Search results for: identification of risks

Authors: Eric Bonetto, Anthony Piermatteo, Fabien Girandola, Gregory Lo Monaco

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The present contribution focuses on the effect of the structure of social representations on group identification. A social representation (SR) is defined as an organized and structured set of cognitions, produced and shared by members of a same group about a same social object. Within this framework, the central core theory establishes a structural distinction between central cognitions – or 'core' – and peripheral ones: the former are theoretically considered as more connected than the later to group members’ social identity and may play a greater role in SRs’ ability to allow group identification by means of a common vision of the object of representation. Indeed, the central core provides a reference point for the in-group as it constitutes a consensual vision that gives meaning to a social object particularly important to individuals and to the group. However, while numerous contributions clearly refer to the underlying role of SRs in group identification, there are only few empirical evidences of this aspect. Thus, we hypothesize an effect of the structure of SRs on group identification. More precisely, central cognitions (vs. peripheral ones) will lead to a stronger group identification. In addition, we hypothesize that the refutation of a cognition will lead to a stronger group identification than its activation. The SR mobilized here is that of 'studying' among a population of first-year undergraduate psychology students. Thus, a pretest (N = 82), using an Attribute-Challenge Technique, was designed in order to identify the central and the peripheral cognitions to use in the primings of our main study. The results of this pretest are in line with previous studies. Then, the main study (online; N = 184), using a social priming methodology, was based on a 2 (Structural status of the cognitions belonging to the prime: central vs. peripheral) x 2 (Type of prime: activation vs. refutation) experimental design in order to test our hypotheses. Results revealed, as expected, the main effect of the structure of the SR on group identification. Indeed, central cognitions trigger a higher level of identification than the peripheral ones. However, we observe neither effect of the type of prime, nor interaction effect. These results experimentally demonstrate for the first time the effect of the structure of SRs on group identification and indicate that central cognitions are more connected than peripheral ones to group members’ social identity. These results will be discussed considering the importance of understanding identity as a function of SRs and on their ability to potentially solve the lack of consideration of the definition of the group in Social Representations Theory.

Keywords: group identification, social identity, social representations, structural approach

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Authors: A. Ballard

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The ability to track goods and products en route in the delivery system, in the warehouse, and on the top floor is a huge advantage to shippers and retailers. Recently the emergence of radio frequency identification (RFID) technology has enabled this better than ever before. However, a significant problem exists in that RFID technology depends on the quality of the information stored for each tagged product. Because of the profusion of names for colours, it is very difficult to ascertain that stored values are recognised by all users who view the product visually. This paper reports the findings of a study in which 50 consumers and 50 logistics workers were shown colour swatches and asked to choose the name of the colour from a multiple choice list. They were then asked to match consumer products, including toasters, jumpers, and toothbrushes, with the identifying inventory information available for each one. The findings show that the ability to match colours was significantly stronger with the color swatches than with the consumer products and that while logistics professionals made more frequent correct identification than the consumers, their results were still unsatisfactorily low. Based on these findings, a proposed universal model of colour identification numbers has been developed.

Keywords: consumer preferences, supply chain logistics, radio frequency identification, RFID, colour preference

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Authors: Yangze Lan, Ruihua Xv, Feng Zhou, Yijia Shan, Longhao Zhang, Qinghui Xv

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Receiving and dispatching trains is an important part of railroad organization, and the risky evaluation of operating personnel is still reflected by scores, lacking further excavation of wrong answers and operating accidents. With natural language processing (NLP) technology, this study extracts the keywords and key phrases of 40 relevant risk events about receiving and dispatching trains and reclassifies the risk events into 8 categories, such as train approach and signal risks, dispatching command risks, and so on. Based on the historical risk data of personnel, the K-Means clustering method is used to classify the risk level of personnel. The result indicates that the high-risk operating personnel need to strengthen the training of train receiving and dispatching operations towards essential trains and abnormal situations.

Keywords: receiving and dispatching trains, natural language processing, risk evaluation, K-means clustering

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Authors: Ayman El Behiry, Rasha Nabil Zahran, Reda Tarabees, Eman Marzouk, Musaad Al-Dubaib

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Mastitis is one of the most economic disease affecting dairy cows worldwide. Its classic diagnosis using bacterial culture and biochemical findings is a difficult and prolonged method. In this research, using of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) permitted identification of different microorganisms with high accuracy and rapidity (only 24 hours for microbial growth and analysis). During the application of MALDI-TOF MS, one hundred twenty strains of Staphylococcus and Streptococcus species isolated from milk of cows affected by clinical and subclinical mastitis were identified, and the results were compared with those obtained by traditional methods as API and VITEK 2 Systems. 37 of totality 39 strains (~95%) of Staphylococcus aureus (S. aureus) were exactly detected by MALDI TOF MS and then confirmed by a nuc-based PCR technique, whereas accurate identification was observed in 100% (50 isolates) of the coagulase negative staphylococci (CNS) and Streptococcus agalactiae (31 isolates). In brief, our results demonstrated that MALDI-TOF MS is a fast and truthful technique which has the capability to replace conventional identification of several bacterial strains usually isolated in clinical laboratories of microbiology.

Keywords: identification, mastitis pathogens, mass spectral, phenotypical

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Authors: Mahalakshmi Vivekanandan S.

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As per the recent changes happening in the global policies, climate-related changes and the impact it causes across every sector are viewed as green swan events – in essence, climate-related changes can often happen and lead to risk and a lot of uncertainty, but needs to be mitigated instead of considering them as black swan events. This brings about a question on how this risk can be computed so that the financial institutions can plan to mitigate it. Climate-related changes impact all risk types – credit risk, market risk, operational risk, liquidity risk, reputational risk and other risk types. And the models required to compute this has to consider the different industrial needs of the counterparty, as well as the factors that are contributing to this – be it in the form of different risk drivers, or the different transmission channels or the different approaches and the granular form of data availability. This brings out the suggestion that the climate-related changes, though it affects Pillar I risks, will be a Pillar II risk. This has to be modeled specifically based on the financial institution’s actual exposure to different industries instead of generalizing the risk charge. And this will have to be considered as the additional capital to be met by the financial institution in addition to their Pillar I risks, as well as the existing Pillar II risks. In this paper, the author presents a risk assessment framework to model and assess climate change risks - for both credit and market risks. This framework helps in assessing the different scenarios and how the different transition risks affect the risk associated with the different parties. This research paper delves into the topic of the increase in the concentration of greenhouse gases that in turn cause global warming. It then considers the various scenarios of having the different risk drivers impacting the Credit and market risk of an institution by understanding the transmission channels and also considering the transition risk. The paper then focuses on the industry that’s fast seeing a disruption: the automobile industry. The paper uses the framework to show how the climate changes and the change to the relevant policies have impacted the entire financial institution. Appropriate statistical models for forecasting, anomaly detection and scenario modeling are built to demonstrate how the framework can be used by the relevant agencies to understand their financial risks. The paper also focuses on the climate risk calculation for the Pillar II Capital calculations and how it will make sense for the bank to maintain this in addition to their regular Pillar I and Pillar II capital.

Keywords: capital calculation, climate risk, credit risk, pillar ii risk, scenario modeling

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Authors: Mohamed Adnan Landolsi, Ali F. Almutairi

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The paper addresses the problem of line-of-sight (LOS) vs. non-line-of-sight (NLOS) propagation link identification in ultra-wideband (UWB) wireless networks, which is necessary for improving the accuracy of radiolocation and positioning applications. A LOS/NLOS likelihood hypothesis testing approach is applied based on exploiting distinctive statistical features of the channel impulse response (CIR) using parameters related to the “skewness” of the CIR and its root mean square (RMS) delay spread. A log-normal fit is presented for the probability densities of the CIR parameters. Simulation results show that different environments (residential, office, outdoor, etc.) have measurable differences in their CIR parameters’ statistics, which is then exploited in determining the nature of the propagation channels. Correct LOS/NLOS channel identification rates exceeding 90% are shown to be achievable for most types of environments. Additional improvement is also obtained by combining both CIR skewness and RMS delay statistics.

Keywords: UWB, propagation, LOS, NLOS, identification

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Authors: Feride Eskin Bacaksiz, Aytolan Yildirim

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Practices voluntarily performed by organizations for their employees well-being, create an emotional imperative for employees in accordance with reciprocity norm. Changes in desired course occur in organizational outputs and attitudes towards organization among employees perceiving their organizations as virtuous and supportive. The aim of this study was to examine the effect of organizational virtuousness on performance and organizational identification levels of employees and mediating role of perceived organizational support in this relationship. The data of this descriptive and methodological study were collected from 336 nurses working in a public university hospital in 2015. Participant information form, Organizational Virtuousness, Perceived Organizational Support, Organizational Identification, and Employee Performance scales were used to collect the data. Descriptive, correlative, psychometric analyses and Structural Equation Modeling were performed for the data analysis. Most of the participants were female, under 30 years of age, graduated degrees and staff nurse. Mean scores obtained by the participants from scales were calculated as 3.43(SD=.99) for organizational virtuousness, 2.99 (SD=1.16) for perceived organizational support, 3.18 (SD=1.03) for organizational identification and 3.84 (SD=0.66) for employee performance. It was found that correlation between organizational virtuousness and employee performance regressed from r=0.64 to r=-0.01 and correlation between organizational virtuousness and organizational identification regressed from r=0.55 to r=-0.16 and became statistically non-significant (p < 0.05) via mediating role of perceived organizational support. According to the results, perceived organizational support assumes full mediation on the impact of organizational virtues of employee performance and organizational identification levels. Therefore, organizations, which intend to positively affect employees attitudes towards organization and their performance, should both extend organizational virtuous activities and affect perceptions of employees; whereas, employees should perceive that they are supported by their organization.

Keywords: employee performance, organizational identification, organizational virtuousness, perceived organizational support

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Authors: Odey Moses Ogah, Felix Terhemba Ikyereve

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The study was carried out to analyzed risks in financing agriculture by agricultural cooperatives in Benue State, Nigeria. The study made use of research questionnaires for data collection. A multistage sampling technique was used to select a sample of 210 respondents from 21 agricultural cooperatives. Both descriptive and inferential statistics were employed in data analysis. Loan defaulting (66.7%) and reduction in savings by members (51.4%) were the major causes of risks faced by agricultural cooperatives in financing agriculture in the study area. Other causes include adverse changes in commodity prices (48.6%), disaster (45.7%), among others. It was found that risks adversely influence the profitability and competition of agricultural cooperatives (82.9%). Multiple regression analysis results showed that the coefficient of multiple determinations was 0.67, implying that the explanatory variables included in the model accounted for 67% of the variation in the level of profitability of agricultural cooperatives. The number of loans, average amount of loan and the interest rate were significant and important determinants of profitability of the cooperatives. The majority of the respondents (88.6%) made use of loan guarantors as a strategy of managing loan default/no repayment. It was found that the majority (70%) of the respondents were faced with the challenge of lack of insurance cover. The study recommends that agricultural cooperative officials should be encouraged to undergo formal training and education to easily acquire administrative skills in the management of agricultural loans; Farmer's loan size should be increased and released on time to enable them to use it effectively. Policies that enhance insuring farm activities should be put in place to discourage farmers from risk aversion.

Keywords: agriculture, analysis, cooperative, finance, risks

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Authors: David P. Tantua, Abdulkader Helwan

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Biometrics has been recently used for the human identification systems using the biological traits such as the fingerprints and iris scanning. Identification systems based biometrics show great efficiency and accuracy in such human identification applications. However, these types of systems are so far based on some image processing techniques only, which may decrease the efficiency of such applications. Thus, this paper aims to develop a human palmprint identification system using multi-layer perceptron neural network which has the capability to learn using a backpropagation learning algorithms. The developed system uses images obtained from a public database available on the internet (CASIA). The processing system is as follows: image filtering using median filter, image adjustment, image skeletonizing, edge detection using canny operator to extract features, clear unwanted components of the image. The second phase is to feed those processed images into a neural network classifier which will adaptively learn and create a class for each different image. 100 different images are used for training the system. Since this is an identification system, it should be tested with the same images. Therefore, the same 100 images are used for testing it, and any image out of the training set should be unrecognized. The experimental results shows that this developed system has a great accuracy 100% and it can be implemented in real life applications.

Keywords: biometrics, biological traits, multi-layer perceptron neural network, image skeletonizing, edge detection using canny operator

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Authors: Houmame Benbouali, Aboubakr Gribi

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The risks, in general, exist in any project, one can hardly carry out a project without taking risks. The hydraulic works are rather complex projects in their design, realization and exploitation and are often subjected at the multiple risks being able to influence with their good performance and can have a negative impact on their environment. The present study was carried out to quote the impacts caused by purification plant STEP Chlef on the environment, it aims has studied the environmental impacts during construction and when designing this STEP, it is divided into two parts: The first part results from a research task bibliographer which contain three chapters (- cleansing of water-worn- general information on water worn-proceed of purification of waste water). The second part is an experimental part which is divided into four chapters (detailed state initial description of the station of purification-evaluation of the impacts of the project analyzes measurements and recommendations).

Keywords: treatment plant, waste water, waste water treatment, Chlef

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Authors: Sandija Zeverte-Rivza, Irina Pilvere, Baiba Rivza

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The use of renewable energy sources incl. biogas has become topical in accordance with the increasing demand for energy, decrease of fossil energy resources and the efforts to reduce greenhouse gas emissions as well as to increase energy independence from the territories where fossil energy resources are available. As the technologies of biogas production from agricultural biomass develop, risk assessment and risk management become necessary for farms producing such a renewable energy. The need for risk assessments has become particularly topical when discussions on changing the biogas policy in the EU take place, which may influence the development of the sector in the future, as well as the operation of existing biogas facilities and their income level. The current article describes results of the risk assessment for farms producing biomass from agriculture biomass in Latvia, the risk assessment system included 24 risks, that affect the whole biogas production process and the obtained results showed the high significance of political and production risks.

Keywords: biogas production, risks, risk assessment, biosystems engineering

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Authors: E. Krasnova, E. Bulgakova, V. Shchemelinin

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The paper deals with acoustic-spectrographic voice identification method in terms of its performance in non-native language speech. Performance evaluation is conducted by comparing the result of the analysis of recordings containing native language speech with recordings that contain foreign language speech. Our research is based on Tajik and Russian speech of Tajik native speakers due to the character of the criminal situation with drug trafficking. We propose a pilot experiment that represents a primary attempt enter the field.

Keywords: speaker identification, acoustic-spectrographic method, non-native speech, performance evaluation

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Authors: Mohamed Eladham Fadl M. E. Fadl

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In Egypt, wastewater has been used for irrigation in areas with fresh water scarcity. However, continuous applications may cause potential risks. Thus, the current study aims at screening the impacts of long-term wastewater irrigation on soil pollution and human health due to the exposure of heavy metals. Soils of nine sites in Al-Qalyubiyah Governorate, Egypt were sampled and analyzed for different properties. Wastewater resulted in a build-up of metals in soils. The pollution index (PI) showed the order of Cd > Pb > Ni > Zn. The integrated pollution index of Nemerow’s (IPIN) exceeded the safe limit of 0.7. The enrichment factor (EF) surpassed 1.0 value proving anthropogenic effects. The geo-accumulation index (Igeo) indicated that Pb, Ni, and Zn-induced none to moderate pollution, while high threats were associated with Cd. The calculated hazard index proved a potential health risk for humans, particularly children. It is recommended to perform a treatment to the wastewater used in irrigation to avoid such threats.

Keywords: pollution, health risks, heavy metals, effluent, irrigation, GIS techniques

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Authors: David Nantes, George Gilbert

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There are a lot of risks that might crop up as a tunneling project develops, and it's crucial to be aware of them. Due to the unexpected nature of tunneling projects and the interconnectedness of risk occurrences, the risk assessment approach presents a significant challenge. The purpose of this study is to provide a hybrid FDEMATEL-ANP model to help prioritize risks during tunnel construction projects. The ambiguity in expert judgments and the relative severity of interdependencies across risk occurrences are both taken into consideration by this model, thanks to the Fuzzy Decision-Making Trial and Evaluation Laboratory (FDEMATEL). The Analytic Network Process (ANP) method is used to rank priorities and assess project risks. The authors provide a case study of a subway tunneling construction project to back up the validity of their methodology. The results showed that the proposed method successfully isolated key risk factors and elucidated their interplay in the case study. The proposed method has the potential to become a helpful resource for evaluating dangers associated with tunnel construction projects.

Keywords: risk, prioritization, FDEMATEL, ANP, tunneling construction projects

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Authors: Degale Desta, Cheng Jian

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The most important factor in identifying a person is their face. Even identical twins have their own distinct faces. As a result, identification and face recognition are needed to tell one person from another. A face recognition system is a verification tool used to establish a person's identity using biometrics. Nowadays, face recognition is a common technique used in a variety of applications, including home security systems, criminal identification, and phone unlock systems. This system is more secure because it only requires a facial image instead of other dependencies like a key or card. Face detection and face identification are the two phases that typically make up a human recognition system.The idea behind designing and creating a face recognition system using deep learning with Azure ML Python's OpenCV is explained in this paper. Face recognition is a task that can be accomplished using deep learning, and given the accuracy of this method, it appears to be a suitable approach. To show how accurate the suggested face recognition system is, experimental results are given in 98.46% accuracy using Fast-RCNN Performance of algorithms under different training conditions.

Keywords: deep learning, face recognition, identification, fast-RCNN

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Authors: Sitrapee Changmuenwai, Sudaratana Wongweragiat

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It is important that a dry chemical fire extinguisher must be inspected for its readiness. For each inspection, the inspectors need to turn the fire extinguisher tank upside down to let the chemical inside the tank move and prevent solidification, which would make the tank not ready for usage when needed. Each tank weighs approximately 16 kg. The inspectors have to turn each tank upside down twice (2 minutes/round). They need to put the tanks over their shoulder close to their ear in order to hear the chemical flow inside the tank or use their hands to feel it. The survey and questionnaire 'The Questionnaire Know Body', which includes neck, left shoulder, upper and lower right arms suggest that all 12 security staffs have the same fatigues. The current dry chemical fire extinguisher inspection affects various ergonomic health problems. Rapid Entire Body Assessment (REBA) is used for evaluation of posture risks so that the working postures may be redesigned or corrected. The dry chemical fire extinguisher inspection equipment has been developed to reduce ergonomic health risks for the inspectors. A REBA analysis has been performed again, and the risk score has been decreased from 13 to 3. In addition, feedbacks from the first trial of the developed equipment show that there are demands to increase the installation in order to reduce the ergonomic health risks.

Keywords: dry chemical fire extinguisher inspection equipment, ergonomic, REBA, rapid entire body assessment

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Authors: Surbhi Mathur, J. M. Vyas

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Although the rapid development of forensic speaker recognition technology has been conducted, there are still many problems to be solved. The biggest problem arises when the cases involving disguised voice samples come across for the purpose of examination and identification. Such type of voice samples of anonymous callers is frequently encountered in crimes involving kidnapping, blackmailing, hoax extortion and many more, where the speaker makes a deliberate effort to manipulate their natural voice in order to conceal their identity due to the fear of being caught. Voice disguise causes serious damage to the natural vocal parameters of the speakers and thus complicates the process of identification. The sole objective of this doctoral project is to find out the possibility of rendering definite opinions in cases involving disguised speech by experimentally determining the effects of different disguise forms on personal identification and percentage rate of speaker recognition for various voice disguise techniques such as raised pitch, lower pitch, increased nasality, covering the mouth, constricting tract, obstacle in mouth etc by analyzing and comparing the amount of phonetic and acoustic variation in of artificial (disguised) and natural sample of an individual, by auditory as well as spectrographic analysis.

Keywords: forensic, speaker recognition, voice, speech, disguise, identification

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Authors: Rebecca Angeles

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This qualitative case study seeks to understand and explain the deployment of radio frequency identification (RFID) systems in two countries (i.e. in Taiwan for the adoption of electric scooters and in Finland for supporting glass bottle recycling) using the 'Technology-Organization-Environment' theoretical framework. This study also seeks to highlight the relevance and importance of pursuing environmental sustainability in firms and in society in general due to the social urgency of the issues involved.

Keywords: environmental sustainability, radio frequency identification, technology-organization-environment framework, RFID system implementation, case study, content analysis

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Authors: Shih-Ting Fu

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This study aimed to investigate the influence of influencer marketing on fan satisfaction, purchase intention, and team identification. The research employed a questionnaire survey targeting the Chinese Professional Baseball League (CPBL). The sample included 205 participants, encompassing both existing CPBL fans and individuals with no prior baseball viewing habits. The survey assessed the impact of influencer marketing on participants' knowledge, attitudes, and behaviors related to the CPBL. Additionally, it evaluated team identification, fan satisfaction, and purchase intention. Data analysis using SPSS software aimed to identify correlations and effects among the variables. Findings revealed that influencer marketing has a significant positive impact on fan satisfaction, purchase intention, and team identification. Notably, further analysis indicated that the personal characteristics and charisma of influencers significantly influenced fans' perceptions, leading to increased purchase intention and satisfaction. This effect was even stronger than the influence of influencers' expertise and information dissemination regarding sports events or products.

Keywords: influencer marketing, fan satisfaction, team identification, purchase intention, Chinese professional baseball league (CPBL)

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Authors: Serzhan Ashirov, Dana Nour, Rafat Rob, Khaled Alotaibi

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There has been a fast growth in the introduction and use of communications, information, monitoring, and sensing technologies. The new technologies are making their way to the Industrial Control Systems as embedded in products, software applications, IT services, or commissioned to enable integration and automation of increasingly global supply chains. As a result, the lines that separated the physical, digital, and cyber world have diminished due to the vast implementation of the new, disruptive digital technologies. The variety and increased use of these technologies introduce many cybersecurity risks affecting cyber-resilience of the supply chain, both in terms of the product or service delivered to a customer and members of the supply chain operation. US department of energy considers supply chain in the IR4 space to be the weakest link in cybersecurity. The IR4 identified the digitization of the field devices, followed by digitalization that eventually moved through the digital transformation space with little care for the new introduced cybersecurity risks. This paper will examine the best methodologies for securing the electrical substations from cybersecurity attacks due to supply chain risks, and due to digitization effort. SCADA systems are the most vulnerable part of the power system infrastructure due to digitization and due to the weakness and vulnerabilities in the supply chain security. The paper will discuss in details how create a secure supply chain methodology, secure substations, and mitigate the risks due to digitization

Keywords: cybersecurity, supply chain methodology, secure substation, digitization

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Authors: Zain Ul Abdin, Mirza Aizaz Asim, Rao Sohail Ahmad Khan, Luqman Amrao, Fiaz Hussain, Hasooba Hira, Saqi Kosar Abbas

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The success of Integrated vector management programmes mainly depends on the correct identification of insect vector species involved in vector borne diseases. Based on molecular data the most important insect species involved as vectors for Zoonotic diseases in Pakistan were identified. The precise and accurate identification of such type of organism is only possible through molecular based techniques like “DNA barcoding”. Morphological species identification in insects at any life stage, is very challenging, therefore, DNA barcoding was used as a tool for rapid and accurate species identification in a wide variety of taxa across the globe and parallel studies revealed that DNA barcoding data can be effectively used in resolving taxonomic ambiguities, detection of cryptic diversity, invasion biology, description of new species etc. A comprehensive survey was carried out for the collection of insects (both adult and immature stages) in district Faisalabad, Pakistan and their DNA was extracted and mitochondrial cytochrome oxidase subunit I (COI-59) barcode sequences was used for molecular identification of immature and adult life stage.This preliminary research work opens new frontiers for developing sustainable insect vectors management programmes for saving lives of mankind from fatal diseases.

Keywords: zoonotic diseases, cytochrome oxidase, and insect vectors, CO1

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Authors: Kais Manai

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The main part of this work focuses on the study of pion/muon separation at low energy using a nuclear Emulsion Cloud Chamber (ECC) made of lead and nuclear emulsion films. The work consists of two parts: particle reconstruction algorithm and a Neural Network that assigns to each reconstructed particle the probability to be a muon or a pion. The pion/muon separation algorithm has been optimized by using a detailed Monte Carlo simulation of the ECC and tested on real data. The algorithm allows to achieve a 60% muon identification efficiency with a pion misidentification smaller than 3%.

Keywords: nuclear emulsion, particle identification, tracking, neural network

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Authors: Katerine Moraes dos Satons, Gisele Massante Peixoto Tracera, Regina Célia Gollner Zeitoune

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To analyze the psychosocial risks related to the organization of nursing work in outpatient clinics of university hospitals. Cross-sectional epidemiological study developed in 11 outpatient units linked to the three public universities of the city of Rio de Janeiro, Brazil. Participants were 388 nursing professionals who worked in patient care at the time of the research. Data were collected from July to December 2018, using a self-applicable instrument. A questionnaire was used for sociodemographic, occupational and health characterization, and the Work Organization Scale. The bivariate analyses were performed using the odds ratio (OR), with a confidence interval of 95%, significance level of 5%. The organization of nursing work received an assessment of medium psychosocial risk by the professionals participating in the research, demanding interventions in the short and medium term. There was no association between sociodemographic, occupational and health characteristics and the organization of outpatient work. Interventional measures should be performed in the psychosocial risk factors presented in this research, with a view to improving the work environment, so that the importance of maintaining satisfactory material conditions is considered, as well as the adequate quantity of human resources. In addition, it aims to expand the spaces of nursing participation in decision- making, strengthening its autonomy as a profession.

Keywords: occupational risks, nursing, nursing team, worker’s health, psychosocial risks

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Authors: Bale Baidi Blaise, Gilles Marckmann, Liman Kaoye, Talaka Dya, Moustapha Bachirou, Gambo Betchewe, Tibi Beda

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This work highlights the capabilities of particles swarm optimization (PSO) method to identify parameters of hyperelastic models. The study compares this method with Genetic Algorithm (GA) method, Least Squares (LS) method, Pattern Search Algorithm (PSA) method, Beda-Chevalier (BC) method and the Levenberg-Marquardt (LM) method. Four classic hyperelastic models are used to test the different methods through parameters identification. Then, the study compares the ability of these models to reproduce experimental Treloar data in simple tension, biaxial tension and pure shear.

Keywords: particle swarm optimization, identification, hyperelastic, model

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Authors: Brandon Foggo, Nanpeng Yu

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Power distribution circuits undergo frequent network topology changes that are often left undocumented. As a result, the documentation of a circuit’s connectivity becomes inaccurate with time. The lack of reliable circuit connectivity information is one of the biggest obstacles to model, monitor, and control modern distribution systems. To enhance the reliability and efficiency of electric power distribution systems, the circuit’s connectivity information must be updated periodically. This paper focuses on one critical component of a distribution circuit’s topology - the secondary transformer to phase association. This topology component describes the set of phase lines that feed power to a given secondary transformer (and therefore a given group of power consumers). Finding the documentation of this component is call Phase Identification, and is typically performed with physical measurements. These measurements can take time lengths on the order of several months, but with supervised learning, the time length can be reduced significantly. This paper compares several such methods applied to Phase Identification for a large range of real distribution circuits, describes a method of training data selection, describes preprocessing steps unique to the Phase Identification problem, and ultimately describes a method which obtains high accuracy (> 96% in most cases, > 92% in the worst case) using only 5% of the measurements typically used for Phase Identification.

Keywords: distribution network, machine learning, network topology, phase identification, smart grid

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Authors: Nino Damenia

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The paper discusses the risks arising in agriculture in Georgia, the possibilities of their acceptance and prevention, the threat created by the pandemic crisis, and the state programs for overcoming them. The share of agriculture in the country's GDP is 8.3%. Over the past five years, Georgia has imported $ 5.9 billion worth of agri-food products. Despite these figures, agriculture has become an important sector for the Georgian government since 2012, as evidenced by the more than 1.5 billion GEL spent from the 2012-2020 budget for agricultural development. Any field of agriculture, be it poultry, livestock, cereals, fruits, or vegetables, is very sensitive to various climatic and viral risks. Avoiding these risks requires additional investment. It is noteworthy that small farms are mainly affected by the risks, while relatively large farms face fewer problems because they are relatively prepared to face the problems and can avoid them more easily. An example of viral risk in the article is the export of hazelnuts, which has quite a lot of potential. Due to the spoilage of the crop caused by Brown Marmorated Stink Bug (BMSB), hazelnut exports have declined considerably over the years. If the volume of hazelnuts exported in 2016 was 179 378 thousand USD, due to the deficit caused by Brown Marmorated Stink Bug (BMSB) in 2018, it became 57 124 thousand USD. And after the situation was relatively settled, hazelnut seedlings were poisoned. By 2020, this figure improved to 91,088 thousand US dollars. The development of the agricultural sector and the reduction of risks require technological development, investor interest, and even more state support to enable more small farms to have the potential for greater production and sustainable development. The aim of the study is to identify the risks arising in the agricultural sector of Georgia before and after the pandemic, to evaluate them, compare them with the agriculture of some European countries, and to develop the necessary recommendations to avoid the emerging risks. The research uses methods of analysis and synthesis, observation, induction, deduction, and analysis of statistics. The paper is based on both Georgian and foreign scientific research, as well as state-published documentation on agricultural assistance programs. The research is based on the analysis of data published by the European Statistics Office, the National Statistics Office of Georgia, and many other organizations. The results of the study and the recommendations will help reduce the risks in agriculture in Georgia and, in general, to identify the existing potential and the development of the sector as a whole.

Keywords: risk, agriculture, pandemi, brown marmorated stink bug (BMSB)

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Authors: Haythem H. Abdullah, Hesham Elkady

Abstract:

With the fast increase in radio frequency identification (RFID) applications such as medical recording, library management, etc., the limitation of active tags stems from its need to external batteries as well as passive or active chips. The chipless RFID tag reduces the cost to a large extent but at the expense of utilizing the spectrum. The reduction of the cost of chipless RFID is due to the absence of the chip itself. The identification is done by utilizing the spectrum in such a way that the frequency response of the tags consists of some resonance frequencies that represent the bits. The system capacity is decided by the number of resonators within the pre-specified band. It is important to find a solution to enhance the spectrum utilization when using chipless RFID. Target identification is a process that results in a decision that a specific target is present or not. Several target identification schemes are present, but one of the most successful techniques in radar target identification in the oscillatory region is the extinction pulse technique (E-Pulse). The E-Pulse technique is used to identify targets via its characteristics (natural) modes. By introducing an innovative solution for chipless RFID reader and tag designs, the spectrum utilization goes to the optimum case. In this paper, a novel capacity enhancement scheme based on the E-pulse technique is introduced to improve the performance of the chipless RFID system.

Keywords: chipless RFID, E-pulse, natural modes, resonators

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Authors: Hyun-Woo Cho

Abstract:

It is quite important to utilize right time and intelligent production monitoring and diagnosis of industrial processes in terms of quality and safety issues. When compared with monitoring task, fault diagnosis represents the task of finding process variables responsible causing a specific fault in the process. It can be helpful to process operators who should investigate and eliminate root causes more effectively and efficiently. This work focused on the active use of combining a nonlinear statistical technique with a preprocessing method in order to implement practical real-time fault identification schemes for data-rich cases. To compare its performance to existing identification schemes, a case study on a benchmark process was performed in several scenarios. The results showed that the proposed fault identification scheme produced more reliable diagnosis results than linear methods. In addition, the use of the filtering step improved the identification results for the complicated processes with massive data sets.

Keywords: diagnosis, filtering, nonlinear statistical techniques, process monitoring

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Authors: Gangmin Li, Fan Yang

Abstract:

Personalized recommendation is crucial for any recommendation system. One of the techniques for personalized recommendation is to identify the intention. Traditional user intention identification uses the user’s selection when facing multiple items. This modeling relies primarily on historical behaviour data resulting in challenges such as the cold start, unintended choice, and failure to capture intention when items are new. Motivated by recent advancements in Large Language Models (LLMs) like ChatGPT, we present an approach for user intention identification by embracing LLMs with Chain-of-Thought (CoT) prompting. We use the initial user profile as input to LLMs and design a collection of prompts to align the LLM's response through various recommendation tasks encompassing rating prediction, search and browse history, user clarification, etc. Our tests on real-world datasets demonstrate the improvements in recommendation by explicit user intention identification and, with that intention, merged into a user model.

Keywords: personalized recommendation, generative user modelling, user intention identification, large language models, chain-of-thought prompting

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Authors: Alina Svechkina, Boris A. Portnov

Abstract:

In line with a rapid increase in pollution sources and enforcement of stricter air pollution regulation, which lowers pollution levels, it becomes more difficult to identify actual risk sources behind the observed morbidity patterns, and new approaches are required to identify potential risks and take preventive actions. In the present study, we discuss a probabilistic approach to the spatial identification of a priori unidentified environmental health hazards. The underlying assumption behind the tested approach is that the observed adverse health patterns (morbidity, mortality) can become a source of information on the geographic location of environmental risk factors that stand behind them. Using this approach, we analyzed sources of environmental exposure using data on mortality rates available for the year 2015 for NUTS 3 (Nomenclature of Territorial Units for Statistics) subdivisions of the European Union. We identified several areas in the southwestern part of Europe as primary risk sources for the observed mortality patterns. Multivariate regressions, controlled by geographical location, climate conditions, GDP (gross domestic product) per capita, dependency ratios, population density, and the level of road freight revealed that mortality rates decline as a function of distance from the identified hazard location. We recommend the proposed approach an exploratory analysis tool for initial investigation of regional patterns of population morbidity patterns and factors behind it.

Keywords: mortality, environmental hazards, air pollution, distance decay gradient, multi regression analysis, Europe, NUTS3

Procedia PDF Downloads 167