Search results for: web processing service (WPS)

Authors: Andrey Khalov

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The rapid proliferation of unstructured data in IT infrastructure management demands innovative approaches for extracting actionable knowledge. This paper presents a framework for ontology-based knowledge extraction that combines relational graph neural networks (R-GNN) with large language models (LLMs). The proposed method leverages the DOLCE framework as the foundational ontology, extending it with concepts from ITSMO for domain-specific applications in IT service management and outsourcing. A key component of this research is the use of transformer-based models, such as DeBERTa-v3-large, for automatic entity and relationship extraction from unstructured texts. Furthermore, the paper explores how transfer learning techniques can be applied to fine-tune large language models (LLaMA) for using to generate synthetic datasets to improve precision in BERT-based entity recognition and ontology alignment. The resulting IT Ontology (ITO) serves as a comprehensive knowledge base that integrates domain-specific insights from ITIL processes, enabling more efficient decision-making. Experimental results demonstrate significant improvements in knowledge extraction and relationship mapping, offering a cutting-edge solution for enhancing cognitive computing in IT service environments.

Keywords: ontology expansion, synthetic dataset, transformer fine-tuning, concept extraction, DOLCE, BERT, taxonomy, LLM, NER

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Authors: Janusz Bobulski, Mariusz Kubanek

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The main goal of the research is to develop a multimedia container structure containing three types of images: RGB, lidar and infrared, properly calibrated to each other. An additional goal is to develop program libraries for creating and saving this type of file and for restoring it. It will also be necessary to develop a method of data synchronization from lidar and RGB cameras as well as infrared. This type of file could be used in autonomous vehicles, which would certainly facilitate data processing by the intelligent autonomous vehicle management system. Autonomous cars are increasingly breaking into our consciousness. No one seems to have any doubts that self-driving cars are the future of motoring. Manufacturers promise that moving the first of them to showrooms is the prospect of the next few years. Many experts believe that creating a network of communicating autonomous cars will be able to completely eliminate accidents. However, to make this possible, it is necessary to develop effective methods of detection of objects around the moving vehicle. In bad weather conditions, this task is difficult on the basis of the RGB(red, green, blue) image. Therefore, in such situations, you should be supported by information from other sources, such as lidar or infrared cameras. The problem is the different data formats that individual types of devices return. In addition to these differences, there is a problem with the synchronization of these data and the formatting of this data. The goal of the project is to develop a file structure that could be containing a different type of data. This type of file is calling a multimedia container. A multimedia container is a container that contains many data streams, which allows you to store complete multimedia material in one file. Among the data streams located in such a container should be indicated streams of images, films, sounds, subtitles, as well as additional information, i.e., metadata. This type of file could be used in autonomous vehicles, which would certainly facilitate data processing by the intelligent autonomous vehicle management system. As shown by preliminary studies, the use of combining RGB and InfraRed images with Lidar data allows for easier data analysis. Thanks to this application, it will be possible to display the distance to the object in a color photo. Such information can be very useful for drivers and for systems in autonomous cars.

Keywords: an autonomous car, image processing, lidar, obstacle detection

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Authors: Aishatu Ibrahim Birma, Aminu Tukur, Abdulkarim Abbass Gora

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Machine translation plays a vital role in the Field of Natural Language Processing (NLP), breaking down language barriers and enabling communication across diverse communities. In the context of Hausa, a widely spoken language in West Africa, mainly in Nigeria, effective translation systems are essential for enabling seamless communication and promoting cultural exchange. However, due to the unique linguistic characteristics of Hausa, accurate translation remains a challenging task. The research proposes an approach to improving the machine learning translation of Hausa by integrating Named Entity Recognition (NER) techniques. Named entities, such as person names, locations, organizations, and dates, are critical components of a language's structure and meaning. Incorporating NER into the translation process can enhance the quality and accuracy of translations by preserving the integrity of named entities and also maintaining consistency in translating entities (e.g., proper names), and addressing the cultural references specific to Hausa. The NER will be incorporated into Neural Machine Translation (NMT) for the Hausa to English Translation.

Keywords: machine translation, natural language processing (NLP), named entity recognition (NER), neural machine translation (NMT)

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Authors: Jameela Ali Alkrimi, Abdul Rahim Ahmad, Azizah Suliman, Loay E. George

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Red blood cells (RBCs) are among the most commonly and intensively studied type of blood cells in cell biology. The lack of RBCs is a condition characterized by lower than normal hemoglobin level; this condition is referred to as 'anemia'. In this study, a software was developed to isolate RBCs by using a machine learning approach to classify anemic RBCs in microscopic images. Several features of RBCs were extracted using image processing algorithms, including principal component analysis (PCA). With the proposed method, RBCs were isolated in 34 second from an image containing 18 to 27 cells. We also proposed that PCA could be performed to increase the speed and efficiency of classification. Our classifier algorithm yielded accuracy rates of 100%, 99.99%, and 96.50% for K-nearest neighbor (K-NN) algorithm, support vector machine (SVM), and neural network ANN, respectively. Classification was evaluated in highly sensitivity, specificity, and kappa statistical parameters. In conclusion, the classification results were obtained for a short time period with more efficient when PCA was used.

Keywords: red blood cells, pre-processing image algorithms, classification algorithms, principal component analysis PCA, confusion matrix, kappa statistical parameters, ROC

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Authors: Rachid El Aidani, Phuong Nguyen-Tri, Toan Vu-Khanh

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The filter media in synthetic fibre is the most geotextile materials used in aerosol and drainage filtration, particularly for buildings soil reinforcement in civil engineering due to its appropriated properties and its low cost. However, the current understanding of the durability and stability of this material in real service conditions, especially under severe long-term conditions are completely limited. This study has examined the effects of the chemical aging of a filter media in polyester nonwoven under different temperatures (50, 70 and 80˚C) and pH (2. 7 and 12). The effect of aging conditions on mechanical properties, morphology, permeability, thermal stability and molar weigh changes is investigated. The results showed a significant reduction of mechanical properties in term of tensile strength, puncture force and tearing forces of the filter media after chemical aging due to the chemical degradation. The molar mass and mechanical properties changes in different temperature and pH showed a complex dependence of material properties on environmental conditions. The SEM and AFM characterizations showed a significant impact of the thermal aging on the morphological properties of the fibres. Based on the obtained results, the lifetime of the material in different temperatures was determined by the use of the Arrhenius model. These results provide useful information to better understand phenomena occurring during chemical aging of the filter media and may help to predict the service lifetime of this material in real used conditions.

Keywords: nonwoven membrane, chemical aging, mechanical properties, lifetime, filter media

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Authors: Ebasa Girma, Nathnael Minyelshowa, Lebsework Negash

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The use of unmanned aerial vehicles (UAVs) in precision agriculture has seen a huge increase recently. As such, systems that aim to apply various algorithms on the field need a structured framework of abstractions. This paper defines the various tasks of the UAVs in precision agriculture and models them into an architectural framework. The presented architecture is built on the context that there will be minimal physical intervention to do the tasks defined with multiple coordinated and cooperative UAVs. Various tasks such as image processing, path planning, communication, data acquisition, and field mapping are employed in the architecture to provide an efficient system. Besides, different limitation for applying Multi-UAVs in precision agriculture has been considered in designing the architecture. The architecture provides an autonomous end-to-end solution, starting from mission planning, data acquisition, and image processing framework that is highly efficient and can enable farmers to comprehensively deploy UAVs onto their lands. Simulation and field tests show that the architecture offers a number of advantages that include fault-tolerance, robustness, developer, and user-friendliness.

Keywords: deep learning, multi-UAVs, precision agriculture, UAVs architecture

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Authors: Sukrita Mukherjee, Anindita Chaudhuri

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Soft skills are a crucial aspect for employees, and these skills are not confined to any particular field rather, it guarantees further career growth and job opportunities for employees who are seeking growth. Soft skills are also regarded as personality-specific skills that are observable and are qualitative in nature, which determines an employee’s strengths as a leader. When an employee intends to hold his job, then the person must make effective use of his personal resources, that, in turn, impacts his employability in a positive manner. An employee at his workplace is expected to make effective use of his personal resources. The resources that are to be used by the employee are generally of two types. First type of resources are occupation related, which is related with the educational background of the employee, and the second type of resources are the psychological resources of the employee, such as self-knowledge, career orientation awareness, sense of purpose and emotional literacy, that are considered crucial for an employee in his workplace. The present study is a qualitative study which includes 10 individuals working in IT Sector and Service Industry, respectively. For IT sector, graduate people are considered, and for the Service Industry, individuals who have done a Professional course in order to get into the industry are considered. The emerging themes from the findings after thematic analysis reveal that different aspect of Soft skills such as communication, decision making, constant learning, keeping oneself updated with the latest technological advancement, emotional intelligence are some of the important factors that helps an employee not only to sustain his job, but also grow in his workplace.

Keywords: employabiliy, soft skils, employees, resources, workplace

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Authors: Farnoosh Faal

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Institutional and organizational change in social housing organizations can have a significant impact on both the organizations themselves and their stakeholders. This paper provides an overview of the impact of institutional and organizational change on social housing organizations and their stakeholders, including tenants, employees, and other community members. The paper examines the different types of institutional and organizational change that can occur in social housing organizations, such as changes in management structure, funding models, and service delivery methods. It also explores the potential benefits and drawbacks of these changes, including changes in efficiency, service quality, and tenant satisfaction. The paper further discusses the impact of institutional and organizational change on social housing organization stakeholders, including the effects on employee morale, tenant engagement, and community relationships. The paper highlights the importance of effective stakeholder engagement and communication in ensuring a smooth transition to new organizational models and systems. Finally, the paper discusses the challenges and opportunities presented by institutional and organizational change in social housing organizations and provides recommendations for organizations looking to navigate these changes successfully. These recommendations include prioritizing stakeholder engagement, investing in staff training and development, and maintaining a focus on the needs and priorities of tenants and communities. Overall, this paper emphasizes the importance of considering the impact of institutional and organizational change on social housing organizations and their stakeholders and highlights strategies for managing these changes in a way that maximizes benefits and minimizes negative impacts.

Keywords: social housing organizations, stakeholder engagement, institutional change, challenges, opportunities

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Authors: Malik Muhammad Arslan, Muneeb Ullah, Dai Shihan, Faizan Khan, Xiaodong Yang

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Internet Service Providers are driving endless demands for higher bandwidth and data throughput as new services and applications require higher bandwidth. Users want immediate and accurate data delivery. This article focuses on converting old conventional networks into passive optical networks based on time division and wavelength division multiplexing. The main focus of this research is to use a hybrid of time-division multiplexing and wavelength-division multiplexing to improve network efficiency and performance. In this paper, we design an 80 Gbps Passive Optical Network (PON), which meets the need of the Next Generation PON Stage 2 (NGPON2) proposed in this paper. The hybrid of the Time and Wavelength division multiplexing (TWDM) is said to be the best solution for the implementation of NGPON2, according to Full-Service Access Network (FSAN). To co-exist with or replace the current PON technologies, many wavelengths of the TWDM can be implemented simultaneously. By utilizing 8 pairs of wavelengths that are multiplexed and then transmitted over optical fiber for 40 Kms and on the receiving side, they are distributed among 256 users, which shows that the solution is reliable for implementation with an acceptable data rate. From the results, it can be concluded that the overall performance, Quality Factor, and bandwidth of the network are increased, and the Bit Error rate is minimized by the integration of this approach.

Keywords: bit error rate, fiber to the home, passive optical network, time and wavelength division multiplexing

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Authors: Piyush Sharma, Devi Prasad Sharma, Sulabh Bansal

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Diseases are fairly common in fruits and vegetables because of the changing climatic and environmental circumstances. Crop diseases, which are frequently difficult to control, interfere with the growth and output of the crops. Accurate disease detection and timely disease control measures are required to guarantee high production standards and good quality. In India, apples are a common crop that may be afflicted by a variety of diseases on the fruit, stem, and leaves. It is fungi, bacteria, and viruses that trigger the early symptoms of leaf diseases. In order to assist farmers and take the appropriate action, it is important to develop an automated system that can be used to detect the type of illnesses. Machine learning-based image processing can be used to: this research suggested a system that can automatically identify diseases in apple fruit and apple plants. Hence, this research utilizes the hybrid SVM-RBN model. As a consequence, the model may produce results that are more effective in terms of accuracy, precision, recall, and F1 Score, with respective values of 96%, 99%, 94%, and 93%.

Keywords: fruit plant disease, crop disease, machine learning, image processing, SVM-RBN

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Authors: Ricardo Paiva, Rui Soares, Felix Harnau, Bruno Fragoso

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Nickel-based alloys are materials well suited for service in extreme environments subjected to pressure and heat. Some industrial applications for Nickel-based alloys are aerospace and jet engines, oil and gas extraction, pollution control and waste processing, automotive and marine industry. It is generally recognized that grain refinement is an effective methodology to improve the quality of casted parts. Conventional grain refinement techniques involve the addition of inoculation substances, the control of solidification conditions, or thermomechanical treatment with recrystallization. However, such methods often lead to non-uniform grain size distribution and the formation of hard phases, which are detrimental to both wear performance and biocompatibility. Stirring of the melt by electromagnetic fields has been widely used in continuous castings with success for grain refinement, solute redistribution, and surface quality improvement. Despite the advantages, much attention has not been paid yet to the use of this approach on functional castings such as investment casting. Furthermore, the effect of electromagnetic stirring (EMS) fields on Nickel-based alloys is not known. In line with the gaps/needs of the state-of-art, the present research work targets to promote new advances in controlling grain size and morphology of investment cast Nickel based alloys. For such a purpose, a set of experimental tests was conducted. A high-frequency induction furnace with vacuum and controlled atmosphere was used to cast the Inconel 718 alloy in ceramic shells. A coil surrounded the casting chamber in order to induce electromagnetic stirring during solidification. Aiming to assess the effect of the electromagnetic stirring on Ni alloys, the samples were subjected to microstructural analysis and mechanical tests. The results show that electromagnetic stirring can be an effective methodology to modify the grain size and mechanical properties of investment-cast parts.

Keywords: investment casting, grain refinement, electromagnetic stirring, nickel alloys

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Authors: Qian Zaijian

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E-government is one of the hot issues in the current academic research of public policy and management. As the organic integration of information and communication technology (ICT) and public administration, e-government is one of the most important areas in contemporary information society. Policy information system is a basic subsystem of public policy system, its operation affects the overall effect of the policy process or even exerts a direct impact on the operation of a public policy and its success or failure. The basic principle of its operation is information collection, processing, analysis and release for a specific purpose. The function of E-government for public policy information system lies in the promotion of public access to the policy information resources, information transmission through e-participation, e-consultation in the process of policy analysis and processing of information and electronic services in policy information stored, to promote the optimization of policy information systems. However, due to many factors, the function of e-government to promote policy information system optimization has its practical limits. In the building of E-government in our country, we should take such path as adhering to the principle of freedom of information, eliminating the information divide (gap), expanding e-consultation, breaking down information silos and other major path, so as to promote the optimization of public policy information systems.

Keywords: China, e-consultation, e-democracy, e-government, e-participation, ICTs, public policy information systems

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Authors: Yusuke Katayama, Tetsuhisa Kitamura, Kosuke Kiyohara, Sumito Hayashida, Taku Iwami, Takashi Kawamura, Takeshi Shimazu

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Background: Recently, the number of ambulance dispatches has been increasing in Japan and it is, therefore, difficult to accept emergency patients to hospitals smoothly and appropriately because of the limited hospital capacity. To facilitate the request for patient transport by ambulances and hospital acceptance, the emergency information system using information technology has been built up and introduced in various communities. However, its effectiveness has not been insufficiently revealed in Japan. In 2013, we developed a smartphone application system that enables the emergency-medical-service (EMS) personnel to share information about on-scene ambulance and hospital situation. The aim of this study was to assess the introduction effect of this application for EMS system in Osaka City, Japan. Methods: This study was a retrospective study with population-based ambulance records of Osaka Municipal Fire Department. This study period was six years from January 1, 2010 to December 31, 2015. In this study, we enrolled emergency patients that on-scene EMS personnel conducted the hospital selection for them. The main endpoint was difficulty in hospital acceptance at the scene. The definition of difficulty in hospital acceptance at the scene was to make >=5 phone calls by EMS personnel at the scene to each hospital until a decision to transport was determined. The definition of the smartphone application group was emergency patients transported in the period of 2013-2015 after the introduction of this application, and we assessed the introduction effect of smartphone application with multivariable logistic regression model. Results: A total of 600,526 emergency patients for whom EMS personnel selected hospitals were eligible for our analysis. There were 300,131 smartphone application group (50.0%) in 2010-2012 and 300,395 non-smartphone application group (50.0%) in 2013-2015. The proportion of the difficulty in hospital acceptance was 14.2% (42,585/300,131) in the smartphone application group and 10.9% (32,819/300,395) in the non-smartphone application group, and the difficulty in hospital acceptance significantly decreased by the introduction of the smartphone application (adjusted odds ration; 0.730, 95% confidence interval; 0.718-0.741, P<0.001). Conclusions: Sharing information between ambulance and hospital by introducing smartphone application at the scene was associated with decreasing the difficulty in hospital acceptance. Our findings may be considerable useful for developing emergency medical information system with using IT in other areas of the world.

Keywords: difficulty in hospital acceptance, emergency medical service, infomation technology, smartphone application

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Authors: Toshitaka Higashino, Naoki Wakamiya

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Human beings perform a task by perceiving information from outside, recognizing them, and responding them. There have been various attempts to analyze and understand internal processes behind the reaction to a given stimulus by conducting psychological experiments and analysis from multiple perspectives. Among these, we focused on Model Human Processor (MHP). However, it was built based on psychological experiments and thus the relation with brain activity was unclear so far. To verify the validity of the MHP and propose our model from a viewpoint of neuroscience, EEG (Electroencephalography) measurements are performed during experiments in this study. More specifically, first, experiments were conducted where Latin alphabet characters were used as visual stimuli. In addition to response time, ERPs (event-related potentials) such as N100 and P300 were measured by using EEG. By comparing cycle time predicted by the MHP and latency of ERPs, it was found that N100, related to perception of stimuli, appeared at the end of the perceptual processor. Furthermore, by conducting an additional experiment, it was revealed that P300, related to decision making, appeared during the response decision process, not at the end. Second, by experiments using Japanese Hiragana characters, i.e. Japan's own phonetic symbols, those findings were confirmed. Finally, Japanese Kanji characters were used as more complicated visual stimuli. A Kanji character usually has several readings and several meanings. Despite the difference, a reading-related task and a meaning-related task exhibited similar results, meaning that they involved similar information processing processes of the brain. Based on those results, our model was proposed which reflects response time and ERP latency. It consists of three processors: the perception processor from an input of a stimulus to appearance of N100, the cognitive processor from N100 to P300, and the decision-action processor from P300 to response. Using our model, an application system which reflects brain activity can be established.

Keywords: brain activity, EEG, information processing model, model human processor

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Authors: Nguyen Ngoc Que Tran

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Purpose: The purpose of this paper is to investigate the relationship between internal market orientation, external market orientation, employee commitment and job satisfaction. Design/methodology/approach: This study collected data through a survey and utilized simple linear regression and multiple regression analysis to determine if there was any support for the research hypotheses as presented in the previous chapter. Findings: Using data from 256 employees of four leading joint stock banks in Vietnam, the empirical results indicates that employee commitment is positively related with external market orientation, job satisfaction is positively related to employee commitment, and employee commitment and job satisfaction are positively related to external market orientation. However, job satisfaction has no significant positive effect on external market orientation. Theoretical contribution: The primary contribution to marketing theory arising from this study is the integration of job satisfaction, employee commitment, and external market orientation in a single research model. Practical implications: The major contribution to practice is an external market oriented bank has to respond rapidly to the future needs and preferences of its customers. This could result in high levels of commitment to the service process and in doing so provide Vietnamese joint-stock commercial banks with a competitive advantage. The finding is important for the banking service sector in general and the Vietnamese banking industry in particular.

Keywords: employee commitment, job satisfaction and external market orientation, vietnam, bank

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Authors: Ipek Goktepe, Israa Elnemr, Hammad Asim, Hao Feng, Mosbah Kushad, Hee Park, Sheikha Alzeyara, Mohammad Alhajri

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Food safety management in Qatar is under the shared oversight of multiple agencies in two government ministries (Ministry of Public Health and Ministry of Municipality and Environment). Despite the increasing number and diversity of the food service establishments, no systematic food surveillance system is in place in the country, which creates a gap in terms of determining the food safety attitudes and practices applied in the food service operations. Therefore, this study seeks to partially address this gap through determination of food safety knowledge among food handlers, specifically with respect to food preparation and handling practices, and sanitation methods applied in food service providers (FSPs) and a major market in Doha, Qatar. The study covered a sample of 53 FSPs randomly selected out of 200 FSPs. Face-to-face interviews with managers at participating FSPs were conducted using a 40-questions survey. Additionally, 120 produce handlers who are in direct contact with fresh produce at the major produce market in Doha were surveyed using a questionnaire containing 21 questions. A written informed consent was obtained from each survey participant. The survey data were analyzed using the chi-square test and correlation test. The significance was evaluated at p ˂ 0.05. The results from the FSPs surveys indicated that the average age of FSPs was 11 years, with the oldest and newest being established in 1982 and 2015, respectively. Most managers (66%) had college degree and 68% of them were trained on the food safety management system known as HACCP. These surveys revealed that FSP managers’ training and education level were highly correlated with the probability of their employees receiving food safety training while managers with lower education level had no formal training on food safety for themselves nor for their employees. Casual sit-in and fine dine-in restaurants consistently kept records (100%), followed by fast food (36%), and catering establishments (14%). The produce handlers’ survey results showed that none of the workers had any training on safe produce handling practices. The majority of the workers were in the age range of 31-40 years (37%) and only 38% of them had high-school degree. Over 64% of produce handlers claimed to wash their hands 4-5 times per day but field observations pointed limited handwashing as there was soap in the settings. This observation suggests potential food safety risks since a significant correlation (p ˂ 0.01) between the educational level and the hand-washing practices was determined. This assessment on food safety culture through determination of food and produce handlers' level of knowledge and practices, the first of its kind in Qatar, demonstrated that training and education are important factors which directly impact the food safety culture in FSPs and produce markets. These findings should help in identifying the need for on-site training of food handlers for effective food safety practices in food establishments in Qatar.

Keywords: food safety, food safety culture, food service providers, food handlers

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Authors: Chuan-Ming Tung, Tzu-Chiao Yuan

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This research aims to construct the supply indicators and weights of shelter space from a perspective of the needs of the elderly by virtue of literature review, a systematical compilation of related regulations, and the use of the Analytical Hierarchy Process method, the questionnaires regarding the indicators filled out by 16 experts and scholars. The researcher then used 3 schools and 2 activity centers in Banqiao District, New Taipei City, as study cases to evaluate the ‘friendliness’ degree/level for the supply of shelters meeting the needs of elderly people. The supply evaluation indicators of friendly shelters meeting the needs of the elderly include "Administrative Operations and Service Needs" and "Residence-related and Living Needs"; under the "Administrative Operations and Service Needs" are "Management Operations and Information Provision", "Shelter Space Preparedness and Logistics Support", "Medical Care and Social Support", and "Shelters and Medical Environment", a total of 17 assessment items in four indicators, while under the "Residence-related and Living Needs" are "Dietary Needs", "Sleep Needs", "Hygiene and Sanitation Needs", "Accessibility and Convenience Needs ", etc., a total of 18 assessment items in four indicators. The results show that "Residence-related and Living Needs" is the most important item in the main levels of the supply indicators of the needs for friendly shelters to elderly people (weigh value 0.5504), followed by "Administrative Operations and Service Needs" (0.4496). The order of importance of the supply indicators of friendly shelters for the needs of elderly people is as follows: "Hygiene and Sanitation Needs" (0.1721), "Dietary Needs" (0.1340), "Medical Care and Social Support" (0.1300), "Sleep Needs" (0.1277), "Accessibility and Convenience Needs" (0.1166), "Basic Environment of Shelters" (0.1145), "Shelter Space Preparedness and Logistics Support" (0.1115) and "Management Operations and Information Provision" (0.0936). In addition, it can be noticed from the results of the case evaluation that the provision of refuges and shelters, mainly from schools and activity centers, is extremely inadequate for the needs of the elderly. In a set of comprehensive comparisons and contrasts, the evaluation indicators of refuges and shelters that need to be improved are "Medical Care and Social Support", "Hygiene and Sanitation Needs", "Sleep Needs", "Dietary Needs", and "Shelter Space Preparedness and Logistics Support".

Keywords: needs of the elderly people, urban shelters, evaluation indicators/indices., taiwan

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Authors: Dawei Cai, Yuya Tokuda

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The market of localization based service (LBS) is expanding. The acquisition of physical location is the fundamental basis for LBS. GPS, the de facto standard for outdoor localization, does not work well in indoor environment due to the blocking of signals by walls and ceiling. To acquire high accurate localization in an indoor environment, many techniques have been developed. Triangulation approach is often used for identifying the location, but a heavy and complex computation is necessary to calculate the location of the distances between the object and several source points. This computation is also time and power consumption, and not favorable to a mobile device that needs a long action life with battery. To provide a low power consumption approach for a mobile device, this paper presents a fast calculation approach to identify the location of the object without online solving solutions to simultaneous quadratic equations. In our approach, we divide the location identification into two parts, one is offline, and other is online. In offline mode, we make a mapping process that maps the location area to distance space and find a simple formula that can be used to identify the location of the object online with very light computation. The characteristic of the approach is a good tradeoff between the accuracy and computational amount. Therefore, this approach can be used in smartphone and other mobile devices that need a long work time. To show the performance, some simulation experimental results are provided also in the paper.

Keywords: indoor localization, location based service, triangulation, fast calculation, mobile device

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Authors: Akash Verma, Sujit Kumar Samanta

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This study examines a discrete-time Geo/G/1 queueing-inventory system attached with (s, Q) inventory policy. Assume that the customers follow the Bernoulli process on arrival. Each customer demands a single item with arbitrarily distributed service time. The inventory is replenished by an outside supplier, and the lead time for the replenishment is determined by a geometric distribution. There is a single server and infinite waiting space in this facility. Demands must wait in the specified waiting area during a stock-out period. The customers are served on a first-come-first-served basis. With the help of the embedded Markov chain technique, we determine the joint probability distributions of the number of customers in the system and the number of items in stock at the post-departure epoch using the Matrix Analytic approach. We relate the system length distribution at post-departure and outside observer's epochs to determine the joint probability distribution at the outside observer's epoch. We use probability distributions at random epochs to determine the waiting time distribution. We obtain the performance measures to construct the cost function. The optimum values of the order quantity and reordering point are found numerically for the variety of model parameters.

Keywords: discrete-time queueing inventory model, matrix analytic method, waiting-time analysis, cost optimization

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Authors: Kayla Murray, Andrew Green, Gopi Paliyath, Keith Warriner

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Introduction: It is now acknowledged that control of human pathogens associated with fresh produce requires an integrated approach of several interventions as opposed to relying on post-harvest washes to remove field acquired contamination. To this end, current research is directed towards identifying such interventions that can be applied at different points in leafy green processing. Purpose: In the following the efficacy of different gas phase treatments to decontaminate whole lettuce heads during pre-processing storage were evaluated. Methods: Whole Cos lettuce heads were spot inoculated with L. monocytogenes, E. coli O157:H7 or Salmonella spp. The inoculated lettuce heads were then placed in a treatment chamber and exposed to ozone, chlorine dioxide or hydroxyl radicals at different time periods under a range of relative humidity. Survivors of the treatments were enumerated along with sensory analysis performed on the treated lettuce. Results: Ozone gas reduced L. monocytogenes by 2-log10 after ten-minutes of exposure with Salmonella and E. coli O157:H7 being decreased by 0.66 and 0.56-log cfu respectively. Chlorine dioxide gas treatment reduced L. monocytogenes and Salmonella on lettuce heads by 4 log cfu but only supported a 0.8 log cfu reduction in E. coli O157:H7 numbers. In comparison, hydroxyl radicals supported a 2.9 – 4.8 log cfu reduction of model human pathogens inoculated onto lettuce heads but required extended exposure times and relative humidity < 0.8. Significance: From the gas phase sanitizers tested, chlorine dioxide and hydroxyl radicals are the most effective. The latter process holds most promise based on the ease of delivery, worker safety and preservation of lettuce sensory characteristics. Although expose times for hydroxyl radicles was relatively long (24h) this should not be considered a limitation given the intervention is applied in store rooms or in transport containers during transit.

Keywords: gas phase sanitizers, iceberg lettuce heads, leafy green processing

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Authors: Aishwarya Rai

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This study explores the transformative influence of generative AI on startups, businesses, and industries. We will explore how large businesses can benefit in the area of customer operations, where AI-powered chatbots can improve self-service and agent effectiveness, greatly increasing efficiency. In marketing and sales, generative AI could transform businesses by automating content development, data utilization, and personalization, resulting in a substantial increase in marketing and sales productivity. In software engineering-focused startups, generative AI can streamline activities, significantly impacting coding processes and work experiences. It can be extremely useful in product R&D for market analysis, virtual design, simulations, and test preparation, altering old workflows and increasing efficiency. Zooming into the retail and CPG industry, industry findings suggest a 1-2% increase in annual revenues, equating to $400 billion to $660 billion. By automating customer service, marketing, sales, and supply chain management, generative AI can streamline operations, optimizing personalized offerings and presenting itself as a disruptive force. While celebrating economic potential, we acknowledge challenges like external inference and adversarial attacks. Human involvement remains crucial for quality control and security in the era of generative AI-driven transformative innovation. This talk provides a comprehensive exploration of generative AI's pivotal role in reshaping businesses, recognizing its strategic impact on customer interactions, productivity, and operational efficiency.

Keywords: generative AI, digital transformation, LLM, artificial intelligence, startups, businesses

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Authors: Okanta Andrew, Richmond Kweku Frempong

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As mobile networks are upgraded with technologies like WAP, GPRS and UMTS to deliver next-generation multimedia services, so are the banks and other financial institutions also getting ready to unleash the financial products on the mobile platform to meet growing demand for mobile based application services. Hence, the onset of Unstructured Supplementary Services (USSD) Banking which would make banking services available at anywhere, anytime through a string of interactive SMS sessions between a mobile device and an application server of a service provider. The aim of this studies was to find out whether the public will accept the sim banking service when it is implemented. Our target group includes: Working class. E. g. Businessmen/women, office workers, fishermen, market women, teachers etc. Nonworking class. E. g. Students (Tertiary, Senior High School), housewives. etc. The survey was in the form of a questionnaire and a verbal interview (video) which was to investigate their idea about the current banking system and the yet to be introduced sim banking concept. Meanwhile, some challenges accompanied the progression of data gathering because some populace showed reluctance in freeing their information. One other suggestion was that government should put measures against foremost challenges obstructing sim banking in Ghana counter to computers hackers. Government and individual have a key role to undertake to give suitable support to facelift the sim banking industry in the country. It was also suggested that Government put strong regulations on the use of sim banking products and services to streamline all the activities and also create awareness of the need for sim banking and emphasize its relevance in the aspect of national GDP.

Keywords: banking, mobile banking, SIM banking, mobile banking in Ghana

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Authors: S. Jigna, K. Nanda Kumar, T. Anna

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Being a major contributor to the Indian economy and a critical facilitator for the country’s digital India vision, the Indian telecommunications industry is also a major source of employment for the country. Since the last few years, the Indian telecommunication service providers (TSPs), however, are facing business challenges related to increasing competition, losses, debts, and decreasing revenue. The strategic use of digital technologies for a successful digital transformation has the potential to equip organizations to meet these business challenges. Despite an increased focus on digital transformation, the telecom service providers globally, including Indian TSPs, have seen limited success so far. The purpose of this research was thus to identify the factors that are critical for the digital transformation and to what extent they influence the successful digital transformation of the Indian TSPs. The literature review of more than 300 digital transformation-related articles, mostly from 2013-2019, demonstrated a lack of an empirical model consisting of factors for the successful digital transformation of the TSPs. This study theorizes a research framework grounded in multiple theories, and a research model consisting of 7 constructs that may be influencing business success during the digital transformation of the organization was proposed. The questionnaire survey of senior managers in the Indian telecommunications industry was seeking to validate the research model. Based on 294 survey responses, the validation of the Structural equation model using the statistical tool ADANCO 2.1.1 was found to be robust. Results indicate that Digital Capabilities, Digital Strategy, and Corporate Level Data Strategy in that order has a strong influence on the successful Business Performance, followed by IT Function Transformation, Digital Innovation, and Transformation Management respectively. Even though Digital Organization did not have a direct significance on Business Performance outcomes, it had a strong influence on IT Function Transformation, thus affecting the Business Performance outcomes indirectly. Amongst numerous practical and theoretical contributions of the study, the main contribution for the Indian TSPs is a validated reference for prioritizing the transformation initiatives in their strategic roadmap. Also, the main contribution to the theory is the possibility to use the research framework artifact of the present research for quantitative validation in different industries and geographies.

Keywords: corporate level data strategy, digital capabilities, digital innovation, digital strategy

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Authors: Maryam Heidari, James H. Jones Jr.

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Millions of online posts about different topics and products are shared on popular social media platforms. One use of this content is to provide crowd-sourced information about a specific topic, event or product. However, this use raises an important question: what percentage of information available through these services is trustworthy? In particular, might some of this information be generated by a machine, i.e., a bot, instead of a human? Bots can be, and often are, purposely designed to generate enough volume to skew an apparent trend or position on a topic, yet the consumer of such content cannot easily distinguish a bot post from a human post. In this paper, we introduce a model for social media bot detection which uses Bidirectional Encoder Representations from Transformers (Google Bert) for sentiment classification of tweets to identify topic-independent features. Our use of a Natural Language Processing approach to derive topic-independent features for our new bot detection model distinguishes this work from previous bot detection models. We achieve 94\% accuracy classifying the contents of data as generated by a bot or a human, where the most accurate prior work achieved accuracy of 92\%.

Keywords: bot detection, natural language processing, neural network, social media

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Authors: Carolina Silva Ansélmo

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Airports are demand-generating poles that affect the flow of traffic around them. The airport access system must be fast, convenient, and adequately planned, considering its potential users. An airport with good ground access conditions can provide the user with a more satisfactory access experience. When several transport options are available, service providers must understand users' preferences and the expected quality of service. The present study focuses on airport access in a comparative scenario between bus, private vehicle, subway, taxi and urban mobility transport applications to São Paulo/Guarulhos International Airport. The objectives are (i) to identify the factors that influence the choice, (ii) to measure Willingness to Pay (WTP), and (iii) to estimate the market share for each modal. The applied method was Adaptive Choice-based Conjoint Analysis (ACBC) technique using Sawtooth Software. Conjoint analysis, rooted in Utility Theory, is a survey technique that quantifies the customer's perceived utility when choosing alternatives. Assessing user preferences provides insights into their priorities for product or service attributes. An additional advantage of conjoint analysis is its requirement for a smaller sample size compared to other methods. Furthermore, ACBC provides valuable insights into consumers' preferences, willingness to pay, and market dynamics, aiding strategic decision-making to provide a better customer experience, pricing, and market segmentation. In the present research, the ACBC questionnaire had the following variables: (i) access time to the boarding point, (ii) comfort in the vehicle, (iii) number of travelers together, (iv) price, (v) supply power, and (vi) type of vehicle. The case study questionnaire reached 213 valid responses considering the scenario of access from the São Paulo city center to São Paulo/Guarulhos International Airport. As a result, the price and the number of travelers are the most relevant attributes for the sample when choosing airport access. The market share of the selection is mainly urban mobility transport applications, followed by buses, private vehicles, taxis and subways.

Keywords: adaptive choice-based conjoint analysis, ground access to airport, market share, willingness to pay

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Authors: Reza Moslemi, Sebastien Perrier

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Water infrastructure deterioration can result in increased operational costs owing to increased repair needs and non-revenue water and consequently cause a reduced level of service and customer service satisfaction. Various water main condition assessment technologies have been introduced to the market in order to evaluate the level of pipe deterioration and to develop appropriate asset management and pipe renewal plans. One of the challenges for any condition assessment and inspection program is to determine the percentage of the water network and the combination of pipe segments to be inspected in order to obtain a meaningful representation of the status of the entire water network with a desirable level of accuracy. Traditionally, condition assessment has been conducted by selecting pipes based on age or location. However, this may not necessarily offer the best approach, and it is believed that by using a smart sampling methodology, a better and more reliable estimate of the condition of a water network can be achieved. This research investigates three different sampling methodologies, including random, stratified, and systematic. It is demonstrated that selecting pipes based on the proposed clustering and sampling scheme can considerably improve the ability of the inspected subset to represent the condition of a wider network. With a smart sampling methodology, a smaller data sample can provide the same insight as a larger sample. This methodology offers increased efficiency and cost savings for condition assessment processes and projects.

Keywords: condition assessment, pipe degradation, sampling, water main

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Authors: Comfort Mokgothu

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This study investigated the relation between processing information and fitness level of active (fit) and sedentary (unfit) children drawn from rural and urban areas in Botswana. It was hypothesized that fit children would display faster simple reaction time (SRT), choice reaction times (CRT) and movement times (SMT). 60, third grade children (7.0 – 9.0 years) were initially selected and based upon fitness testing, 45 participated in the study (15 each of fit urban, unfit urban, fit rural). All children completed anthropometric measures, skinfold testing and submaximal cycle ergometer testing. The cognitive testing included SRT, CRT, SMT and Choice Movement Time (CMT) and memory sequence length. Results indicated that the rural fit group exhibited faster SMT than the urban fit and unfit groups. For CRT, both fit groups were faster than the unfit group. Collectively, the study shows that the relationship that exists between physical fitness and cognitive function amongst the elderly can tentatively be extended to the pediatric population. Physical fitness could be a factor in the speed at which we process information, including decision making, even in children.

Keywords: decision making, fitness, information processing, reaction time, cognition movement time

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Authors: Hao Mi, Ming Yang, Tian-yue Yang

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Ultrasonic infrared nondestructive testing is a kind of testing method with high speed, accuracy and localization. However, there are still some problems, such as the detection requires manual real-time field judgment, the methods of result storage and viewing are still primitive. An intelligent non-destructive detection system based on embedded linux is put forward in this paper. The hardware part of the detection system is based on the ARM (Advanced Reduced Instruction Set Computer Machine) core and an embedded linux system is built to realize image processing and defect detection of thermal images. The CLAHE algorithm and the Butterworth filter are used to process the thermal image, and then the boa server and CGI (Common Gateway Interface) technology are used to transmit the test results to the display terminal through the network for real-time monitoring and remote monitoring. The system also liberates labor and eliminates the obstacle of manual judgment. According to the experiment result, the system provides a convenient and quick solution for industrial non-destructive testing.

Keywords: remote monitoring, non-destructive testing, embedded Linux system, image processing

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Authors: Daniel Gonzales, Zev Winkelman, Trung Tran, Ricardo Sanchez, Dulani Woods, John Hollywood

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We have developed a distributed computing capability, Digital Forensics Compute Cluster (DFORC2) to speed up the ingestion and processing of digital evidence that is resident on computer hard drives. DFORC2 parallelizes evidence ingestion and file processing steps. It can be run on a standalone computer cluster or in the Amazon Web Services (AWS) cloud. When running in a virtualized computing environment, its cluster resources can be dynamically scaled up or down using Kubernetes. DFORC2 is an open source project that uses Autopsy, Apache Spark and Kafka, and other open source software packages. It extends the proven open source digital forensics capabilities of Autopsy to compute clusters and cloud architectures, so digital forensics tasks can be accomplished efficiently by a scalable array of cluster compute nodes. In this paper, we describe DFORC2 and compare it with a standalone version of Autopsy when both are used to process evidence from hard drives of different sizes.

Keywords: digital forensics, cloud computing, cyber security, spark, Kubernetes, Kafka

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Authors: Shayan Rezvanigilkolaei, Shayesteh Vefaghnematollahi

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Electrical impedance tomography is a non-invasive medical imaging technique suitable for medical applications. This paper describes an electrical impedance tomography device with the ability to navigate a robotic arm to manipulate a target object. The design of the device includes various hardware and software sections to perform medical imaging and control the robotic arm. In its hardware section an image is formed by 16 electrodes which are located around a container. This image is used to navigate a 3DOF robotic arm to reach the exact location of the target object. The data set to form the impedance imaging is obtained by having repeated current injections and voltage measurements between all electrode pairs. After performing the necessary calculations to obtain the impedance, information is transmitted to the computer. This data is fed and then executed in MATLAB which is interfaced with EIDORS (Electrical Impedance Tomography Reconstruction Software) to reconstruct the image based on the acquired data. In the next step, the coordinates of the center of the target object are calculated by image processing toolbox of MATLAB (IPT). Finally, these coordinates are used to calculate the angles of each joint of the robotic arm. The robotic arm moves to the desired tissue with the user command.

Keywords: electrical impedance tomography, EIT, surgeon robot, image processing of electrical impedance tomography

Procedia PDF Downloads 272