Search results for: learning strategy

Authors: Qingyu Zhang, Helin Ma, Lili Weng, Mei Cao

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Green supply chain management has been an important organizational strategy to reduce environmental risks and improve financial performance. Firms have to adopt green supply chain practices to meet the official regulations and reduce peer pressure in China. This paper exhibits an empirical study of the drivers of green supply chain management practices and the environmental and economic performance of green supply chain management implementation in Chinese firms. While China is the fastest-growing emerging economy, it has paid a high ecological price. It is reported that China hosts 7 of the world’s 10 most polluted cities. The continued environmental deterioration and the resultant heightened regulatory control and public scrutiny have posed new operating challenges to firms conducting business in China. These challenges make the country an ideal setting to conduct the present study. A research questionnaire was developed to gather data in China. The questionnaire targeted managers and employees in Chinese companies. The data were collected in the last quarter of 2015, involving industries such as electronic & communicational equipment, textile & clothing, pharmaceutical & healthcare, and so on. This study confirms and validates that (1) both internal and external drivers play a significant role in the implementation of green supply chain management practices; (2) green purchase and investment recovery have a significant impact on firms’ environmental and economic performance; (3) with the improvement of the firms’ environmental performance, their economic performance will improve.

Keywords: economic performance, environmental performance, external driver, green supply chain management

Procedia PDF Downloads 362

Authors: Chen Xi, Liu Xuebing, Lao Xueru, Kuan Sinman, Jiang Yike, Wang Hanwei, Yang Xiaolang, Zhou Junjie, Xie Jinpeng

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To further promote the development of smart cities, the microscopic "nerve endings" of the City Intelligent Model (CIM) are extended to be more sensitive. In this paper, we develop a pedestrian trajectory twin terminal based on the CIM and CNN technology. It also uses 5G networks, architectural and geoinformatics technologies, convolutional neural networks, combined with deep learning networks for human behavior recognition models, to provide empirical data such as 'pedestrian flow data and human behavioral characteristics data', and ultimately form spatial performance evaluation criteria and spatial performance warning systems, to make the empirical data accurate and intelligent for prediction and decision making.

Keywords: urban planning, urban governance, CIM, artificial intelligence, sustainable development

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Authors: Latifa Alenezi, Liz Croot, Janet Harris

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Chronic Low Back Pain (CLBP) is one of the most common and recurrent musculoskeletal problems that causes patients to access health care services frequently. The Bio-psychosocial Model emphasises that psychological, behavioural and social factors contribute to the development and persistence of CLBP. Cognitive behavioural therapy (CBT) is a psychological pain management strategy that can be used by physiotherapists treating chronic low back pain. However, evidence of the effectiveness of CBT for CLBP varies between different studies. The proposed study was preceded by a mixed methods systematic review that found that CBT has a beneficial effect for CLBP patients when compared to waiting list or other treatments; however, there is variation in effectiveness across different settings. Little is known about how CBT is applied by physiotherapists in physiotherapy settings. The interest of this study is directed towards generating an explanation and understanding of why, when, and how some physiotherapists make decisions and choose to apply CBT for CLBP patients, whereas others do not. Also, how and for what type of CLBP patients does CBT work, and for whom might CBT not work? Therefore, the study will take a qualitative approach to explore CLBP patients’, physiotherapists’ and managers’ perceptions of CBT and how it is used in physiotherapy to enable a deeper understanding and richer explanation of CBT effectiveness and help to inform research and practice. The study will use grounded theory approach to generate an explanatory theory of the clinical application of CBT for CLBP in physiotherapy settings. Physiotherapists, patients and managers of physiotherapy services will be interviewed. Grounded theory techniques will be used to analyse the data. The presentation will describe findings from the interviews and the emerging theory. This research will help to further inform RCTs about the effectiveness of CBT for CLBP in physiotherapy.

Keywords: CBT, CLBP, perception, physiotherapy, theory

Procedia PDF Downloads 219

Authors: Gulshad Azatova, Aleksandr Kapitonov, Natig Aminov

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Multiagent systems have gained significant attention in various fields, such as robotics, autonomous vehicles, and distributed computing, where multiple agents cooperate and communicate to achieve complex tasks. Efficient communication among agents is a crucial aspect of these systems, as it directly impacts their overall performance and scalability. This scholarly work provides an exploration of essential communication elements and conducts a comparative assessment of diverse protocols utilized in multiagent systems. The emphasis lies in scrutinizing the strengths, weaknesses, and applicability of these protocols across various scenarios. The research also sheds light on emerging trends within communication protocols for multiagent systems, including the incorporation of machine learning methods and the adoption of blockchain-based solutions to ensure secure communication. These trends provide valuable insights into the evolving landscape of multiagent systems and their communication protocols.

Keywords: communication, multi-agent systems, protocols, consensus

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Authors: Arlene Villarama, Micol Grace Guanzon, Zenaida Ramos

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This paper provides insights into teaching English as a Foreign Language in the Philippines. The authors reviewed relevant theories and literature, and provide an analysis of the issues in teaching English in the Philippine setting in the light of these theories. The authors made an investigation in Bagong Barrio National High School (BBNHS) - a public school in Caloocan City. The institution has a population of nearly 3,000 students. The performances of randomly chosen 365 respondents were scrutinised. The study regarding the success of teaching English as a foreign language to Filipino children were highlighted. This includes the respondents’ family background, surroundings, way of living, and their behavior and understanding regarding education. The results show that there is a significant relationship between demonstrative, communal, and logical areas that touch the efficacy of introducing English as a foreign Dialectal. Filipino children, by nature, are adventurous and naturally joyful even for little things. They are born with natural skills and capabilities to discover new things. They highly consider activities and work that ignite their curiosity. They love to be recognised and are inspired the most when given the assurance of acceptance and belongingness. Fun is the appealing influence to ignite and motivate learning. The magic word is excitement. The study reveals the many facets of the accumulation and transmission of erudition, in introduction and administration of English as a foreign phonological; it runs and passes through different channels of diffusion. Along the way, there are particles that act as obstructions in protocols where knowledge are to be gathered. Data gained from the respondents conceals a reality that is beyond one’s imagination. One significant factor that touches the inefficacy of understanding and using English as a foreign language is an erroneous outset gained from an old belief handed down from generation to generation. This accepted perception about the power and influence of the use of language, gives the novices either a negative or a positive notion. The investigation shows that a higher number of dislikes in the use of English can be tracked down from the belief of the story on how the English language came into existence. The belief that only the great and the influential have the right to use English as a means of communication kills the joy of acceptance. A significant notation has to be examined so as to provide a solution or if not eradicate the misconceptions that lie behind the substance of the matter. The result of the authors’ research depicts a substantial correlation between the emotional (demonstrative), social (communal), and intellectual (logical). The focus of this paper is to bring out the right notation and disclose the misconceptions with regards to teaching English as a foreign language. This will concentrate on the emotional, social, and intellectual areas of the Filipino learners and how these areas affect the transmittance and accumulation of learning. The authors’ aim is to formulate logical ways and techniques that would open up new beginnings in understanding and acceptance of the subject matter.

Keywords: accumulation, behaviour, facets, misconceptions, transmittance

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Authors: Venkataraman Sankaranarayanan, Sougata Ray

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While extant research has examined many aspects of differential corporate environmental outcomes and behavior, a holistic and integrated view of heterogeneity in corporate environment sustainability (CES) practices remains a puzzle to be fully unraveled – its extent and nature, its relationship to macro or micro level influences, or strategic orientations. Such a perspective would be meaningful for the field given notable strides in CES practices and the corporate social responsibility agenda over the last two decades, in the backdrop of altered global socio-political sensitivities and technological advances. To partly address this gap, this exploratory research adopted a content analysis approach to code patterns in the sustainability disclosures of the 160 largest global firms spread over 8 years. The sample of firms spanned seven industries, nine countries and three continents thereby presenting data rich and diverse enough in several dimensions to be representative of global heterogeneity in CES practices. Through a factor analysis of the coded data, four strategic CES orientations were extracted through the analysis, that effectively straddles most of the variation observed in current CES practices – one that seeks to reduce environmental damage on account of the firm’s operations, another that prioritizes minimalism, a third that focuses on broader ecological status quo, and a final one that champions the ‘business of green’, extending the CES agenda beyond the firm’s boundaries. These environment sustainability strategy orientations are further examined to elicit prominent patterns and explore plausible antecedents.

Keywords: corporate social responsibility, corporate sustainability, environmental management, heterogeneity, strategic orientation

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Authors: Anam Alam, Rahim Jamaluddin Kanji

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With the rapid growth of event in everywhere, event extraction has now become an important matter to retrieve the information from the unstructured data. One of the challenging problems is to extract the event from it. An event is an observable occurrence of interaction among entities. The paper investigates the effectiveness of event extraction capabilities of three software tools that are Wandora, Nitro and SPSS. We performed standard text mining techniques of these tools on the data sets of (i) Afghan War Diaries (AWD collection), (ii) MUC4 and (iii) WebKB. Information retrieval measures such as precision and recall which are computed under extensive set of experiments for Event Extraction. The experimental study analyzes the difference between events extracted by the software and human. This approach helps to construct an algorithm that will be applied for different machine learning methods.

Keywords: event extraction, Wandora, nitro, SPSS, event analysis, extraction method, AFG, Afghan War Diaries, MUC4, 4 universities, dataset, algorithm, precision, recall, evaluation

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Authors: Jayant Balaji Athavale, Sean Clarke

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Background: According to the WHO, every year, more than 700,000 people die by suicide, which is one person around every 45 seconds. Suicide is the fourth leading cause of death among 15 to 29-year-olds globally. The most common situations or life events that might cause suicidal thoughts are financial problems/unemployment, rejections, relationship breakups, sexual/substance abuse and mental illnesses. Mental/psychological weakness caused due to defects in one’s personality is one of the main reasons why people feel they cannot cope in such situations and contemplate suicide. A WHO Mental Health Action Plan 2013–2020 lists a 4-point strategy to enhance mental health by ‘implementing strategies for promotion and prevention in mental health.’ Methodology: With 40 years of spiritual research background, the team at the Maharshi University of Spirituality has studied the spiritual root causes that can significantly affect one’s mental health and the solutions to improve it. Results/Findings: According to spiritual science, the time and nature of death are mostly due to spiritual reasons. A person would mostly contemplate and attempt suicide when he is spiritually most vulnerable. Spiritual practice, as per universal principles, helps in protecting a person spiritually and prevents him from getting such thoughts of self-harm or acting upon them by controlling such impulses. The University has had much success in helping people to overcome the defects in their personalities, including those with suicidal thoughts, through spiritual practices such as chanting the Name of God and the Personality Defect Removal (PDR) process developed by the Author. Conclusion: If such techniques were taught in educational institutions, they could be simple yet effective self-help tools to prevent thoughts of suicide and enhance mental health and well-being.

Keywords: suicide, mental health, abuse, suicide prevention, personality defect removal

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Authors: Temesgen Kassa Getahun, Gezahegn Mamo, Beksisa Urge

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A cross-sectional study was conducted from December 2019 to May 2020 with the aim of determining the seroprevalence of brucellosis in dairy cows and their owners in the central highland of Oromia, Ethiopia. A total of 352 blood samples from dairy cattle, 149 from animal owners, and 17 from farm workers were collected and initially screened using the Rose Bengal Plate test and confirmed by the Complement Fixation test. Overall seroprevalence was 0.6% (95% CI: 0.0016–0.0209) in bovines and 1.2% (95% CI: 0.0032–0.0427) in humans. Market-based stock replacement (OR=16.55, p=0.002), breeding by artificial insemination (OR=7.58, p=0.05), and parturition pen (OR = 11.511, p=0.027) were found to be significantly associated with the seropositivity for Brucella infection in dairy cattle. Human housing (OR=1.8, p=0.002), contact with an aborted fetus (OR=21.19, p=0.017), drinking raw milk from non-aborted (OR=24.99, p=0.012), aborted (OR=5.72, p=0.019) and retained fetal membrane (OR=4.22, p=0.029) cows had a significant influence on human brucellosis. A structured interview question was administered to 284 respondents. Accordingly, most respondents had no knowledge of brucellosis (93.3%), and in contrast, 90% of them consumed raw milk. In conclusion, the present seroprevalence study revealed that brucellosis was low among dairy cattle and exposed individuals in the study areas. However, since there were no control strategies implemented in the study areas, there is a potential risk of transmission of brucellosis in dairy cattle and the exposed human population in the study areas. Implementation of a test and slaughter strategy with compensation to farmers is recommended, while in the case of human brucellosis, continuous social training and implementing one health approach framework must be applied.

Keywords: abortion, bovine brucellosis, human brucellosis, risk factors, seroprevalence

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Authors: Mehrnoosh Abouzari, Shahrokh Shahraei

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With the development of artificial intelligence in the present age, intelligent machines and systems have proven their actual and potential capabilities and are mindful of increasing their presence in various fields of human life in the fields of industry, financial transactions, marketing, manufacturing, service affairs, politics, economics and various branches of the humanities .Therefore, despite the conservatism and prudence of law enforcement, the traces of artificial intelligence can be seen in various areas of law. Including judicial robotics capability estimation, intelligent judicial decision making system, intelligent defender and attorney strategy adjustment, dissemination and regulation of different and scattered laws in each case to achieve judicial coherence and reduce opinion, reduce prolonged hearing and discontent compared to the current legal system with designing rule-based systems, case-based, knowledge-based systems, etc. are efforts to apply AI in law. In this article, we will identify the ways in which AI is applied in its laws and regulations, identify the dominant concerns in this area and outline the relationship between these two areas in order to answer the question of how artificial intelligence can be used in different areas of law and what the implications of this application will be. The authors believe that the use of artificial intelligence in the three areas of legislative, judiciary and executive power can be very effective in governments' decisions and smart governance, and helping to reach smart communities across human and geographical boundaries that humanity's long-held dream of achieving is a global village free of violence and personalization and human error. Therefore, in this article, we are going to analyze the dimensions of how to use artificial intelligence in the three legislative, judicial and executive branches of government in order to realize its application.

Keywords: artificial intelligence, law, intelligent system, judge

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Authors: Siliang Luan, Zhongtai Jiang

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The risk of highway incidents is commonly recognized as a major concern for transportation authorities due to the hazardous consequences and negative influence. It is crucial to respond to these unpredictable events as soon as possible faced by emergency management decision makers. In this paper, we focus on path planning for emergency vehicles, one of the most significant processes to avoid congestion and reduce rescue time. A Mixed-Integer Linear Programming with Semi-Soft Time Windows Model (MIPSSTWM) is conducted to plan an optimal routing respectively considering the time consumption of arcs and nodes of the urban road network and the highway network, especially in developing countries with an enormous population. Here, the arcs indicate the road segments and the nodes include the intersections of the urban road network and the on-ramp and off-ramp of the highway networks. An attempt in this research has been made to develop a comprehensive and executive strategy for emergency vehicle routing in heavy traffic conditions. The proposed Cuckoo Search (CS) algorithm is designed by imitating obligate brood parasitic behaviors of cuckoos and Lévy Flights (LF) to solve this hard and combinatorial problem. Using a Chinese city as our case study, the numerical results demonstrate the approach we applied in this paper outperforms the previous method without considering the nodes of the road network for a real-world situation. Meanwhile, the accuracy and validity of the CS algorithm also show better performances than the traditional algorithm.

Keywords: emergency vehicle, path planning, cs algorithm, urban traffic management and urban planning

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Authors: T. M. Tawfik, M. A. Badr, E. Y. El-Kady, O. E. Abdellatif

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Electric power shortage is a serious problem in remote rural communities in Egypt. Over the past few years, electrification of remote communities including efficient on-site energy resources utilization has achieved high progress. Remote communities usually fed from diesel generator (DG) networks because they need reliable energy and cheap fresh water. The main objective of this paper is to design an optimal economic power supply from hybrid standalone energy system (HSES) as alternative energy source. It covers energy requirements for reverse osmosis desalination unit (DU) located in National Research Centre farm in Noubarya, Egypt. The proposed system consists of PV panels, Wind Turbines (WT), Batteries, and DG as a backup for supplying DU load of 105.6 KWh/day rated power with 6.6 kW peak load operating 16 hours a day. Optimization of HSES objective is selecting the suitable size of each of the system components and control strategy that provide reliable, efficient, and cost-effective system using net present cost (NPC) as a criterion. The harmonization of different energy sources, energy storage, and load requirements are a difficult and challenging task. Thus, the performance of various available configurations is investigated economically and technically using iHOGA software that is based on genetic algorithm (GA). The achieved optimum configuration is further modified through optimizing the energy extracted from renewable sources. Effective minimization of energy charging the battery ensures that most of the generated energy directly supplies the demand, increasing the utilization of the generated energy.

Keywords: energy management, hybrid system, renewable energy, remote area, optimization

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Authors: Shao-Hsun Keng, Hwang-Ruey Song

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This paper examines the causal effect of the tenure track system on instructors’ grading practices and teaching effectiveness by taking advantage of a natural experiment in Taiwan. The results show that assistant professors subject to the tenure track policy are more likely to grade leniently and fail fewer students. The course grade is 5% higher in classes taught by assistant professors subject to the tenure system. However, the tendency to grade leniently is reversed after assistant professors subject to the tenure system are promoted to a higher rank. Our findings are consistent with the exchange theory. We also show that teaching and student efforts are adversely affected by the tenure policy, which could reduce student learning and the quality of the workforce in the long run.

Keywords: tenure track system, grading leniency, study time, grade inflation

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Authors: Suliman Al Balawi

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Food waste is a significant problem in the Kingdom of Saudi Arabia (KSA). About SR13 billion worth of food is wasted per year in the KSA. From moral, social, and economic perspectives, it is essential to reduce the wastage of food. Although studies have identified the amount of food waste in the KSA, there is a lack of research on why people in the KSA waste food; thus, it is difficult to design efficient intervention programs to reduce food waste. This research investigates the key factors that influence the food waste behavior of the people of the KSA. A food waste behavior model is proposed in this study that has moral disengagement at the center of the model. Following a literature survey, it is hypothesised that religiosity, hedonic value, frugality, and trait cynicism are the antecedents of moral disengagement that are likely to impact the food waste behavior of the people of the KSA. The study further posits that an intervention strategy in the form of a social marketing campaign that focuses on lowering the level of moral disengagement could reduce the food waste behavior of the people of the KSA. This study will apply a pre-test/post-test experimental design (control group). A random sampling method will be used to select participants from the (employees of a chosen firm) in the KSA. The social marketing campaign will be run for six months through the Corporate Social Responsibility Department of the Company, and to analyse the experimental data, structural equation modeling (SEM) will be used. The outcomes of the study will demonstrate the effectiveness of a social marketing campaign for improving the food waste behavior of the people of the KSA and will ultimately lay the foundation for designing efficient intervention programs in the future. This study will contribute to the knowledge on food waste behavior by testing a newly proposed food waste behavior model in the KSA.

Keywords: food waste, social marketing, Saudi Arabia, moral disengagement

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Authors: Masoumeh Haghbin Nazarpak, Hamidreza Tolabi, Aryan Ekhlasi

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Bone defects are mentioned as one of the most challenging clinical conditions, affecting millions of people each year. A fracture, osteoporosis, tumor, or infection usually causes these defects. At present, autologous and allogeneic grafts are used to correct bone defects, but these grafts have some difficulties, such as limited access, infection, disease transmission, and immune rejection. Bone tissue engineering is considered a new strategy for repairing bone defects. However, problems with scaffolds’ design with unique structures limit their clinical applications. In addition, numerous in-vitro studies have been performed on the behavior of bone cells in two-dimensional environments. Still, cells grow in physiological situations in the human body in a three-dimensional environment. As a result, the controlled design of porous structures with high structural complexity and providing the necessary flexibility to meet specific needs in bone tissue repair is beneficial. For this purpose, a three-dimensional composite scaffold based on gelatin and sodium alginate hydrogels is used in this research. In addition, the antibacterial drug-loaded halloysite nanotubes were introduced into the hydrogel scaffold structure to provide a suitable substrate for controlled drug release. The presence of halloysite nanotubes improved hydrogel’s properties, while the drug eliminated infection and disease transmission. Finally, it can be acknowledged that the composite scaffold prepared in this study for bone tissue engineering seems promising.

Keywords: halloysite nanotubes, bone tissue engineering, composite scaffold, controlled drug release

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Authors: Ali Kazemi

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Those within the volatile and interconnected international economic markets, appropriately predicting market trends, hold substantial fees for traders and financial establishments. Traditional device mastering strategies have made full-size strides in forecasting marketplace movements; however, monetary data's complicated and networked nature calls for extra sophisticated processes. This observation offers a groundbreaking method for monetary marketplace prediction that leverages the synergistic capability of Graph Convolutional Networks (GCNs) and Long Short-Term Memory (LSTM) networks. Our suggested algorithm is meticulously designed to forecast the traits of inventory market indices and cryptocurrency costs, utilizing a comprehensive dataset spanning from January 1, 2015, to December 31, 2023. This era, marked by sizable volatility and transformation in financial markets, affords a solid basis for schooling and checking out our predictive version. Our algorithm integrates diverse facts to construct a dynamic economic graph that correctly reflects market intricacies. We meticulously collect opening, closing, and high and low costs daily for key inventory marketplace indices (e.g., S&P 500, NASDAQ) and widespread cryptocurrencies (e.g., Bitcoin, Ethereum), ensuring a holistic view of marketplace traits. Daily trading volumes are also incorporated to seize marketplace pastime and liquidity, providing critical insights into the market's shopping for and selling dynamics. Furthermore, recognizing the profound influence of the monetary surroundings on financial markets, we integrate critical macroeconomic signs with hobby fees, inflation rates, GDP increase, and unemployment costs into our model. Our GCN algorithm is adept at learning the relational patterns amongst specific financial devices represented as nodes in a comprehensive market graph. Edges in this graph encapsulate the relationships based totally on co-movement styles and sentiment correlations, enabling our version to grasp the complicated community of influences governing marketplace moves. Complementing this, our LSTM algorithm is trained on sequences of the spatial-temporal illustration discovered through the GCN, enriched with historic fee and extent records. This lets the LSTM seize and expect temporal marketplace developments accurately. Inside the complete assessment of our GCN-LSTM algorithm across the inventory marketplace and cryptocurrency datasets, the version confirmed advanced predictive accuracy and profitability compared to conventional and opportunity machine learning to know benchmarks. Specifically, the model performed a Mean Absolute Error (MAE) of 0.85%, indicating high precision in predicting day-by-day charge movements. The RMSE was recorded at 1.2%, underscoring the model's effectiveness in minimizing tremendous prediction mistakes, which is vital in volatile markets. Furthermore, when assessing the model's predictive performance on directional market movements, it achieved an accuracy rate of 78%, significantly outperforming the benchmark models, averaging an accuracy of 65%. This high degree of accuracy is instrumental for techniques that predict the course of price moves. This study showcases the efficacy of mixing graph-based totally and sequential deep learning knowledge in economic marketplace prediction and highlights the fee of a comprehensive, records-pushed evaluation framework. Our findings promise to revolutionize investment techniques and hazard management practices, offering investors and economic analysts a powerful device to navigate the complexities of cutting-edge economic markets.

Keywords: financial market prediction, graph convolutional networks (GCNs), long short-term memory (LSTM), cryptocurrency forecasting

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Authors: Houxiang Zhu, Chun Liang

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The CRISPR-Cpf1 system has been successfully applied in genome editing. However, target efficiency of the CRISPR-Cpf1 system varies among different gRNA sequences. The published CRISPR-Cpf1 gRNA data was reanalyzed. Many sequences and structural features of gRNAs (e.g., the position-specific nucleotide composition, position-nonspecific nucleotide composition, GC content, minimum free energy, and melting temperature) correlated with target efficiency were found. Using machine learning technology, a support vector machine (SVM) model was created to predict target efficiency for any given gRNAs. The first web service application, CRISPR-DT (CRISPR DNA Targeting), has been developed to help users design optimal gRNAs for the CRISPR-Cpf1 system by considering both target efficiency and specificity. CRISPR-DT will empower researchers in genome editing.

Keywords: CRISPR-Cpf1, genome editing, target efficiency, target specificity

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Authors: Keerthie Dissanayake, Chandrika Jayasinghe, Priyani Wanigasekara, Jayampathy Dissanayake, Ajith Sominanda

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The routine use of Disease Activity Score-28 (DAS28) to assess the disease activity in rheumatoid arthritis (RA) is limited due to its dependency on laboratory investigations and the complex calculations involved. In contrast, the clinical disease activity index (CDAI) is simple to calculate, which makes the "treat to target" strategy for the management of RA more practical. We aimed to assess the validity of CDAI compared to DAS28 in RA patients in Sri Lanka. A total of 103 newly diagnosed RA patients were recruited, and their disease activity was calculated using DAS 28 and CDAI during the first visit to the clinic (0 months) and re-assessed at 4 and 9 months of the follow-up visits. The validity of the CDAI, compared to DAS 28, was evaluated. Patients had a female preponderance (6:1) and a short symptom duration (mean = 6.33 months). The construct validity of CDAI, as assessed by Cronbach's α test, was 0.868. Convergent validity was assessed by correlation and Kappa statistics. Strong positive correlations were observed between CDAI and DAS 28 at the baseline (0 months), 4, and 9 months of evaluation (Spearman's r = 0.9357, 0.9354, 0.9106, respectively). Moderate-good inter-rater agreements between the DAS-28 and CDAI were observed (Weighted kappa of 0.660, 0.519, and 0.741 at 0, 4, and 9 months respectively). Discriminant validity, as assessed by ROC curves at 0, 4th, and 9th months of the evaluation, showed the area under the curve (AUC) of 0.958, 0.985, and 0.914, respectively. The suggested cut-off points for different CDAI disease activity categories according to ROC curves were ≤ 2 (Remission), >2 to ≤ 5 (low), >5 to ≤ 18 (moderate), > 18 (high). These findings indicate that the CDAI has good concordance with DAS 28 in assessing the disease activity in RA patients in this study sample.

Keywords: rheumatoid arthritis, CDAI, disease activity, Sri Lanka, validation

Procedia PDF Downloads 138

Authors: Claire Norman-Maillet

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Insider fraud, otherwise known as occupational, employee, or internal fraud, is a financial crime threat. Perpetrated by defrauding (or attempting to defraud) one’s current, prospective, or past employer, an ‘employee’ covers anyone employed by the company, including board members and contractors. The Coronavirus pandemic has forced insider fraud into the spotlight, and it isn’t dimming. As the focus of most academics and practitioners has historically been on that of ‘external fraud’, insider fraud is often overlooked or not considered to be a real threat. However, since COVID-19 changed the working world, pushing most of us into remote or hybrid working, employers cannot easily keep an eye on what their staff are doing, which has led to reliance on trust and transparency. This, therefore, brings about an increased risk of insider fraud perpetration. The objective of this paper is to explore why insider fraud is, therefore, now the biggest threat to a business. To achieve the research objective, participating individuals within the financial crime sector (either as a practitioner or consultants) attended semi-structured interviews with the researcher. The principal recruitment strategy for these individuals was via the researcher’s LinkedIn network. The main findings in the research suggest that insider fraud has been ignored and rejected as a threat to a business, owing to a reluctance to admit that a colleague may perpetrate. A positive of the Coronavirus pandemic is that it has forced insider fraud into a more prominent position and giving it more importance on a business’ agenda and risk register. Despite insider fraud always having been a possibility (and therefore a risk) within any business, it is very rare that a business has given it the attention it requires until now, if at all. The research concludes that insider fraud needs to prioritised by all businesses, and even ahead of external fraud. The research also provides advice on how a business can add new or enhance existing controls to mitigate the risk.

Keywords: insider fraud, occupational fraud, COVID-19, COVID, coronavirus, pandemic, internal fraud, financial crime, economic crime

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Authors: Iftekhar Hassan, Sayedil Morsalin, Easir A Khan

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Accidents involving fire occur frequently in recent times and their causes showing a great deal of variety which require intervention methods and risk assessment strategies are unique in each case. On September 4, 2020, a fire and explosion occurred in a confined space caused by a methane gas leak from an underground pipeline in Baitus Salat Jame mosque during Night (Esha) prayer in Narayanganj District, Bangladesh that killed 34 people. In this research, this incident is simulated using Fire Dynamics Simulator (FDS) software to analyze and understand the nature of the accident and associated consequences. FDS is an advanced computational fluid dynamics (CFD) system of fire-driven fluid flow which solves numerically a large eddy simulation form of the Navier–Stokes’s equations for simulation of the fire and smoke spread and prediction of thermal radiation, toxic substances concentrations and other relevant parameters of fire. This study focuses on understanding the nature of the fire and consequence evaluation due to thermal radiation caused by vapor cloud explosion. An evacuation modeling was constructed to visualize the effect of evacuation time and fractional effective dose (FED) for different types of agents. The results were presented by 3D animation, sliced pictures and graphical representation to understand fire hazards caused by thermal radiation or smoke due to vapor cloud explosion. This study will help to design and develop appropriate respond strategy for preventing similar accidents.

Keywords: consequence modeling, fire and explosion, fire dynamics simulation (FDS), thermal radiation

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Authors: Irakli Manvelidze, Genadi Iashvili, Giga Phartenadze, Giorgi Katamadze

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Establishment of electronic governance in the region is facing serious problems. Organizational, technical, social and methodological problems have been identified after the research. These problems currently create serious barriers and prevent the development of effective e-governance. Lack of human resources, difference in program targets of the centre and the region, lack of citizens’ awareness about the project of electronic governance are other issues that should be mentioned. In spite of positive changes the overall situation concerning development of modern information-communication technologies in Adjara is not satisfactory. The information systems in the region can be described as transforming in a democratic way which needs serious reforms. Current situation shows that unsystematic, uncoordinated actions were made which overall represents more chaotic rather than coordinated systematic process. Therefore, a strategic document ‘Adjarian Electronic Government’ should be created which will ensure systematic development of electronic governance in the region. The implementation of the strategy of ‘Adjarian Electronic Government’ should be based on not only conceptual and instrumental but also legal basics. A legal normative basis should be created which will include formation of electronic government’s instrumental basis as well as creation of united regional system of electronic document management. Meanwhile types of documents which would be used in inter institutional relations should be defined under a legal norm. Creation of regional united system of e-filing will regulate regional public institutions, relations between local self-government and public organizations as well as it will ensure coordinated work of all regional public institutions.

Keywords: e-government, information society, public administration, reforming state governance, public institutions

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Authors: Nidhi Kaushal, Sanjit Mishra

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Narrative writings in literature are ample source of knowledge and easily understandable. In every old tradition, we found that people learn ethics from oral tales. They had their leaders and lessons of leadership in their stories. In India, we have sufficient amount of stories of leaders. Whether the story is of an ordinary person or a corporate leader of large firm, it always has a unique message of motivation. The objective of this paper is to elaborate the story lines in literature and get the leadership lessons from them, so that we can set up a new concept of leadership based on scholarship of literature. This is our hypothesis that leadership lessons can be learned from the study of literary writings and it can also act an innovative way of learning the management skills through literature. The role of the leader can be familiarly communicated in the form of the tales. Describing a positive psychological narrative from the text is the best way to manifesting an idea into the minds of people. We accomplished this paper that leadership as an attribute can be learned from the folk psychological literary writings.

Keywords: leadership, literature, management, psychology

Procedia PDF Downloads 258

Authors: Daniel Mueller, Melanie Breitbach, Stefan Cornelius, Sarah Pakulla-Dickel, Margaretha Koenig, Anke Prochnow, Mario Scherer

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The European STR standard set (ESS) of loci as well as the new expanded CODIS core loci set as recommended by the CODIS Core Loci Working Group, has led to a higher standardization and harmonization in STR analysis across borders. Various multiplex PCRs assays have since been developed for the analysis of these 17 ESS or 23 CODIS expansion STR markers that all meet high technical demands. However, forensic analysts are often faced with difficult STR results and the questions thereupon. What is the reason that no peaks are visible in the electropherogram? Did the PCR fail? Was the DNA concentration too low? QIAGEN’s newest Investigator STR kits contain a novel Quality Sensor (QS) that acts as internal performance control and gives useful information for evaluating the amplification efficiency of the PCR. QS indicates if the reaction has worked in general and furthermore allows discriminating between the presence of inhibitors or DNA degradation as a cause for the typical ski slope effect observed in STR profiles of such challenging samples. This information can be used to choose the most appropriate rework strategy.Based on the latest PCR chemistry called FRM 2.0, QIAGEN now provides the next technological generation for STR analysis, the Investigator ESSplex SE QS and Investigator 24plex QS Kits. The new PCR chemistry ensures robust and fast PCR amplification with improved inhibitor resistance and easy handling for a manual or automated setup. The short cycling time of 60 min reduces the duration of the total PCR analysis to make a whole workflow analysis in one day more likely. To facilitate the interpretation of STR results a smart primer design was applied for best possible marker distribution, highest concordance rates and a robust gender typing.

Keywords: PCR, QIAGEN, quality sensor, STR

Procedia PDF Downloads 481

Authors: Huimin Zhao, Xiaoquan Liu, Haochen Liu

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The major challenge facing Alzheimer's Disease (AD) drug development is how to effectively improve cognitive function in clinical practice. Growing evidence indicates that stimulating hippocampal neurogenesis is a strategy for restoring cognition in animal models of AD. The mitogen-activated protein kinase (MAPK) pathway is a crucial factor in neurogenesis, which is negatively regulated by Dual-specificity phosphatase 16 (DUSP16). Transcriptome analysis of post-mortem brain tissue revealed up-regulation of DUSP16 expression in AD patients. Additionally, DUSP16 was involved in regulating the proliferation and neural differentiation of neural progenitor cells (NPCs). Nevertheless, whether the effect of DUSP16 on ameliorating cognitive disorders by influencing NPCs differentiation in AD mice remains unclear. Our study demonstrates an association between DUSP16 SNPs and clinical progression in individuals with mild cognitive impairment (MCI). Besides, we found that increased DUSP16 expression in both 3×Tg and SAMP8 models of AD led to NPC differentiation impairments. By silencing DUSP16, cognitive benefits, the induction of AHN and synaptic plasticity, were observed in AD mice. Furthermore, we found that DUSP16 is involved in the process of NPC differentiation by regulating c-Jun N-terminal kinase (JNK) phosphorylation. Moreover, the increased DUSP16 may be regulated by the ETS transcription factor (ELK1), which binds to the promoter region of DUSP16. Loss of ELK1 resulted in decreased DUSP16 mRNA and protein levels. Our data uncover a potential regulatory role for DUSP16 in adult hippocampal neurogenesis and provide a possibility to find the target of AD intervention.

Keywords: alzheimer's disease, cognitive function, DUSP16, hippocampal neurogenesis

Procedia PDF Downloads 61

Authors: Mohammad Reza Fazeli

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Nowadays, the fourth industry, known as the digital transformation of industries, is seen as one of the top subjects in the history of structural revolution, which has led to the high-tech and tactical dominance of the organization. In the face of these profits, the undefined and non-transparent nature of the after-effects of investing in digital transformation has hindered many organizations from attempting this area of this industry. One of the important frameworks in the field of understanding digital transformation in all organizations is the maturity model of digital transformation. This model includes two main parts of digital transformation maturity dimensions and digital transformation maturity stages. Mediating factors of digital maturity and organizational performance at the individual (e.g., motivations, attitudes) and at the organizational level (e.g., organizational culture) should be considered. For successful technology adoption processes, organizational development and human resources must go hand in hand and be supported by a sound communication strategy. Maturity models are developed to help organizations by providing broad guidance and a roadmap for improvement. However, as a result of a systematic review of the literature and its analysis, it was observed that none of the 18 maturity models in the field of digital transformation fully meet all the criteria of appropriateness, completeness, clarity, and objectivity. A maturity assessment framework potentially helps systematize assessment processes that create opportunities for change in processes and organizations enabled by digital initiatives and long-term improvements at the project portfolio level. Cultural characteristics reflecting digital culture are not systematically integrated, and specific digital maturity models for the service sector are less clearly presented. It is also clearly evident that research on the maturity of digital transformation as a holistic concept is scarce and needs more attention in future research.

Keywords: digital transformation, organizational performance, maturity models, maturity assessment

Procedia PDF Downloads 76

Authors: Chunfang Zhou

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The growing issues of sustainability have increased the discussions on how to foster “green engineers” from diverse perspectives in both contexts of education and organizations. As creativity has been considered as the first stage of innovation process that can also be regarded as a path to sustainability, this paper will particularly propose creativity as a scientific literacy meaning a collection of awareness, ability, and skills about sustainability. From this sense, creativity should be an element in IT engineering education and organizational learning programmes, since IT engineers are one group of key actors in designing, researching and developing social media products that are most important channels of improving public awareness of sustainability. This further leads this paper to discuss by which pedagogical strategies and by which training methods in organizations, creativity and sustainability can be integrated into IT engineering education and IT enterprise innovation process in order to meeting the needs of ‘creative engineers’ in the society changes towards sustainability. Accordingly, this paper contributes to future work on the links between creativity, innovation, sustainability, and IT engineering development both theoretically and practically.

Keywords: creativity, innovation, IT engineers, sustainability

Procedia PDF Downloads 309

Authors: Gen Sakoda, Hideki Takayasu, Misako Takayasu

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Waste reduction is a fundamental problem for sustainability. Methods for waste reduction with point-of-sales (POS) data are proposed, utilizing the knowledge of a recent econophysics study on a statistical property of POS data. Concretely, the non-stationary time series analysis method based on the Particle Filter is developed, which considers abnormal fluctuation scaling known as Taylor's law. This method is extended for handling incomplete sales data because of stock-outs by introducing maximum likelihood estimation for censored data. The way for optimal stock determination with pricing the cost of waste reduction is also proposed. This study focuses on the examination of the methods for large sales numbers where Taylor's law is obvious. Numerical analysis using aggregated POS data shows the effectiveness of the methods to reduce food waste maintaining a high profit for large sales numbers. Moreover, the way of pricing the cost of waste reduction reveals that a small profit loss realizes substantial waste reduction, especially in the case that the proportionality constant  of Taylor’s law is small. Specifically, around 1% profit loss realizes half disposal at =0.12, which is the actual  value of processed food items used in this research. The methods provide practical and effective solutions for waste reduction keeping a high profit, especially with large sales numbers.

Keywords: food waste reduction, particle filter, point-of-sales, sustainable development goals, Taylor's law, time series analysis

Procedia PDF Downloads 121

Authors: Reuben Kinyuru Njuguna, Martin Mabuya Njuguna

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Digital platforms, such as The Internet, and the advent of digital marketing strategies, have led to many changes in the marketing of goods and services. These have resulted in improved service quality, enhanced customer relations, productivity gains, marketing transaction cost reductions, improved customer service and flexibility in fulfilling customers’ changing needs and lifestyles. Consequently, the purpose of this study was to determine the effect of digital marketing practices on the financial performance of mobile network operators in the telecommunications industry in Kenya. The objectives of the study were to establish how digital customer relationship management strategies on performance of mobile network operators in Kenya. The study used an explanatory cross-sectional survey research design, while the target population was made up of from the 4 major mobile network operators in Kenya, namely Safaricom Limited, Airtel Networks Kenya Limited, Finserve Africa Limited and Telkom Kenya Limited. Sampling strategy was stratified sampling with a sample size of 97 respondents. Digital customer relationship strategies were seen to influence firm performance, through enhancing convenience, building trust, encouraging growth in market share through creating sustainable relationships, building commitment with customers, enhancing customer retention and customer satisfaction. Digital customer relationship management were seen to maximize gross profits by increasing customer satisfaction, loyalty and retention. The study recommended upscaling the use of digital customer relationship management strategies to further enhance firm performance, given their great potential in this regard.

Keywords: customer relationship management, customer service delivery, performance, customer satisfaction

Procedia PDF Downloads 221

Authors: Ying Wang, Jianhong Xiang, Yu Zhong

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The offset Quadrature Amplitude Modulation-based Filter Bank Multi-Carrier (FBMC) system provides superior spectral properties over Orthogonal Frequency Division Multiplexing. However, seriously affected by imaginary interference, its performances are hampered in many areas. In this paper, we propose a Precoding-Assisted Frequency Division Multiple Access (PA-FDMA) modulation scheme. By spreading FBMC symbols into the frequency domain and transmitting them with a precoding matrix, the impact of imaginary interference can be eliminated. Specifically, we first generate the coding pre-solution matrix with a nonuniform Fast Fourier Transform and pick the best columns by introducing auxiliary factors. Secondly, according to the column indexes, we obtain the precoding matrix for one symbol and impose scaling factors to ensure that the power is approximately constant throughout the transmission time. Finally, we map the precoding matrix of one symbol to multiple symbols and transmit multiple data frames, thus achieving frequency-division multiple access. Additionally, observing the interference between adjacent frames, we mitigate them by adding frequency Cyclic Prefixes (CP) and evaluating them with a signal-to-interference ratio. Note that PA-FDMA can be considered a CP-available FBMC technique because the underlying strategy is FBMC. Simulation results show that the proposed scheme has better performance compared to Single Carrier Frequency Division Multiple Access (SC-FDMA), etc.

Keywords: PA-FDMA, SC-FDMA, FBMC, non-uniform fast fourier transform

Procedia PDF Downloads 43

Authors: Mihai Caramihai, Dan Vasilescu

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The main research objective of the experimental bioprocess analyzed in this paper was to obtain large biomass quantities. The bioprocess is performed in 100 L Bioengineering bioreactor with 42 L cultivation medium made of peptone, meat extract and sodium chloride. The reactor was equipped with pH, temperature, dissolved oxygen, and agitation controllers. The operating parameters were 37 oC, 1.2 atm, 250 rpm and air flow rate of 15 L/min. The main objective of this paper is to present a case study to demonstrate that intelligent control, describing the complexity of the biological process in a qualitative and subjective manner as perceived by human operator, is an efficient control strategy for this kind of bioprocesses. In order to simulate the bioprocess evolution, an intelligent control structure, based on fuzzy logic has been designed. The specific objective is to present a fuzzy control approach, based on human expert’ rules vs. a modeling approach of the cells growth based on bioprocess experimental data. The kinetic modeling may represent only a small number of bioprocesses for overall biosystem behavior while fuzzy control system (FCS) can manipulate incomplete and uncertain information about the process assuring high control performance and provides an alternative solution to non-linear control as it is closer to the real world. Due to the high degree of non-linearity and time variance of bioprocesses, the need of control mechanism arises. BIOSIM, an original developed software package, implements such a control structure. The simulation study has showed that the fuzzy technique is quite appropriate for this non-linear, time-varying system vs. the classical control method based on a priori model.

Keywords: intelligent, control, fuzzy model, bioprocess optimization

Procedia PDF Downloads 311