Search results for: intelligent late

Authors: Maggie Shen

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Ever since the late 20th century, business giants have been competing to provide better experiences for their users. One way they strive to do so is through more efficiently connecting users with their goals, with recommendation systems that filter out unnecessary or less relevant information. Today’s top online platforms such as Amazon, Netflix, Airbnb, Tiktok, Facebook, and Google all utilize algorithmic recommender systems for different purposes—Product recommendation, movie recommendation, travel recommendation, relationship recommendation, etc. However, while bringing unprecedented convenience and efficiency, the prevalence of algorithmic recommendation systems also influences society in many ways. In using a variety of primary, secondary, and social media sources, this paper explores the impacts of algorithms, particularly algorithmic recommender systems, on different sectors of society. Four fields of interest will be specifically addressed in this paper: economy, international relations, political ideologies, and education.

Keywords: algorithms, economy, international relations, political ideologies, education

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Authors: Hsien-Tsen Wang

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Business Intelligence (BI) has long helped organizations make informed decisions based on data-driven insights and gain competitive advantages in the marketplace. In the past two decades, businesses witnessed not only the dramatically increasing volume and heterogeneity of business data but also the emergence of new technologies, such as Artificial Intelligence (AI), Semantic Web (SW), Cloud Computing, and Big Data. It is plausible that the convergence of these technologies would bring more value out of business data by establishing linked data frameworks and connecting in ways that enable advanced analytics and improved data utilization. In this paper, we first review and summarize current BI applications and methodology. Emerging technologies that can be integrated into BI applications are then discussed. Finally, we conclude with a proposed synergy framework that aims at achieving a more flexible, scalable, and intelligent BI solution.

Keywords: business intelligence, artificial intelligence, semantic web, big data, cloud computing

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Authors: Dmitriy Babenko, Sergey Yegorov, Ilya Korshukov, Aidana Sultanbekova, Valentina Barkhanskaya, Tatiana Bashirova, Yerzhan Zhunusov, Yevgeniya Li, Viktoriya Parakhina, Svetlana Kolesnichenko, Yeldar Baiken, Aruzhan Pralieva, Zhibek Zhumadilova, Matthew S. Miller, Gonzalo H. Hortelano, Anar Turmuhambetova, Antonella E. Chesca, Irina Kadyrova

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Introduction: The rapidly evolving COVID-19 pandemic, along with the re-emergence of pathogens causing acute respiratory infections (ARI), has necessitated the development of novel diagnostic tools to differentiate various causes of ARI. MALDI-MS, due to its wide usage and affordability, has been proposed as a potential instrument for diagnosing SARS-CoV-2 versus non-SARS-CoV-2 ARI. The aim of this study was to investigate the potential of MALDI-MS in conjunction with a machine learning model to accurately distinguish between symptomatic infections caused by SARS-CoV-2 and non-SARS-CoV-2 during both the early and later phases of the pandemic. Furthermore, this study aimed to analyze mass spectrometry (MS) data obtained from nasal swabs of healthy individuals. Methods: We gathered mass spectra from 252 samples, comprising 108 SARS-CoV-2-positive samples obtained in 2020 (Covid 2020), 7 SARS-CoV- 2-positive samples obtained in 2023 (Covid 2023), 71 samples from symptomatic individuals without SARS-CoV-2 (Control non-Covid ARVI), and 66 samples from healthy individuals (Control healthy). All the samples were subjected to RT-PCR testing. For data analysis, we employed the caret R package to train and test seven machine-learning algorithms: C5.0, KNN, NB, RF, SVM-L, SVM-R, and XGBoost. We conducted a training process using a five-fold (outer) nested repeated (five times) ten-fold (inner) cross-validation with a randomized stratified splitting approach. Results: In this study, we utilized the Covid 2020 dataset as a case group and the non-Covid ARVI dataset as a control group to train and test various machine learning (ML) models. Among these models, XGBoost and SVM-R demonstrated the highest performance, with accuracy values of 0.97 [0.93, 0.97] and 0.95 [0.95; 0.97], specificity values of 0.86 [0.71; 0.93] and 0.86 [0.79; 0.87], and sensitivity values of 0.984 [0.984; 1.000] and 1.000 [0.968; 1.000], respectively. When examining the Covid 2023 dataset, the Naive Bayes model achieved the highest classification accuracy of 43%, while XGBoost and SVM-R achieved accuracies of 14%. For the healthy control dataset, the accuracy of the models ranged from 0.27 [0.24; 0.32] for k-nearest neighbors to 0.44 [0.41; 0.45] for the Support Vector Machine with a radial basis function kernel. Conclusion: Therefore, ML models trained on MALDI MS of nasopharyngeal swabs obtained from patients with Covid during the initial phase of the pandemic, as well as symptomatic non-Covid individuals, showed excellent classification performance, which aligns with the results of previous studies. However, when applied to swabs from healthy individuals and a limited sample of patients with Covid in the late phase of the pandemic, ML models exhibited lower classification accuracy.

Keywords: SARS-CoV-2, MALDI-TOF MS, ML models, nasopharyngeal swabs, classification

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Authors: William Elnemer, Nauman Hussain, Samir Al-Ali, Henry Shu, Diane Ghanem, Babar Shafiq

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Introduction: The incidence of infection in open tibial shaft injuries varies depending on the severity of the injury, with rates ranging from 1.8% for Gustilo-Anderson type I to 42.9% for type IIIB fractures. The timely administration of antibiotics upon presentation to the emergency department (ED) is an essential component of fracture management, and evidence indicates that prompt delivery of antibiotics is associated with improved outcomes. The objective of this study is to identify factors that contribute to the expedient administration of antibiotics. Methods: This is a retrospective study of open tibial shaft fractures at an academic Level I trauma center. Current Procedural Terminology (CPT) codes identified all patients treated for open tibial shaft fractures between 2015 and 2021. Open fractures were identified by reviewing ED and provider notes, and with ballistic fractures were considered open. Chart reviews were performed to extract demographics, fracture characteristics, postoperative outcomes, time to operative room, time to antibiotic order, and delivery. Univariate statistical analysis compared patients who received early antibiotics (EA), which were delivered within one hour of ED presentation, and those who received late antibiotics (LA), which were delivered outside of one hour of ED presentation. A multivariate analysis was performed to investigate patient, fracture, and transport/ED characteristics contributing to faster delivery of antibiotics. The multivariate analysis included the dependent variables: ballistic fracture, activation of Delta Trauma, Gustilo-Andersen (Type III vs. Type I and II), AO-OTA Classification (Type C vs. Type A and B), arrival between 7 am and 11 pm, and arrival via Emergency Medical Services (EMS) or walk-in. Results: Seventy ED patients with open tibial shaft fractures were identified. Of these, 39 patients (55.7%) received EA, while 31 patients (44.3%) received LA. Univariate analysis shows that the arrival via EMS as opposed to walk-in (97.4% vs. 74.2%, respectively, p = 0.01) and activation of Delta Trauma (89.7% vs. 51.6%, respectively, p < 0.001) was significantly higher in the EA group vs. the LA group. Additionally, EA cases had significantly shorter intervals between the antibiotic order and delivery when compared to LA cases (0.02 hours vs. 0.35 hours, p = 0.007). No other significant differences were found in terms of postoperative outcomes or fracture characteristics. Multivariate analysis shows that a Delta Trauma Response, arrival via EMS, and presentation between 7 am and 11 pm were independent predictors of a shorter time to antibiotic administration (Odds Ratio = 11.9, 30.7, and 5.4, p = 0.001, 0.016, and 0.013, respectively). Discussion: Earlier antibiotic delivery is associated with arrival to the ED between 7 am and 11 pm, arrival via EMS, and a coordinated Delta Trauma activation. Our findings indicate that in cases where administering antibiotics is critical to achieving positive outcomes, it is advisable to employ a coordinated Delta Trauma response. Hospital personnel should be attentive to the rapid administration of antibiotics to patients with open fractures who arrive via walk-in or during late-night hours.

Keywords: antibiotics, emergency department, fracture management, open tibial shaft fractures, orthopaedic surgery, time to or, trauma fractures

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Authors: Svetlana Chovancova, Frantisek Illek, Jan Winkler

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The effect of tillage technology of maize on intensity of weed infestation and weed species composition was observed at experimental field. Maize is grown consecutively since 2001. The experimental site is situated at an altitude of 230 m above sea level in the Czech Republic. Variants of tillage technology are CT: plowing – conventional tillage 0.22 m, MT: loosening – disc tillage on the depth of 0.1 – 0.12 m, NT: direct sowing – without tillage. The evaluation of weed infestation was carried out by numerical method in years 2012 and 2013. Within the monitoring were found 20 various species of weeds. Conventional tillage (CT) primarily supports the occurrence of perennial weeds (Cirsium arvense, Convolvulus arvensis). Late spring species (Chenopodium album, Echinochloa crus-galli) were more frequently noticed on variants of loosening (MT) and direct sowing (NT). Different tillage causes a significant change of weed species spectrum in maize.

Keywords: weeds, maize, tillage, loosening, direct sowing

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Authors: H. Yousefnia, R. Enayati, M. Hosntalab, S. Zolghadri, A. Bahrami-Samani

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Bone metastases occur in many cases at an early stage of the tumour disease, however their symptoms are recognized rather late. The aim of this study was the preparation of 153Sm-(4-{[bis-(phosphonomethyl))carbamoyl]methyl}-7,10-bis(carboxymethyl) 1,4,7,10-tetraazacyclododec-1-yl) acetic acid (BPAMD) for bone pain palliation therapy. 153Sm was produced at Tehran research reactor via 152Sm(n,γ)153Sm reaction. 200 µl of 1mg/ml BPAMD solution was added to the vial containing 1 mCi 153Sm and the mixture was heated up to 90 0C for 1 h. The radiochemical purity of the complex was measured by ITLC method. The final solution with radiochemical purity of more than 95% was injected to BALB mice and bio distribution was determined up to 48 h. SPECT images were acquired after 2 and 24 h post injection. While high bone uptake was confirmed by both the bio distribution studies and SPECT imaging, accumulation in other organs was approximately negligible. The results show that 153Sm-BPAMD can be used as an excellent tracer for bone pain palliation therapy.

Keywords: bone metastases, BPAMD, 153Sm, radiotherapy

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Authors: Ali Ganoun, Wesam Algablawi, Wasim BenAnaif

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Video based traffic surveillance based on License Plate Recognition (LPR) system is an essential part for any intelligent traffic management system. The LPR system utilizes computer vision and pattern recognition technologies to obtain traffic and road information by detecting and recognizing vehicles based on their license plates. Generally, the video based LPR system is a challenging area of research due to the variety of environmental conditions. The LPR systems used in a wide range of commercial applications such as collision warning systems, finding stolen cars, controlling access to car parks and automatic congestion charge systems. This paper presents an automatic LPR system of Libyan license plate. The performance of the proposed system is evaluated with three video sequences.

Keywords: license plate recognition, localization, segmentation, recognition

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Authors: Manolo Dulva Hina, Clement Thierry, Assia Soukane, Amar Ramdane-Cherif

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In this paper, we presented our innovative way of determining the driving context for a driving assistance system. We invoke the fusion of all parameters that describe the context of the environment, the vehicle and the driver to obtain the driving context. We created a training set that stores driving situation patterns and from which the system consults to determine the driving situation. A machine-learning algorithm predicts the driving situation. The driving situation is an input to the fission process that yields the action that must be implemented when the driver needs to be informed or assisted from the given the driving situation. The action may be directed towards the driver, the vehicle or both. This is an ongoing work whose goal is to offer an alternative driving assistance system for safe driving, green driving and comfortable driving. Here, ontologies are used for knowledge representation.

Keywords: cognitive driving, intelligent transportation system, multimodal system, ontology, machine learning

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Authors: Madhuri, H. R. Tewari, P. K. Bhowmick

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The study attempts to find out the role of the community and the government support, flood experience, flood education, and education of the male-headed households in their livelihood resilience. The study is based on a randomly drawn sample of 472 households from the river basins of Ganga and Kosi in the district of Bhagalpur, Bihar. Structural equation modeling (SEM) and analysis of variance (ANOVA) methods are used to analyze the data. The findings of the study reveal that the role(s) of the community support though is found to be more significant in comparison to the government supports for its stand by position in rescue and livelihood resilience of the affected households whereas the government support arrives late and in far less quantity than what is required. However, the government's support is equally vital due its control over resources, which essentially needed in rescue and rehabilitation of the affected households. The study unravels the strategic value of households' indigenous knowledge and their flood experience in livelihood resilience.

Keywords: flood education, flood experience, livelihood resilience, community support, government support

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Authors: Si Chen, Quanhong Jiang

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In the increasingly mature posture recognition technology, human movement information is widely used in sports rehabilitation, human-computer interaction, medical health, human posture assessment, and other fields today; this project uses the most original ideas; it is proposed to use the collection equipment for the collection of myoelectric data, reflect the muscle posture change on a degree of freedom through data processing, carry out data-muscle three-dimensional model joint adjustment, and realize basic pose recognition. Based on this, bionic aids or medical rehabilitation equipment can be further developed with the help of robotic arms and cutting-edge technology, which has a bright future and unlimited development space.

Keywords: pose recognition, 3D animation, electromyography, machine learning, bionics

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Authors: Chander Shekhar, Jeetendra Yadav, Shaziya Allarakha

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Hypertension has been described as an 'iceberg disease' as those who suffered are ignored and hence usually seek healthcare services at a very late stage. It is estimated that more than 2 million Indians are suffering from hypertensive heart disease that contributed to above 0.13 million deaths in 2016. The paper study aims to know the prevalence of Hypertension in India and its variation by socioeconomic backgrounds and to find out risk factors discriminating hypertension with special emphasis on consumption of tobacco and alcohol among men aged 15-54 years in India. The paper uses NFHS (2015-16) data. The paper used binary logistic regression and discriminant analysis to find significant predictors and discriminants of interest. The prevalence of hypertension was 16.5% in the study population. The results suggest that consumption of alcohol and tobacco are significant discriminant characteristics in carrying hypertension irrespective of what socioeconomic background characteristic he possesses.

Keywords: hypertention, alcohol, tobacco, discriminant

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Authors: M. Yavuz Hüseyinca, Şuayip Küpeli

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The Chemical Index of Alteration (CIA) values of Late Eocene-Oligocene aged sandstones that exposed on the eastern edge of Tuz Lake (Central Anatolia, Turkey) range from 49 to 59 with an average of 51. The A-CN-K diagram indicates that sandstones underwent post-depositional K-metasomatism. The original average CIA value before the K-metasomatism is calculated as 55. This value is lower than that of Post Archean Australian Shale (PAAS) and defines a low intense chemical weathering in the source-area. Extrapolation of sandstones back to the plagioclase-alkali feldspar line in the A-CN-K diagram suggests a high average plagioclase to alkali feldspar ratio in the provenance and a composition close to granodiorite. The Zr/Sc and Th/Sc ratios with the Al₂O₃-Zr-TiO₂ space do not show zircon addition that refuse both recycling of sediments and sorting effect. All these data suggest direct and rapid transportation from the source due to topographic uplift and probably arid to semi-arid climate conditions for the sandstones.

Keywords: central Anatolia, sandstone, sorting, weathering

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Authors: Mohammad Alawairdhi

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Customer Relationship Management (CRM) started gaining attention as late as the 1990s, and since then efforts are ongoing to define the domain’s precise specifications. There is yet no single agreed upon definition. However, a predominant majority perceives CRM as a mechanism for enhancing interaction with customers, thereby strengthening the relationship between a business and its clients. From the perspective of Information Technology (IT) companies, CRM systems can be viewed as facilitating software products or services to automate the marketing, selling and servicing functions of an organization. In this paper, we have proposed a Bluetooth enabled CRM system for small- and medium-scale organizations. In the proposed system, Bluetooth technology works as an automatic identification token in addition to its common use as a communication channel. The system comprises a server side accompanied by a user-interface support for both client and server sides. The system has been tested in two environments and users have expressed ease of use, convenience and understandability as major advantages of the proposed solution.

Keywords: customer relationship management, CRM, bluetooth, automatic identification token

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Authors: Hilmi Yazici

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Just after Ottoman period, new more homogenic republic was struggling to form a national identity and dealing with the cultural and historical background of the nation. This new republic had an aim of modernization and westernization which started in the late ottoman period. In this process, the culture was an important basis to form a new nation and it clearly put forward that the new citizens of the new national republic are to have a modern and national culture. The result of this aimed change was to find the Turkish culture suppressed among the common people of the Anatolia and to take the western modernization and breed this with national culture. So in this context, we can say that this approach separated the people from ottoman culture and its roots to empower the national identity. Repeatedly, it may be said that Turkish folkloric music was an important basis for the new revolution, on the other hand classical Turkish music was alienated with the idea that it didn’t belong to Turkish culture. So the aim of this study is to determine how these efforts to nationalize a new identity and culture was successful and conscious intervention to folkloric Turkish music became efficient.

Keywords: opera, nationalism in music, Turkish music

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Authors: Mahdi Asghari Ozma, Fatemeh Aghamohammadzadeh, Mahin Ahangar Oskouee

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In late 2019, the people of the world were involved with a new infection by the coronavirus, named SARS-COV-2 (COVID-19), which disseminated around the world quickly. This infection has the ability to affect various systems of the body, including respiratory, gastrointestinal, urinary, and hematology, which can be transmitted by various body samples in different ways. To control this fast-transmitted infection by preventing its transmission to other people, rapid diagnosis is vital, which can be done by examining the patient's clinical symptoms and also using various serological, molecular, and radiological methods. Symptoms caused by COVID-19 in patients include fever, cough, sore throat, headache, fatigue, shortness of breath, loss of taste or smell, skin rash, myalgia, and conjunctivitis. These clinical features were appearing gradually in different time periods from the onset of the infection, and patients showed varied and new symptoms at different times, which show the variety of symptoms over time during the spread of the infection.

Keywords: COVID-19, diagnosis, symptom, variation, novel coronavirus

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Authors: M. Habab, C. Benachaiba, B. Mazari, H. Madi, C. Benoudjafer

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The use of Distributed Generation (DG) has been increasing in recent years to fill the gap between energy supply and demand. This paper presents the grid connected wind energy system with UPQC based on fuzzy controller to compensate for voltage and current disturbances. The proposed system can improve power quality at the point of installation on power distribution systems. Simulation results show the capability of the DG-UPQC intelligent system to compensate sags voltage and current harmonics at the Point of Common Coupling (PCC).

Keywords: shunt active filter, series active filter, UPQC, power quality, sags voltage, distributed generation, wind turbine

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Authors: Mario Calabrese, Francesca Iandolo, Pietro Vito, Raffaele D'Amore, Francesco Caputo

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This article presents a synopsis of Nature-Based Solutions (NBS), a fresh and emerging concept in mitigating and adapting to climate change. It outlines a classification of NBS, from the least intrusive to the most advanced engineering, and provides illustrations of each. Moreover, it gives an overview of the 'Life Metro Adapt' initiative, which dealt with the climatic challenges faced by the Milan Metropolitan City and encouraged the development of climate change adaptation methods using alternative, nature-focused solutions. Lastly, the article emphasizes the necessity of raising awareness about environmental issues to ensure that NBS becomes a regular practice today and can be refined in the future.

Keywords: nature-based solutions, urban resilience, climate change adaptation, life metro adapt initiative

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Authors: H. R. Fazlollahi

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Dark Energy origin is unknown and so describing this mysterious component in large scale structure needs to manipulate our theories in general relativity. Although in most models, dark energy arises from extra terms through modifying Einstein-Hilbert action, maybe its origin traces back to fundamental aspects of ground energy of space-time given in quantum mechanics. Hence, diluting space-time in general relativity with quantum mechanics properties leads to the Karolyhazy relation corresponding energy density of quantum fluctuations of space-time. Through generalized uncertainty principle and an eye to Karolyhazy approach in this study we extend energy density of quantum fluctuations of space-time. Also, the application of this idea is considered in late time evolution and we have shown how extra term in generalized uncertainty principle plays as a plausible interaction term role in suggested model.

Keywords: generalized uncertainty principle, karolyhazy approach, agegraphic dark energy, cosmology

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Authors: S. Gherbi, F. Bouchareb

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This paper deals with the novel intelligent bio-inspired control strategies, it presents a novel approach based on an optimal fuzzy immune PID parameters tuning, it is a combination of a PID controller, inspired by the human immune mechanism with fuzzy logic. Such controller offers more possibilities to deal with the delayed systems control difficulties due to the delay term. Indeed, we use an optimization approach to tune the four parameters of the controller in addition to the fuzzy function; the obtained controller is implemented in a modified Smith predictor structure, which is well known that it is the most efficient to the control of delayed systems. The application of the presented approach to control a three tank delay system shows good performances and proves the efficiency of the method.

Keywords: delayed systems, fuzzy immune PID, optimization, Smith predictor

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Authors: Abdul Razak Rahmat, Azizah Ahmad, Azman Ta’aa

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The deployment of Business Intelligence (BI) for organization at the beginning phase is very crucial. Results from the previous studies found that more than half of the BI project fails to meet the objective even though a lot money are spent. Based on that problem, the readiness level of BI for the organization is important to identify in order to reduce the risk before the actual BI project is implemented. In this paper, rigorous literature review on the aspect success factors such as Critical Success Factors (CSFs), Readiness Factors (RFs), Success Factors (SFs), are discussed by different authors. The paper also adopted a few models from previous study as a guide for the assessment of BI readiness. The expected finding from this research is the Business Intelligent Readiness Model (BiRM) as a guild before implement the BI system.

Keywords: business intelligence readiness model, business intelligence for higher learning, BI readiness factors, BI critical success factors(CSF)

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Authors: Radu Pop, Adrian Bot, Vasile Rednic, Emil Bruj, Oana Raita, Liviu Vaida

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Our research presents a study concerning optimization of water flow capture for micro-hydro power plants in order to increase the energy production. It is known that the fish ladder whole, were the water is capture is fix, and the water flow may vary with the river flow, this means that on the fish ladder we will have different servitude flows, sometimes more than needed. We propose to demonstrate that the ‘winter intake’ from micro-hydro power plant, could be automated with an intelligent system which is capable to read some imposed data and adjust the flow in to the needed value. With this automation concept, we demonstrate that the performance of the micro-hydro power plant could increase, in some flow operating regimes, with approx. 10%.

Keywords: energy, micro-hydro, water intake, fish ladder

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Authors: Rakesh Dubey, Vaishali Bahl, Dalveer Kaur

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The spiralling urge for high rate data transmission over wireless mediums needs intelligent use of electromagnetic resources considering restrictions like power ingestion, spectrum competence, robustness against multipath propagation and implementation intricacy. Orthogonal frequency division multiplexing (OFDM) is a capable technique for next generation wireless communication systems. For such high rate data transfers there is requirement of proper allocation of resources like power and capacity amongst the sub channels. This paper illustrates various available methods of allocating power and the capacity requirement with the constraint of Shannon limit.

Keywords: Additive White Gaussian Noise, Multi-Carrier Modulation, Orthogonal Frequency Division Multiplexing (OFDM), Signal to Noise Ratio (SNR), Water Filling

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Authors: Halimi Mohamed Taher, Kordoghli Bassem, Ben Hassen Mohamed, Sakli Faouzi

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Textile industry has been an important part of many developing countries economies such as Tunisia. This industry is confronted with a challenging and increasing competitive environment. Good quality management in production process is the key factor for retaining existence especially in raw material exploitation. The present work aims to develop an intelligent system for fabric inspection. In the first step, we have studied the method used for fabric control which takes into account the default length and localization in woven. In the second step, we have used a method based on the fuzzy logic to minimize the Demerit point indicator with appropriate total rollers length, so that the quality problem becomes multi-objective. In order to optimize the total fabric quality, we have applied the genetic algorithm (GA).

Keywords: fabric control, Fuzzy logic, genetic algorithm, quality management

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Authors: Pouriya Angosht Baft, Farzan Safari Sabet

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Globalization should be considered as a process that has affected all areas of human activity, including the foreign policy of countries. The phenomenon of globalization has created tremendous changes in the economic, political and cultural fields. Obviously, no country can keep itself away from the new global consequences and globalization process. Dealing with the world requires formulating a realistic and intelligent foreign policy. By examining the phenomenon of globalization and its impact on foreign policy, this article aims to provide solutions for formulating a more active and effective foreign policy. The conclusion of this research is that Iran's foreign policy has gradually moved towards more realism and maintaining and strengthening national interests in the changing world has been the focus of foreign policy makers and decision makers. Strengthening the course of more realism in the future should be at the center of formulating Iran's foreign policy.

Keywords: globalization, foreign policy, international relations, realism, iran

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Authors: Xochilt Ramirez-Garcia, Mario Garcia-Valdez

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Contextual recommendations are implemented in Recommender Systems to improve user satisfaction, recommender system makes accurate and suitable recommendations for a particular situation reaching personalized recommendations. The context provides information relevant to the Recommender System and is used as a filter for selection of relevant items for the user. This paper presents a Context-aware Recommender System, which uses techniques based on Collaborative Filtering and Content-Based, as well as fuzzy rules, to recommend items inside the context. The dataset used to test the system is Trip Advisor. The accuracy in the recommendations was evaluated with the Mean Absolute Error.

Keywords: algorithms, collaborative filtering, intelligent systems, fuzzy logic, recommender systems

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Authors: Rahmatollah Amirjani

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By the emergence of the debate over the failure of Regionalism in the late 1970s, Critical Regional­ism was introduced as a different way to respond to the state of architecture in the post-war era. Critical Regionalism is most often understood as a discourse that not only mediates the language of modern architecture with the local cultures but also revives the relation between architecture and spectator as indexed by capitalism. Since the inception of Critical Regionalism, a large number of architectural practices have emerged around the globe; however, the work of the well-known Portuguese architect, Álvaro Siza, is considered as a unique case amongst works associated with the discourse of Critical Regionalism. This paper intends to respond to a number of questions, including; what are the origins of Critical Regionalism? How does Siza’s design strategy correspond to the thematic of Critical Regionalism? How does Siza recover the relation between object and subject in most of his projects? Using Siza’s housing project for the Malagueira district in Évora, Portugal, this article will attempt to answer these questions, and highlight Alvaro Siza’s design procedure which goes beyond the existing discourse of Critical Regionalism and contributes to our understanding of this practice.

Keywords: Alvaro Siza, critical regionalism, Malagueira housing, placelessness

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Authors: Rizwan Arshad, Alessio Panza, Nimra Inayat, Syeda Mariam Batool Kazmi, Shawana Azmat

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The rapidly expanding use of immunotherapy for a wide range of cancers from late to early stages has, predictably, been accompanied by evidence of inequities in access to these highly effective but costly treatments. In this survey-based case study, we aimed to develop a One-window services model (OWSM) based on Anderson’s behavioral model to enhance competence in accessing cancer medications, particularly immunotherapies, through the analysis of 20 patient surveys conducted in the Armed forces bone marrow transplant center of the district, Rawalpindi from November to December 2022. The purposive sampling technique was used. Cronbach’s alpha coefficient was found to be 0.71. It was analyzed using SPSS version 26 with descriptive analysis, and results showed that the majority of the cancer patients were non-competent to access their prescribed cancer immunotherapy because of individual-level, socioeconomic, and organizational barriers.

Keywords: cancer immunotherapy, one-window services model, accessibility, competence

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Authors: Bohuslava Juhasova, Igor Halenar, Martin Juhas

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The contribution deals with the current situation in modern manufacturing enterprises, which is affected by digital virtualization of different parts of the production process. The overview part of this article points to the fact, that wide informatization of all areas causes substitution of real elements and relationships between them with their digital, often virtual images, in real practice. Key characteristics of the systems implemented using digital twin technology along with essential conditions for intelligent products deployment were identified across many published studies. The goal was to propose a template for the production system realization using digital twin technology as a supplement to standardized concepts for Industry 4.0. The main resulting idea leads to the statement that the current trend of implementation of the new technologies and ways of communication between industrial facilities erases the boundaries between the real environment and the virtual world.

Keywords: communication, digital twin, Industry 4.0, simulation, virtualization

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Authors: Nestor A. Garcia Fragoso, Tetyana Baydyk, Ernst Kussul

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This article contains information from our investigation in the field of voice recognition. For this purpose, we created a voice database that contains different phrases in two languages, English and Spanish, for men and women. As a classifier, the LIRA (Limited Receptive Area) grayscale neural classifier was selected. The LIRA grayscale neural classifier was developed for image recognition tasks and demonstrated good results. Therefore, we decided to develop a recognition system using this classifier for voice recognition. From a specific set of speakers, we can recognize the speaker’s voice. For this purpose, the system uses spectrograms of the voice signals as input to the system, extracts the characteristics and identifies the speaker. The results are described and analyzed in this article. The classifier can be used for speaker identification in security system or smart buildings for different types of intelligent devices.

Keywords: extreme learning, LIRA neural classifier, speaker identification, voice recognition

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Authors: Driss Bouyahya

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During the late 1960s, Islam-oriented social movements have encroached to reach the Moroccan public spheres and mobilize huge waves of people from different walks of life under the banners of a rhetoric that resonates with the Muslim way of life away from Modernity and globalization tenets. In this respect, the present study investigates and explores some of the ways utilized by the Movement for Unity and Reform in Morocco as an Islam-oriented movement to recruit students massively at universities. The significance of this study lies in demystifying the recruitment strategies and mechanisms, considered essential for the Islam-oriented social movements to mobilize. This research paper uses a quantitative method to collect and analyze data through two different structured questionnaires. One of the major findings is that this Islam-oriented movement uses different techniques to recruit students, namely social networks, its websites and You-tube as three main modern and sophisticated means of communication. In a nutshell, this paper´s findings fill some of the gaps in the literature in regard to Islam-oriented movements ‘mobilization strategies.

Keywords: changing, ideology, Islam, party

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