Search results for: virtual environments computer auditing

Authors: Amarendar Reddy Addula

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Definition of Artificial Intelligence: Artificial intelligence is the simulation of mortal intelligence processes by machines, especially computer systems. Explicit operations of AI comprise expert systems, natural language processing, and speech recognition, and machine vision. Artificial Intelligence (AI) is an original medium for digital business, according to a new report by Gartner. The last 10 times represent an advance period in AI’s development, prodded by the confluence of factors, including the rise of big data, advancements in cipher structure, new machine literacy ways, the materialization of pall computing, and the vibrant open- source ecosystem. Influence of AI to a broader set of use cases and druggies and its gaining fashionability because it improves AI’s versatility, effectiveness, and rigidity. Edge AI will enable digital moments by employing AI for real- time analytics closer to data sources. Gartner predicts that by 2025, further than 50 of all data analysis by deep neural networks will do at the edge, over from lower than 10 in 2021. Responsible AI is a marquee term for making suitable business and ethical choices when espousing AI. It requires considering business and societal value, threat, trust, translucency, fairness, bias mitigation, explainability, responsibility, safety, sequestration, and nonsupervisory compliance. Responsible AI is ever more significant amidst growing nonsupervisory oversight, consumer prospects, and rising sustainability pretensions. Generative AI is the use of AI to induce new vestiges and produce innovative products. To date, generative AI sweats have concentrated on creating media content similar as photorealistic images of people and effects, but it can also be used for law generation, creating synthetic irregular data, and designing medicinals and accoutrements with specific parcels. AI is the subject of a wide- ranging debate in which there's a growing concern about its ethical and legal aspects. Constantly, the two are varied and nonplussed despite being different issues and areas of knowledge. The ethical debate raises two main problems the first, abstract, relates to the idea and content of ethics; the alternate, functional, and concerns its relationship with the law. Both set up models of social geste, but they're different in compass and nature. The juridical analysis is grounded on anon-formalistic scientific methodology. This means that it's essential to consider the nature and characteristics of the AI as a primary step to the description of its legal paradigm. In this regard, there are two main issues the relationship between artificial and mortal intelligence and the question of the unitary or different nature of the AI. From that theoretical and practical base, the study of the legal system is carried out by examining its foundations, the governance model, and the nonsupervisory bases. According to this analysis, throughout the work and in the conclusions, International Law is linked as the top legal frame for the regulation of AI.

Keywords: artificial intelligence, ethics & human rights issues, laws, international laws

Procedia PDF Downloads 95

Authors: Djalal Hamed

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The aim of this paper is to perform an analytic solution of steady state natural convection in a narrow rectangular channel between two vertical parallel MTR-type fuel plates, imposed under a cosine shape heat flux to determine the margin of the nuclear core power at which the natural convection cooling mode can ensure a safe core cooling, where the cladding temperature should not be reach the specific safety limits (90 °C). For this purpose, a simple computer program is developed to determine the principal parameter related to the nuclear core safety such as the temperature distribution in the fuel plate and in the coolant (light water) as a function of the reactor power. Our results are validated throughout a comparison against the results of another published work, which is considered like a reference of this study.

Keywords: buoyancy force, friction force, natural convection, thermal hydraulic analysis, vertical heated rectangular channel

Procedia PDF Downloads 316

Authors: Carol C. Opara, Olukemi E. Adetuyi-Olu-Francis

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The need for ICT in Teacher Education due to the nature of 21st-century learners who are computer citizens is essential. The recent increase in the use of Mobile phones has equally revealed the importance of Mobile Applications for learning purposes. However, teacher-trainees and the trainers need to be well-grounded in basic ICT skills for an appropriate outcome. This study seeks to assess the use of Mobile Applications for language learning in Teacher Education teaching-learning process. A 22-item e-questionnaire was used to elicit information from teacher-trainers and teachers-trainees from Faculties of Education in Nigerian Universities. Major findings of this study include: That teacher-education sector is not adequately prepared for manipulative use of ICT and Mobile Applications for teaching and learning process; etc. It was recommended among others that, teacher-trainers should be trained and re-trained on the manipulative use of Mobile devices and the several applications for teaching-learning purpose, especially language education.

Keywords: information and communications technology, ICT, language learning, mobile application, sustainable development, teacher education

Procedia PDF Downloads 168

Authors: Wendy De Gomez

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The University of Waterloo is situated in central Canada in the Province of Ontario- one hour from the metropolitan city of Toronto. For over 30 years, it has held Canada’s top spot as the most innovative university; and has been consistently ranked in the top 25 computer science and top 50 engineering schools in the world. Waterloo benefits from the federal government’s over 100 domestic innovation policies which have assisted in the country’s 15th place global ranking in the World Intellectual Property Organization’s (WIPO) 2022 Global Innovation Index. Yet undoubtedly, the University of Waterloo’s unique characteristics are what propels its innovative creativeness forward. This paper will provide a contextual definition of innovation in higher education and then demonstrate the five operational attributes that contribute to the University of Waterloo’s innovative reputation. The methodology is based on statistical analyses obtained from ranking bodies such as the QS World University Rankings, a secondary literature review related to higher education innovation in Canada, and case studies that exhibit the operationalization of the attributes outlined below. The first attribute is geography. Specifically, the paper investigates the network structure effect of the Toronto-Waterloo high-tech corridor and the resultant industrial relationships built there. The second attribute is University Policy 73-Intellectal Property Rights. This creator-owned policy grants all ownership to the creator/inventor regardless of the use of the University of Waterloo property or funding. Essentially, through the incentivization of IP ownership by all researchers, further commercialization and entrepreneurship are formed. Third, this IP policy works hand in hand with world-renowned business incubators such as the Accelerator Centre in the dedicated research and technology park and velocity, a 14-year-old facility that equips and guides founders to build and scale companies. Communitech, a 25-year-old provincially backed facility in the region, also works closely with the University of Waterloo to build strong teams, access capital, and commercialize products. Fourth, Waterloo’s co-operative education program contributes 31% of all co-op participants to the Canadian economy. Home to the world’s largest co-operative education program, data shows that over 7,000 from around the world recruit Waterloo students for short- and long-term placements- directly contributing to the student’s ability to learn and optimize essential employment skills when they graduate. Finally, the students themselves at Waterloo are exceptional. The entrance average ranges from the low 80s to the mid-90s depending on the program. In computer, electrical, mechanical, mechatronics, and systems design engineering, to have a 66% chance of acceptance, the applicant’s average must be 95% or above. Singularly, none of these five attributes could lead to the university’s outstanding track record of innovative creativity, but when bundled up into a 1000 acre- 100 building main campus with 6 academic faculties, 40,000+ students, and over 1300 world-class faculty, the recipe for success becomes quite evident.

Keywords: IP policy, higher education, economy, innovation

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Authors: Dmitriy Kuptsov

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Tree data structures, such as binary or in general k-ary trees, are essential in computer science. The applications of these data structures can range from data search and retrieval to sorting and ranking algorithms. Naive implementations of these data structures can consume prohibitively large volumes of random access memory limiting their applicability in certain solutions. Thus, in these cases, more advanced representation of these data structures is essential. In this paper we present the design of the compact version of ternary tree data structure and demonstrate the results for the experimental evaluation using static dictionary problem. We compare these results with the results for binary and regular ternary trees. The conducted evaluation study shows that our design, in the best case, consumes up to 12 times less memory (for the dictionary used in our experimental evaluation) than a regular ternary tree and in certain configuration shows performance comparable to regular ternary trees. We have evaluated the performance of the algorithms using both 32 and 64 bit operating systems.

Keywords: algorithms, data structures, succinct ternary tree, per- formance evaluation

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Authors: Y. Galerkin, E. Popova, K. Soldatova

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There is an evident trend to elevate pressure ratio of a single stage of a turbo compressors - axial compressors in particular. Whilst there was an opinion recently that a pressure ratio 1,9 was a reasonable limit, later appeared information on successful modeling tested of stages with pressure ratio up to 2,8. The Authors recon that lack of information on high pressure stages makes actual a study of rational choice of design parameters before high supersonic flow problems solving. The computer program of an engineering type was developed. Below is presented a sample of its application to study possible parameters of the impeller of the stage with pressure ratio π*=3,0. Influence of two main design parameters on expected efficiency, periphery blade speed and flow structure is demonstrated. The results had lead to choose a variant for further analysis and improvement by CFD methods.

Keywords: supersonic stage, impeller, efficiency, flow rate coefficient, work coefficient, loss coefficient, oblique shock, direct shock

Procedia PDF Downloads 467

Authors: Farrukh Shahzad

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The rich Islamic resources related to religious text, Islamic sciences, and history are widely available in print and in electronic format online. However, most of these works are only available in Arabic language. In this research, an attempt is made to utilize these resources to create interactive web applications in Arabic, English and other languages. The system utilizes the Pattern Recognition, Knowledge Management, Data Mining, Information Retrieval and Management, Indexing, storage and data-analysis techniques to parse, store, convert and manage the information from authentic Arabic resources. These interactive web Apps provide smart multi-lingual search, tree based search, on-demand information matching and linking. In this paper, we provide details of application architecture, design, implementation and technologies employed. We also presented the summary of web applications already developed. We have also included some screen shots from the corresponding web sites. These web applications provide an Innovative On-line Learning Systems (eLearning and computer based education).

Keywords: Islamic resources, Muslim scholars, hadith, narrators, history, fiqh

Procedia PDF Downloads 283

Authors: Ahmed H. Amer, A. Amar, Sh. Hamada, I. I. Bondouk, F. A. El-Hussiny

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Elastic scattering of α-particles from 9Be and 11B nuclei at different alpha energies have been analyzed. Optical model parameters (OMPs) of α-particles elastic scattering by these nuclei at different energies have been obtained. In the present calculations, the real part of the optical potential are derived by folding of nucleon-nucleon (NN) interaction into nuclear matter density distribution of the projectile and target nuclei using computer code FRESCO. A density-dependent version of the M3Y interaction (CDM3Y6), which is based on the G-matrix elements of the Paris NN potential, has been used. Volumetric integrals of the real and imaginary potential depth (JR, JW) have been calculated and found to be energy dependent. Good agreement between the experimental data and the theoretical predictions in the whole angular range. In double folding (DF) calculations, the obtained normalization coefficient Nr is in the range 0.70–1.32.

Keywords: elastic scattering, optical model, double folding model, density distribution

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Authors: Ye Zhang, Chuanjun Liu

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In-service aircraft is exposed to different types of threaten, e.g. bird strike, ground vehicle impact, and run-way debris, or even lightning strike, etc. To satisfy the aircraft damage tolerance design requirements, the designer has to understand the threatening level for different types of the aircraft structures, either metallic or composite. Exposing to low-velocity impacts may produce very serious internal damages such as delaminations and matrix cracks without leaving visible mark onto the impacted surfaces for composite structures. This internal damage can cause significant reduction in the load carrying capacity of structures. The semi-probabilistic method provides a practical and proper approximation to establish the impact-threat based energy cut-off level for the damage tolerance evaluation of the aircraft components. Thus, the probabilistic distribution of impact threat and the realistic impact energy level cut-offs are the essential establishments required for the certification of aircraft composite structures. A new survey of impact threat to civil aircraft in-service has recently been carried out based on field records concerning around 500 civil aircrafts (mainly single aisles) and more than 4.8 million flight hours. In total 1,006 damages caused by low-velocity impact events had been screened out from more than 8,000 records including impact dents, scratches, corrosions, delaminations, cracks etc. The impact threat dependency on the location of the aircraft structures and structural configuration was analyzed. Although the survey was mainly focusing on the metallic structures, the resulting low-energy impact data are believed likely representative to general civil aircraft, since the service environments and the maintenance operations are independent of the materials of the structures. The probability of impact damage occurrence (Po) and impact energy exceedance (Pe) are the two key parameters for describing the statistic distribution of impact threat. With the impact damage events from the survey, Po can be estimated as 2.1x10-4 per flight hour. Concerning the calculation of Pe, a numerical model was developed using the commercial FEA software ABAQUS to backward estimate the impact energy based on the visible damage characteristics. The relationship between the visible dent depth and impact energy was established and validated by drop-weight impact experiments. Based on survey results, Pe was calculated and assumed having a log-linear relationship versus the impact energy. As the product of two aforementioned probabilities, Po and Pe, it is reasonable and conservative to assume Pa=PoxPe=10-5, which indicates that the low-velocity impact events are similarly likely as the Limit Load events. Combing Pa with two probabilities Po and Pe obtained based on the field survey, the cutoff level of realistic impact energy was estimated and valued as 34 J. In summary, a new survey was recently done on field records of civil aircraft to investigate the probabilistic distribution of impact threat. Based on the data, two probabilities, Po and Pe, were obtained. Considering a conservative assumption of Pa, the cutoff energy level for the realistic impact energy has been determined, which provides potential applicability in damage tolerance certification of future civil aircraft.

Keywords: composite structure, damage tolerance, impact threat, probabilistic

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Authors: Robert Caulk

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A generalized framework for adaptive machine learning deployments in algorithmic trading is introduced, tested, and released as open-source code. The presented software aims to test the hypothesis that recent data contains enough information to form a probabilistically favorable short-term price prediction. Further, the framework contains various adaptive machine learning techniques that are geared toward generating profit during strong trends and minimizing losses during trend changes. Results demonstrate that this adaptive machine learning approach is capable of capturing trends and generating profit. The presentation also discusses the importance of defining the parameter space associated with the dynamic training data-set and using the parameter space to identify and remove outliers from prediction data points. Meanwhile, the generalized architecture enables common users to exploit the powerful machinery while focusing on high-level feature engineering and model testing. The presentation also highlights common strengths and weaknesses associated with the presented technique and presents a broad range of well-tested starting points for feature set construction, target setting, and statistical methods for enforcing risk management and maintaining probabilistically favorable entry and exit points. The presentation also describes the end-to-end data processing tools associated with FreqAI, including automatic data fetching, data aggregation, feature engineering, safe and robust data pre-processing, outlier detection, custom machine learning and statistical tools, data post-processing, and adaptive training backtest emulation, and deployment of adaptive training in live environments. Finally, the generalized user interface is also discussed in the presentation. Feature engineering is simplified so that users can seed their feature sets with common indicator libraries (e.g. TA-lib, pandas-ta). The user also feeds data expansion parameters to fill out a large feature set for the model, which can contain as many as 10,000+ features. The presentation describes the various object-oriented programming techniques employed to make FreqAI agnostic to third-party libraries and external data sources. In other words, the back-end is constructed in such a way that users can leverage a broad range of common regression libraries (Catboost, LightGBM, Sklearn, etc) as well as common Neural Network libraries (TensorFlow, PyTorch) without worrying about the logistical complexities associated with data handling and API interactions. The presentation finishes by drawing conclusions about the most important parameters associated with a live deployment of the adaptive learning framework and provides the road map for future development in FreqAI.

Keywords: machine learning, market trend detection, open-source, adaptive learning, parameter space exploration

Procedia PDF Downloads 89

Authors: Julio Kauss, Miguel Cadillo, David Mauricio

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E-commerce is a business model that allows companies to optimize the processes of buying, selling, transferring goods and exchanging services through computer networks or the Internet. In Peru, the electronic commerce is used infrequently. This situation is due, in part to the fact that there is no model that allows companies to implement an e-commerce solution, which means that most SMEs do not have adequate knowledge to adapt to electronic commerce. In this work, a reference model is proposed for the implementation of an e-commerce solution in Peruvian SMEs in the retail sector. It consists of five phases: Business Analysis, Business Modeling, Implementation, Post Implementation and Results. The present model was validated in a SME of the Peruvian retail sector through the implementation of an electronic commerce platform, through which the company increased its sales through the delivery channel by 10% in the first month of deployment. This result showed that the model is easy to implement, is economical and agile. In addition, it allowed the company to increase its business offer, adapt to e-commerce and improve customer loyalty.

Keywords: e-commerce, retail, SMEs, reference model

Procedia PDF Downloads 320

Authors: Melissa Dorsey

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Moral distress and compassion fatigue plague nurses in the Cardiothoracic Intensive Care Unit (CTICU) and cause an unnecessary level of turnover. Dueling Burnout describes an initiative that was implemented in the CTICU to reduce the level of burnout the nurses endure by encouraging dual roles with collaborating departments. Purpose: Critical care nurses are plagued by burnout, moral distress, and compassion fatigue due to the intensity of care provided. The purpose of the dual role program was to decrease these issues by providing relief from the intensity of the critical care environment while maintaining full-time employment. Relevance/Significance: Burnout, moral distress, and compassion fatigue are leading causes of Cardiothoracic Critical Care (CTCU) turnover. A contributing factor to burnout is the workload related to serving as a preceptor for a constant influx of new nurses (RN). As a result of these factors, the CTICU averages 17% nursing turnover/year. The cost, unit disruption, and, most importantly, distress of the clinical nurses required an innovative approach to create an improved work environment and experience. Strategies/Implementation/Methods: In May 2018, a dual role pilot was initiated for nurses. The dual role constitutes .6 full-time equivalent hours (FTE) worked in CTICU in combination with .3 FTE worked in the Emergency Department (ED). ED nurses who expressed an interest in cross-training to CTICU were also offered the dual role opportunity. The initial hypothesis was that full-time employees would benefit from a change in clinical setting leading to increased engagement and job satisfaction. The dual role also presents an opportunity for professional development through the expansion of clinical skills in another specialty. Success of the pilot led to extending the dual role to areas beyond the ED. Evaluation/Outcomes/Results: The number of dual role clinical nurses has grown to 22. From the dual role cohort, only one has transferred out of CTICU. This is a 5% turnover rate for this group of nurses as compared to the average turnover rate of 17%. A role satisfaction survey conducted with the dual role cohort found that because of working in a dual role, 76.5% decreased their intent to leave, 100% decreased their level of burnout, and 100% reported an increase in overall job satisfaction. Nurses reported the ability to develop skills that are transferable between departments. Respondents emphasized the appreciation gained from working in multiple environments; the dual role served to transform their care. Conclusions/Implications: Dual role is an effective strategy to retain experienced nurses, decrease burnout and turnover, improve collaboration, and provide flexibility to meet staffing needs. The dual role offers RNs an expansion of skills, relief from high acuity and orientee demands, while improving job satisfaction.

Keywords: nursing retention, burnout, pandemic, strategic staffing, leadership

Procedia PDF Downloads 183

Authors: Devinder Singh, Rajneesh Kumar, Arvind Kumar

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The present investigation deals with the deformation of micropolar generalized thermoelastic solid subjected to thermo-mechanical loading due to a thermal laser pulse. Laplace transform and Fourier transform techniques are used to solve the problem. Thermo-mechanical laser interactions are taken as distributed sources to describe the application of the approach. The closed form expressions of normal stress, tangential stress, coupled stress and temperature are obtained in the domain. Numerical inversion technique of Laplace transform and Fourier transform has been implied to obtain the resulting quantities in the physical domain after developing a computer program. The normal stress, tangential stress, coupled stress and temperature are depicted graphically to show the effect of relaxation times. Some particular cases of interest are deduced from the present investigation.

Keywords: pulse laser, integral transform, thermoelastic, boundary value problem

Procedia PDF Downloads 616

Authors: Web Huei Chou, Li Yi Chun, Wenwe Yu, Han Teng Weng, H. Yuan, T. Yang

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The prevalence of dementia is estimated to rise to 78 million by 2030 and 139 million by 2050. Among those affected, Alzheimer's disease is the most common form of dementia, contributing to 60–70% of cases. Addressing this growing challenge is crucial, especially considering the impact on older individuals and their caregivers. To reduce the behavioral and psychological symptoms of dementia, people with dementia use a variety of pharmaceutical and non-pharmacological treatments, and some studies have found the use of non-pharmacological interventions. Treatment of depression, cognitive function, and social activities has potential benefits. Butler developed reminiscence therapy as a method of treating dementia. Through ‘life review,’ individuals can recall their past events, activities, and experiences, which can reduce the depression of the elderly and improve their Quality of life to help give meaning to their lives and help them live independently. The life review process uses a variety of memory triggers, such as household items, past objects, photos, and music, and can be conducted collectively or individually and structured or unstructured. However, despite the advantages of nostalgia therapy, past research has always pointed out that current research lacks rigorous experimental evaluation and cannot describe clear research results and generalizability. Therefore, this study aims to study physiological sensing experiments to find a feasible experimental and verification method to provide clearer design and design specifications for reminiscence therapy and to provide a more widespread application for healthy aging. This study is an ongoing research project, a collaboration between the School of Design at Yunlin University of Science and Technology in Taiwan and the Department of Medical Engineering at Chiba University in Japan. We use traditional rice dishes from Taiwan and Japan as nostalgic content to construct a narrative structure for the elderly in the two countries respectively for life review activities, providing an easy-to-carry nostalgic therapy game with an intuitive interactive design. This experiment is expected to be completed in 36 months. The design team constructed and designed the game after conducting literary and historical data surveys and interviews with elders to confirm the nostalgic historical data in Taiwan and Japan. The Japanese team planned the Electrodermal Activity (EDA) and Blood Volume Pulse (BVP) experimental environments and Data calculation model, and then after conducting experiments on elderly people in two places, the research results were analyzed and discussed together. The research has completed the first 24 months of pre-study, design work, and pre-study and has entered the project acceptance stage.

Keywords: reminiscence therapy, aging health, design research, life review

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Authors: Isabel N. Sierra-Garcia, Maria J. Ferreira, Sandro Figuereido, Newton Gomes, Helena Silva, Angela Cunha

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Plant-associated microbial communities are considered crucial in the adaptation of halophytes to coastal environments. The plant microbiota can be horizontally acquired from the environment or vertically transmitted from generation to generation via seeds. Recruiting of the microbial communities by the plant is affected by geographical location, soil source, host genotype, and cultivation practice. There is limited knowledge reported on the microbial communities in halophytes the influence of biotic and abiotic factors. In this work, the microbiota associated with the halophyte Salicornia ramosissima was investigated to determine whether the structure of bacterial communities is influenced by host genotype or soil source. For this purpose, two contrasting sites where S. ramosissima is established in the estuarine system of the Ria de Aveiro were investigated. One site corresponds to a natural salt marsh where S. ramosissima plants are present (wild plants), and the other site is a former salt pan that nowadays are subjected to intensive crop production of S. ramosissima (crop plants). Bacterial communities from the rhizosphere, seeds and root endosphere of S. ramossisima from both sites were investigated by sequencing bacterial 16S rRNA gene using the Illumina MiSeq platform. The analysis of the sequences showed that the three plant-associated compartments, rhizosphere, root endosphere, and seed endosphere, harbor distinct microbiomes. However, bacterial richness and diversity were higher in seeds of wild plants, followed by rhizosphere in both sites, while seeds in the crop site had the lowest diversity. Beta diversity measures indicated that bacterial communities in root endosphere and seeds were more similar in both wild and crop plants in contrast to rhizospheres that differed by local, indicating that the recruitment of the similar bacterial communities by the plant genotype is active in regard to the site. Moreover, bacterial communities from the root endosphere and rhizosphere were phylogenetically more similar in both sites, but the phylogenetic composition of seeds in wild and crop sites was distinct. These results indicate that cultivation practices affect the seed microbiome. However, minimal vertical transmission of bacteria from seeds to adult plants is expected. Seeds from the crop site showed higher abundances of Kushneria and Zunongwangia genera. Bacterial members of the classes Alphaprotebacteria and Bacteroidia were the most ubiquitous across sites and compartments and might encompass members of the core microbiome. These findings indicate that bacterial communities associated with S. ramosissima are more influenced by host genotype rather than local abiotic factors or cultivation practices. This study provides a better understanding of the composition of the plant microbiota in S. ramosissima , which is essential to predict the interactions between plant and associated microbial communities and their effects on plant health. This knowledge is useful to the manipulations of these microbial communities to enhance the health and productivity of this commercially important plant.

Keywords: halophytes, plant microbiome, Salicornia ramosissima, agriculture

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Authors: Alireza Pour Ebrahimi, Vahid Abasi

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Recently by the extension of internet usage, Research on the intrusion detection system takes a significant importance. Many of improvement systems prevent internal and external network attacks by providing security through firewalls and antivirus. In recently years, intrusion detection systems gradually turn from host-based systems and depend on O.S to the distributed systems which are running on multiple O.S. In this work, by considering the diversity of computer networks whit respect to structure, architecture, resource, services, users and also security goals requirement a fully distributed collaborative intrusion detection system based on peer to peer architecture is suggested. in this platform each partner device (matched device) considered as a peer-to-peer network. All transmitted information to network are visible only for device that use security scanning of a source. Experimental results show that the distributed architecture is significantly upgradeable in respect to centralized approach.

Keywords: network, intrusion detection system, peer to peer, internal and external network

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Authors: Shangdong Zhu, Yunzhou Zhang, Jie Zhang, Hang Hu, Yazhou Zhang

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Image stitching is a very important branch in the field of computer vision, especially for panoramic map. In order to eliminate shape distortion, a novel stitching method is proposed based on gradually changing matrix when images are horizontal. For images captured horizontally, this paper assumes that there is only translational operation in image stitching. By analyzing each parameter of the homography matrix, the global homography matrix is gradually transferred to translation matrix so as to eliminate the effects of scaling, rotation, etc. in the image transformation. This paper adopts matrix approximation to get the minimum value of the energy function so that the shape distortion at those regions corresponding to the homography can be minimized. The proposed method can avoid multiple horizontal images stitching failure caused by accumulated shape distortion. At the same time, it can be combined with As-Projective-As-Possible algorithm to ensure precise alignment of overlapping area.

Keywords: image stitching, gradually changing matrix, horizontal direction, matrix approximation, homography matrix

Procedia PDF Downloads 319

Authors: Nadia Belu, Laurenţiu Mihai Ionescu, Agnieszka Misztal

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The automotive industry is one of the most important industries in the world that concerns not only the economy, but also the world culture. In the present financial and economic context, this field faces new challenges posed by the current crisis, companies must maintain product quality, deliver on time and at a competitive price in order to achieve customer satisfaction. Two of the most recommended techniques of quality management by specific standards of the automotive industry, in the product development, are Failure Mode and Effects Analysis (FMEA) and Control Plan. FMEA is a methodology for risk management and quality improvement aimed at identifying potential causes of failure of products and processes, their quantification by risk assessment, ranking of the problems identified according to their importance, to the determination and implementation of corrective actions related. The companies use Control Plans realized using the results from FMEA to evaluate a process or product for strengths and weaknesses and to prevent problems before they occur. The Control Plans represent written descriptions of the systems used to control and minimize product and process variation. In addition Control Plans specify the process monitoring and control methods (for example Special Controls) used to control Special Characteristics. In this paper we propose a computer-aided solution with Genetic Algorithms in order to reduce the drafting of reports: FMEA analysis and Control Plan required in the manufacture of the product launch and improved knowledge development teams for future projects. The solution allows to the design team to introduce data entry required to FMEA. The actual analysis is performed using Genetic Algorithms to find optimum between RPN risk factor and cost of production. A feature of Genetic Algorithms is that they are used as a means of finding solutions for multi criteria optimization problems. In our case, along with three specific FMEA risk factors is considered and reduce production cost. Analysis tool will generate final reports for all FMEA processes. The data obtained in FMEA reports are automatically integrated with other entered parameters in Control Plan. Implementation of the solution is in the form of an application running in an intranet on two servers: one containing analysis and plan generation engine and the other containing the database where the initial parameters and results are stored. The results can then be used as starting solutions in the synthesis of other projects. The solution was applied to welding processes, laser cutting and bending to manufacture chassis for buses. Advantages of the solution are efficient elaboration of documents in the current project by automatically generating reports FMEA and Control Plan using multiple criteria optimization of production and build a solid knowledge base for future projects. The solution which we propose is a cheap alternative to other solutions on the market using Open Source tools in implementation.

Keywords: automotive industry, FMEA, control plan, automotive technology

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Authors: Nurulnadwan Aziz, Ariffin Abdul Mutalib, Siti Mahfuzah Sarif

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This paper reports an ongoing project regarding the development of Conceptual Design Model of Assistive Courseware for Low Vision (AC4LV) learners. Having developed the intended model, it has to be validated prior to producing it as guidance for the developers to develop an AC4LV. This study requires two phases of validation process which are through expert review and prototyping method. This paper presents a part of the validation process which is findings from experts review on Conceptual Design Model of AC4LV which has been carried out through a questionnaire. Results from 12 international and local experts from various respectable fields in Human-Computer Interaction (HCI) were discussed and justified. In a nutshell, reviewed Conceptual Design Model of AC4LV was formed. Future works of this study are to validate the reviewed model through prototyping method prior to testing it to the targeted users.

Keywords: assistive courseware, conceptual design model, expert review, low vision learners

Procedia PDF Downloads 546

Authors: Igor Faulmann, Arnaud Saj, Roland Maurer

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Spatial cognition consists in a plethora of high level cognitive abilities: among them, the ability to learn and to navigate in large scale environments is probably one of the most complex skills. Navigation is thought to rely on the ability to read a cognitive map, defined as an allocentric representation of ones environment. Those representations are of course intimately related to the two geometrical primitives of the environment: distance and direction. Also, many recent studies point to a predominant hippocampal and para-hippocampal role in spatial cognition, as well as in the more specific cluster of navigational skills. In a previous study in humans, we used a newly validated test assessing cognitive map processing by evaluating the ability to judge relative distances and directions: the CMRT (Cognitive Map Recall Test). This study identified in topographically disorientated patients (1) behavioral differences between the evaluation of distances and of directions, and (2) distinct causality patterns assessed via VLSM (i.e., distinct cerebral lesions cause distinct response patterns depending on the modality (distance vs direction questions). Thus, we hypothesized that: (1) if the CMRT really taps into the same resources as real navigation, there would be hippocampal, parahippocampal, and parietal activation, and (2) there exists underlying neuroanatomical and functional differences between the processing of this two modalities. Aiming toward a better understanding of the neuroanatomical correlates of the CMRT in humans, and more generally toward a better understanding of how the brain processes the cognitive map, we adapted the CMRT as an fMRI procedure. 23 healthy subjects (11 women, 12 men), all living in Geneva for at least 2 years, underwent the CMRT in fMRI. Results show, for distance and direction taken together, than the most active brain regions are the parietal, frontal and cerebellar parts. Additionally, and as expected, patterns of brain activation differ when comparing the two modalities. Furthermore, distance processing seems to rely more on parietal regions (compared to other brain regions in the same modality and also to direction). It is interesting to notice that no significant activity was observed in the hippocampal or parahippocampal areas. Direction processing seems to tap more into frontal and cerebellar brain regions (compared to other brain regions in the same modality and also to distance). Significant hippocampal and parahippocampal activity has been shown only in this modality. This results demonstrated a complex interaction of structures which are compatible with response patterns observed in other navigational tasks, thus showing that the CMRT taps at least partially into the same brain resources as real navigation. Additionally, differences between the processing of distances and directions leads to the conclusion that the human brain processes each modality distinctly. Further research should focus on the dynamics of this processing, allowing a clearer understanding between the two sub-processes.

Keywords: cognitive map, navigation, fMRI, spatial cognition

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Authors: Songyun Chen

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Recent scholarly attention to sentiment analysis has provided researchers with a deeper understanding of how emotions are conveyed in writing and leveraged by academic authors as a persuasive tool. Using the National Research Council (NRC) Sentiment Lexicons (version 1.0) created by the National Research Council Canada, this study examined specific emotions in research articles (RAs) across four disciplines, including literature, education, biology, and computer & information science based on four datasets totaling over three million tokens, aiming to reveal how the emotions are conveyed by authors in academic writing. The results showed that four emotions—trust, anticipation, joy, and surprise—were observed in all four disciplines, while sadness emotion was spotted solely in literature. With the emotion of trust being overwhelmingly prominent, the rest emotions varied significantly across disciplines. The findings contribute to our understanding of emotion strategy applied in academic writing and genre characteristics of RAs.

Keywords: sentiment analysis, specific emotions, emotional landscape, research articles, academic writing

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Authors: Matthew Yeager, Christopher Willy, John Bischoff

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The conceptualization and design phases of a system lifecycle consume a significant amount of the lifecycle budget in the form of direct tasking and capital, as well as the implicit costs associated with unforeseeable design errors that are only realized during downstream phases. Ad hoc or iterative approaches to generating system requirements oftentimes fail to consider the full array of feasible systems or product designs for a variety of reasons, including, but not limited to: initial conceptualization that oftentimes incorporates a priori or legacy features; the inability to capture, communicate and accommodate stakeholder preferences; inadequate technical designs and/or feasibility studies; and locally-, but not globally-, optimized subsystems and components. These design pitfalls can beget unanticipated developmental or system alterations with added costs, risks and support activities, heightening the risk for suboptimal system performance, premature obsolescence or forgone development. Supported by rapid advances in learning algorithms and hardware technology, sensors and sensor systems have become commonplace in both commercial and industrial products. The evolving array of hardware components (i.e. sensors, CPUs, modular / auxiliary access, etc…) as well as recognition, data fusion and communication protocols have all become increasingly complex and critical for design engineers during both concpetualization and implementation. This work seeks to develop and utilize a non-deterministic approach for sensor system design within the multi-attribute tradespace exploration (MATE) paradigm, a technique that incorporates decision theory into model-based techniques in order to explore complex design environments and discover better system designs. Developed to address the inherent design constraints in complex aerospace systems, MATE techniques enable project engineers to examine all viable system designs, assess attribute utility and system performance, and better align with stakeholder requirements. Whereas such previous work has been focused on aerospace systems and conducted in a deterministic fashion, this study addresses a wider array of system design elements by incorporating both traditional tradespace elements (e.g. hardware components) as well as popular multi-sensor data fusion models and techniques. Furthermore, statistical performance features to this model-based MATE approach will enable non-deterministic techniques for various commercial systems that range in application, complexity and system behavior, demonstrating a significant utility within the realm of formal systems decision-making.

Keywords: multi-attribute tradespace exploration, data fusion, sensors, systems engineering, system design

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Authors: Georges Ghazi, Marc-Henry Devillers, Ruxandra M. Botez

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Aircraft flight trajectory optimization has been identified to be a promising solution for reducing both airline costs and the aviation net carbon footprint. Nowadays, this role has been mainly attributed to the flight management system. This system is an onboard multi-purpose computer responsible for providing the crew members with the optimized flight plan from a destination to the next. To accomplish this function, the flight management system uses a variety of look-up tables to compute the optimal speed and altitude for each flight regime instantly. Because the cruise is the longest segment of a typical flight, the proposed algorithm is focused on minimizing fuel consumption for this flight phase. In this paper, a complete methodology to estimate the aircraft performance and subsequently compute the optimal speed in cruise is presented. Results showed that the obtained performance database was accurate enough to predict the flight costs associated with the cruise phase.

Keywords: Cessna Citation X, cruise speed optimization, flight cost, cost index, and golden section search

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Authors: Mary T. McKinley

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As socio-economic globalization impacts education and turns knowledge into a commodity, institutions of higher education are becoming more intentional about infusing a global and intercultural perspective into education via the recruitment of international students. Coming from dissimilar cultures, many of these students are evaluated and held accountable to Euro-American values of independence, self-reliance, and autonomy. Not surprisingly, these students often experience culture shock with deleterious effects on their mental health and academic functioning. Thus, it is critical to understand the experiences of international students with the hope that such knowledge will keep the field of psychology from promulgating Eurocentric ideals and values and prevent the training of these students as good-enough White therapists. Using a critical narrative inquiry framework, this study elicits stories about the challenges encountered by international students as they navigate their clinical training in the presence of acculturative stress and potentially different worldviews. With its emphasis on story-telling as meaning making, narrative research design is hinged on the assumption that people are interpretive beings who make meaning of themselves and their world through the language of stories. Also, dominant socially-constructed narratives play a central role in creating and maintaining hegemonic structures that privilege certain individuals and ideologies at the expense of others. On this premise, narrative inquiry begins with an exploration of the experiences of participants in their lived stories. Bounded narrative segments were read, interpreted, and analyzed using a critical events approach. Throughout the process, issues of reliability and researcher bias were addressed by keeping a reflective analytic memo, as well as triangulating the data using peer-reviewers and check-ins with participants. The findings situate culture at the epicenter of international students’ acculturation challenges as well as their resiliency in psychology doctoral programs. It was not uncommon for these international students to experience ethical dilemmas inherent in learning content that conflicted with their cultural beliefs and values. Issues of cultural incongruence appear to be further exacerbated by visible markers for differences like speech accent and clothing attire. These stories also link the acculturative stress reported by international students to the experiences of perceived racial discrimination and lack of support from the faculty, administration, peers, and the society at large. Beyond the impact on the international students themselves, there are implications for internationalization in psychology with the goal of equipping doctoral programs to be better prepared to meet the needs of their international students. More than ever before, programs need to liaise with international students’ services and work in tandem to meet the unique needs of this population of students. Also, there exists a need for multiculturally competent supervisors working with international students with varying degrees of acculturation. In addition to making social justice and advocacy salient in students’ multicultural training, it may be helpful for psychology doctoral programs to be more intentional about infusing cross-cultural theories, indigenous psychotherapies, and/or when practical, the possibility for geographically cross-cultural practicum experiences in the home countries of international students while taking into consideration the ethical issues for virtual supervision.

Keywords: decolonizing pedagogies, international students, multiculturalism, psychology doctoral programs

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Authors: Maria Reznakova, Michala Strnadova, Lukas Reznak

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Successful achievement of strategic goals requires an effective performance management system, i.e. determining the appropriate indicators measuring the rate of goal achievement. Assuming that the goal of the owners is to grow the assets they invested in, it is vital to identify the key performance indicators, which contribute to value creation. These indicators are known as value drivers. Based on the undertaken literature search, a value driver is defined as any factor that affects the value of an enterprise. The important factors are then monitored by both financial and non-financial indicators. Financial performance indicators are most useful in strategic management, since they indicate whether a company's strategy implementation and execution are contributing to bottom line improvement. Non-financial indicators are mainly used for short-term decisions. The identification of value drivers, however, is problematic for companies which are not publicly traded. Therefore financial ratios continue to be used to measure the performance of companies, despite their considerable criticism. The main drawback of such indicators is the fact that they are calculated based on accounting data, while accounting rules may differ considerably across different environments. For successful enterprise performance management it is vital to avoid factors that may reduce (or even destroy) its value. Among the known factors reducing the enterprise value are the lack of capital, lack of strategic management system and poor quality of production. In order to gain further insight into the topic, the paper presents results of the research identifying factors that adversely affect the performance of mechanical engineering enterprises in the Czech Republic. The research methodology focuses on both the qualitative and the quantitative aspect of the topic. The qualitative data were obtained from a questionnaire survey of the enterprises senior management, while the quantitative financial data were obtained from the Analysis Major Database for European Sources (AMADEUS). The questionnaire prompted managers to list factors which negatively affect business performance of their enterprises. The range of potential factors was based on a secondary research – analysis of previously undertaken questionnaire surveys and research of studies published in the scientific literature. The results of the survey were evaluated both in general, by average scores, and by detailed sub-analyses of additional criteria. These include the company specific characteristics, such as its size and ownership structure. The evaluation also included a comparison of the managers’ opinions and the performance of their enterprises – measured by return on equity and return on assets ratios. The comparisons were tested by a series of non-parametric tests of statistical significance. The results of the analyses show that the factors most detrimental to the enterprise performance include the incompetence of responsible employees and the disregard to the customers‘ requirements.

Keywords: business value, financial ratios, performance measurement, value drivers

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Authors: McClain Thiel

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Object detection and localization has historically required two or more sensors due to the loss of information from 3D to 2D space, however, most surveillance systems currently in use in the real world only have one sensor per location. Generally, this consists of a single low-resolution camera positioned above the area under observation (mall, jewelry store, traffic camera). This is not sufficient for robust 3D tracking for applications such as security or more recent relevance, contract tracing. This paper proposes a lightweight system for 3D person tracking that requires no additional hardware, based on compressed object detection convolutional-nets, facial landmark detection, and projective geometry. This approach involves classifying the target into a demographic category and then making assumptions about the relative locations of facial landmarks from the demographic information, and from there using simple projective geometry and known constants to find the target's location in 3D space. Preliminary testing, although severely lacking, suggests reasonable success in 3D tracking under ideal conditions.

Keywords: monocular distancing, computer vision, facial analysis, 3D localization

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Authors: Natalia V. Beloglazova, Pieterjan Lenain, Martin Hedstrom, Dietmar Knopp, Sarah De Saeger

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In recent years polycyclic aromatic hydrocarbons (PAHs), which represent a hazard to humans and entire ecosystem, have been receiving an increased interest due to their mutagenic, carcinogenic and endocrine disrupting properties. They are formed in all incomplete combustion processes of organic matter and, as a consequence, ubiquitous in the environment. Benzo(a)pyrene (BaP) is on the priority list published by the Environmental Agency (US EPA) as the first PAH to be identified as a carcinogen and has often been used as a marker for PAHs contamination in general. It can be found in different types of water samples, therefore, the European Commission set up a limit value of 10 ng L–1 (10 ppt) for BAP in water intended for human consumption. Generally, different chromatographic techniques are used for PAHs determination, but these assays require pre-concentration of analyte, create large amounts of solvent waste, and are relatively time consuming and difficult to perform on-site. An alternative robust, stand-alone, and preferably cheap solution is needed. For example, a sensing unit which can be submerged in a river to monitor and continuously sample BaP. An affinity sensor based on capacitive transduction was developed. Natural antibodies or their synthetic analogues can be used as ligands. Ideally the sensor should operate independently over a longer period of time, e.g. several weeks or months, therefore the use of molecularly imprinted polymers (MIPs) was discussed. MIPs are synthetic antibodies which are selective for a chosen target molecule. Their robustness allows application in environments for which biological recognition elements are unsuitable or denature. They can be reused multiple times, which is essential to meet the stand-alone requirement. BaP is a highly lipophilic compound and does not contain any functional groups in its structure, thus excluding non-covalent imprinting methods based on ionic interactions. Instead, the MIPs syntheses were based on non-covalent hydrophobic and π-π interactions. Different polymerization strategies were compared and the best results were demonstrated by the MIPs produced using electropolymerization. 4-vinylpyridin (VP) and divinylbenzene (DVB) were used as monomer and cross-linker in the polymerization reaction. The selectivity and recovery of the MIP were compared to a non-imprinted polymer (NIP). Electrodes were functionalized with natural receptor (monoclonal anti-BaP antibody) and with MIPs selective towards BaP. Different sets of electrodes were evaluated and their properties such as sensitivity, selectivity and linear range were determined and compared. It was found that both receptor can reach the cut-off level comparable to the established ML, and despite the fact that the antibody showed the better cross-reactivity and affinity, MIPs were more convenient receptor due to their ability to regenerate and stability in river till 7 days.

Keywords: antibody, benzo(a)pyrene, capacitive sensor, MIPs, river water

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Authors: Jacopo Baboni Schilingi

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We here describe the theoretical and philosophical understanding of a long term use and development of algorithmic computer-based tools applied to music composition. The findings of our research lead us to interrogate some specific processes and systems of communication engaged in the discovery of specific cultural artworks: artistic creation in the sono-musical domain. Our hypothesis is that the patterns of auditory learning cannot be only understood in terms of social transmission but would gain to be questioned in the way they rely on various ranges of acoustic stimuli modes of consciousness and how the different types of memories engaged in the percept-action expressive systems of our cultural communities also relies on these shadowy conscious entities we named “Reduced Descriptive Structures”.

Keywords: algorithmic sonic computation, corrected and self-correcting learning patterns in acoustic perception, morphological derivations in sensorial patterns, social unconscious modes of communication

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Authors: Bagireanu Astrid, Bros-Williamson Julio, Duncheva Mila, Currie John

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The Architecture, Engineering, and Construction (AEC) sector plays a critical role in the global transition toward sustainable and net-zero built environments. However, the industry faces unique challenges in planning for net-zero while struggling with low productivity, cost overruns and overall resistance to change. Traditional practices fall short due to their inability to meet the requirements for systemic change, especially as governments increasingly demand transformative approaches. Working in silos and rigid hierarchies and a short-term, client-centric approach prioritising immediate gains over long-term benefit stands in stark contrast to the fundamental requirements for the realisation of net-zero objectives. These practices have limited capacity to effectively integrate AEC stakeholders and promote the essential knowledge sharing required to address the multifaceted challenges of achieving net-zero. In the context of built environment, procurement may be described as the method by which a project proceeds from inception to completion. Collaborative procurement methods under the Integrated Practices (IP) umbrella have the potential to align more closely with net-zero objectives. This paper explores the synergies between collaborative procurement principles and the pursuit of net zero in the AEC sector, drawing upon the shared values of cross-disciplinary collaboration, Early Supply Chain involvement (ESI), use of standards and frameworks, digital information management, strategic performance measurement, integrated decision-making principles and contractual alliancing. To investigate the role of collaborative procurement in advancing net-zero objectives, a structured research methodology was employed. First, the study focuses on a systematic review on the application of collaborative procurement principles in the AEC sphere. Next, a comprehensive analysis is conducted to identify common clusters of these principles across multiple procurement methods. An evaluative comparison between traditional procurement methods and collaborative procurement for achieving net-zero objectives is presented. Then, the study identifies the intersection between collaborative procurement principles and the net-zero requirements. Lastly, an exploration of key insights for AEC stakeholders focusing on the implications and practical applications of these findings is made. Directions for future development of this research are recommended. Adopting collaborative procurement principles can serve as a strategic framework for guiding the AEC sector towards realising net-zero. Synergising these approaches overcomes fragmentation, fosters knowledge sharing, and establishes a net-zero-centered ecosystem. In the context of the ongoing efforts to amplify project efficiency within the built environment, a critical realisation of their central role becomes imperative for AEC stakeholders. When effectively leveraged, collaborative procurement emerges as a powerful tool to surmount existing challenges in attaining net-zero objectives.

Keywords: collaborative procurement, net-zero, knowledge sharing, architecture, built environment

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Authors: Bharatendra Rai

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The sequence of words in text data has long-term dependencies and is known to suffer from vanishing gradient problems when developing deep learning models. Although recurrent networks such as long short-term memory networks help to overcome this problem, achieving high text classification performance is a challenging problem. Convolutional recurrent networks that combine the advantages of long short-term memory networks and convolutional neural networks can be useful for text classification performance improvements. However, arriving at suitable hyperparameter values for convolutional recurrent networks is still a challenging task where fitting a model requires significant computing resources. This paper illustrates the advantages of using convolutional recurrent networks for text classification with the help of statistically planned computer experiments for hyperparameter tuning.

Keywords: long short-term memory networks, convolutional recurrent networks, text classification, hyperparameter tuning, Tukey honest significant differences

Procedia PDF Downloads 129