Search results for: sustainable supply chain performance

Authors: Amirhossein Mohajerzadeh, Abolghasem Mohajerzadeh

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In this paper, target parameter is estimated with desirable precision in hierarchical wireless sensor networks (WSN) while the proposed algorithm also tries to prolong network lifetime as much as possible, using efficient data collecting algorithm. Target parameter distribution function is considered unknown. Sensor nodes sense the environment and send the data to the base station called fusion center (FC) using hierarchical data collecting algorithm. FC builds underlying phenomena based on collected data. Considering the aggregation level, x, the goal is providing the essential infrastructure to find the best value for aggregation level in order to prolong network lifetime as much as possible, while desirable accuracy is guaranteed (required sample size is fully depended on desirable precision). First, the sample size calculation algorithm is discussed, second, the average queue length based on M/M[x]/1/K queue model is determined and it is used for energy consumption calculation. Nodes can decrease transmission cost by aggregating incoming data. Furthermore, the performance of the new algorithm is evaluated in terms of lifetime and estimation accuracy.

Keywords: aggregation, estimation, queuing, wireless sensor network

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Authors: A. Yongsheng Guo, B. Obedat. Abdulazeez, C. Xiaoxian Zhu

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This study aimed to identify the barriers to the development of small and medium-sized enterprises (SMEs) in China and build a theoretical framework to evaluate the support provided by the authorities and institutions. A grounded theory approach was adopted to collect and analyze data. 32 interviews were conducted with SME managers, and open, axial and selective coding was utilized to develop themes. Based on institutional theory, grounded theory models were used to present findings. The findings showed that the main barriers in the business environment were defaulting on contracts, bureaucracy in procedures, lack of financial and legal support, limited intermediaries and channels, and poor quality of products and services. This study found that many programs were provided to support SMEs. A theoretical framework was developed to evaluate the performance of the programs from the managers’ perspective. The concepts of economy, efficiency and effectiveness were used to evaluate the perceived value of the programs. This study suggests that specialized programs are needed to suit sector-specific requirements, and creative packages are helpful in supporting SMEs' growth.

Keywords: business support, public economics, public programme, SME

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Authors: Arthur D. Wiedemann, Christopher Fuller, Kyle A. Pascioni

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With the introduction of electric motors, small unmanned aerial vehicle designers have to consider trade-offs between acoustic noise and thrust generated. Currently, there are few low-computational tools available for predicting acoustic noise emitted by a propeller into the far-field. Artificial neural networks offer a highly non-linear and adaptive model for predicting isolated and interactive tonal noise. But neural networks require large data sets, exceeding practical considerations in modeling experimental results. A methodology known as physics guided machine learning has been applied in this study to reduce the required data set to train the network. After building and evaluating several neural networks, the best model is investigated to determine how the network successfully predicts the acoustic waveform. Lastly, a post-network transfer function is developed to remove discontinuity from the predicted waveform. Overall, methodologies from physics guided machine learning show a notable improvement in prediction performance, but additional loss functions are necessary for constructing predictive networks on small datasets.

Keywords: aeroacoustics, machine learning, propeller, rotor, neural network, physics guided machine learning

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Authors: Ebenezer O. Olaniyi, Oyebade K. Oyedotun, Khashman Adnan

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In the food industry high quality production is required within a limited time to meet up with the demand in the society. In this research work, we have developed a model which can be used to replace the human operator due to their low output in production and slow in making decisions as a result of an individual differences in deciding the defective and healthy banana. This model can perform the vision attributes of human operators in deciding if the banana is defective or healthy for food production based. This research work is divided into two phase, the first phase is the image processing where several image processing techniques such as colour conversion, edge detection, thresholding and morphological operation were employed to extract features for training and testing the network in the second phase. These features extracted in the first phase were used in the second phase; the classification system phase where the multilayer perceptron using backpropagation neural network was employed to train the network. After the network has learned and converges, the network was tested with feedforward neural network to determine the performance of the network. From this experiment, a recognition rate of 97% was obtained and the time taken for this experiment was limited which makes the system accurate for use in the food industry.

Keywords: banana, food processing, identification system, neural network

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Authors: Khue Nguyen Dinh, Loi Nguyen Van, Thanh Nguyen Nhu

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In this paper, we propose an adaptive method to resolve ambiguities and a ghost target removal process to extract targets detected by a ground-based pulse-Doppler radar using medium pulse repetition frequency (PRF) waveforms. The ambiguity resolution method is an adaptive implementation of the coincidence algorithm, which is implemented on a two-dimensional (2D) range-velocity matrix to resolve range and velocity ambiguities simultaneously, with a proposed clustering filter to enhance the anti-error ability of the system. Here we consider the scenario of multiple target environments. The ghost target removal process, which is based on the power after Doppler processing, is proposed to mitigate ghosting detections to enhance the performance of ground-based radars using a short PRF schedule in multiple target environments. Simulation results on a ground-based pulsed Doppler radar model will be presented to show the effectiveness of the proposed approach.

Keywords: ambiguity resolution, coincidence algorithm, medium PRF, ghosting removal

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Authors: Wanhyun Cho, Soonja Kang, Sangkyoon Kim, Soonyoung Park

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In this paper, we present the human action recognition method using the variational Bayesian HMM with the Dirichlet process mixture (DPM) of the Gaussian-Wishart emission model (GWEM). First, we define the Bayesian HMM based on the Dirichlet process, which allows an infinite number of Gaussian-Wishart components to support continuous emission observations. Second, we have considered an efficient variational Bayesian inference method that can be applied to drive the posterior distribution of hidden variables and model parameters for the proposed model based on training data. And then we have derived the predictive distribution that may be used to classify new action. Third, the paper proposes a process of extracting appropriate spatial-temporal feature vectors that can be used to recognize a wide range of human behaviors from input video image. Finally, we have conducted experiments that can evaluate the performance of the proposed method. The experimental results show that the method presented is more efficient with human action recognition than existing methods.

Keywords: human action recognition, Bayesian HMM, Dirichlet process mixture model, Gaussian-Wishart emission model, Variational Bayesian inference, prior distribution and approximate posterior distribution, KTH dataset

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Authors: Jamshid Hussain, Kuen Song Lin

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Over one thousand tons of pig hair biowaste (PHB) are produced yearly in Taiwan. The improper disposal of PHB can have a negative impact on the environment, consequently contributing to the spread of diseases. The treatment of PHB has become a major environmental and economic challenge. Innovative treatments must be developed because of the heavy metal and sulfur content of PHB. Like most organic materials, PHB is composed of many organic volatiles that contain large amounts of hydrogen. Hydrogen gas can be effectively produced by the catalytic gasification of PHB using a laboratory-scale fixed-bed gasifier, employing 15 wt% NiO/Al₂O₃ catalyst at 753–913 K. The derived kinetic parameters were obtained and refined using simulation calculations. FE–SEM microphotograph showed that NiO/Al₂O₃ catalyst particles are Spherical or irregularly shaped with diameters of 10–20 nm. HR–TEM represented that the fresh Ni particles were evenly dispersed and uniform in the microstructure of Al₂O₃ support. The sizes of the NiO nanoparticles were vital in determining catalyst activity. As displayed in the pre-edge XANES spectra of the NiO/Al₂O₃ catalysts, it exhibited a non-intensive absorbance nature for the 1s to 3d transition, which is prohibited by the selection rule for an ideal octahedral symmetry. Similarly, the populace of Ni(II) and Ni(0) onto Al₂O₃ supports are proportional to the strength of the 1s to 4pxy transition, respectively. The weak shoulder at 8329–8334 eV and a strong character at 8345–8353 eV were ascribed to the 1s to 4pxy shift, which suggested the presence of NiO types onto Al₂O₃ support in PHB catalytic gasification. As determined by the XANES analyses, Ni(II)→Ni(0) reduction was mostly observed. The oxidation of PHB onto the NiO/Al₂O₃ surface may have resulted in Ni(0) and the formation of tar during the gasification process. The EXAFS spectra revealed that the Ni atoms with Ni–Ni/Ni–O bonds were found. The Ni–O bonding proved that the produced syngas were unable to reduce NiO to Ni(0) completely. The weakness of the Ni–Ni bonds may have been caused by the highly dispersed Ni in the Al₂O₃ support. The central Ni atoms have Ni–O (2.01 Å) and Ni–Ni (2.34 Å) bond distances in the fresh NiO/Al₂O₃ catalyst. The PHB was converted into hydrogen-rich syngas (CO + H₂, >89.8% dry basis). When PHB (250 kg h−1) was catalytically gasified at 753–913 K, syngas was produced at approximately 5.45 × 105 kcal h−1 of heat recovery with 76.5%–83.5% cold gas efficiency. The simulation of the pilot-scale PHB catalytic gasification demonstrated that the system could provide hydrogen (purity > 99.99%) and generate electricity for an internal combustion engine of 100 kW and a proton exchange membrane fuel cell (PEMFC) of 175 kW. A projected payback for a PHB catalytic gasification plant with a capacity of 10- or 20-TPD (ton per day) was around 3.2 or 2.5 years, respectively.

Keywords: pig hair biowaste, catalytic gasification, hydrogen production, PEMFC, resource recovery

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Authors: Larissa Negris de Souza, Ana Regina Mizrahy Cuperschmid, Daniel de Carvalho Moreira

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Augmented Reality (AR) alters the elaboration of the architectural project, which relates to project cognition: representation, visualization, and perception of information. Understanding these features from the earliest stages of the design can facilitate the study of relationships, zoning, and overall dimensions of the forms. This paper’s goal was to explore a new approach for information visualization during the early stages of architectural design using Augmented Reality (AR). A three-dimensional marker inspired by the Rubik’s Cube was developed, and its performance, evaluated. This investigation interwovens the acquired knowledge of traditional briefing methods and contemporary technology. We considered the concept of patterns (Alexander et al. 1977) to outline geometric forms and associations using visual programming. The Design Science Research was applied to develop the study. An SDK was used in a game engine to generate the AR app. The tool's functionality was assessed by verifying the readability and precision of the reconfigurable 3D marker. The results indicated an inconsistent response. To use AR in the early stages of architectural design the system must provide consistent information and appropriate feedback. Nevertheless, we conclude that our framework sets the ground for looking deep into AR tools for briefing design.

Keywords: augmented reality, cuboid marker, early design stages, graphic representation, patterns

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Authors: Dalal N. Hammod, Ekhlas K. Gbashi

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Today, cryptography is used in many applications to achieve high security in data transmission and in real-time communications. AES has long gained global acceptance and is used for securing sensitive data in various industries but has suffered from slow processing and take a large time to transfer data. This paper suggests a method to enhance Advance Encryption Standard (AES) Algorithm based on time and permutation. The suggested method (MAES) is based on modifying the SubByte and ShiftRrows in the encryption part and modification the InvSubByte and InvShiftRows in the decryption part. After the implementation of the proposal and testing the results, the Modified AES achieved good results in accomplishing the communication with high performance criteria in terms of randomness, encryption time, storage space, and avalanche effects. The proposed method has good randomness to ciphertext because this method passed NIST statistical tests against attacks; also, (MAES) reduced the encryption time by (10 %) than the time of the original AES; therefore, the modified AES is faster than the original AES. Also, the proposed method showed good results in memory utilization where the value is (54.36) for the MAES, but the value for the original AES is (66.23). Also, the avalanche effects used for calculating diffusion property are (52.08%) for the modified AES and (51.82%) percentage for the original AES.

Keywords: modified AES, randomness test, encryption time, avalanche effects

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Authors: Sekkal Nawel, Mahammed Nadir

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The proliferation of online activities on Online Social Networks (OSNs) has captured significant user attention. However, this growth has been hindered by the emergence of fraudulent accounts that do not represent real individuals and violate privacy regulations within social network communities. Consequently, it is imperative to identify and remove these profiles to enhance the security of OSN users. In recent years, researchers have turned to machine learning (ML) to develop strategies and methods to tackle this issue. Numerous studies have been conducted in this field to compare various ML-based techniques. However, the existing literature still lacks a comprehensive examination, especially considering different OSN platforms. Additionally, the utilization of bio-inspired algorithms has been largely overlooked. Our study conducts an extensive comparison analysis of various fake profile detection techniques in online social networks. The results of our study indicate that supervised models, along with other machine learning techniques, as well as unsupervised models, are effective for detecting false profiles in social media. To achieve optimal results, we have incorporated six bio-inspired algorithms to enhance the performance of fake profile identification results.

Keywords: machine learning, bio-inspired algorithm, detection, fake profile, system, social network

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Authors: Pesaru Vigneshwar Reddy, Parvathaneni Pavan

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Green organic chemistry which is the latest and one of the most researched topics now-a- days has been in demand since 1990’s. Majority of the research in green organic chemistry chemicals are some of the important starting materials for greater number of major chemical industries. The production of organic chemicals has raw materials (or) reagents for other application is major sector of manufacturing polymers, pharmaceuticals, pesticides, paints, artificial fibers, food additives etc. organic synthesis on a large scale compound to the labratory scale, involves the use of energy, basic chemical ingredients from the petro chemical sectors, catalyst and after the end of the reaction, seperation, purification, storage, packing distribution etc. During these processes there are many problems of health and safety for workers in addition to the environmental problems caused there by use and deposition as waste. Green chemistry with its 12 principles would like to see changes in conventional way that were used for decades to make synthetic organic chemical and the use of less toxic starting materials. Green chemistry would like to increase the efficiency of synthetic methods, to use less toxic solvents, reduce the stage of synthetic routes and minimize waste as far as practically possible. In this way, organic synthesis will be part of the effort for sustainable development Green chemistry is also interested for research and alternatives innovations on many practical aspects of organic synthesis in the university and research labaratory of institutions. By changing the methodologies of organic synthesis, health and safety will be advanced in the small scale laboratory level but also will be extended to the industrial large scale production a process through new techniques. The three key developments in green chemistry include the use of super critical carbondioxide as green solvent, aqueous hydrogen peroxide as an oxidising agent and use of hydrogen in asymmetric synthesis. It also focuses on replacing traditional methods of heating with that of modern methods of heating like microwaves traditions, so that carbon foot print should reduces as far as possible. Another beneficiary of this green chemistry is that it will reduce environmental pollution through the use of less toxic reagents, minimizing of waste and more bio-degradable biproducts. In this present paper some of the basic principles, approaches, and early achievements of green chemistry has a branch of chemistry that studies the laws of passing of chemical reactions is also considered, with the summarization of green chemistry principles. A discussion about E-factor, old and new synthesis of ibuprofen, microwave techniques, and some of the recent advancements also considered.

Keywords: energy, e-factor, carbon foot print, micro-wave, sono-chemistry, advancement

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Authors: Manirath Wongsim, Chatchawarn Srimontree, Pornpichit Phosri

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Today, the majority of the data innovation may be currently majorly influencing business, what more accepted part of the accountant may be evolving. Information Technology elements have been appearing to be crucial in triggering changes of accountants’ roles. Thus, this study aims to investigate IT competencies among professional accountants to enhance firm performance. This research was conducted with 47 respondents at five organizations in Thailand and used quantitative research. The results indicate that the factor IT competencies for professional accountants in Thai small to medium accounting within the organizational issues defines18 factors. Specifically, these new factors, based on the research findings and the literature, then unique to IT competencies for professional accountants, include ERP software skills and accounting law and legal skills. The evidence in this study suggests that Analytical skills, teamwork skills, and accounting software were ranked as much-needed skills to be acquired by accountants while communication skills were ranked as the most required skills and delegation skills as the least required. The findings of the research’s empirical evidence suggest that organizations should understand appropriate in developing information technology influence competencies for knowledge employees in general and professional accountants in particular and provide assistance in all processes of decision making.

Keywords: IT competencies, IT competences for professional accountants, IT skills for accounting, IT skills in SMEs

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Authors: Lahcen Daoudi, Fatima Zahra Omdi, Abldelali Gourfi

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In Morocco, as in most Mediterranean countries, water scarcity is a common situation because of low and unevenly distributed rainfall. The expansions of irrigated lands, as well as the growth of urban and industrial areas and tourist resorts, contribute to an increase of water demand. Therefore in the 1960s Morocco embarked on an ambitious program to increase the number of dams to boost water retention capacity. However, the decrease in the capacity of these reservoirs caused by sedimentation is a major problem; it is estimated at 75 million m3/year. Dams and reservoirs became unusable for their intended purposes due to sedimentation in large rivers that result from soil erosion. Soil erosion presents an important driving force in the process affecting the landscape. It has become one of the most serious environmental problems that raised much interest throughout the world. Monitoring soil erosion risk is an important part of soil conservation practices. The estimation of soil loss risk is the first step for a successful control of water erosion. The aim of this study is to estimate the soil loss risk and its spatial distribution in the different fields of Morocco and to prioritize areas for soil conservation interventions. The approach followed is the Revised Universal Soil Loss Equation (RUSLE) using remote sensing and GIS, which is the most popular empirically based model used globally for erosion prediction and control. This model has been tested in many agricultural watersheds in the world, particularly for large-scale basins due to the simplicity of the model formulation and easy availability of the dataset. The spatial distribution of the annual soil loss was elaborated by the combination of several factors: rainfall erosivity, soil erodability, topography, and land cover. The average annual soil loss estimated in several basins watershed of Morocco varies from 0 to 50t/ha/year. Watersheds characterized by high-erosion-vulnerability are located in the North (Rif Mountains) and more particularly in the Central part of Morocco (High Atlas Mountains). This variation of vulnerability is highly correlated to slope variation which indicates that the topography factor is the main agent of soil erosion within these basin catchments. These results could be helpful for the planning of natural resources management and for implementing sustainable long-term management strategies which are necessary for soil conservation and for increasing over the projected economic life of the dam implemented.

Keywords: soil loss, RUSLE, GIS-remote sensing, watershed, Morocco

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Authors: Achirawatt Tungsombatsanti, Toansakul Santiboon, Kamon Ponkham

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Strategies of the STEM education was aimed to prepare of an interdisciplinary and applied approach for the instructional of science, technology, engineering, and mathematics in an integrated students for enhancing engagement of their science skills to the Problem-Based Learning (PBL) method in Borabu School with a sample consists of 80 students in 2 classes at the 12th grade level of their learning achievements on electromagnetic issue. Research administrations were to separate on two different instructional model groups, the 40-experimental group was designed with the STEM instructional experimenting preparation and induction in a 40-student class and the controlling group using the PBL was designed to students identify what they already know, what they need to know, and how and where to access new information that may lead to the resolution of the problem in other class. The learning environment perceptions were obtained using the 35-item Physics Laboratory Environment Inventory (PLEI). Students’ creating attitude skills’ sustainable development toward physics were assessed with the Test Of Physics-Related Attitude (TOPRA) The term scaling was applied to the attempts to measure the attitude objectively with the TOPRA was used to assess students’ perceptions of their science attitude toward physics. Comparisons between pretest and posttest techniques were assessed students’ learning achievements on each their outcomes from each instructional model, differently. The results of these findings revealed that the efficiency of the PLB and the STEM based on criteria indicate that are higher than the standard level of the 80/80. Statistically, significant of students’ learning achievements to their later outcomes on the controlling and experimental physics class groups with the PLB and the STEM instructional designs were differentiated between groups at the .05 level, evidently. Comparisons between the averages mean scores of students’ responses to their instructional activities in the STEM education method are higher than the average mean scores of the PLB model. Associations between students’ perceptions of their physics classes to their attitudes toward physics, the predictive efficiency R2 values indicate that 77%, and 83% of the variances in students’ attitudes for the PLEI and the TOPRA in physics environment classes were attributable to their perceptions of their physics PLB and the STEM instructional design classes, consequently. An important of these findings was contributed to student understanding of scientific concepts, attitudes, and skills as evidence with STEM instructional ought to higher responding than PBL educational teaching. Statistically significant between students’ learning achievements were differentiated of pre and post assessments which overall on two instructional models.

Keywords: learning instructional managements, problem-based learning, STEM education, method, enhancement, students learning achievements, science attitude, physics classes

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Authors: Soo Hyung Kim

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Two different learning approaches were suggested: focusing on factual knowledge or focusing on the embedded meaning in the statements. Each way of learning has positive effects on different question categories, where factual knowledge helps more with simple fact questions, and searching for meaning in given information helps learn causal relationship and the embedded meaning. To test this belief, two groups of learners (12 male and 39 female adults aged 18-37) watched a ten-minute long Youtube video about various factual events of American history, their meaning, and the causal relations of the events. The fact group was asked to focus on factual knowledge in the video, and the meaning group was asked to focus on the embedded meaning in the video. After watching the video, both groups took multiple-choice questions, which consisted of 10 questions asking the factual knowledge addressed in the video and 10 questions asking embedded meaning in the video, such as the causal relationship between historical events and the significance of the event. From ANCOVA analysis, it was found that the factual knowledge showed higher performance on the factual questions than the meaning group, although there was no group difference on the questions about the meaning between the two groups. The finding suggests that teacher instruction plays an important role in learners constructing a different type of knowledge in online learning.

Keywords: factual knowledge, instruction, meaning-based knowledge, online learning

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Authors: Tazeen Fatima

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Use of project management in web & software development projects is very significant. It has been observed that even with the application of effective project management, projects usually do not complete their lifecycle and fail. To minimize these failures, key performance indicators have been introduced in previous studies to counter project failures. However, there are always gaps and problems in the KPIs identified. Despite of incessant efforts at technical and managerial levels, projects still fail. There is no substantial approach to identify and avoid these failures in the very beginning of the project lifecycle. In this study, we aim to answer these research problems by analyzing the concept of predictive analytics which is a specialized technology and is very easy to use in this era of computation. Project organizations can use data gathering, compute power, and modern tools to render efficient Predictions. The research aims to identify such a predictive analytics approach. The core objective of the study was to reduce failures and introduce effective implementation of project management principles. Existing predictive analytics methodologies, tools and solution providers were also analyzed. Relevant data was gathered from projects and was analyzed via predictive techniques to make predictions well advance in time to render effective project management in web & software development industry.

Keywords: project management, predictive analytics, predictive analytics methodology, project failures

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Authors: Sonia Perez-Gamboa, Qingquan Sun, Yan Zhang

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Non-intrusive sensor-based human activity recognition (HAR) is utilized in a spectrum of applications, including fitness tracking devices, gaming, health care monitoring, and smartphone applications. Deep learning models such as convolutional neural networks (CNNs) and long short term memory (LSTM) recurrent neural networks (RNNs) provide a way to achieve HAR accurately and effectively. In this paper, we design a multi-layer hybrid architecture with CNN and LSTM and explore a variety of multi-layer combinations. Based on the exploration, we present a lightweight, hybrid, and multi-layer model, which can improve the recognition performance by integrating local features and scale-invariant with dependencies of activities. The experimental results demonstrate the efficacy of the proposed model, which can achieve a 94.7% activity recognition rate on a benchmark human activity dataset. This model outperforms traditional machine learning and other deep learning methods. Additionally, our implementation achieves a balance between recognition rate and training time consumption.

Keywords: deep learning, LSTM, CNN, human activity recognition, inertial sensor

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Authors: J. Satya Eswari, Ch. Venkateswarlu

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The formulation of a commercial pharmaceutical product involves several composition factors and response characteristics. When the formulation requires to satisfy multiple response characteristics which are conflicting, an optimal solution requires the need for an efficient multiobjective optimization technique. In this work, a regression is combined with a non-dominated sorting differential evolution (NSDE) involving Naïve & Slow and ε constraint techniques to derive different multiobjective optimization strategies, which are then evaluated by means of a trapidil pharmaceutical formulation. The analysis of the results show the effectiveness of the strategy that combines the regression model and NSDE with the integration of both Naïve & Slow and ε constraint techniques for Pareto optimization of trapidil formulation. With this strategy, the optimal formulation at pH=6.8 is obtained with the decision variables of micro crystalline cellulose, hydroxypropyl methylcellulose and compression pressure. The corresponding response characteristics of rate constant and release order are also noted down. The comparison of these results with the experimental data and with those of other multiple regression model based multiobjective evolutionary optimization strategies signify the better performance for optimal trapidil formulation.

Keywords: pharmaceutical formulation, multiple regression model, response surface method, radial basis function network, differential evolution, multiobjective optimization

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Authors: Xinyong Li

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A new coupling system was constructed by combining photo-electrochemical cell with eletro-fenton cell (PEC-EF). The electrode material in this system was derived from MnyFe₁₋yCo Prussian-Blue-Analog (PBA). Mn₀.₄Fe₀.₆Co₀.₆₇-N@C spin-coated on carbon paper behaved as the gas diffusion cathode and Mn₀.₄Fe₀.₆Co₀.₆₇O₂.₂ spin-coated on fluorine-tin oxide glass (FTO) as anode. The two separated cells could degrade Sulfamethoxazole (SMX) simultaneously and some coupling mechanisms by PEC and EF enhancing the degradation efficiency were investigated. The continuous on-site generation of H₂O₂ at cathode through an oxygen reduction reaction (ORR) was realized over rotating ring-disk electrode (RRDE). The electron transfer number (n) of the ORR with Mn₀.₄Fe₀.₆Co₀.₆₇-N@C was 2.5 in the selected potential and pH range. The photo-electrochemical properties of Mn₀.₄Fe₀.₆Co₀.₆₇O₂.₂ were systematically studied, which displayed good response towards visible light. The photo-induced electrons at anode can transfer to cathode for further use. Efficient photo-electro-catalytic performance was observed in degrading SMX. Almost 100% SMX removal was achieved in 120 min. This work not only provided a highly effective technique for antibiotic treatment but also revealed the synergic effect between PEC and EF.

Keywords: Electro-Fenton, photo-electrochemical, synergic effect, sulfamethoxazole

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Authors: Mohammad Amjad, Muhammad Iqbal Zafar, Ashfaq Ahmed Maan, Muhammad Tayyab Kashif

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Obesity is an abnormal physical condition where an increased and undesirable fat accumulates in the human body. Obesity is an international phenomenon. In the present study, 12 schools were randomly selected from each district considering the areas i.e. Elite Private Schools in the private sector, Government schools in urban areas and Government schools in rural areas. Interviews were conducted with male students studying in grade 5 to grade 9 in each school. The sample size was 600 students; 300 from Faisalabad district and 300 from Rawalpindi district in Pakistan. A well-structured and pre-tested questionnaire was used for data collection. The calibrated scales were used to attain the heights and weights of the respondents. Obesity of school-going children depends on family types, family size, family history, junk food consumption, mother’s education, weekly time spent in walking, and sports facility at school levels. Academic performance, physical health and psychological health of school going children are affected with obesity. Concrete steps and policies could minimize the incidence of obesity in children in Pakistan.

Keywords: body mass index, cardiovascular disease, fast food, morbidity, overweight

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Authors: Subramaniam Chandran, A. Geetha

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This paper addresses three issues: how to prepare the instructional design for imparting English language skill from inter-disciplinary self-learning material; how the disadvantaged students are benefited from such kind of language skill imparted through m-learning; and how do m-learners perform better than the other learners. This paper examines these issues through an experimental study conducted among the distance learners enrolled in a preparatory program for bachelor’s degree. This program is designed for the disadvantaged learners especially for the school drop-outs to qualify to pursue graduate program through distant education. It also explains how mobile learning helps them to enhance their capacity in learning despite their rural background and other disadvantages. In India, nearly half of the students enrolled in schools do not complete their study. The pursuance of higher education is very low when compared with developed countries. This study finds a significant increase in their learning capacity and mobile learning seems to be a viable alternative where the conventional system could not reach the disadvantaged learners. Improving the English language skill is one of the reasons for such kind of performance. Exercises framed from the relevant self-learning material for enhancing English language skill not only improves language skill but also widens the subject-knowledge. This paper explains these issues out of the study conducted among the disadvantaged learners.

Keywords: English language skill, disadvantaged learners, distance education, m-learning

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Authors: María Molinos-Senante, Giulia Romano

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This paper aims at investigating the effect of ownership in the efficiency assessment of municipal solid waste management. In doing so, the Data Envelopment Analysis meta-frontier approach integrating unsorted waste as undesirable output was applied. Three different clusters of municipalities have been created on the basis of the ownership type of municipal waste operators. In the second stage of analysis, the paper investigates factors affecting efficiency, in order to provide an outlook of levers to be used by policy and decision makers to improve efficiency, taking into account different management models in force. Results show that public waste management firms have better performance than mixed and private ones since their efficiency scores are significantly larger. Moreover, it has been demonstrated that the efficiency of waste management firms is statistically influenced by the age of population, population served, municipal size, population density and tourism rate. It evidences the importance of economies of scale on the cost efficiency of waste management. This issue is relevant for policymakers to define and implement policies aimed to improve the long-term sustainability of waste management in municipalities.

Keywords: data envelopment analysis, efficiency, municipal solid waste, ownership, undesirable output

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Authors: Akram Salah Eddine Belaidi, Said Kenai, El-Hadj Kadri, Benchaâ Benabed, Hamza Soualhi

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Self-compacting concrete (SCC) was developed in the middle of the 1980’s in Japan. SCC flows alone under its dead weight and consolidates itself without any entry of additional compaction energy and without segregation. As an integral part of a SCC, self-compacting mortars (SCM) may serve as a basis for the mix design of concrete since the measurement of the rheological properties of SCCs. This paper discusses the effect of using natural pozzolana (PZ) and marble powder (MP) in two alternative systems ratios PZ/MP = 1 and 1/3 of the performance of the SCC. A total of 11 SCC’s were prepared having a constant water-binder (w/b) ratio of 0.40 and total cementitious materials content of 475 kg/m3. Then, the fresh properties of the mortars were tested for mini-slump flow diameter and mini-V-funnel flow time for SCMs and Slumps flow test, L-Box height ratio, V-Funnel flow time and sieve stability for SCC. Moreover, the development in the compressive strength was determined at 3, 7, 28, 56, and 90 days. Test results have shown that using of ternary blends improved the fresh properties of the mixtures. The compressive strength of SCC at 90 days with 30% of PZ and MP was similar to those of ordinary concrete use in situ.

Keywords: self-compacting mortar, self-compacting concrete, natural pozzolana, marble powder, rheology, compressive strength

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Authors: Yong Zhao, Jian He, Cheng Zhang

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Cardiovascular diseases caused by hypertension are extremely threatening to human health, and early diagnosis of hypertension can save a large number of lives. Traditional hypertension detection methods require special equipment and are difficult to detect continuous blood pressure changes. In this regard, this paper first analyzes the principle of heart rate variability (HRV) and introduces sliding window and power spectral density (PSD) to analyze the time domain features and frequency domain features of HRV, and secondly, designs an HRV-based hypertension prediction network by combining Resnet, attention mechanism, and multilayer perceptron, which extracts the frequency domain through the improved ResNet18 features through a modified ResNet18, its fusion with time-domain features through an attention mechanism, and the auxiliary prediction of hypertension through a multilayer perceptron. Finally, the network was trained and tested using the publicly available SHAREE dataset on PhysioNet, and the test results showed that this network achieved 92.06% prediction accuracy for hypertension and outperformed K Near Neighbor(KNN), Bayes, Logistic, and traditional Convolutional Neural Network(CNN) models in prediction performance.

Keywords: feature extraction, heart rate variability, hypertension, residual networks

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Authors: Amalia Sholihati, Bambang Riyanto Trilaksono

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As an island nation, is a necessity for the Republic of Indonesia to have a capable military defense on land, sea or air that the development of military weapons such as rockets for air defense becomes very important. RKX rocket-200 is one of the guided missiles which are developed by consortium Indonesia and coordinated by LAPAN that serve to intercept the target. RKX-200 is designed to have the speed of Mach 0.5-0.9. RKX rocket-200 belongs to the category two-stage rocket that control is carried out on the second stage when the rocket has separated from the booster. The requirement for better performance to intercept missiles with higher maneuverability continues to push optimal guidance law development, which is derived from non-linear equations. This research focused on the design and implementation of a guidance system based OGL on the rocket RKX-200 while considering the limitation of rockets such as aerodynamic rocket and actuator. Guided missile control system has three main parts, namely, guidance system, navigation system and autopilot systems. As for other parts such as navigation systems and other supporting simulated on MATLAB based on the results of previous studies. In addition to using the MATLAB simulation also conducted testing with hardware-based ARM TWR-K60D100M conjunction with a navigation system and nonlinear models in MATLAB using Hardware-in-the-Loop Simulation (HILS).

Keywords: RKX-200, guidance system, optimal guidance law, Hils

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Authors: Netsanet Kebede Hundessa

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Substrate modification of thin film composite (TFC) membranes with various crosslinkers is typically necessary for organic solvent nanofiltration (OSN) applications. This modification is aimed at enhancing membrane stability and solvent resistance, but it often results in a decline in permeance. This study introduces a distinct approach by developing a coordination-crosslinked polyimide substrate, which differs from the covalently-crosslinked substrates traditionally used. This developed substrate achieves enhanced solvent resistance, improved hydrophilicity, and optimized porous microstructure simultaneously. The study investigates the effects of an alkaline coagulation bath, subsequent ion exchange, and further solvent activation. The resulting TFC membrane successfully overcomes the typical permeability-selectivity trade-off of OSN membranes. It demonstrates significantly improved solvent permeance (1.5–2 times higher than previously reported data) with values of 65.2 LMH/bar for methanol, 33.1 LMH/bar for ethanol, and 59.1 LMH/bar for acetone while maintaining competitive solute rejection (>98% for Rose Bengal). This research is expected to provide a new direction for developing high-performance OSN composite membranes and other separation applications.

Keywords: metal coordinatiom, thin film composite membrane, organic solvent nanofiltration, solvent activation

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Authors: Festus M. Epetimehin

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Resources are essential materials required for production of goods and services. Effective allocation of these resources can engender the success of current business activities and its sustainability for future generation. The study examined effect of resource allocation of small agribusinesses on entrepreneurship development in Southwest Nigeria. Sample size of 385 was determined using Cochran’s formula. 350 valid copies of questionnaire were used in the analysis. In order to achieve the objective, research design (descriptive and cross sectional designs) was used to gather data for the study through the administration of questionnaire to respondents. Both descriptive and inferential statistics were used to investigate the objective of the study. The result obtained indicated that resource allocation by small agribusinesses had a substantial positive effect on entrepreneurship development with the p-value of (0.0000) which was less than the 5.0% critical value with a positive regression coefficient of 0.53. The implication of this is that the ability of the entrepreneurs to deploy their resources efficiently through adequate realization of better gross margin could enhance business activities and development. The study recommends that business owners still need some level of serious training and exposure on how to manage modern small agribusiness resources to enhance business performance. The intervention of Agricultural Development Programme (ADP) and other Agricultural institutions are needed in this regard.

Keywords: resource, resource allocation, small businesses, agriculture, entrepreneurship development

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Authors: Peerawat Khongkliang, Prawit Kongjan, Tsuyoshi Imai, Poonsuk Prasertsan, Sompong O-Thong

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A two-stage thermophilic fermentation and electrohydrogenesis process was used to convert cassava starch processing wastewater into hydrogen gas. Maximum hydrogen yield from fermentation stage by Thermoanaerobacterium thermosaccharolyticum PSU-2 was 248 mL H2/g-COD at optimal pH of 6.5. Optimum hydrogen production rate of 820 mL/L/d and yield of 200 mL/g COD was obtained at HRT of 2 days in fermentation stage. Cassava starch processing wastewater fermentation effluent consisted of acetic acid, butyric acid and propionic acid. The effluent from fermentation stage was used as feedstock to generate hydrogen production by microbial electrolysis cell (MECs) at an applied voltage of 0.6 V in second stage with additional 657 mL H2/g-COD was produced. Energy efficiencies based on electricity needed for the MEC were 330 % with COD removals of 95 %. The overall hydrogen yield was 800-900 mL H2/g-COD. Microbial community analysis of electrohydrogenesis by DGGE shows that exoelectrogens belong to Acidiphilium sp., Geobacter sulfurreducens and Thermincola sp. were dominated at anode. These results show two-stage thermophilic fermentation, and electrohydrogenesis process improved hydrogen production performance with high hydrogen yields, high gas production rates and high COD removal efficiency.

Keywords: cassava starch processing wastewater, biohydrogen, thermophilic fermentation, microbial electrolysis cell

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Authors: Pukhrambam Helena Chanu, Janardan Yadav

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This study investigates the potential of various fungal isolates to solubilize zinc and counteract rice pathogens, with the aim of mitigating zinc deficiency and disease prevalence in rice farming. Soil samples from the rhizosphere were collected, and zinc-solubilizing fungi were isolated and purified. Molecular analysis identified Talaromyces sp, Talaromyces versatilis, Talaromyces pinophilus, and Aspergillus terreus as effective zinc solubilizers. Through qualitative and quantitative assessments, it was observed that solubilization efficiencies varied among the isolates over time, with Talaromyces versatilis displaying the highest capacity for solubilization. This variability in solubilization rates may be attributed to differences in fungal metabolic activity and their ability to produce organic acids that facilitate zinc release from insoluble sources in the soil. In inhibition assays against rice pathogens, the fungal isolates exhibited antagonistic properties, with Talaromyces versatilis demonstrating the most significant inhibition rates. This antagonistic activity may be linked to the production of secondary metabolites, such as antibiotics or lytic enzymes by fungi, which inhibit the growth of rice pathogens. The ability of Talaromyces versatilis to outperform other isolates in both zinc solubilization and pathogen inhibition highlights its potential as a multifunctional biocontrol agent in rice cultivation systems. These findings emphasize the potential of fungi as natural solutions for enhancing zinc uptake and managing diseases in rice cultivation. Utilizing indigenous zinc-solubilizing fungi offers a sustainable and environmentally friendly approach to addressing zinc deficiency in soils, reducing the need for chemical fertilizers. Moreover, harnessing the antagonistic activity of these fungi can contribute to integrated disease management strategies, minimizing reliance on synthetic pesticides and promoting ecological balance in agroecosystems. Additionally, the study included the evaluation of dipping time under different concentrations, viz.,10 ppm, 20 ppm, and 30 ppm of biosynthesized nano ZnO on rice seedlings. This investigation aimed to optimize the application of nano ZnO for efficient zinc uptake by rice plants while minimizing potential risks associated with excessive nanoparticle exposure. Evaluating the effects of varying concentrations and dipping durations provides valuable insights into the safe and effective utilization of nano ZnO as a micronutrient supplement in rice farming practices.

Keywords: biosynthesized nano ZnO, rice, root dipping, zinc solubilizing fungi.

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Authors: Benlakhdar Mohamed Larbi, Yagoub Asma

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Purpose: This study aims at highlighting the significance and importance of utilizing marketing information system (MKIS) on decision-making, by clarifying the need for quick and efficient decision-making due to time saving and preventing of duplication of work. Design, methodology, approach: The study shows the roles of each part of MKIS for developing marketing strategy, which present a real challenge to individuals and institutions in an era characterized by uncertainty and clarifying the importance of each part separately, depending on decision type and the nature of the situation. The empirical research method was evaluated by specialized experts, conducted by means of questionnaires. Correlation analysis was employed to test the validity of the procedure. Results: The empirical study findings confirmed positive relationships between the level of utilizing and adopting ‘decision support system and marketing intelligence’ and the success of an organizational decision-making, and provide the organization with a competitive advantage as it allows the organization to solve problems. Originality/value: The study offer better understanding of performance- increasing market share as an organizational decision making based on marketing information system.

Keywords: database, marketing research, marketing intelligence, decision support system, decision-making

Procedia PDF Downloads 334