Search results for: customer discovery

Authors: Mohammad Azam

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The purpose of this study is to investigate risk and real excess portfolio returns using inflation adjusted risk-free rates, a measuring technique that focuses on the momentum augmented Fama-French six-factor model and use monthly data from 1994 to 2022. With the exception of profitability, the data show that market, size, value, momentum, and investment factors are all strongly associated to excess portfolio stock returns using ordinary lease square regression technique. According to the Gibbons, Ross, and Shanken test, the momentum augmented Fama-French six-factor model outperforms the market. This technique discovery may be utilised by academics and professionals to acquire an in-depth knowledge of the Pakistan Stock Exchange across a broad stock pattern for investing decisions and portfolio construction.

Keywords: real excess portfolio returns, momentum augmented fama & french five-factor model, GRS-test, pakistan stock exchange

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Authors: Thilina Ranaweera, Enes Makalic, John L. Hopper, Adrian Bickerstaffe

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Data are the primary asset of biomedical researchers, and the engine for both discovery and research translation. As the volume and complexity of research datasets increase, especially with new technologies such as large single nucleotide polymorphism (SNP) chips, so too does the requirement for software to manage, process and analyze the data. Researchers often need to execute complicated queries and conduct complex analyzes of large-scale datasets. Existing tools to analyze such data, and other types of high-dimensional data, unfortunately suffer from one or more major problems. They typically require a high level of computing expertise, are too simplistic (i.e., do not fit realistic models that allow for complex interactions), are limited by computing power, do not exploit the computing power of large-scale parallel architectures (e.g. supercomputers, GPU clusters etc.), or are limited in the types of analysis available, compounded by the fact that integrating new analysis methods is not straightforward. Solutions to these problems, such as those developed and implemented on parallel architectures, are currently available to only a relatively small portion of medical researchers with access and know-how. The past decade has seen a rapid expansion of data management systems for the medical domain. Much attention has been given to systems that manage phenotype datasets generated by medical studies. The introduction of heterogeneous genomic data for research subjects that reside in these systems has highlighted the need for substantial improvements in software architecture. To address this problem, we have developed SPARK, an enabling and translational system for medical research, leveraging existing high performance computing resources, and analysis techniques currently available or being developed. It builds these into The Ark, an open-source web-based system designed to manage medical data. SPARK provides a next-generation biomedical data management solution that is based upon a novel Micro-Service architecture and Big Data technologies. The system serves to demonstrate the applicability of Micro-Service architectures for the development of high performance computing applications. When applied to high-dimensional medical datasets such as genomic data, relational data management approaches with normalized data structures suffer from unfeasibly high execution times for basic operations such as insert (i.e. importing a GWAS dataset) and the queries that are typical of the genomics research domain. SPARK resolves these problems by incorporating non-relational NoSQL databases that have been driven by the emergence of Big Data. SPARK provides researchers across the world with user-friendly access to state-of-the-art data management and analysis tools while eliminating the need for high-level informatics and programming skills. The system will benefit health and medical research by eliminating the burden of large-scale data management, querying, cleaning, and analysis. SPARK represents a major advancement in genome research technologies, vastly reducing the burden of working with genomic datasets, and enabling cutting edge analysis approaches that have previously been out of reach for many medical researchers.

Keywords: biomedical research, genomics, information systems, software

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Authors: Chris Nelson

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Quality and excellence are qualitative topics that are usually addressed based on knowledge and past experience from leadership and those in charge of the organization. The significance of this study is to highlight the differences and similarities between these two mindsets and how an operational staff can most appropriately use them in the workplace. Quality and excellence are two words that are talked about a lot in the manufacturing world. Buzzwords such as operational excellence, quality controls, and efficiencies are discussed in the boardroom as well on the shop floor. These terms are used quite frequently and with good reasons. When a person visits their favorite local restaurant, They go because 1) they like the food and 2) the people are some of the greatest individuals to be around. With that in mind, they know they always put out quality food. They do not always go because the quality of the food is far superior than other restaurants. But the quality of ingredients always meets their expectations. When they compare them to the term excellence, they are disappointed. The food never looks like the pictures on the menu. But when have you ever been to a restaurant where the food looks the same as on the menu? For them, when evaluating which buzzword to use as a guiding star, its simple: excellence. The corporation can accomplish these goals by operating at a standard that far exceeds customer’s wants and needs.

Keywords: industrial engineering, innovation, management and technology, logistics and scheduling, six sigma

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Authors: Sherrene Bogle, Verlia Bogle, Tyrone Anderson

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In recent years, organizations have become increasingly interested in the possibility of analyzing social media as a means of gaining meaningful feedback about their products and services. The aspect based sentiment analysis approach is used to predict the sentiment for Twitter datasets for Digicel and Lime, the main mobile companies in Jamaica, using supervised learning classification techniques. The results indicate an average of 82.2 percent accuracy in classifying tweets when comparing three separate classification algorithms against the purported baseline of 70 percent and an average root mean squared error of 0.31. These results indicate that the analysis of sentiment on social media in order to gain customer feedback can be a viable solution for mobile companies looking to improve business performance.

Keywords: machine learning, sentiment analysis, social media, supervised learning

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Authors: Jyothirmayee Pola

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Ideally, a test-driven development (TDD) or agile or any other process should be able to define and implement performance, scalability, and reliability (PSR) of the product with a higher quality of service (QOS) and should have the ability to fix any PSR issues with lesser cost before it hits the production. Most PSR test strategies for new product introduction (NPI) include assumptions about production load requirements but never accurate. NPE (New product Enhancement) include assumptions for new features that are being developed whilst workload distribution for older features can be derived by analyzing production transactions. This paper talks about how to shift left PSR towards design phase of release management process to get better QOS w.r.t PSR for any product under development. It also explains the ROI for future customer onboarding both for Service Oriented Architectures (SOA) and Microservices architectures and how to define PSR requirements.

Keywords: component PSR, performance engineering, performance tuning, reliability, return on investment, scalability, system PSR

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Authors: Jim Shih-Chiao Chin, Yu Ting Yeh, Shui Lien Chen, Yi-Fen Tsai

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his study is taking Adidas Company as the object, explored the brand awareness directly or indirectly affects brand affect and word of mouth. First, explored the brand awareness on category fit and image fit, and examined the influence of category fit and image fit on extension attitude. This study then designates the effect of extension attitude on brand affect and word-of-mouth. The relationship of brand awareness on brand affect and word-of-mouth was also explored. The study participants are people who have purchased Adidas extension products. A total of 700 valid questionnaires were collected and statistical software AMOS 20.0 was used to examine the research hypotheses by using structural equation modeling (SEM). Finally, theoretical implications and research directions are provided for future studies.

Keywords: brand extension, brand awareness, product category fit, brand image fit, brand affect, word-of-mouth (WOM)

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Authors: Michal Lysek, Mike Danilovic, Jasmine Lihua Liu

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HMS Industrial Networks AB has been recognized as one of the most innovative companies in the industrial communication industry worldwide. The creation of their Anybus innovation during the 1990s contributed considerably to the company’s success. From inception, HMS’ employees were innovating for the purpose of creating new business (the creation phase). After the Anybus innovation, they began the process of internationalization (the commercialization phase), which in turn led them to concentrate on cost reduction, product quality, delivery precision, operational efficiency, and increasing growth (the growth phase). As a result of this transformation, performing new radical innovations have become more complicated. The purpose of our research was to explore the dynamics of innovation at HMS from the aspect of key actors, activities, and events, over the three phases, in order to understand what led to the creation of their Anybus innovation, and why it has become increasingly challenging for HMS to create new radical innovations for the future. Our research methodology was based on a longitudinal, retrospective study from the inception of HMS in 1988 to 2014, a single case study inspired by the grounded theory approach. We conducted 47 interviews and collected 1 024 historical documents for our research. Our analysis has revealed that HMS’ success in creating the Anybus, and developing a successful business around the innovation, was based on three main capabilities – cultivating customer relations on different managerial and organizational levels, inspiring business relations, and balancing complementary human assets for the purpose of business creation. The success of HMS has turned the management’s attention away from past activities of key actors, of their behavior, and how they influenced and stimulated the creation of radical innovations. Nowadays, they are rhetorically focusing on creativity and innovation. All the while, their real actions put emphasis on growth, cost reduction, product quality, delivery precision, operational efficiency, and moneymaking. In the process of becoming an international company, HMS gradually refocused. In so doing they became profitable and successful, but they also forgot what made them innovative in the first place. Fortunately, HMS’ management has come to realize that this is the case and they are now in search of recapturing innovation once again. Our analysis indicates that HMS’ management is facing several barriers to innovation related path dependency and other lock-in phenomena. HMS’ management has been captured, trapped in their mindset and actions, by the success of the past. But now their future has to be secured, and they have come to realize that moneymaking is not everything. In recent years, HMS’ management have begun to search for innovation once more, in order to recapture their past capabilities for creating radical innovations. In order to unlock their managerial perceptions of customer needs and their counter-innovation driven activities and events, to utilize the full potential of their employees and capture the innovation opportunity for the future.

Keywords: barriers to innovation, dynamics of innovation, in search of excellence and innovation, radical innovation

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Authors: Jeong-Hyun Park, Young-Sik Park, Hyo-Teag Jung

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This paper presents static analysis deployment model for code quality on R&D Projects of SW Development. The proposed model includes the scope of R&D projects and index for static analysis of source code, operation model and execution process, environments and infrastructure system for R&D projects of SW development. There is the static analysis result of pilot project as case study based on the proposed deployment model and environment, and strategic considerations for success operation of the proposed static analysis deployment model for R&D Projects of SW Development. The proposed static analysis deployment model in this paper will be adapted and improved continuously for quality upgrade of R&D projects, and customer satisfaction of developed source codes and products.

Keywords: static analysis, code quality, coding rules, automation tool

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Authors: Murtala Mohammed Alamai, Abdullahi Marshal Idris, Adama Idris

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Today, marketing does not only involve selecting target markets, but it also involves communicating with the customers through various means to put across your selling point. Modern marketing involves driving new product development based on customer needs by getting feedback from them. Utilizing the latest technology for better communication with the customers is the latest advancement in Marketing in the 21st century. The survey approach was used where a sample of tourist destinations across the six geographical zones of the country at random was done to ascertain the use of information communication systems in promoting their products and or services, the findings revealed that only a few utilize these modern advanced means in marketing and promoting their products and a need to develop effective and up to date online services for marketing was proffered as solutions to the findings observed.

Keywords: information, communication, travel, trade, promotion

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Authors: Anna Rogozińska-Pawełczyk

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A psychological contract is an agreement between the employer and an employee that covers the parties’ informal and frequently non-verbalized obligations and expectations towards each other. The contract is a cognitive pattern-governing employee’s behaviour in the organization. A gap between employee’s expectations and the organizational reality may lead to difficult-to-solve conflicts or cause the employee to modify their behaviour towards organizational values and goals, if they are willing and ready to verbalize their expectations. The article discusses psychological contracts in the financial institutions in Poland. Its theoretical part outlines the types of psychological contracts in organizations (relational, transactional, and balanced) and shows the process of their verbalization. The purpose of the article is to present how the type of the psychological contract relates to employee’s readiness to verbalize it. The article ends with conclusions arising from the study.

Keywords: customer contact staff in banks, employee expectations, financial institutions, mutual expectations, psychological contract, verbalization of the psychological contract

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Authors: Jana Ismail, Layla Fallatah, Maha Alshmaisi

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ChatGPT, a cutting-edge language model built on the GPT-3.5 architecture, has garnered attention for its profound natural language processing capabilities, holding promise for transformative applications in customer service and content creation. This study delves into ChatGPT's architecture, aiming to comprehensively understand its strengths and potential limitations. Through systematic experiments across diverse domains, such as general knowledge and creative writing, we evaluated the model's coherence, context retention, and task-specific accuracy. While ChatGPT excels in generating human-like responses and demonstrates adaptability, occasional inaccuracies and sensitivity to input phrasing were observed. The study emphasizes the impact of prompt design on output quality, providing valuable insights for the nuanced deployment of ChatGPT in conversational AI and contributing to the ongoing discourse on the evolving landscape of natural language processing in artificial intelligence.

Keywords: artificial Inelegance, chatGPT, open AI, NLP

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Authors: Manuela Nayantara Jeyaraj

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'Digital Divide' is a concept that has existed in this paradigm ever since the discovery of the first-generation technologies. Before the turn of the century, it was basically used to describe the gap between those with telephone communication access and those without it. At present, it is plainly descriptive in itself to illustrate the cavity among those with Internet access and those without. Though the concept of digital divide has been merely lying in sight for as long as time itself, the friction it caused has not yet been fully realized to solve major crisis situations. Unlike well-developed countries, Sri Lanka is still in the verge of moving farther away from a developing country in the race towards reaching a developed state. Access to technological resources varies from region to region, even within the island itself, with one region having a considerable percentage of its community exposed to the Internet and its related technologies, and the other unaware of such. Thus, this paper intends to analyze the roots for the still-extant gap instigated based on the concept of ‘Digital Divide’ and explores the plausible potentials that could be brought about by narrowing this prevailing percentage among the population, specifically entrenching the advantages reaped towards an economic augmentation and culture or lifestyle revolution on the path towards development.

Keywords: communication, digital divide, society, Sri Lanka

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Authors: Tarun Jain, Lovnish Gupta, Soumen Basu

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Organic pollutants like phenols and organic dyes present in industrial waste water are posing a hazardous threat to aquatic ecosystem. Several measures have been adopted for the neutralization and photodecomposition of these harmful organic moieties, among these semiconductor photocatalysis has been provided a major thrust after the discovery of Honda-Fujishema effect. Present study demonstrates the adsorption of TiO2- P25 in nano size (~36 nm) on cement balls for effective photodegradation of Alizarin and penta chlorophenol (PCP) under UV light illumination. Triton-X was used as a stabilizer for effective adsorption of TiO2 on cement balls (TCB) followed by calcination at ~300oC for 4 h. The TCB’s were dispersed randomly in a self designed reactor for phototcatalytic performance as shown in scheme 1. The change in concentration of alizarin and PCP was observed under UV-Vis spectroscopy, PCP was detoxified within 40 min while alizarin photodecomposed within 15 min of UV light irradiation. Taking into consideration the go green slogan and future prospective this technique can be also utilized under visible light and on mass scale because this is an effective tool for environmental remediation and waste water treatment.

Keywords: organic pollutants, TiO2 cement balls, photodegradation, UV light irradiation

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Authors: Salma Kaouthar Letaief

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This article investigates the experience of diaspora in the writings of Algerian diasporic writers, namely: Leila Sebbar’s Silence on the Shores (2000), Keltoum Staali’ December’s Mimosa (2012). The study discusses the collective trauma of violence in Algeria and overseas. The experience of displacement of the characters to an alien territory compel their journey with issues related to nostalgia, identity crisis, alienation, racism, and in-betweeness. The focus in this research is, thus, on Algerian immigrants’ experience in the host country and their psychological conflicts. The theories Multiculturalism and Psychoanalysis are used to analyse the novels in this paper. While Multiculturalism examines how characters negotiate and navigate their identities in multicultural settings, Psychoanalysis enables the analysis of how characters in diasporic novels grapple with issues of identity, belonging, and self-discovery. Hence, interweaving multiculturalism and psychoanalysis provides an interdisciplinary framework that addresses both the socio-cultural and psychological aspects of the diasporic experience. Accordingly, this paper is an attempt to examine the diasporic experience and cultural dialectics.

Keywords: diaspora, algerian diasporic writers, trauma, algeria, displacement, identity crisis, cultural dialects

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Authors: Saleh Abu Hashanah, Abirami Radhakrishnan, Dessa David

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Sustainable practices in the supply chain have been an area of focus that require consideration of environmental, economic, and social sustainability practices. This paper aims to examine the use of blockchain as a disruptive technology to promote sustainable supply chains. Content analysis was used to analyze the uses of blockchain technology in sustainable supply chains. The results showed that blockchain technology features such as traceability, transparency, smart contracts, accountability, trust, immutability, anti-fraud, and decentralization promote sustainable supply chains. It is found that these features have impacted organizational efficiency in operations, transportation, and production, minimizing costs and reducing carbon emissions. In addition, blockchain technology has been found to elicit customer trust in the products.

Keywords: blockchain technology, sustainability, supply chains, economic sustainability, environmental sustainability, social sustainability

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Authors: Awatef Hicheur Cairns, Billel Gueni, Hind Hafdi, Christian Joubert, Nasser Khelifa

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Given the ever changing needs of the job markets, education and training centers are increasingly held accountable for student success. Therefore, education and training centers have to focus on ways to streamline their offers and educational processes in order to achieve the highest level of quality in curriculum contents and managerial decisions. Educational process mining is an emerging field in the educational data mining (EDM) discipline, concerned with developing methods to discover, analyze and provide a visual representation of complete educational processes. In this paper, we present our distributed computation platform which allows different education centers and institutions to load their data and access to advanced data mining and process mining services. To achieve this, we present also a comparative study of the different clustering techniques developed in the context of process mining to partition efficiently educational traces. Our goal is to find the best strategy for distributing heavy analysis computations on many processing nodes of our platform.

Keywords: educational process mining, distributed process mining, clustering, distributed platform, educational data mining, ProM

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Authors: Ali Murat Guler

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A variety of experiments have been developed over the past decades, aiming at the detection of Weakly Interactive Massive Particles (WIMPs) via their scattering in an instrumented medium. The sensitivity of these experiments has improved with a tremendous speed, thanks to a constant development of detectors and analysis methods. Detectors capable of reconstructing the direction of the nuclear recoil induced by the WIMP scattering are opening a new frontier to possibly extend Dark Matter searches beyond the neutrino background. Measurement of WIMP’s direction will allow us to detect the galactic origin of dark matter and, therefore to have a clear signal-background separation. The NEWSdm experiment, based on nuclear emulsions, is intended to measure the direction of WIMP-induced nuclear coils with a solid-state detector, thus with high sensitivity. We discuss the discovery potential of a directional experiment based on the use of a solid target made of newly developed nuclear emulsions and novel read-out systems achieving nanometric resolution. We also report results of a technical test conducted in Gran Sasso.

Keywords: dark matter, direct detection, nuclear emulsion, WIMPS

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Authors: Lee Bih Ni, Kiu Su Na

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This paper discusses the Chinese Language Teaching as a Second Language by focusing on Immersion Teaching. Researchers used narrative literature review to describe the current states of both art and science in focused areas of inquiry. Immersion teaching comes with a standard that teachers must reliably meet. Chinese language-immersion instruction consists of language and content lessons, including functional usage of the language, academic language, authentic language, and correct Chinese sociocultural language. Researchers used narrative literature reviews to build a scientific knowledge base. Researchers collected all the important points of discussion, and put them here with reference to the specific field where this paper is originally based on. The findings show that Chinese Language in immersion teaching is not like standard foreign language classroom; immersion setting provides more opportunities to teach students colloquial language than academic. Immersion techniques also introduce a language’s cultural and social contexts in a meaningful and memorable way. It is particularly important that immersion teachers connect classwork with real-life experiences. Immersion also includes more elements of discovery and inquiry based learning than do other kinds of instructional practices. Students are always and consistently interpreted the conclusions and context clues.

Keywords: a second language, Chinese language teaching, immersion teaching, instructional strategies

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Authors: Senda Trabelsi, Sébastien Poncet, Michel Poirier

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Ice slurries are considered as a promising phase-changing secondary fluids for air-conditioning, packaging or cooling industrial processes. An experimental study has been here carried out to measure the rheological characteristics of ice slurries. Ice slurries consist in a solid phase (flake ice crystals) and a liquid phase. The later is composed of a mixture of liquid water and an additive being here either (1) Propylene-Glycol (PG) or (2) Ethylene-Glycol (EG) used to lower the freezing point of water. Concentrations of 5%, 14% and 24% of both additives are investigated with ice mass fractions ranging from 5% to 85%. The rheological measurements are carried out using a Discovery HR-2 vane-concentric cylinder with four full-length blades. The experimental results show that the behavior of ice slurries is generally non-Newtonian with shear-thinning or shear-thickening behaviors depending on the experimental conditions. In order to determine the consistency and the flow index, the Herschel-Bulkley model is used to describe the behavior of ice slurries. The present results are finally validated against an experimental database found in the literature and the predictions of an Artificial Neural Network model.

Keywords: ice slurry, propylene-glycol, ethylene-glycol, rheology

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Authors: Lien-Fa Lin, Yung-Ming Li, Fu-Shun Hsieh

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With the advancement of information technology and development of group commerce, people have obviously changed in their lifestyle. However, group commerce faces some challenging problems. The products or services provided by vendors do not satisfactorily reflect customers’ opinions, so that the sale and revenue of group commerce gradually become lower. On the other hand, the process for a formed customer group to reach group-purchasing consensus is time-consuming and the final decision is not the best choice for each group members. In this paper, we design a social decision support mechanism, by using group discussion message to recommend suitable options for group members and we consider social influence and personal preference to generate option ranking list. The proposed mechanism can enhance the group purchasing decision making efficiently and effectively and venders can provide group products or services according to the group option ranking list.

Keywords: social network, group decision, text mining, group commerce

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Authors: Panaya Sudta, Wanchalerm Patanacharoenwong, Prachya Bumrungkun

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As With the evolution of smart grids, ensuring the reliability and efficiency of electrical systems in smart cities has become crucial. This paper proposes a distinct approach that combines advanced machine learning techniques to accurately predict electrical failures and address voltage reliability issues. This approach aims to improve the accuracy and efficiency of reliability evaluations in smart cities. The aim of this research is to develop a comprehensive predictive model that accurately predicts electrical failures and voltage reliability in smart cities. This model integrates RFM analysis, K-means clustering, and LSTM networks to achieve this objective. The research utilizes RFM analysis, traditionally used in customer value assessment, to categorize and analyze electrical components based on their failure recency, frequency, and monetary impact. K-means clustering is employed to segment electrical components into distinct groups with similar characteristics and failure patterns. LSTM networks are used to capture the temporal dependencies and patterns in customer data. This integration of RFM, K-means, and LSTM results in a robust predictive tool for electrical failures and voltage reliability. The proposed model has been tested and validated on diverse electrical utility datasets. The results show a significant improvement in prediction accuracy and reliability compared to traditional methods, achieving an accuracy of 92.78% and an F1-score of 0.83. This research contributes to the proactive maintenance and optimization of electrical infrastructures in smart cities. It also enhances overall energy management and sustainability. The integration of advanced machine learning techniques in the predictive model demonstrates the potential for transforming the landscape of electrical system management within smart cities. The research utilizes diverse electrical utility datasets to develop and validate the predictive model. RFM analysis, K-means clustering, and LSTM networks are applied to these datasets to analyze and predict electrical failures and voltage reliability. The research addresses the question of how accurately electrical failures and voltage reliability can be predicted in smart cities. It also investigates the effectiveness of integrating RFM analysis, K-means clustering, and LSTM networks in achieving this goal. The proposed approach presents a distinct, efficient, and effective solution for predicting and mitigating electrical failures and voltage issues in smart cities. It significantly improves prediction accuracy and reliability compared to traditional methods. This advancement contributes to the proactive maintenance and optimization of electrical infrastructures, overall energy management, and sustainability in smart cities.

Keywords: electrical state prediction, smart grids, data-driven method, long short-term memory, RFM, k-means, machine learning

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Authors: Christopher Viens, Bosko Gajic, Steve Krase

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Stick-Slip is a term that is often overused and commonly diagnosed from surface drilling parameters of torque and differential pressure, but the actual magnitude of the condition is rarely captured at the BHA level as the necessary measurements are seldom deployed. Deployment of an accurate stick-slip measurement downhole has led to an interesting discovery that goes against long held traditional drilling lore. A divide has been identified between stick-slip as independent bit and BHA conditions. This phenomenon in horizontal laterals is common, but few M/LWD systems have been able to capture it. Utilizing measurements of downhole RPM bore pressure, high-speed magnetometer data, bending moment, and continuous inclination, the wellbore spiraling phenomenon is able to be captured, quantified, and intimately tied back to systematic effects of BHA stalling and micro-sliding. An operator in the Permian Basin has identified that this phenomenon is contributing to increased tortuosity and drag. Utilizing downhole torque measurements the root causes of the stick-slip and spiraling phenomenon were identified and able to engineered out of the system.

Keywords: bending moment, downhole dynamics measurements, micro sliding, wellbore spiraling

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Authors: Fuyang Peng, Donghong Li

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The aim of information systems integration is to make all the data sources, applications and business flows integrated into the new environment so that unwanted redundancies are reduced and bottlenecks and mismatches are eliminated. Two issues have to be dealt with to meet such requirements: the software architecture that supports resource integration, and the adaptor development tool that help integration and migration of legacy applications. In this paper, a service-enabled dependable integration environment (SDIE), is presented, which has two key components, i.e., a dependable service integration platform and a legacy application integration tool. For the dependable platform for service integration, the service integration bus, the service management framework, the dependable engine for service composition, and the service registry and discovery components are described. For the legacy application integration tool, its basic organization, functionalities and dependable measures taken are presented. Due to its service-oriented integration model, the light-weight extensible container, the service component combination-oriented p-lattice structure, and other features, SDIE has advantages in openness, flexibility, performance-price ratio and feature support over commercial products, is better than most of the open source integration software in functionality, performance and dependability support.

Keywords: application integration, dependability, legacy, SOA

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Authors: Sivilai Jayankura

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The objective is to study the behaviors, lifestyles and consumption of the student of Suan Sunandha Rajabhat University. This paper is survey research by using a questionnaire to collect the data with students of Suan Sunandha Rajabhat University for 385 sampling, random coincidence sampling has been provide. Data analysis by descriptive statistics include the distribution, frequency, percentage, average, and standard deviation. The result found that the majority of students are female, and spend their time with their own ideas, like socializing with friends and shopping at the shopping mall, see the movie at the theaters and at the night time will enjoy with their mobile phone and found they long for the quality-price and also brand name regarding the dress. The media and promotion is a key factor impact to the decision to purchase the product and service with mobile phones will be good business to expand business channel also.

Keywords: consumption of teenager, internet, lifestyle behavior, Suan Sunundha Rajabhat University

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Authors: Itiola Kehinde Adeniran

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This paper investigated the influence of harnessing entrepreneurial opportunities on the national security in Nigeria with a specific focus on the security situation of the post-amnesty programmes of the Federal Government in Ondo State. The self-administered structured questionnaire was employed to collect data from one hundred and twenty participants through purposive sampling method. Inferential statistics was used to analyze the data, specifically; ordinary least squares linear regression method was employed with the aid of statistical package for social science (SPSS) version 20 in order to determine the influence of independent variable (entrepreneurial opportunities) on dependent variable (national security). The result showed that business opportunities have a significant influence on the rate of criminal activities. The study also revealed that entrepreneurial opportunity creation and discovery as well as providing a model on how these entrepreneurial opportunities could be effectively and efficiently utilized jointly predict better national security, which counted for 69% variance of crime rate reduction. The paper, therefore, recommended that citizens should be encouraged to develop an interest in the skill-based activities in order to change their mindset towards self-employment which can motivate them in identify entrepreneurial opportunities.

Keywords: entrepreneurship, entrepreneurial opportunities, national security, unemployment

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Authors: Mona Rezaei, Habib Honari, Mehrzad Hamidi, Fatemeh Kiani

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Make strong brands has become a priority for many organizations in marketing. Brand is an important indicator of marketing status. Brand Strength is in kept customer, profit, brand development and gain competitive advantage and In fact it is a concept that was created from a consumer perspective. It is assumed that the creation of a strong brand is creating numerous marketing benefits. The purpose of this study was to evaluate the psychometric characteristics of the questionnaire the most strong sports brands in the consumer society. Questionnaire was conducted to a sample of 340 customers of sports brands. Psychometric parameters were determined by using appropriate statistical methods. The results of the factor analysis and Varimax rotation revealed five factors of strong brands. The results confirms that questionnaire structure have acceptable associated to the data and confirmed all indicators of the model. Reliability (859/0) was satisfactory. According to calculated psychometric indices, this questionnaire could be appropriate to assess the most strong sports brands.

Keywords: reliability, strong brand, sport brands, psychometric

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Authors: Pablo Martinez, Emad Mohamed, Osama Mohsen, Yasser Mohamed

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Highway and bridge agencies, such as the Ministry of Transportation in Ontario, use the Bridge Condition Index (BCI) which is defined as the weighted condition of all bridge elements to determine the rehabilitation priorities for its bridges. Therefore, accurate forecasting of BCI is essential for bridge rehabilitation budgeting planning. The large amount of data available in regard to bridge conditions for several years dictate utilizing traditional mathematical models as infeasible analysis methods. This research study focuses on investigating different classification models that are developed to predict the bridge condition index in the province of Ontario, Canada based on the publicly available data for 2800 bridges over a period of more than 10 years. The data preparation is a key factor to develop acceptable classification models even with the simplest one, the k-NN model. All the models were tested, compared and statistically validated via cross validation and t-test. A simple k-NN model showed reasonable results (within 0.5% relative error) when predicting the bridge condition in an incoming year.

Keywords: asset management, bridge condition index, data mining, forecasting, infrastructure, knowledge discovery in databases, maintenance, predictive models

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Authors: Sabahattin Comertpay, Sandra Pastorino, Rosanna Mezzapelle, Mika Tanji, Oriana Strianese, Andrea Napolitano, Tracey Weigel, Joseph Friedberg, Paul Sugarbaker, Thomas Krausz, Ena Wang, Amy Powers, Giovanni Gaudino, Harvey I. Pass, Fatmagul Ozcelik, Barbara L. Parsons, Haining Yang, Michele Carbone

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Tumors are thought to be monoclonal in origin. This paradigm arose decades ago, primarily from the study of hematopoietic malignancies and sarcomas. The clonal origin of malignant mesothelioma (MM), a deadly cancer resistant to the current therapies, has not been investigated. Examination of the pleura from patients with MM shows often the presence of multiple pleural nodules, raising the question of whether they represent independent or metastatic growth processes. To investigate the clonality patterns of MM, we used the HUMARA (Human Androgen Receptor) assay to examine 14 sporadic and 2 familial Malignant Mesotheliomas (MM). Of 16 specimens studied, 15 were informative and 14/15 revealed two electrophoretically distinct methylated HUMARA alleles, indicating a polyclonal origin for these tumors. This discovery has important clinical implications, because an accurate assessment of tumor clonality is key to the design of novel molecular strategies for the treatment of MM.

Keywords: malignant mesothelioma, clonal origin, HUMARA, sarcomas

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Authors: Subarna Ferdous, Mitsuru Ikeda

Abstract:

For the shrimp companies to remain relevant to its local and international consumers, they must offer new shrimp product and services. It must work actively not just to create value for the consumer, but to involve the consumer in co-creating value for shrimp product innovation in the market. In this theoretical work, we conceptualize the business concept of value co-creation in the context of shrimp products, and propose a framework of value co-creation for shrimp product innovation in shrimp industries. With guidance on value co-creation in in shrimp industry, and shrimp value chain actors mapped to the co-creation cycle, companies can use the framework to offer new shrimp product to consumer communities. Although customer co-creation is known approach in the world, it is not commonly used by the companies in Bangladesh. This paper makes an original contribution by conceptualizing co-creation and set the examples of best co-creation practices in food sector. The results of the study provide management with guidelines for successful co-creation projects with an innovation- and market-oriented approach. The framework also provides a basis for further research in this area.

Keywords: bangladesh, shrimp industry, value co-creation, shrimp product

Procedia PDF Downloads 497

Authors: Fatima Ammari, Meriem Chenouf

Abstract:

Synthesis of gold nano particles has attracted much attention since the pioneering discovery of the high catalytic activity of supported gold nano particles in the reaction of CO oxidation at low temperature. In this research field, we used Na-montmorillonite for gold nanoparticles stabilization; different loading percentage 1, 2 and 5%. The gold nano particles were obtained using chemical reduction method using NaBH4 as reductant agent. The obtained gold nano particles Au-mont stabilized in Na-montmorillonite were used as catalysts for reduction of 4-nitrophenol to aminophenol with sodium borohydride at room temperature. The UV-Vis results confirm directly the gold nano particles formation. The XRD and N2 adsorption results showed the formation of gold nano particles in the pores of montmorillonite with an average size of 5 nm obtained on samples with 2%Au-mont. The gold particles size increased with the increase of gold loading percentage. The reduction reaction of 4-nitrophenol into 4-aminophenol with NaBH4 catalyzed by Au-Na-montmorillonite catalyst exhibits remarkably a high activity; the reaction was completed within 9 min for 1Au-mont and within 3 min for 2Au-mont.

Keywords: chemical reduction, gold, montmorillonite, nano particles, 4-nitrophenol

Procedia PDF Downloads 301