Search results for: performance vs. security

Authors: Amit Gill, Lalith Wijerathne, Sebastian Poledna

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This research presents the details of the implementation of high performance computing (HPC) extension of agent-based economic models (ABEMs) to simulate hundreds of millions of heterogeneous agents. ABEMs offer an alternative approach to study the economy as a dynamic system of interacting heterogeneous agents, and are gaining popularity as an alternative to standard economic models. Over the last decade, ABEMs have been increasingly applied to study various problems related to monetary policy, bank regulations, etc. When it comes to predicting the effects of local economic disruptions, like major disasters, changes in policies, exogenous shocks, etc., on the economy of the country or the region, it is pertinent to study how the disruptions cascade through every single economic entity affecting its decisions and interactions, and eventually affect the economic macro parameters. However, such simulations with hundreds of millions of agents are hindered by the lack of HPC enhanced ABEMs. In order to address this, a scalable Distributed Memory Parallel (DMP) implementation of ABEMs has been developed using message passing interface (MPI). A balanced distribution of computational load among MPI-processes (i.e. CPU cores) of computer clusters while taking all the interactions among agents into account is a major challenge for scalable DMP implementations. Economic agents interact on several random graphs, some of which are centralized (e.g. credit networks, etc.) whereas others are dense with random links (e.g. consumption markets, etc.). The agents are partitioned into mutually-exclusive subsets based on a representative employer-employee interaction graph, while the remaining graphs are made available at a minimum communication cost. To minimize the number of communications among MPI processes, real-life solutions like the introduction of recruitment agencies, sales outlets, local banks, and local branches of government in each MPI-process, are adopted. Efficient communication among MPI-processes is achieved by combining MPI derived data types with the new features of the latest MPI functions. Most of the communications are overlapped with computations, thereby significantly reducing the communication overhead. The current implementation is capable of simulating a small open economy. As an example, a single time step of a 1:1 scale model of Austria (i.e. about 9 million inhabitants and 600,000 businesses) can be simulated in 15 seconds. The implementation is further being enhanced to simulate 1:1 model of Euro-zone (i.e. 322 million agents).

Keywords: agent-based economic model, high performance computing, MPI-communication, MPI-process

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Authors: Abolfazl Alishahi Ghalehjoughi

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Economic independence and security of Islamic world is the top priority. Economic dependence of Muslim countries on economies of non-Muslim imperialist countries results in political and cultural dependencies, and such dependencies will jeopardize the noble Islamic culture; because the will of a dependent country to implements the noble teachings of Islam would be faced with challenges. Solidarity of Muslim countries to achieve a uniformed and resistive economy-based Islamic economic system can improve ability of Islamic world to resist and counteract economic shocks produced by imperialists. Islam is the most complete religion in every aspect, from ideological and epistemological, to legislative and ethical, and economic aspect is no exception. Islam provides solutions to develop a flourishing economy for the whole Islamic nation. Knowledge of such solutions and identification of mechanisms to operationalise them in Islamic communities can highly contributed to establishment of the superior Islamic economy. Encourage of hard working, achievement and knowledge production, correction of consumption patterns, optimized management of import and export, avoiding Islamically prohibited income, economic discipline and equity, and promotion of interest free loan and the like are among the most important solutions to realize such resistive economy.

Keywords: resistive economy, cultural independence, Islam, solidarity

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Authors: Philipp Sommer, Amgad Agoub

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The construction sector significantly impacts global CO₂ emissions, particularly through the energy usage of residential buildings. To address this, various governments, including Germany's, are focusing on reducing emissions via sustainable refurbishment initiatives. This study examines the application of machine learning (ML) to estimate energy demands dynamically in residential buildings and enhance the potential for large-scale sustainable refurbishment. A major challenge in Germany is the lack of extensive publicly labeled datasets for energy performance, as energy performance certificates, which provide critical data on building-specific energy requirements and consumption, are not available for all buildings or require on-site inspections. Conversely, England and other countries in the European Union (EU) have rich public datasets, providing a viable alternative for analysis. This research adapts insights from these English datasets to the German context by developing a comprehensive data schema and calibration dataset capable of predicting building energy demand effectively. The study proposes a minimal feature set, determined through feature importance analysis, to optimize the ML model. Findings indicate that ML significantly improves the scalability and accuracy of energy demand forecasts, supporting more effective emissions reduction strategies in the construction industry. Integrating energy performance certificates into municipal heat planning in Germany highlights the transformative impact of data-driven approaches on environmental sustainability. The goal is to identify and utilize key features from open data sources that significantly influence energy demand, creating an efficient forecasting model. Using Extreme Gradient Boosting (XGB) and data from energy performance certificates, effective features such as building type, year of construction, living space, insulation level, and building materials were incorporated. These were supplemented by data derived from descriptions of roofs, walls, windows, and floors, integrated into three datasets. The emphasis was on features accessible via remote sensing, which, along with other correlated characteristics, greatly improved the model's accuracy. The model was further validated using SHapley Additive exPlanations (SHAP) values and aggregated feature importance, which quantified the effects of individual features on the predictions. The refined model using remote sensing data showed a coefficient of determination (R²) of 0.64 and a mean absolute error (MAE) of 4.12, indicating predictions based on efficiency class 1-100 (G-A) may deviate by 4.12 points. This R² increased to 0.84 with the inclusion of more samples, with wall type emerging as the most predictive feature. After optimizing and incorporating related features like estimated primary energy consumption, the R² score for the training and test set reached 0.94, demonstrating good generalization. The study concludes that ML models significantly improve prediction accuracy over traditional methods, illustrating the potential of ML in enhancing energy efficiency analysis and planning. This supports better decision-making for energy optimization and highlights the benefits of developing and refining data schemas using open data to bolster sustainability in the building sector. The study underscores the importance of supporting open data initiatives to collect similar features and support the creation of comparable models in Germany, enhancing the outlook for environmental sustainability.

Keywords: machine learning, remote sensing, residential building, energy performance certificates, data-driven, heat planning

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Authors: González A. Julio, Ramírez L. Leonardo, Puerta A. Gabriel

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Telemedicine services use a large amount of data, most of which are diagnostic images in Digital Imaging and Communications in Medicine (DICOM) and Health Level Seven (HL7) formats. Metadata is generated from each related image to support their identification. This study presents the use of decision trees for the optimization of information search processes for diagnostic images, hosted on the cloud server. To analyze the performance in the server, the following quality of service (QoS) metrics are evaluated: delay, bandwidth, jitter, latency and throughput in five test scenarios for a total of 26 experiments during the loading and downloading of DICOM images, hosted by the telemedicine group server of the Universidad Militar Nueva Granada, Bogotá, Colombia. By applying decision trees as a data mining technique and comparing it with the sequential search, it was possible to evaluate the search times of diagnostic images in the server. The results show that by using the metadata in decision trees, the search times are substantially improved, the computational resources are optimized and the request management of the telemedicine image service is improved. Based on the experiments carried out, search efficiency increased by 45% in relation to the sequential search, given that, when downloading a diagnostic image, false positives are avoided in management and acquisition processes of said information. It is concluded that, for the diagnostic images services in telemedicine, the technique of decision trees guarantees the accessibility and robustness in the acquisition and manipulation of medical images, in improvement of the diagnoses and medical procedures in patients.

Keywords: cloud storage, decision trees, diagnostic image, search, telemedicine

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Authors: Rama Seshu Doguparti

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This paper presents the experimental investigation on the bond behavior of geo polymer concrete. The bond behavior of geo polymer concrete cubes of grade M35 reinforced with 16 mm TMT rod is analyzed. The results indicate that the bond performance of reinforced geo polymer concrete is good and thus proves its application for construction.

Keywords: geo-polymer, concrete, bond strength, behaviour

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Authors: Rushva Parihar, Anushka Barua

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The negative repercussions of a warming planet are already visible, with biodiversity loss, water scarcity, and extreme weather events becoming ever so frequent. The agriculture sector is perhaps the most impacted, and modern agriculture has failed to defend farmers from the effects of climate change. This, coupled with the added pressure of higher demands for food production caused due to population growth, has only compounded the impact. Traditional agricultural practices that are routed in indigenous knowledge have long safeguarded the delicate balance of the ecosystem through sustainable production techniques. This paper uses secondary data to explore these traditional processes (like Beejamrita, Jeevamrita, sheep penning, earthen bunding, and others) from around the world that have been developed over centuries and focuses on how they can be used to tackle contemporary issues arising from climate change (such as nutrient and water loss, soil degradation, increased incidences of pests). Finally, the resulting framework has been applied to the context of Indian agriculture as a means to combat climate change and improve food security, all while encouraging documentation and transfer of local knowledge as a shared resource among farmers.

Keywords: sustainable food systems, traditional agricultural practices, climate smart agriculture, climate change, indigenous knowledge

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Authors: Che Hsiu Chen, Su Yun Chen, Hon Wen Cheng

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Greater core stability may benefit sports performance by providing a foundation for greater force production in the upper and lower extremities. Core stability exercises on instability device (such as the TRX suspension systems) were found to be able to induce higher core muscle activity than performing on a stable surface. However, high intensity interval TRX suspension exercises training on sport performances remain unclear. The purpose of this study was to examine whether high intensity TRX suspension training could improve sport performance. Twenty-four healthy university female students (age 19.0 years, height 157.9 cm, body mass 51.3 kg, fat mass 25.2 %) were voluntarily participated in this study. After a familiarization session, each participant underwent five suspension exercises (e.g., hip abduction in plank alternative, hamstring curl, 45-degree row, lunge and oblique crunch). Each type of exercise was performed for 30 seconds, followed by 30 seconds break, two times per week for eight weeks while each exercise session was increased by 10 seconds every week. The results showed that the fat mass (about 12.92%) decreased significantly, sit and reach test (9%), 1 minute sit-up test (17.5%), standing broad jump (4.8%), physical fitness index (10.3%) increased significantly after 8-week high intensity TRX suspension training. Hence, eight weeks of high intensity interval TRX suspension exercises training can improve hamstring flexibility, trunk endurance, jump ability, aerobic fitness and fat mass percentage decreased substantially.

Keywords: core endurance, jump, flexibility, cardiovascular fitness

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Authors: Ahmad Naqi

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Today, the passively controlled buildings are extensively becoming popular due to its excellent lateral load resistance circumstance. Typically, these buildings are enhanced with a damping device that has high market demand. Some manufacturer falsified the damping device parameter during the production to achieve the market demand. Therefore, this paper evaluates the seismic performance of buildings equipped with damping devices, which their parameter modified to simulate the falsified devices, intentionally. For this purpose, three benchmark buildings of 4-, 10-, and 20-story were selected from JSSI (Japan Society of Seismic Isolation) manual. The buildings are special moment resisting steel frame with oil damper in the longitudinal direction only. For each benchmark buildings, two types of structural elements are designed to resist the lateral load with and without damping devices (hereafter, known as Trimmed & Conventional Building). The target building was modeled using STERA-3D, a finite element based software coded for study purpose. Practicing the software one can develop either three-dimensional Model (3DM) or Lumped Mass model (LMM). Firstly, the seismic performance of 3DM and LMM models was evaluated and found excellent coincide for the target buildings. The simplified model of LMM used in this study to produce 66 cases for both of the buildings. Then, the device parameters were modified by ± 40% and ±20% to predict many possible conditions of falsification. It is verified that the building which is design to sustain the lateral load with support of damping device (Trimmed Building) are much more under threat as a result of device falsification than those building strengthen by damping device (Conventional Building).

Keywords: passive control system, oil damper, seismic assessment, lumped mass model

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Authors: Olugbade Damola, Adekomi Adebimbo, Sofowora Olaniyi Alaba

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One of the major problems facing education in Nigeria is the provision of quality Science and Technology education. Inadequate teaching facilities, non-usage of innovative teaching strategies, ineffective classroom management, lack of students’ motivation and poor integration of ICT has resulted in the increase in percentage of students who failed Basic Science and Technology in Junior Secondary Certification Examination for National Examination Council in Nigeria. To address these challenges, the Federal Government came up with a road map on education. This was with a view of enhancing quality education through integration of modern technology into teaching and learning, enhancing quality assurance through proper monitoring and introduction of innovative methods of teaching. This led the researcher to investigate how MOODLE LMS could be used to enhance students’ learning outcomes in BST. A sample of 120 students was purposively selected from four secondary schools in Ogbomoso. The experimental group was taught using MOODLE LMS, while the control group was taught using the conventional method. Data obtained were analyzed using mean, standard deviation and t-test. The result showed that MOODLE LMS was an effective learning platform in teaching BST in junior secondary schools (t=4.953, P<0.05). Students’ attitudes towards BST was also enhanced through MOODLE LMS (t=15.632, P<0.05). The use of MOODLE LMS significantly enhanced students’ retention (t=6.640, P<0.05). In conclusion, the Federal Government efforts at enhancing quality assurance through integration of modern technology and e-learning in Secondary schools proved to have yielded good result has students found MOODLE LMS to be motivating and interactive. Attendance was improved.

Keywords: basic science and technology, MOODLE LMS, performance, quality assurance

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Authors: S. Pirrello

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Sydney’s booming real estate market has pushed property developers to invest in historically “no-go” areas, which were previously too expensive to develop. These areas are usually near rivers where the sites are underlain by deep alluvial and estuarine sediments. In these ground conditions, conventional bored pile techniques are often not competitive. Contiguous Flight Auger (CFA) and Drilled Displacement (DD) Piles techniques are on the other hand suitable for these ground conditions. This paper deals with the design and construction challenges encountered with these piling techniques for a series of high-rise towers in Sydney’s West. The advantages of DD over CFA piles such as reduced overall spoil with substantial cost savings and achievable rock sockets in medium strength bedrock are discussed. Design performances were assessed with PIGLET. Pile performances are validated in two stages, during constructions with the interpretation of real-time data from the piling rigs’ on-board computer data, and after construction with analyses of results from high strain pile dynamic testing (PDA). Results are then presented and discussed. High Strain testing data are presented as Case Pile Wave Analysis Program (CAPWAP) analyses.

Keywords: contiguous flight auger (CFA) , DEFPIG, case pile wave analysis program (CAPWAP), drilled displacement piles (DD), pile dynamic testing (PDA), PIGLET, PLAXIS, repute, pile performance

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Authors: Borja Ruiz de Arbulo Alonso

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This paper analyzes the impact of flipped instruction in adult learners of Spanish as a second language in a face-to-face course at Boston University. Given the limited amount of contact hours devoted to studying world languages in the American higher education system, implementing strategies to free up classroom time for communicative language practice is key to ensure student success in their learning process. In an effort to improve the way adult learners acquire a second language, this paper examines the role that regular pre-class and web-based exposure to Spanish grammar plays in student performance at the end of the academic term. It outlines different types of web-based pre-class activities and compares this approach to more traditional classroom practice. To do so, this study works for three months with two similar groups of adult learners in an intermediate-level Spanish class. Both groups use the same course program and have the same previous language experience, but one receives an additional set of instructor-made online materials containing a variety of grammar explanations and online activities that need to be reviewed before attending class. Since the online activities cover material and concepts that have not yet been studied in class, students' oral and written production in both groups is measured by means of a writing activity and an audio recording at the end of the three-month period. These assessments will ascertain the effects of exposing the control group to the grammar of the target language prior to each lecture throughout and demonstrate where flipped instruction helps adult learners of Spanish achieve higher performance, but also identify potential problems.

Keywords: educational technology, flipped classroom, second language acquisition, student success

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Authors: Hamid Sharif, Nazish Saleem Abbas, Muhammad Haris Jamil

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Visible light communication is an emerging technology for almost a decade now; there is a growing need for VLC systems to overcome the challenges faced by radio frequency RF communication systems. With the advancement in the development of solid-state sources, in the future would replace incandescent and fluorescent light sources. These solid-state devices are not only to be used for illumination but can also be employed for communication and navigational purposes. The replacement of conventional illumination sources with highly efficient light-emitting diodes (LED's) (generally white light) will reduce energy consumption as well as environmental pollution. White LEDs dissipate very less power as compared to conventional light sources. The use of LED's is not only beneficial in terms of power consumption, but it also has an intrinsic capability for indoor wireless communication as compared to indoor RF communication. It is considerably low in cost to operate than the RF systems such as Wi-Fi routers, allows convenient means of reusing the bandwidth, and there is a huge potential for high data rate transmissions with enhanced data security. This paper provides an overview of some of the current challenges with VLC and proposes a possible solution to deal with these challenges; it also examines some joint protocols to optimize the joint illumination and communication functionality.

Keywords: visible light communication, line of sight, root mean square delay spread, light emitting diodes

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Authors: Rayeheh Khatami, Toktam Hanaei, Mohammad Reza Mansouri Daneshvar

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Today, many local and national governments are developing urban agriculture as an effective tool in responding to challenges such as food security, poverty and environmental problems. In fact, urban agriculture plays an important role in food system, which can provide citizens' income and become one of the components of economic, social and environmental systems. The purpose of this paper is to analyze the urban agriculture and urban food systems in order to understand the impact of urban foods production on environmental planning in non-western city region context. To achieve such objective, we carry out a case study in Mashhad city of Iran by using qualitative approaches. A survey on documentary studies and planning tools integrate with face to face interview with experts which explain the role of food system in environmental planning process. The paper extends the use of food in the environmental planning, specifically to examine this role to create agricultural garden as a mean to improve agricultural system in non-western country. The paper is concluded with a set of recommendations for researchers and policymakers who seek to create spaces in order to implement urban agriculture in cities for food justice.

Keywords: urban agriculture , agricultural park, city region food system, Mashhad

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Authors: Mary Cheptanui Sambu

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Teaching practice is an integral component of students who are training to be teachers, as it provides them with an opportunity to gain experience in an actual teaching and learning environment. This study explored the experiences of trainee teachers from a local university in Kenya, undergoing a three-month teaching practice in Special Secondary schools in the country. The main aim of the study was to understand the trainees’ experiences, their expectations, and the realities encountered during the teaching practice period. The study focused on special secondary schools for learners with hearing impairment. A descriptive survey design was employed and a sample size of forty-four respondents from special secondary schools for learners with hearing impairment was purposively selected. A questionnaire was administered to the respondents and the data obtained analysed using the Statistical Package for the Social Sciences (SPSS). Preliminary analysis shows that challenges facing special secondary schools include inadequate teaching and learning facilities and resources, low academic performance among learners with hearing impairment, an overloaded curriculum and inadequate number of teachers for the learners. The study findings suggest that the Kenyan government should invest more in the education of special needs children, particularly focusing on increasing the number of trained teachers. In addition, the education curriculum offered in special secondary schools should be tailored towards the needs and interest of learners. These research findings will be useful to policymakers and curriculum developers, and will provide information that can be used to enhance the education of learners with hearing impairment; this will lead to improved academic performance, consequently resulting in better transitions and the realization of Vision 2030.

Keywords: hearing impairment, special secondary schools, trainee, teaching practice

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Authors: Rodrigo Buaiz Boabaid

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Tokenization of Blue Bonds is an emerging Green Finance tool that has the potential to scale Blue Carbon Projects to fight climate change. This innovative solution has a huge potential to democratize the green finance market and catalyze innovations in the climate change finance sector. Switzerland has emerged as a leader in the Green Finance space and is well-positioned to drive the adoption of Tokenization of Blue & Green Bonds. This unique approach has the potential to unlock new sources of capital and enable global investors to participate in the financing of sustainable blue carbon projects. By leveraging the power of blockchain technology, Tokenization of Blue Bonds can provide greater transparency, efficiency, and security in the investment process, while also reducing transaction costs. Investments are in line with the highest regulations and designed according to the stringent legal framework and compliance standards set by Switzerland. The potential benefits of Tokenization of Blue Bonds are significant and could transform the way that sustainable projects are financed. By unlocking new sources of capital, this approach has the potential to accelerate the deployment of Blue Carbon projects and create new opportunities for investors to participate in the fight against climate change.

Keywords: blue carbon, blue bonds, green finance, Tokenization, blockchain solutions

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Authors: Thidarat Imyen, Paisan Kongkachuichay

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Cu-Zn/core-shell Al-MCM-41 catalyst with various copper species, prepared by a combination of three methods—substitution, ion-exchange, and impregnation, was studied for the selective catalytic reduction (SCR) of NO with NH3 at 300 °C for 150 min. In order to investigate the effects of Zn introduction on the nature of the catalyst, Cu/core-shell Al-MCM-41 and Zn/core-shell Al-MCM-41 catalysts were also studied. The roles of Zn promoter in the acidity and the NOx adsorption properties of the catalysts were investigated by in situ Fourier transform infrared spectroscopy (FTIR) of NH3 and NOx adsorption, and temperature-programmed desorption (TPD) of NH3 and NOx. The results demonstrated that the acidity of the catalyst was enhanced by the Zn introduction, as exchanged Zn(II) cations loosely bonded with Al-O-Si framework could create Brønsted acid sites by interacting with OH groups. Moreover, Zn species also provided the additional sites for NO adsorption in the form of nitrite (NO2–) and nitrate (NO3–) species, which are the key intermediates for SCR reaction. In addition, the effect of Zn on the nature of copper was studied by in situ FTIR of CO adsorption and in situ X-ray adsorption near edge structure (XANES). It was found that Zn species hindered the reduction of Cu(II) to Cu(0), resulting in higher Cu(I) species in the Zn promoted catalyst. The Cu-Zn/core-shell Al-MCM-41 exhibited higher catalytic activity compared with that of the Cu/core-shell Al-MCM-41 for the whole reaction time, as it possesses the highest amount of Cu(I) sites, which are responsible for SCR catalytic activity. The Cu-Zn/core-shell Al-MCM-41 catalyst also reached the maximum NO conversion of 100% with the average NO conversion of 76 %. The catalytic performance of the catalyst was further improved by using Zn promoter in the form of ZnO instead of reduced Zn species. The Cu-ZnO/core-shell Al-MCM-41 catalyst showed better catalytic performance with longer working reaction time, and achieved the average NO conversion of 81%.

Keywords: Al-MCM-41, copper, nitrogen oxide, selective catalytic reduction, zinc

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Authors: Amandeep Sharma, Digvaijay Verma, Ruplal Choudhary

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Food processing is an activity across the globe that help in better handling of agricultural produce, including dairy, meat, and fish. The operations carried out in the food industry includes raw material quality authenticity; sorting and grading; processing into various products using thermal treatments – heating, freezing, and chilling; packaging; and storage at the appropriate temperature to maximize the shelf life of the products. All this is done to safeguard the food products and to ensure the distribution up to the consumer. The approaches to develop predictive models based on mathematical or statistical tools or empirical models’ development has been reported for various milk processing activities, including plant maintenance and wastage. Recently AI is the key factor for the fourth industrial revolution. AI plays a vital role in the food industry, not only in quality and food security but also in different areas such as manufacturing, packaging, and cleaning. A new conceptual model was developed, which shows that smaller sample size as only spectra would be required to predict the other values hence leads to saving on raw materials and chemicals otherwise used for experimentation during the research and new product development activity. It would be a futuristic approach if these tools can be further clubbed with the mobile phones through some software development for their real time application in the field for quality check and traceability of the product.

Keywords: predictive modlleing, ann, ai, food

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Authors: Angela U. Makolo

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Protein-coding and Non-coding regions determine the biology of a sequenced transcriptome. Research advances have shown that Non-coding regions are important in disease progression and clinical diagnosis. Existing bioinformatics tools have been targeted towards Protein-coding regions alone. Therefore, there are challenges associated with gaining biological insights from transcriptome sequence data. These tools are also limited to computationally intensive sequence alignment, which is inadequate and less accurate to identify both Protein-coding and Non-coding regions. Alignment-free techniques can overcome the limitation of identifying both regions. Therefore, this study was designed to develop an efficient sequence alignment-free model for identifying both Protein-coding and Non-coding regions in sequenced transcriptomes. Feature grouping and randomization procedures were applied to the input transcriptomes (37,503 data points). Successive iterations were carried out to compute the gradient vector that converged the developed Protein-coding and Non-coding Region Identifier (PNRI) model to the approximate coefficient vector. The logistic regression algorithm was used with a sigmoid activation function. A parameter vector was estimated for every sample in 37,503 data points in a bid to reduce the generalization error and cost. Maximum Likelihood Estimation (MLE) was used for parameter estimation by taking the log-likelihood of six features and combining them into a summation function. Dynamic thresholding was used to classify the Protein-coding and Non-coding regions, and the Receiver Operating Characteristic (ROC) curve was determined. The generalization performance of PNRI was determined in terms of F1 score, accuracy, sensitivity, and specificity. The average generalization performance of PNRI was determined using a benchmark of multi-species organisms. The generalization error for identifying Protein-coding and Non-coding regions decreased from 0.514 to 0.508 and to 0.378, respectively, after three iterations. The cost (difference between the predicted and the actual outcome) also decreased from 1.446 to 0.842 and to 0.718, respectively, for the first, second and third iterations. The iterations terminated at the 390th epoch, having an error of 0.036 and a cost of 0.316. The computed elements of the parameter vector that maximized the objective function were 0.043, 0.519, 0.715, 0.878, 1.157, and 2.575. The PNRI gave an ROC of 0.97, indicating an improved predictive ability. The PNRI identified both Protein-coding and Non-coding regions with an F1 score of 0.970, accuracy (0.969), sensitivity (0.966), and specificity of 0.973. Using 13 non-human multi-species model organisms, the average generalization performance of the traditional method was 74.4%, while that of the developed model was 85.2%, thereby making the developed model better in the identification of Protein-coding and Non-coding regions in transcriptomes. The developed Protein-coding and Non-coding region identifier model efficiently identified the Protein-coding and Non-coding transcriptomic regions. It could be used in genome annotation and in the analysis of transcriptomes.

Keywords: sequence alignment-free model, dynamic thresholding classification, input randomization, genome annotation

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Authors: Swati Bajpai, S. P. K Jena

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Background: There is dramatic increase in the prevalence and severity of overweight in adolescents, raising concerns about their psychosocial and cognitive consequences, thereby indicating the immediate need to understand the effects of increased weight on scholastic performance. Although the body of research is currently limited, available results have identified an inverse relationship between obesity and cognition in adolescents. Aim: to examine the association between increased Body Mass Index in adolescents and their neurocognitive functioning. Methods: A case –control study of 28 subjects in the age group of 11-17 years (14 Males and 14 females) was taken on the basis of main inclusion criteria (Body Mass Index). All of them were randomized to (experimental group: overweight) and (control group: normal weighted). A complete neurocognitive assessment was carried out using validated psychological scales namely, Color Progressive Matrices (to assess intelligence); Bender Visual Motor Gestalt Test (Perceptual motor functioning); PGI-Memory Scale for Children (memory functioning) and Malin’s Intelligence Scale Indian Children (verbal and performance ability). Results: statistical analysis of the results depicted that 57% of the experimental group lack in cognitive abilities, especially in general knowledge (99.1±12.0 vs. 102.8±6.7), working memory (91.5±8.4 vs. 93.1±8.7), concrete ability (82.3±11.5 vs. 92.6±1.7) and perceptual motor functioning (1.5±1.0 vs. 0.3±0.9) as compared to control group. Conclusion: Our investigations suggest that weight gain results, at least in part, from a neurological predisposition characterized by reduced executive function, and in turn obesity itself has a compounding negative impact on the brain. Though, larger sample is needed to make more affirmative claims.

Keywords: adolescents, body mass index, neurocognition, obesity

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Authors: P. Hooshangitabrizi, I. Contreras, N. Bhuiyan

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This work presents an online scheduling problem which accommodates multiple requests of patients for chemotherapy treatments in a cancer center of a major metropolitan hospital in Canada. To solve the problem, an adaptive flexible approach is proposed which systematically combines two optimization models. The first model is intended to dynamically schedule arriving requests in the form of waiting lists whereas the second model is used to reschedule the already booked patients with the goal of finding better resource allocations when new information becomes available. Both models are created as mixed integer programming formulations. Various controllable and flexible parameters such as deviating the prescribed target dates by a pre-determined threshold, changing the start time of already booked appointments and the maximum number of appointments to move in the schedule are included in the proposed approach to have sufficient degrees of flexibility in handling arrival requests and unexpected changes. Several computational experiments are conducted to evaluate the performance of the proposed approach using historical data provided by the oncology clinic. Our approach achieves outstandingly better results as compared to those of the scheduling system being used in practice. Moreover, several analyses are conducted to evaluate the effect of considering different levels of flexibility on the obtained results and to assess the performance of the proposed approach in dealing with last-minute changes. We strongly believe that the proposed flexible adaptive approach is very well-suited for implementation at the clinic to provide better patient-care services and to utilize available resource more efficiently.

Keywords: chemotherapy scheduling, multi-appointment modeling, optimization of resources, satisfaction of patients, mixed integer programming

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Authors: Lucas L. L. Fortes, Sandro T. M. Gonçalves

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In this work, it is analyzed the wideband performance with the mesh discretization impoverishment of the Conformal Finite Difference Time-Domain (C-FDTD) approaches developed by Raj Mittra, Supriyo Dey and Wenhua Yu for the Finite Difference Time-Domain (FDTD) method. These approaches are a simple and efficient way to optimize the scattering simulation of curved surfaces for Dielectric and Perfect Electric Conducting (PEC) structures in the FDTD method, since curved surfaces require dense meshes to reduce the error introduced due to the surface staircasing. Defined, on this work, as D-FDTD-Diel and D-FDTD-PEC, these approaches are well-known in the literature, but the improvement upon their application is not quantified broadly regarding wide frequency bands and poorly discretized meshes. Both approaches bring improvement of the accuracy of the simulation without requiring dense meshes, also making it possible to explore poorly discretized meshes which bring a reduction in simulation time and the computational expense while retaining a desired accuracy. However, their applications present limitations regarding the mesh impoverishment and the frequency range desired. Therefore, the goal of this work is to explore the approaches regarding both the wideband and mesh impoverishment performance to bring a wider insight over these aspects in FDTD applications. The D-FDTD-Diel approach consists in modifying the electric field update in the cells intersected by the dielectric surface, taking into account the amount of dielectric material within the mesh cells edges. By taking into account the intersections, the D-FDTD-Diel provides accuracy improvement at the cost of computational preprocessing, which is a fair trade-off, since the update modification is quite simple. Likewise, the D-FDTD-PEC approach consists in modifying the magnetic field update, taking into account the PEC curved surface intersections within the mesh cells and, considering a PEC structure in vacuum, the air portion that fills the intersected cells when updating the magnetic fields values. Also likewise to D-FDTD-Diel, the D-FDTD-PEC provides a better accuracy at the cost of computational preprocessing, although with a drawback of having to meet stability criterion requirements. The algorithms are formulated and applied to a PEC and a dielectric spherical scattering surface with meshes presenting different levels of discretization, with Polytetrafluoroethylene (PTFE) as the dielectric, being a very common material in coaxial cables and connectors for radiofrequency (RF) and wideband application. The accuracy of the algorithms is quantified, showing the approaches wideband performance drop along with the mesh impoverishment. The benefits in computational efficiency, simulation time and accuracy are also shown and discussed, according to the frequency range desired, showing that poorly discretized mesh FDTD simulations can be exploited more efficiently, retaining the desired accuracy. The results obtained provided a broader insight over the limitations in the application of the C-FDTD approaches in poorly discretized and wide frequency band simulations for Dielectric and PEC curved surfaces, which are not clearly defined or detailed in the literature and are, therefore, a novelty. These approaches are also expected to be applied in the modeling of curved RF components for wideband and high-speed communication devices in future works.

Keywords: accuracy, computational efficiency, finite difference time-domain, mesh impoverishment

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Authors: Junyu Chen, Peng Xu

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In the context of global efforts to enhance building energy efficiency, accurate thermal load forecasting is crucial for both device sizing and predictive control. Variable Refrigerant Flow (VRF) systems are widely used in buildings around the world, yet VRF zonal load prediction has received limited attention. Due to differences between VRF zones in building-level prediction methods, zone-level load forecasting could significantly enhance accuracy. Given that modern VRF systems generate high-quality data, this paper introduces transfer learning to leverage this data and further improve prediction performance. This framework also addresses the challenge of predicting load for building zones with no historical data, offering greater accuracy and usability compared to pure white-box models. The study first establishes an initial variable set of VRF zonal building loads and generates a foundational white-box database using EnergyPlus. Key variables for VRF zonal loads are identified using methods including SRRC, PRCC, and Random Forest. XGBoost and LSTM are employed to generate pre-trained black-box models based on the white-box database. Finally, real-world data is incorporated into the pre-trained model using transfer learning to enhance its performance in operational buildings. In this paper, zone-level load prediction was integrated with transfer learning, and a framework was proposed to improve the accuracy and applicability of VRF zonal load prediction.

Keywords: zonal load prediction, variable refrigerant flow (VRF) system, transfer learning, energyplus

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Authors: Yogesh Kumar Singh, T. S. Murugesh Prabhu, Upasana Dutta, Girishchandra Yendargaye, Rahul Yadav, Rohini Gopinath Kale, Binay Kumar, Manoj Khare

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The Indian subcontinent is severely affected by floods that cause intense irreversible devastation to crops and livelihoods. With increased incidences of floods and their related catastrophes, an Early Warning System for Flood Prediction and an efficient Flood Management System for the river basins of India is a must. Accurately modeled hydrological conditions and a web-based early warning system may significantly reduce economic losses incurred due to floods and enable end users to issue advisories with better lead time. This study describes the design and development of an EWS-FP using advanced computational tools/methods, viz. High-Performance Computing (HPC), Remote Sensing, GIS technologies, and open-source tools for the Mahanadi River Basin of India. The flood prediction is based on a robust 2D hydrodynamic model, which solves shallow water equations using the finite volume method. Considering the complexity of the hydrological modeling and the size of the basins in India, it is always a tug of war between better forecast lead time and optimal resolution at which the simulations are to be run. High-performance computing technology provides a good computational means to overcome this issue for the construction of national-level or basin-level flash flood warning systems having a high resolution at local-level warning analysis with a better lead time. High-performance computers with capacities at the order of teraflops and petaflops prove useful while running simulations on such big areas at optimum resolutions. In this study, a free and open-source, HPC-based 2-D hydrodynamic model, with the capability to simulate rainfall run-off, river routing, and tidal forcing, is used. The model was tested for a part of the Mahanadi River Basin (Mahanadi Delta) with actual and predicted discharge, rainfall, and tide data. The simulation time was reduced from 8 hrs to 3 hrs by increasing CPU nodes from 45 to 135, which shows good scalability and performance enhancement. The simulated flood inundation spread and stage were compared with SAR data and CWC Observed Gauge data, respectively. The system shows good accuracy and better lead time suitable for flood forecasting in near-real-time. To disseminate warning to the end user, a network-enabled solution is developed using open-source software. The system has query-based flood damage assessment modules with outputs in the form of spatial maps and statistical databases. System effectively facilitates the management of post-disaster activities caused due to floods, like displaying spatial maps of the area affected, inundated roads, etc., and maintains a steady flow of information at all levels with different access rights depending upon the criticality of the information. It is designed to facilitate users in managing information related to flooding during critical flood seasons and analyzing the extent of the damage.

Keywords: flood, modeling, HPC, FOSS

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Authors: Benil Mathew Baby, Leonid Shpanin, Misko Abramiuk

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High-voltage energy production on board the unmanned aerial vehicle (UAV) is one of the most rapidly growing emerging technologies for different applications in aerospace. Different energy harvesting and production techniques have already been investigated in multirotor drones, where the energy collected comes from the systems surrounding the ambient environment and typically involves the conversion of solar, kinetic, or thermal energies into electrical energy. In this contribution, a UAV structure is proposed for the production of a few tens of kilovolts on board of the UAV. The high voltage production mechanism on board of the UAV has not been investigated previously. The UAV geometry using the multirotor drone for production the high voltage on board of the UAV has been investigated theoretically using the ANSYS and MATLAB Finite Element Analysis (FEA) simulation tools. The industrially made MANTIS X8-PRO octocopter frame kit was used to explore the octocopter operation which was modelled for simulation studies. The high voltage electric circuit and components using octocopter geometry are developed through the integration of the mechanical parts on board of the UAV. Analysis of the modelled octocopter geometry and its performance is presented via a graphical representation of simulated parameters. The possibility of not using the landing gear in the proposed octocopter geometry is demonstrated. The conducted study evaluates the octocopter’s high voltage control technique and its impact on UAV energy consumption. FEA simulation results of the modelled high voltage electric circuit on board of the octocopter are presented exploring the performance of the octocopter and the structural challenges of its configuration. Applications of the proposed octocopter structure are discussed.

Keywords: high voltage production, energy harvesting, object modeling and control, unmanned aerial vehicle

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Authors: Wen Ma, Yong Peng, Zhixiang Li

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Security journey is a vital focus on the field of Rail Transportation. Accidents caused by the damage of the high-speed train windshield have occurred many times and have given rise to terrible consequences. Train windshield consists of tempered glass and polyvinyl butyral (PVB) film. In this work, the quasi-static tests and the split Hopkinson pressure bar (SHPB) tests were carried out first to obtain the mechanical properties and constitutive model for the tempered glass and PVB film. These tests results revealed that stress and Young’s modulus of tempered glass were wake-sensitive to strain rate, but stress and Young’s modulus of PVB film were strong-sensitive to strain rate. Then impact experiment of the windshield was carried out to investigate dynamic response and failure characteristics of train windshield. In addition, a finite element model based on the combined finite element method was proposed to investigate fracture and fragmentation responses of train windshield under different-velocity impact. The results can be used for further design and optimization of the windshield for high-speed train application.

Keywords: constitutive model, impact response, mechanism properties, PVB film, tempered glass

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Authors: Shaila Rana, Wasim Alhamdani

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Effective cybersecurity training is of the utmost importance, given the plethora of attacks that continue to increase in complexity and ubiquity. VR cybersecurity training remains a starkly understudied discipline. Studies that evaluated the effectiveness of VR cybersecurity training over traditional methods are required. An engaging and interactive platform can support knowledge retention of the training material. Consequently, an effective form of cybersecurity training is required to support a culture of cybersecurity awareness. Measurements of effectiveness varied throughout the studies, with surveys and observations being the two most utilized forms of evaluating effectiveness. Further research is needed to evaluate the effectiveness of VR cybersecurity training and traditional training. Additionally, research for evaluating if VR cybersecurity training is more effective than traditional methods is vital. This paper proposes a methodology to compare the two cybersecurity training methods and their effectiveness. The proposed framework includes developing both VR and traditional cybersecurity training methods and delivering them to at least 100 users. A quiz along with a survey will be administered and statistically analyzed to determine if there is a difference in knowledge retention and user satisfaction. The aim of this paper is to bring attention to the need to study VR cybersecurity training and its effectiveness compared to traditional training methods. This paper hopes to contribute to the cybersecurity training field by providing an effective way to train users for security awareness. If VR training is deemed more effective, this could create a new direction for cybersecurity training practices.

Keywords: virtual reality cybersecurity training, VR cybersecurity training, traditional cybersecurity training

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Authors: Jorge R. Santos, Pedro Sebastiao

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In recent years there has been a great growth in the use of drones, being used in several areas such as security, agriculture, or research. The existence of some systems that allow the remote control of drones is a reality; however, these systems are quite simple and directed to specific functionality. This paper proposes the development of a web platform made in Vue.js and Node.js to control, manage, and monitor drones in real time. Using a microservice architecture, the proposed project will be able to integrate algorithms that allow the optimization of processes. Communication with remote devices is suggested via HTTP through 3G, 4G, and 5G networks and can be done in real time or by scheduling routes. This paper addresses the case of forest fires as one of the services that could be included in a system similar to the one presented. The results obtained with the elaboration of this project were a success. The communication between the web platform and drones allowed its remote control and monitoring. The incorporation of the fire detection algorithm in the platform proved possible a real time analysis of the images captured by the drone without human intervention. The proposed system has proved to be an asset to the use of drones in fire detection. The architecture of the application developed allows other algorithms to be implemented, obtaining a more complex application with clear expansion.

Keywords: drone control, microservices, node.js, unmanned aerial vehicles, vue.js

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Authors: Vivek Krishna, Nikhil Jain, A. Mary Posonia A., Albert Mayan J

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Terrorism and insurgency are significant global issues that require constant attention and effort from governments and scientists worldwide. To combat these threats, nations invest billions of dollars in developing new defensive technologies to protect civilians. Breakthroughs in vehicle automation have led to the use of sophisticated machines for many dangerous and critical anti-terrorist activities. Our concept of an "Unmanned Ground Vehicle" can carry out tasks such as border security, surveillance, mine detection, and active combat independently or in tandem with human control. The robot's movement can be wirelessly controlled by a person in a distant location or can travel to a pre-programmed destination autonomously in situations where personal control is not feasible. Our defence system comprises two units: the control unit that regulates mobility and the motion tracking unit. The remote operator robot uses the camera's live visual feed to manually operate both units, and the rover can automatically detect movement. The rover is operated by manpower who controls it using a joystick or mouse, and a wireless modem enables a soldier in a combat zone to control the rover via an additional controller feature.

Keywords: robotics, computer vision, Machine learning, Artificial intelligence, future of AI

Procedia PDF Downloads 129

Authors: Yingjeng James Li, Yun Jyun Ou, Chih Chi Hsu, Chiao-Chih Hu

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A fuel cell is a device that produces electric power by reacting fuel and oxidant electrochemically. There is no pollution produced from a fuel cell if hydrogen is employed as the fuel. Therefore, a fuel cell is considered as a zero emission device and is a source of green power. A membrane electrode assembly (MEA) is the key component of a fuel cell. It is, therefore, beneficial to develop MEAs with high performance. In this study, an MEA for proton exchange membrane fuel cell (PEMFC) was prepared from a 15-micron thick reinforced PEM. The active area of such MEA is 25 cm2. Carbon supported platinum (Pt/C) was employed as the catalyst for both anode and cathode. The platinum loading is 0.6 mg/cm2 based on the sum of anode and cathode. Commercially available carbon papers coated with a micro porous layer (MPL) serve as gas diffusion layers (GDLs). The original thickness of the GDL is 250 μm. It was compressed down to 163 μm when assembled into the single cell test fixture. Polarization curves were taken by using eight different test conditions. At our standard test condition (cell: 70 °C; anode: pure hydrogen, 100%RH, 1.2 stoic, ambient pressure; cathode: air, 100%RH, 3.0 stoic, ambient pressure), the cell current density is 1250 mA/cm2 at 0.6 V, and 2400 mA/cm2 at 0.4 V. At self-humidified condition and cell temperature of 55 °C, the cell current density is 1050 mA/cm2 at 0.6 V, and 2250 mA/cm2 at 0.4 V. Hydrogen crossover rate of the MEA is 0.0108 mL/min*cm2 according to linear sweep voltammetry experiments. According to the MEA’s Pt loading and the cyclic voltammetry experiments, the Pt electrochemical surface area is 60 m2/g. The ohmic part of the impedance spectroscopy results shows that the membrane resistance is about 60 mΩ*cm2 when the MEA is operated at 0.6 V.

Keywords: fuel cell, membrane electrode assembly, proton exchange membrane, reinforced

Procedia PDF Downloads 296

Authors: Maryam Mostafaee, Hassan Sadeghi Naeini, Sara Mostowfi

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Today’s Knowledge management (KM), plays an important role in organizations. Basically, knowledge management is in the relation of using it for taking advantage of work forces in an organization for forwarding the goals and demand of that organization used at the most. The purpose of knowledge management is not only to manage existing documentation, information, and Data through an organization, but the most important part of KM is to control most important and key factor of those information and Data. For sure it is to chase the information needed for the employees in the right time of needed to take from genuine source for bringing out the best performance and result then in this matter the performance of organization will be at most of it. There are a lot of definitions over the objective of management released. Management is the science that in force the accurate knowledge with repeating to the organization to shape it and take full advantages for reaching goals and targets in the organization to be used by employees and users, but the definition of Knowledge based on Kalinz dictionary is: Facts, emotions or experiences known by man or group of people is ‘ knowledge ‘: Based on the Merriam Webster Dictionary: the act or skill of controlling and making decision about a business, department, sport team, etc, based on the Oxford Dictionary: Efficient handling of information and resources within a commercial organization, and based on the Oxford Dictionary: The art or process of designing manufactured products: the scale is a beautiful work of industrial design. When knowledge management performed executive in universities, discovery and create a new knowledge be facilitated. Make procedures between different units for knowledge exchange. College's officials and employees understand the importance of knowledge for University's success and will make more efforts to prevent the errors. In this strategy, is explored factors and affective trends and manage of it in University. In this research, Iranian universities for a time being analyzed that over usage of knowledge management, how they are behaving and having understood this matter: 1. Discovery of knowledge management in Iranian Universities, 2. Transferring exciting knowledge between faculties and unites, 3. Participate of employees for getting and using and transferring knowledge, 4.The accessibility of valid sources, 5. Researching over factors and correct processes in the university. We are pointing in some examples that we have already analyzed which is: -Enabling better and faster decision-making, -Making it easy to find relevant information and resources, -Reusing ideas, documents, and expertise, -Avoiding redundant effort. Consequence: It is found that effectiveness of knowledge management in the Industrial design field is low. Based on filled checklist by Education officials and professors in universities, and coefficient of effectiveness Calculate, knowledge management could not get the right place.

Keywords: knowledge management, industrial design, educational curriculum, learning performance

Procedia PDF Downloads 372