketing transaction cost reductions, improved customer service and flexibility in fulfilling customers’ changing needs and lifestyles. Consequently, the purpose of this study was to determine the effect of digital marketing practices on the financial performance of mobile network operators in the telecommunications industry in Kenya. The objectives of the study were to establish how digital customer relationship management strategies on performance of mobile network operators in Kenya. The study used an explanatory cross-sectional survey research design, while the target population was made up of from the 4 major mobile network operators in Kenya, namely Safaricom Limited, Airtel Networks Kenya Limited, Finserve Africa Limited and Telkom Kenya Limited. Sampling strategy was stratified sampling with a sample size of 97 respondents. Digital customer relationship strategies were seen to influence firm performance, through enhancing convenience, building trust, encouraging growth in market share through creating sustainable relationships, building commitment with customers, enhancing customer retention and customer satisfaction. Digital customer relationship management were seen to maximize gross profits by increasing customer satisfaction, loyalty and retention. The study recommended upscaling the use of digital customer relationship management strategies to further enhance firm performance, given their great potential in this regard.

Keywords: customer relationship management, customer service delivery, performance, customer satisfaction

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Authors: B. Petrović, L. Rutonjski, M. Baucal, M. Teodorović, O. Čudić, B. Basarić

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Purpose/Objective: Radiotherapy treatment planning requires use of CT simulator, in order to acquire CT images. The overall performance of CT simulator determines the quality of radiotherapy treatment plan, and at the end, the outcome of treatment for every single patient. Therefore, it is strongly advised by international recommendations, to set up a quality control procedures for every machine involved in radiotherapy treatment planning process, including the CT scanner/ simulator. The overall process requires number of tests, which are used on daily, weekly, monthly or yearly basis, depending on the feature tested. Materials/Methods: Two phantoms were used: a dedicated phantom CIRS 062QA, and a QA phantom obtained with the CT simulator. The examined CT simulator was Siemens Somatom Definition as Open, dedicated for radiation therapy treatment planning. The CT simulator has a built in software, which enables fast and simple evaluation of CT QA parameters, using the phantom provided with the CT simulator. On the other hand, recommendations contain additional test, which were done with the CIRS phantom. Also, legislation on ionizing radiation protection requires CT testing in defined periods of time. Taking into account the requirements of law, built in tests of a CT simulator, and international recommendations, the intitutional QC programme for CT imulator is defined, and implemented. Results: The CT simulator parameters evaluated through the study were following: CT number accuracy, field uniformity, complete CT to ED conversion curve, spatial and contrast resolution, image noise, slice thickness, and patient table stability.The following limits are established and implemented: CT number accuracy limits are +/- 5 HU of the value at the comissioning. Field uniformity: +/- 10 HU in selected ROIs. Complete CT to ED curve for each tube voltage must comply with the curve obtained at comissioning, with deviations of not more than 5%. Spatial and contrast resultion tests must comply with the tests obtained at comissioning, otherwise machine requires service. Result of image noise test must fall within the limit of 20% difference of the base value. Slice thickness must meet manufacturer specifications, and patient stability with longitudinal transfer of loaded table must not differ of more than 2mm vertical deviation. Conclusion: The implemented QA tests gave overall basic understanding of CT simulator functionality and its clinical effectiveness in radiation treatment planning. The legal requirement to the clinic is to set up it’s own QA programme, with minimum testing, but it remains user’s decision whether additional testing, as recommended by international organizations, will be implemented, so to improve the overall quality of radiation treatment planning procedure, as the CT image quality used for radiation treatment planning, influences the delineation of a tumor and calculation accuracy of treatment planning system, and finally delivery of radiation treatment to a patient.

Keywords: CT simulator, radiotherapy, quality control, QA programme

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Authors: I Gede Puja Astawa, Yoedy Moegiharto, Ahmad Zainudin, Imam Dui Agus Salim, Nur Annisa Anggraeni

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Performance of Orthogonal Frequency Division Multiplexing (OFDM) system can be improved by adding channel coding (error correction code) to detect and correct the errors that occur during data transmission. One can use the convolution code. This paper presents performance of OFDM using Space Time Block Codes (STBC) diversity technique use QAM modulation with code rate 1/2. The evaluation is done by analyzing the value of Bit Error Rate (BER) vs. Energy per Bit to Noise Power Spectral Density Ratio (Eb/No). This scheme is conducted 256 sub-carrier which transmits Rayleigh multipath channel in OFDM system. To achieve a BER of 10-3 is required 30 dB SNR in SISO-OFDM scheme. For 2x2 MIMO-OFDM scheme requires 10 dB to achieve a BER of 10-3. For 4x4 MIMO-OFDM scheme requires 5 dB while adding convolution in a 4x4 MIMO-OFDM can improve performance up to 0 dB to achieve the same BER. This proves the existence of saving power by 3 dB of 4x4 MIMO-OFDM system without coding, power saving 7 dB of 2x2 MIMO-OFDM system without coding and significant power savings from SISO-OFDM system.

Keywords: convolution code, OFDM, MIMO, QAM, BER

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Authors: Mohieldin Elmashad, Salwa Yassin

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Expansive soils regarded as one of the most problematic unsaturated formations in the Egyptian arid zones and present a great challenge in civil engineering, in general, and geotechnical engineering, in particular. Severe geotechnical complications and consequent structural damages have been arising due to an excessive and differential volumetric change upon wetting and change in water content. Different studies have been carried out concerning the swelling performance of the expansive soils using different additives including phospho-gypsum as an industrial waste product. However, this paper describes the results of a comprehensive testing programme that was carried out to investigate the effect of phospho-gypsum (PG) and sodium chloride (NaCl), as an additive mixture, on the swelling performance of constituent samples of swelling soils. The constituent samples comprise commercial bentonite collected from a natural site, mixed with different percentages of PG-NaCl mixture. The testing programme had been scoped to cover the physical and chemical properties of the constituent samples. In addition, a mineralogical study using x-ray diffraction (XRD) was performed on the collected bentonite and the mixed bentonite with PG-NaCl mixture samples. The obtained results of this study showed significant improvement in the swelling performance of the tested samples with the increase of the proposed PG-NaCl mixture content.

Keywords: expansive soils, industrial waste, mineralogical study, swelling performance, X-ray diffraction

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Authors: David Percy

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Landslides are a geologic phenomenon that affects a large number of inhabited places and are constantly being monitored and studied for the prediction of future occurrences. Reconstructability analysis (RA) is a methodology for extracting informative models from large volumes of data that work exclusively with discrete data. While RA has been used in medical applications and social science extensively, we are introducing it to the spatial sciences through applications like landslide prediction. Since RA works exclusively with discrete data, such as soil classification or bedrock type, working with continuous data, such as porosity, requires that these data are binned for inclusion in the model. RA constructs models of the data which pick out the most informative elements, independent variables (IVs), from each layer that predict the dependent variable (DV), landslide occurrence. Each layer included in the model retains its classification data as a primary encoding of the data. Unlike other machine learning algorithms that force the data into one-hot encoding type of schemes, RA works directly with the data as it is encoded, with the exception of continuous data, which must be binned. The usual physical and derived layers are included in the model, and testing our results against other published methodologies, such as neural networks, yields accuracy that is similar but with the advantage of a completely transparent model. The results of an RA session with a data set are a report on every combination of variables and their probability of landslide events occurring. In this way, every combination of informative state combinations can be examined.

Keywords: reconstructability analysis, machine learning, landslides, raster analysis

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Authors: David Gligor

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The purpose of this study was to build on Fisher's (1997) seminal article. First, it sought to determine how companies can achieve supply chain fit (i.e., match between the products' characteristics and the underlying supply chain design). Second, it attempted to develop a better understanding of how environmental conditions impact the relationship between supply chain fit and performance. The findings indicate that firm supply chain agility allows organizations to quickly adjust the structure of their supply chains and therefore, achieve supply chain fit. In addition, archival and survey data were used to explore the moderating effects of six environmental uncertainty dimensions: munificence, market dynamism, technological dynamism, technical complexity, product diversity, and geographic dispersion. All environmental variables, except technological dynamism, were found to impact the relationship between supply chain fit and firm performance.

Keywords: supply chain fit, environmental uncertainty, supply chain agility, management engineering

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Authors: Waleed A. Basuliman, Khalid S. AlSaleh, Mohamed Z. Ramadan

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Applying the anthropometric dimensions is considered one of the important factors when designing any human-machine system. In this study, the estimation of anthropometric dimensions has been improved by developing artificial neural network that aims to predict the anthropometric measurements of the male in Saudi Arabia. A total of 1427 Saudi males from age 6 to 60 participated in measuring twenty anthropometric dimensions. These anthropometric measurements are important for designing the majority of work and life applications in Saudi Arabia. The data were collected during 8 months from different locations in Riyadh City. Five of these dimensions were used as predictors variables (inputs) of the model, and the remaining fifteen dimensions were set to be the measured variables (outcomes). The hidden layers have been varied during the structuring stage, and the best performance was achieved with the network structure 6-25-15. The results showed that the developed Neural Network model was significantly able to predict the body dimensions for the population of Saudi Arabia. The network mean absolute percentage error (MAPE) and the root mean squared error (RMSE) were found 0.0348 and 3.225 respectively. The accuracy of the developed neural network was evaluated by compare the predicted outcomes with a multiple regression model. The ANN model performed better and resulted excellent correlation coefficients between the predicted and actual dimensions.

Keywords: artificial neural network, anthropometric measurements, backpropagation, real anthropometric database

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Authors: Bowei Yuan, Shi Li, Liuyang Song, Huaqing Wang, Lingli Cui

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Convolutional neural networks (CNN) have received extensive attention in the field of fault diagnosis. Many fault diagnosis methods use CNN for fault type identification. However, when the amount of raw data collected by sensors is massive, the neural network needs to perform a time-consuming classification task. In this paper, a mechanical fault diagnosis method based on vibration signal down-sampling and the improved one-dimensional convolutional neural network is proposed. Through the robust principal component analysis, the low-rank feature matrix of a large amount of raw data can be separated, and then down-sampling is realized to reduce the subsequent calculation amount. In the improved one-dimensional CNN, a smaller convolution kernel is used to reduce the number of parameters and computational complexity, and regularization is introduced before the fully connected layer to prevent overfitting. In addition, the multi-connected layers can better generalize classification results without cumbersome parameter adjustments. The effectiveness of the method is verified by monitoring the signal of the centrifugal pump test bench, and the average test accuracy is above 98%. When compared with the traditional deep belief network (DBN) and support vector machine (SVM) methods, this method has better performance.

Keywords: fault diagnosis, vibration signal down-sampling, 1D-CNN

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Authors: Romeo Botes, Imelda Smit

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In today’s modern age of technology vast amounts of data needs to be processed in real-time to keep users satisfied. This data comes from various sources and in many formats, including electronic and mobile devices such as GPRS modems and GPS devices. They make use of different protocols including TCP, UDP, and HTTP/s for data communication to web servers and eventually to users. The data obtained from these devices may provide valuable information to users, but are mostly in an unreadable format which needs to be processed to provide information and business intelligence. This data is not always current, it is mostly historical data. The data is not subject to implementation of consistency and redundancy measures as most other data usually is. Most important to the users is that the data are to be pre-processed in a readable format when it is entered into the database. To accomplish this, programmers build processing programs and scripts to decode and process the information stored in databases. Programmers make use of various techniques in such programs to accomplish this, but sometimes neglect the effect some of these techniques may have on database performance. One of the techniques generally used,is to pull data from the database server, process it and push it back to the database server in one single step. Since the processing of the data usually takes some time, it keeps the database busy and locked for the period of time that the processing takes place. Because of this, it decreases the overall performance of the database server and therefore the system’s performance. This paper follows on a paper discussing the performance increase that may be achieved by utilizing array lists along with a pull-process-push data processing technique split in three steps. The purpose of this paper is to expand the number of clients when comparing the two techniques to establish the impact it may have on performance of the CPU storage and processing time.

Keywords: performance measures, algorithm techniques, data processing, push data, process data, array list

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Authors: Jihyun Park

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This research suggests that meaning in life or Ikigai can be associated with better academic performances in Japanese college students. To measure meaning in life in Japanese college students, the Ikigai questionnaire and the Meaning in Life Questionnaire (MLQ) are both used, and the survey was collected using Microsoft Teams Forms for a total of 80 Japanese college students. The data revealed that students who have a higher than a 3.0 grade point average (GPA) showed the highest score in both the Ikigai and MLQ. The participants with between a 2.0 and a 3.0 GPA reported lower scores in both MLQ and Ikigai than the previous participants. The group of students who have lower than a 2.0 GPA had the lowest scores for MLQ and Ikigai. This result can indicate that implementing meaning in life or Ikigai to early college students can bring about better academic performance, which also can improve students’ college life better as well.

Keywords: college students' academic performance, Ikigai, meaning in life, purpose of life

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Authors: Mahrukh Shehzadi

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Pakistan is a democratic republic but has spent much time under military rulers; after a few years of independence, Pakistan faced three martial laws in 1958, 1969, and 1977, and the latest in 1999 by General Musharraf. The purpose of this thesis is to analyze the politics, policies and overall performance of Pakistan People’s Party Government from 2008-2013. PPP won a significant victory in the elections of 2008. The co-chairman, Mr. Asif Ali Zardari, announced the end of the fourth dictatorship. It was for the first time in Pakistan’s history that an elected government completed its term (2008-2013). While the completion of its term is an achievement, the performance of the democratically-elected government – federal, provincial and local does not inspire much confidence. Poor governance, persistent confrontational relations between the executive and the judiciary, charges of corruption, and the incompetence of the political leadership to build consensus to combat terrorism continue to cast criticisms on the democratic process and the civilian regime’s capability to sustain democracy. In the present study, the researcher will try to describe and explain the public thinking pattern regarding the policies opted for by the PPP-led government and their impact on the people’s minds of Pakistan.

Keywords: democracy, performance, policies, state, manifesto

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Authors: Komlan Sedzro

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We apply the non-parametric, unconditional, hyperbolic order-α quantile estimator to appraise the relative efficiency of Microfinance Institutions in Africa in terms of outreach. Our purpose is to verify if these institutions, which must constantly try to strike a compromise between their social role and financial sustainability are operationally efficient. Using data on African MFIs extracted from the Microfinance Information eXchange (MIX) database and covering the 2004 to 2006 periods, we find that more efficient MFIs are also the most profitable. This result is in line with the view that social performance is not in contradiction with the pursuit of excellent financial performance. Our results also show that large MFIs in terms of asset and those charging the highest fees are not necessarily the most efficient.

Keywords: data envelopment analysis, microfinance institutions, quantile estimation of efficiency, social and financial performance

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Authors: Anocha Kimkong, Natnichar Kleebbuabarn

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This research work has the objective to analyze the financial status and operational performance of Suan Sunandha Rajabhat University (SSRU) in 3 fiscal years (2011-2013). The tool used is a form to record financial statements and balances of the university. The analysis is based on the calculation that regards the figures in the fiscal year of 2011 as the 100% bases to be compared with the same figures in the fiscal years of 2012 and 2013, which are multiplied by 100 and divided by the base figures. The outcomes are the percentages of each year, which can reflect the rising, stable, and falling trends. The results from the analysis reveal that SSRU’s financial status is getting better because the gross assets, debts and accumulated cash are increasing in the fiscal years of 2012 and 2013. Concerning the operational performance, the university’s incomes and expenses are rising from the fiscal year of 2011. This makes the university’s incomes grow higher than expenses.

Keywords: financial status, operational performance, Suan Sunandha Rajabhat University, balances

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Authors: Muhammad Tahir

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Purpose The purpose of the study is to find anchoring bias behavior in mutual fund return with its parent firm performance in Pakistan. Research Methodology The paper used monthly returns of equity funds whose parent firm exist from 2011 to 2021, along with parent firm return. Proximity to 52-week highest return calculated by dividing fund return by parent firm 52-week highest return. Control variables are also taken and used pannel regression model to estimate our results. For robust results, we also used feasible generalize least square (FGLS) model. Findings The results showed that there exist anchoring biased in mutual fund return with its parent firm performance. The FGLS results reaffirms the same results as obtained from panner regression results. Proximity to 52-week highest Xc is significant in both models. Research Implication Since most of mutual funds has a parent firm, anchoring behavior biased found in mutual fund with its parent firm performance. Practical Implication Mutual fund investors in Pakistan invest in equity funds in which behavioral bias exist, although there might be better opportunity in market. Originality/Value Addition Our research is a pioneer study to investigate anchoring bias in mutual fund return with its parent firm performance. Research limitations Our sample is limited to only 23 equity funds, which has a parent firm and data was available from 2011 to 2021.

Keywords: mutual fund, anchoring bias, 52-week high return, proximity to 52-week high, parent firm performance, pannel regression, FGLS

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Authors: Marina Tsetseli, Eleni Zetou, Maria Michalopoulou, Nikos Vernadakis

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Game performance, besides the accuracy and the quality skills execution, depends heavily on where the athletes will focus their attention while performing a skill. The purpose of the present study was to examine and compare the effect of internal and external focus of attention instructions on the decision making in tennis at players 8-9 years old (M=8.4, SD=0.49). The participants (N=40) were divided into two groups and followed an intervention training program that lasted 4 weeks; first group (N=20) under internal focus of attention instructions and the second group (N=20) under external focus of attention instructions. Three measurements took place (pre-test, post-test, and retention test) in which the participants were video recorded while playing matches in real scoring conditions. GPAI (Game Performance Assessment Instrument) was used to evaluate decision making in three game situations; service, return of the service, baseline game. ANOVA repeated measures (2 groups x 3 measurements) revealed a significant interaction between groups and measurements. Specifically, the data analysis showed superiority of the group that was instructed to focus externally. The high scores of the external attention group were maintained at the same level at the third measurement as well, which indicates that the impact was concerning not only performance but also learning. Thus, cues that lead to an external focus of attention enhance the decision-making skill and therefore the game performance of the young tennis players.

Keywords: decision making, evaluation, focus of attention, game performance, tennis

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Authors: Zeplin Jiwa Husada Tarigan, Sautma Ronni Basana, Widjojo Suprapto

Abstract:

Manufacturing companies in East Java develop their own ERP system or alter the ERP system which is developed by other companies to suit their needs. To make their own system, the companies mostly assign several employees from various departments to create a project team, and the employees are from the departments that are going to utilize the ERP system as the integrated data. The project team decides the making of the ERP system from the preparation stage until the going live implementation process. In designing the business process, the top management is working together with the project team until the project is accomplished. The completion of the ERP projects depends on the project to be undertaken itself, the strategy chosen to complete the project, the work method selection, the measurement system to monitor the project, the evaluation system of the project, and, in the end, the declaration of 'going live' of the ERP project. There is an increase in the business performance for the companies that have implemented the information technology or ERP as they manage to integrate all management functions within their companies. To investigate, some questionnaires are distributed to 100 manufacturing companies, and 90 questionnaires are returned; however, there are only 46 companies that develop their own ERP system, so the response rate is 46%. The result of data analysis using PLS shows that the management competency brings impacts to the project team and the process design. The process design is adjusted to the real process in order to implement the ERP, but it does not bring direct impacts to the business performance. The implementation of ERP brings positive impacts to the company business performance.

Keywords: management competency, project team, process design, ERP implementation, business performance

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Authors: Bin Liu

Abstract:

MicroRNAs (miRNAs) are small non-coding RNA molecules, functioning in transcriptional and post-transcriptional regulation of gene expression. The discrimination of the real pre-miRNAs from the false ones (such as hairpin sequences with similar stem-loops) is necessary for the understanding of miRNAs’ role in the control of cell life and death. Since both their small size and sequence specificity, it cannot be based on sequence information alone but requires structure information about the miRNA precursor to get satisfactory performance. Kmers are convenient and widely used features for modeling the properties of miRNAs and other biological sequences. However, Kmers suffer from the inherent limitation that if the parameter K is increased to incorporate long range effects, some certain Kmer will appear rarely or even not appear, as a consequence, most Kmers absent and a few present once. Thus, the statistical learning approaches using Kmers as features become susceptible to noisy data once K becomes large. In this study, we proposed a Gapped k-mer approach to overcome the disadvantages of Kmers, and applied this method to the field of miRNA prediction. Combined with the structure status composition, a classifier called imiRNA-GSSC was proposed. We show that compared to the original imiRNA-kmer and alternative approaches. Trained on human miRNA precursors, this predictor can achieve an accuracy of 82.34 for predicting 4022 pre-miRNA precursors from eleven species.

Keywords: gapped k-mer, imiRNA-GSSC, microRNA precursor, support vector machine

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Authors: Suleiman Garba, Haruna Ishaku

Abstract:

Information and communication technology (ICT) includes any communication device encompassing: radio, television, cellular phones, computer, satellite systems and so on, as well as the various services and applications associated with them. The significance of ICT cannot be over-emphasized in education. The teaching and learning processes have integrated with the application of ICTs for effectiveness and enhancement of academic performance among the students. Today, as the educational sector is faced with series of changes and reforms, it was noted that the problem of information technology illiteracy was a serious one among the schools’ teachers in the country as it cuts across primary, secondary schools and tertiary institutions. This study investigated the impact of ICT on the academic performance of senior secondary schools students in Gwagwalada Area Council of Federal Capital Territory (FCT), Abuja. A sample of 120 SSS III students was involved in the study. They were selected by using simple random sampling technique. A questionnaire was developed and validated through expert judgement and reliability co-efficient of 0.81 was obtained. It was used to gather relevant data from the respondents. Findings revealed that there was positive impact of ICT on academic performance of senior secondary schools students. The findings indicated the causes of poor academic performance among the students as lack of qualified teachers to teach in schools, peer group influence, and bullying. Significantly, the findings revealed that ICT had a positive impact on students’ academic performance. The null hypotheses were tested using t-test at 0.05 level of significance. It was discovered that there was significant difference between male and female secondary schools’ students' impact of ICT on academic performance in Gwagawalada Area Council of FCT-Abuja. Based on these findings, some recommendations were made which include: adequate funds should be provided towards procurement of ICT resources, relevant textbooks to enhance students’ active participation in learning processes and students should be provided with internet accessibility at inexpensive rate so as to create a platform for accessing useful information in the pursuit of academic excellence.

Keywords: academic performance, impact, information communication technology, schools, students

Procedia PDF Downloads 208