Search results for: object of critical infrastructure

Authors: Zahra Hamidi

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Promoting cycling, as an affordable environmentally friendly mode of transport to replace private car use has been central to sustainable transport policies. Cycling is faster than walking and combined with public transport has the potential to extend the opportunities that people can access. In other words, cycling, besides direct positive health impacts, can improve people mobility and ultimately their quality of life. Transport literature well supports the close relationship between mobility, quality of life, and, well being. At the same time inequity in the distribution of access and mobility has been associated with the key aspects of injustice and social exclusion. The pattern of social exclusion and inequality in access are also often related to population characteristics such as age, gender, income, health, and ethnic background. Therefore, while investing in transport infrastructure it is important to consider the equity of provided access for different population groups. This paper proposes a method to evaluate the equity of cycling in a city from Rawls egalitarian perspective. Since this perspective is concerned with the difference between individuals and social groups, this method combines accessibility measures and Theil index of inequality that allows capturing the inequalities ‘within’ and ‘between’ groups. The paper specifically focuses on two population characteristics as gender and ethnic background. Following Rawls equity principles, this paper measures accessibility by bikes to a selection of urban activities that can be linked to the concept of the social primary goods. Moreover, as growing number of cities around the world have launched bike-sharing systems (BSS) this paper incorporates both private and public bikes networks in the estimation of accessibility levels. Additionally, the typology of bike lanes (separated from or shared with roads), the presence of a bike sharing system in the network, as well as bike facilities (e.g. parking racks) have been included in the developed accessibility measures. Application of this proposed method to a real case study, the city of Malmö, Sweden, shows its effectiveness and efficiency. Although the accessibility levels were estimated only based on gender and ethnic background characteristics of the population, the author suggests that the analysis can be applied to other contexts and further developed using other properties, such as age, income, or health.

Keywords: accessibility, cycling, equity, gender

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Authors: M. Madheswaran, A. R. Prashant, S. Ramakrishna, V. Ramesh Naidu, P. Govindan, P. Aravindakshan

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Shock Response spectrum (SRS) tests are one of the tests that are conducted on some critical systems of spacecraft as part of environmental testing. The SRS tests are conducted to simulate the pyro shocks that occur during launch phases as well as during deployment of spacecraft appendages. Some of the methods to carryout SRS tests are pyro technique method, impact hammer method, drop shock method and using electro dynamic shakers. The pyro technique, impact hammer and drop shock methods are open loop tests, whereas SRS testing using electrodynamic shaker is a controlled closed loop test. SRS testing using electrodynamic shaker offers various advantages such as simple test set up, better controllability and repeatability. However, it is important to devise a a proper test methodology so that safety of the electro dynamic shaker and that of test specimen are not compromised. This paper discusses the challenges that are involved in conducting SRS tests, shaker validation and the necessary precautions to be considered. Approach involved in choosing various test parameters like synthesis waveform, spectrum convergence level, etc., are discussed. A case study of SRS test conducted on an optical payload of Indian Geo stationary spacecraft is presented.

Keywords: maxi-max spectrum, SRS (shock response spectrum), SDOf (single degree of freedom), wavelet synthesis

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Authors: Michelle Eliane Hernández-García, Angélica Lozano

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The traffic accidents study usually contemplates the relation between factors such as the type of vehicle, its operation, and the road infrastructure. Traffic accidents can be explained by different factors, which have a greater or lower relevance. Two zones are studied, a mixed industrial zone and the extended zone of it. The first zone has mainly residential (57%), and industrial (23%) land uses. Trucks are mainly on the roads where industries are located. Four sensors give information about traffic and speed on the main roads. The extended zone (which includes the first zone) has mainly residential (47%) and mixed residential (43%) land use, and just 3% of industrial use. The traffic mix is composed mainly of non-trucks. 39 traffic and speed sensors are located on main roads. The traffic mix in a mixed land use zone, could be related to traffic accidents. To understand this relation, it is required to identify the elements of the traffic mix which are linked to traffic accidents. Models that attempt to explain what factors are related to traffic accidents have faced multiple methodological problems for obtaining robust databases. Poisson regression models are used to explain the accidents. The objective of the Poisson analysis is to estimate a vector to provide an estimate of the natural logarithm of the mean number of accidents per period; this estimate is achieved by standard maximum likelihood procedures. For the estimation of the relation between traffic accidents and the traffic mix, the database is integrated of eight variables, with 17,520 observations and six vectors. In the model, the dependent variable is the occurrence or non-occurrence of accidents, and the vectors that seek to explain it, correspond to the vehicle classes: C1, C2, C3, C4, C5, and C6, respectively, standing for car, microbus, and van, bus, unitary trucks (2 to 6 axles), articulated trucks (3 to 6 axles) and bi-articulated trucks (5 to 9 axles); in addition, there is a vector for the average speed of the traffic mix. A Poisson model is applied, using a logarithmic link function and a Poisson family. For the first zone, the Poisson model shows a positive relation among traffic accidents and C6, average speed, C3, C2, and C1 (in a decreasing order). The analysis of the coefficient shows a high relation with bi-articulated truck and bus (C6 and the C3), indicating an important participation of freight trucks. For the expanded zone, the Poisson model shows a positive relation among traffic accidents and speed average, biarticulated truck (C6), and microbus and vans (C2). The coefficients obtained in both Poisson models shows a higher relation among freight trucks and traffic accidents in the first industrial zone than in the expanded zone.

Keywords: freight transport, industrial zone, traffic accidents, traffic mix, trucks

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Authors: Lichung Jen, Yi Chun Liu, Kuan-Wei Lee

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Fruitful data has been accumulated in database nowadays and is commonly used as support for decision-making. In the healthcare industry, hospital, for instance, ordering pharmacy inventory is one of the key decision. With large drug inventory, the current cost increases and its expiration dates might lead to future issue, such as drug disposal and recycle. In contrast, underestimating demand of the pharmacy inventory, particularly standing drugs, affects the medical treatment and possibly hospital reputation. Prescription behaviour of hospital physicians is one of the critical factor influencing this decision, particularly irregular prescription behaviour. If a drug’s usage amount in the month is irregular and less than the regular usage, it may cause the trend of subsequent stockpiling. On the contrary, if a drug has been prescribed often than expected, it may result in insufficient inventory. We proposed a hierarchical Bayesian mixture model with two components to identify physicians’ regular/irregular prescription patterns with probabilities. Heterogeneity of hospital is considered in our proposed hierarchical Bayes model. The result suggested that modeling the prescription patterns of physician is beneficial for estimating the order quantity of medication and pharmacy inventory management of the hospital. Managerial implication and future research are discussed.

Keywords: hierarchical Bayesian model, poission mixture model, medicines prescription behavior, irregular behavior

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Authors: B. Pavan Kumar Reddy, P. Michael Preetam Raj, Souri Banerjee, Souvik Kundu

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In this work, the fabrication and characterization of copper-doped zinc oxide (Cu:ZnO) based memristor devices with aluminum (Al) and indium tin oxide (ITO) metal electrodes are reported. The thin films of Cu:ZnO was synthesized using low-cost and low-temperature chemical process. The Cu:ZnO was then deposited onto ITO bottom electrodes using spin-coater technique, whereas the top electrode Al was deposited utilizing physical vapor evaporation technique. Ellipsometer was employed in order to measure the Cu:ZnO thickness and it was found to be 50 nm. Several surface and materials characterization techniques were used to study the thin-film properties of Cu:ZnO. To ascertain the efficacy of Cu:ZnO for memristor applications, electrical characterizations such as current-voltage (I-V), data retention and endurance were obtained, all being the critical parameters for next-generation memory. The I-V characteristic exhibits switching behavior with asymmetrical hysteresis loops. This work imputes the resistance switching to the positional drift of oxygen vacancies associated with respect to the Al/Cu:ZnO junction. Further, a non-linear curve fitting regression techniques were utilized to determine the equivalent circuit for the fabricated Cu:ZnO memristors. Efforts were also devoted in order to establish its potentiality for different electronic applications.

Keywords: copper doped, metal-oxides, oxygen vacancies, resistive switching

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Authors: Ola I. S. El Dardery, Ismail Gomaa, Adel R.M. Rayan, Ghada El Khayat, Sara H. Sabry

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Continuous improvement activities are becoming a key factor of the success of any organization, those improvement activities include but not limited to kaizen, six sigma, lean projects, and continuous improvement projects. Kaizen is a Japanese philosophy of continuous improvement by making small incremental changes to improve an organization’s performance, reduce costs, reduce delay time, reduce waste in production, etc. This study aims at proposing a new measuring technique for kaizen activities using a Sustainable balanced scorecard structure. A survey questionnaire was developed and introduced to kaizen participants in both Egypt and Japan with the purpose of allocating key performance indicators for both kaizen process (critical success factors) and result (kaizen benefits) into the five perspectives of sustainable balanced scorecard. The study contributes to the literature by presenting a new kaizen measurement of both kaizen process and results, that will illuminate the benefits of using kaizen. Also, the presented measurement can help in the sustainability of kaizen implementation. Determining the combination of the proper kaizen measures could be used by any industry whether service or manufacturing to better measure kaizen activates. The comparison between Japanese measures, as the leaders of kaizen philosophy, and Egyptian measures will help recommending better practices of kaizen in Egypt, and contributing to the 2030 sustainable development goals.

Keywords: continuous improvements, kaizen, performance, sustainable balanced scorecard

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Authors: Kulachai Kultawanich, Prakob Koraneekij, Jaitip Na-Songkhla

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The way of learning has been changed into a new paradigm since the improvement of network and communication technology, so learners have to interact with massive amount of the information. Thus, information literacy has become a critical set of abilities required by every college and university in the world. Connectivism is considered to be an alternative way to design information literacy course in online learning environment, such as Virtual Classroom (VC). With the change of learning pedagogy, VC is employed to improve the social capability by integrating cloud-based technology. This paper aims to study the use of Cloud-based Virtual Classroom (CBVC) in Connectivism learning process to enhance information literacy and self-efficacy of twenty-one undergraduate students who registered in an e-publishing course at Chulalongkorn University. The data were gathered during 6 weeks of the study by using the following instruments: (1) Information literacy test (2) Information literacy rubrics (3) Information Literacy Self-Efficacy (ILSE) Scales and (4) Questionnaire. The result indicated that students have information literacy and self-efficacy posttest mean scores higher than pretest mean scores at .05 level of significant after using CBVC in Connectivism learning process. Additionally, the study identified that the Connectivism learning process proved useful for developing information rich environment and a sense of community, and the CBVC proved useful for developing social connection.

Keywords: cloud-based, virtual classroom, connectivism, information literacy

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Authors: Smah Almotiri

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One of the most common fields of natural language processing (NLP) is sentimental analysis. The inferred feeling in the text can be successfully mined for various events using sentiment analysis. Twitter is viewed as a reliable data point for sentimental analytics studies since people are using social media to receive and exchange different types of data on a broad scale during the COVID-19 epidemic. The processing of such data may aid in making critical decisions on how to keep the situation under control. The aim of this research is to look at how sentimental states differed in a single geographic region during the lockdown at two different times.1162 tweets were analyzed related to the COVID-19 pandemic lockdown using keywords hashtags (lockdown, COVID-19) for the first sample tweets were from March 23, 2020, until April 23, 2020, and the second sample for the following year was from March 1, 2020, until April 4, 2020. Natural language processing (NLP), which is a form of Artificial intelligence, was used for this research to calculate the sentiment value of all of the tweets by using AFINN Lexicon sentiment analysis method. The findings revealed that the sentimental condition in both different times during the region's lockdown was positive in the samples of this study, which are unique to the specific geographical area of New Zealand. This research suggests applying machine learning sentimental methods such as Crystal Feel and extending the size of the sample tweet by using multiple tweets over a longer period of time.

Keywords: sentiment analysis, Twitter analysis, lockdown, Covid-19, AFINN, NodeJS

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Authors: Taejin Kim, Heonwoo Lee, Jong-Ho Kim, Dongchul Lee

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Recently, there have been various high-rise building projects which reflect unique inspiration from architects to their feature. And it is frequently found that some of these buildings have diagrid structural system. Diagrid system provides engineers many options for structural plan, since it has triangular module so it can form a number of complex shapes. Unlike braced frame systems, diagonal members in diagrid system resist gravity and horizontal loads simultaneously. Correspondingly, diagrid members take roles of both beams and columns, and it is expected that their ductile capacity may depend on the amount of gravity loads. However, not enough studies have been made for this issue so far, which means that there is demand of examination on the seismic behavior of diagrid members under large gravity loads. Therefore, in this study, the ductile capacity of diagrid members was evaluated through analytical and experimental method. Several cases that have different vertical load condition were set up for both approaches to consider the effect of initial compression force due to gravity load. Regarding the result, it was found that buckling in a diagonal member occurs at smaller drift angle when larger gravity load acts on the specimen, which also reduces the amount of energy dissipation. It means that axial stress in a diagonal member reaches critical buckling force early due to the combined axial force from not only horizontal load but also gravity load.

Keywords: buckling, diagrid, ductility, seismic performance

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Authors: M. A. Abdelfattah, F. K. Waleed

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Anticoccidials were utilized widely in veterinary practice for the avoidance of coccidiosis in poultry and assume a huge job as development promotants in ruminants. Ionophore harming is every now and again happens because of accidental access to medicated feed, errors in feed mixing, incorrect dosage calculation or misuse in non-recommended species. Camels on several farms in Eastern area of Saudi Arabia were accidently fed with a feed pellet containing 13 ppm salinomycin. One hundred and sixty-three camels died with mortality rate of 100%. The poisoning was clinically characterized by restlessness with tail lift to the top, jerk in the muscles of legs and thighs, excessive sweating, frequent setting and standing with body imbalance, lateral and sternal recumbences with the legs stretched back, eye tears with dilated pupil, vomiting of the stomach content, loss of consciousness and death of some of them. Feed analysis indicated the presence of salinomycin in pelleted feed in a range of 13 mg/kg-47 mg/kg. Necropsy findings and histopathological examinations were presented. Regulations and legal implications concerning with sale of contaminated feed in Saudi market are discussed in the light of feed law and by-law. The necessity for an effective implication of regulation concerning application of quality assurance systems based on the principles of Good Manufacturing Practice (GMP) and the application of Hazard Analysis of Critical Control Point (HACCP) during feed production is necessary to avoid feed accident.

Keywords: medicated feed, salinomycin, anticoccidial, camel, toxicity

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Authors: Nadia Ezzat Al-Kirbasee, Ahlam Hussein Hassan, Shatha Raheem Helal Alhimidi, Doaa Ezzat Al-Kirbasee, Muhsen Abood Muhsen Al-Ibadi

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Through DFT/QTAIM calculations, we have provided new insights into the nature of the M-M, M-H, M-O, and M-C bonds of the (Cp*Ru)n(Cp*Os)3−n(μ3-O)2(μ-H)(Cp* = η5-C5Me5, n= 3,2,1,0). The topological analysis of the electron density reveals important details of the chemical bonding interactions in the clusters. Calculations confirm the absence of bond critical points (BCP) and the corresponding bond paths (BP) between Ru-Ru, Ru-Os, and Os-Os. The position of bridging hydrides and Oxo atoms coordinated to Ru-Ru, Ru-Os, and Os-Os determines the distribution of the electron densities and which strongly affects the formation of the bonds between these transition metal atoms. On the other hand, the results confirm that the four clusters contain a 6c–12e and 4c–2e bonding interaction delocalized over M3(μ-H)(μ-O)2 and M3(μ-H), respectively, as revealed by the non-negligible delocalization indexes calculations. The small values for electron density ρ(b) above zero, together with the small values, again above zero, for laplacian ∇2ρ(b) and the small negative values for total energy density H(b) are shown by the Ru-H, Os-H, Ru-O, and Os-O bonds in the four clusters are typical of open shell interactions. Also, the topological data for the bonds between Ru and Os atoms with the C atoms of the pentamethylcyclopentadienyl (Cp*) ring ligands are basically similar and show properties very consistent with open shell interactions in the QTAIM classification.

Keywords: metal-metal and metal-ligand interactions, organometallic complexes, topological analysis, DFT and QTAIM analyses

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Authors: Neslinur Hizli, Berrak Kirbaş Akyürek

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Beşiktaş, one of the historical coastal district of İstanbul, is on the very edge of the radical transformation because of an approaching ‘Beşiktaş Public Square Project’. At this juncture, due its location, presence on the coast, population density and distance to the other centers of the city, the decisions to be taken are critical to whole Istanbul that will be majorly affected from this transformation. As the new project aims to pedestrianize the area by placing the vehicular traffic under the ground, Beşiktaş and its square will change from top to bottom. Among those considerations, through the advantages and disadvantages the perception of the existing conditions of the Beşiktaş play significant role. The motive of this paper is the lack of determination and clarity on the cognition of the Square. After brief analysis on the historical transformation of the area, prominent studies on the criteria of public square are revised. Through cognitive mapping methodology, characteristics of the Square and the public space in general find a place to discuss from individual views. This study aims to discuss and review Beşiktaş Public Square from perspective, mind and behavior of the users. Cognitive map study with thirty subjects (30) is evaluated and categorized upon the five elements that Kevin Lynch defined as the images of the city. The results obtained digitized and represented with tables and graphs. Findings of the research underline the crucial issues on the approaching change in Beşiktaş. Thus, this study may help to develop comprehensive ideas and new suggestions on the Square.

Keywords: Beşiktaş public square, cognitive map, perception, public space

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Authors: Mehdi Montakhabrazlighi, Ercan Balikci

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The neural network (NN) method is applied to alloy development of single crystal Ni-base Superalloys with low density and improved mechanical strength. A set of 1200 dataset which includes chemical composition of the alloys, applied stress and temperature as inputs and density and time to rupture as outputs is used for training and testing the network. Thermodynamic phase diagram modeling of the screened alloys is performed with Thermocalc software to model the equilibrium phases and also microsegregation in solidification processing. The model is first trained by 80% of the data and the 20% rest is used to test it. Comparing the predicted values and the experimental ones showed that a well-trained network is capable of accurately predicting the density and time to rupture strength of the Ni-base superalloys. Modeling results is used to determine the effect of alloying elements, stress, temperature and gamma-prime phase volume fraction on rupture strength of the Ni-base superalloys. This approach is in line with the materials genome initiative and integrated computed materials engineering approaches promoted recently with the aim of reducing the cost and time for development of new alloys for critical aerospace components. This work has been funded by TUBITAK under grant number 112M783.

Keywords: neural network, rupture strength, superalloy, thermocalc

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Authors: Shalini Tripathi, Pardeep Kumar

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The method of translating observed symptoms into disease names is known as disease diagnosis. The ability to solve clinical problems in a complex manner is critical to a doctor's effectiveness in providing health care. The accuracy of his or her expertise is crucial to the survival and well-being of his or her patients. Artificial Intelligence (AI) has a huge economic influence depending on how well it is applied. In the medical sector, human brain-simulated intellect can help not only with classification accuracy, but also with reducing diagnostic time, cost and pain associated with pathologies tests. In light of AI's present and prospective applications in the biomedical, we will identify them in the paper based on potential benefits and risks, social and ethical consequences and issues that might be contentious but have not been thoroughly discussed in publications and literature. Current apps, personal tracking tools, genetic tests and editing programmes, customizable models, web environments, virtual reality (VR) technologies and surgical robotics will all be investigated in this study. While AI holds a lot of potential in medical diagnostics, it is still a very new method, and many clinicians are uncertain about its reliability, specificity and how it can be integrated into clinical practice without jeopardising clinical expertise. To validate their effectiveness, more systemic refinement of these implementations, as well as training of physicians and healthcare facilities on how to effectively incorporate these strategies into clinical practice, will be needed.

Keywords: Artificial Intelligence, medical diagnosis, virtual reality, healthcare ethical implications 

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Authors: Tarandeep Kaur

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Generation Y and Z nursing students have a much higher need for technology-based stimulation than previous generations, as they may find traditional methods of education boring and disinterested. These generations prefer experiential learning and the use of advanced technology for enhanced learning. Therefore, nursing educators must acquire knowledge to make better use of technology and technological tools for instruction. Millennials and generation are digital natives, optimistic, assertive, want engagement, instant feedback, and collaborative approach. The integration of technology and the efficacy of its use can be challenging for nursing educators. The SAMR (substitution, augmentation, modification, and redefinition) model designed and developed by Dr. Ruben Puentedura can help nursing educators to engage their students in different levels of technology integration for effective learning. Nursing educators should understand that technology use in the classroom must be purposeful. The influx of technology in nursing education is ever-changing; therefore, nursing educators have to constantly enhance and develop technical skills to keep up with the emerging technology in the schools as well as hospitals. In the Saskatchewan Collaborative Bachelor of Nursing (SCBSCN) program at Saskatchewan polytechnic, we use technology at various levels using the SAMR model in our program, including low and high-fidelity simulation labs. We are also exploring futuristic options of using virtual reality and gaming in our classrooms as an innovative way to motivate, increase critical thinking, create active learning, provide immediate feedback, improve student retention and create collaboration.

Keywords: generations, nursing, SAMR, technology

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Authors: Weiming Hu, Xu Li, Xiaonan Li, Zhong Xu, Li Yuan, Xuan Dong

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Maneuver decision-making plays a critical role in high-performance intelligent driving. This paper proposes a risk assessment-based decision-making network (RADMN) to address the problem of driving strategy for the commercial vehicle. RADMN integrates two networks, aiming at identifying the risk degree of collision and rollover and providing decisions to ensure the effectiveness and reliability of driving strategy. In the risk assessment module, risk degrees of the backward collision, forward collision and rollover are quantified for hazard recognition. In the decision module, a deep reinforcement learning based on multi-objective optimization (DRL-MOO) algorithm is designed, which comprehensively considers the risk degree and motion states of each traffic participant. To evaluate the performance of the proposed framework, Prescan/Simulink joint simulation was conducted in highway scenarios. Experimental results validate the effectiveness and reliability of the proposed RADMN. The output driving strategy can guarantee the safety and provide key technical support for the realization of autonomous driving of commercial vehicles.

Keywords: decision-making strategy, risk assessment, multi-objective optimization, commercial vehicle

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Authors: Alie Wube Dametew, Frank Ebinger

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This study investigated the roles of technological innovation on basic metal industries and then developed technological innovation framework for enhancing sustainable competitive advantage in the basic metal industries. The previous research work indicates that technological innovation has critical impact in promoting local industries to improve their performance and achieve sustainable competitive environments. The filed observation, questioner and expert interview result from basic metal industries indicate that the technological capability of local industries to invention, adoption, modification, improving and use a given innovative technology is very poor. As the result, this poor technological innovation was occurred due to improper innovation and technology transfer framework, non-collaborative operating environment between foreign and local industries, very weak national technology policies, problems research and innovation centers, the common miss points on basic metal industry innovation systems were investigated in this study. One of the conclusions of the article is that, through using the developed technological innovation framework in this study, basic metal industries improve innovation process and support an innovative culture for sector capabilities and achieve sustainable competitive advantage.

Keywords: technological innovation, competitive advantage, sustainable, basic metal industry, conceptual model, sustainability, supply chain integration

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Authors: Saheed Biodun Qaasim-Badmusi

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A lot has been written on peaceful co-existence with non-Muslims in Islam, but little attention is paid to the conflict between Ahadith relating to dissociation from non-Muslims as a kernel of Islamic faith, and the one indicating peaceful co-existence with them. Undoubtedly, proper understanding of seemingly contradictory prophetic traditions is an antidote to the bane of pervasive extremism in our society. This is what calls for need to shed light on ‘Harmonization of Conflict Ahadith between Dissociation and Peaceful Co-existence with Non-Muslims. It is in view of the above that efforts are made in this paper to collate Ahadith pertaining to dissociation from non-Muslims as well as co-existence with them. Consequently, a critical study of their authenticity is briefly explained before proceeding to analysis of their linguistic and contextual meanings. To arrive at the accurate interpretation, harmonization is graphically applied. The result shows that dissociation from non –Muslims as a bedrock of Islamic faith could be explained in Sunnah by prohibition of participating or getting satisfaction from their religious matters, and anti-Islamic activities. Also, freedom of apostasy, ignoring da`wah with wisdom and seeking non-Muslims support against Muslims are frowned upon in Sunnah as phenomenon of dissociation from non –Muslims. All the aforementioned are strictly prohibited in Sunnah whether under the pretext of enhancing peaceful co-existence with non-Muslims or not. While peaceful co-existence with non-Muslims is evidenced in Sunnah by permissibility of visiting the sick among them, exchange of gift with them, forgiving the wrong among them, having good relationship with non-Muslim neighbours, ties of non-Muslim kinship, legal business transaction with them and the like. Finally, the degree of peaceful co-existence with non-Muslims is determined by their attitude towards Islam and Muslims.

Keywords: Ahadith, conflict, co-existence, non-Muslims

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Authors: Amira Abdelrasoul, Huu Doan, Ali Lohi

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The goal of the present study was to minimize the ultrafiltration fouling of latex effluent using Cetyltrimethyl ammonium bromide (CTAB) as a cationic surfactant. Hydrophilic Polysulfone and Ultrafilic flat heterogeneous membranes, with MWCO of 60,000 and 100,000, respectively, as well as hydrophobic Polyvinylidene Difluoride with MWCO of 100,000, were used under a constant flow rate and cross-flow mode in ultrafiltration of latex solution. In addition, a Polycarbonate flat membrane with uniform pore size of 0.05 µm was also used. The effect of CTAB on the latex particle size distribution was investigated at different concentrations, various treatment times, and diverse agitation duration. The effects of CTAB on the zeta potential of latex particles and membrane surfaces were also investigated. The results obtained indicated that the particle size distribution of treated latex effluent showed noticeable shifts in the peaks toward a larger size range due to the aggregation of particles. As a consequence, the mass of fouling contributing to pore blocking and the irreversible fouling were significantly reduced. The optimum results occurred with the addition of CTAB at the critical micelle concentration of 0.36 g/L for 10 minutes with minimal agitation. Higher stirring rate had a negative effect on membrane fouling minimization.

Keywords: cationic surfactant, latex particles, membrane fouling, ultrafiltration, zeta potential

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Authors: Benson Ade Eniola Afere

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This paper introduces a family of fourth-order hybrid beta polynomial kernels developed for statistical analysis. The assessment of these kernels' performance centers on two critical metrics: asymptotic mean integrated squared error (AMISE) and kernel efficiency. Through the utilization of both simulated and real-world datasets, a comprehensive evaluation was conducted, facilitating a thorough comparison with conventional fourth-order polynomial kernels. The evaluation procedure encompassed the computation of AMISE and efficiency values for both the proposed hybrid kernels and the established classical kernels. The consistently observed trend was the superior performance of the hybrid kernels when compared to their classical counterparts. This trend persisted across diverse datasets, underscoring the resilience and efficacy of the hybrid approach. By leveraging these performance metrics and conducting evaluations on both simulated and real-world data, this study furnishes compelling evidence in favour of the superiority of the proposed hybrid beta polynomial kernels. The discernible enhancement in performance, as indicated by lower AMISE values and higher efficiency scores, strongly suggests that the proposed kernels offer heightened suitability for statistical analysis tasks when compared to traditional kernels.

Keywords: AMISE, efficiency, fourth-order Kernels, hybrid Kernels, Kernel density estimation

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Authors: Ayoola Idowu Olasebikan

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The global community has become increasingly dependent on various kinds of technologies out of which Information and Communication Technologies (ICTs) appear to be the most prominent. ICTs have become multipurpose tools which have had a revolutionary impact on how we see the world and how we live in it. Yoruba is the most widely spoken African language outside Africa but it remains one of the badly spoken language in the world as a result of its outdated teaching method in the African schools which prevented its standard version from being spoken and written. This paper conducts a critical review of the traditional methods of teaching Yoruba language. It then examines the possibility of leveraging on ICTs for improved methods of teaching Yoruba language to achieve global standard and spread. It identified key ICT platforms that can be deployed for the teaching of Yoruba language and the constraints facing each of them. The paper concludes that Information and Communication Technologies appear to provide veritable opportunity for paradigm shift in the methods of teaching Yoruba Language. It also opines that Yoruba language has the potential to transform economic fortune of Africa for sustainable development provided its teaching is taken beyond the brick and mortar classroom to the virtual classroom/global information super highway called internet or any other ICTs medium. It recommends that students and teachers of Yoruba language should be encouraged to acquire basic skills in computer and internet technology in order to enhance their ability to develop and retrieve electronic Yoruba language teaching materials.

Keywords: Africa, ICT, teaching method, Yoruba language

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Authors: Ravija Gunawardana, Banuka Athuraliya

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Machine learning has emerged as a powerful tool for disease diagnosis and prediction. The use of machine learning algorithms has the potential to improve the accuracy of disease prediction, thereby enabling medical professionals to provide more effective and personalized treatments. This study focuses on developing a machine-learning model for disease prediction using symptoms and X-ray images. The importance of this study lies in its potential to assist medical professionals in accurately diagnosing diseases, thereby improving patient outcomes. Respiratory diseases are a significant cause of morbidity and mortality worldwide, and chest X-rays are commonly used in the diagnosis of these diseases. However, accurately interpreting X-ray images requires significant expertise and can be time-consuming, making it difficult to diagnose respiratory diseases in a timely manner. By incorporating machine learning algorithms, we can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The study utilized the Mask R-CNN algorithm, which is a state-of-the-art method for object detection and segmentation in images, to process chest X-ray images. The model was trained and tested on a large dataset of patient information, which included both symptom data and X-ray images. The performance of the model was evaluated using a range of metrics, including accuracy, precision, recall, and F1-score. The results showed that the model achieved an accuracy rate of over 90%, indicating that it was able to accurately detect and segment regions of interest in the X-ray images. In addition to X-ray images, the study also incorporated symptoms as input data for disease prediction. The study used three different classifiers, namely Random Forest, K-Nearest Neighbor and Support Vector Machine, to predict diseases based on symptoms. These classifiers were trained and tested using the same dataset of patient information as the X-ray model. The results showed promising accuracy rates for predicting diseases using symptoms, with the ensemble learning techniques significantly improving the accuracy of disease prediction. The study's findings indicate that the use of machine learning algorithms can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The model developed in this study has the potential to assist medical professionals in diagnosing respiratory diseases more accurately and efficiently. However, it is important to note that the accuracy of the model can be affected by several factors, including the quality of the X-ray images, the size of the dataset used for training, and the complexity of the disease being diagnosed. In conclusion, the study demonstrated the potential of machine learning algorithms for disease prediction using symptoms and X-ray images. The use of these algorithms can improve the accuracy of disease diagnosis, ultimately leading to better patient care. Further research is needed to validate the model's accuracy and effectiveness in a clinical setting and to expand its application to other diseases.

Keywords: K-nearest neighbor, mask R-CNN, random forest, support vector machine

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Authors: Natalia Carolina Encalada Castillo

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As part of an intended radical policy change compared to former administrations in Ecuador, the transformation of the institutionality of international cooperation during the period of President Rafael Correa was considered as a key element for the construction of the state of 'Good Living'. This intention led to several regulatory changes in the reception of cooperation for development, and even the departure of some foreign cooperation agencies. Moreover, Ecuador launched the initiative to become a donor of cooperation towards other developing countries through the ‘South-South Cooperation’ approach. All these changes were institutionalized through the Ecuadorian System of International Cooperation as a new framework to establish rules and policies that guarantee a sovereign management of foreign aid. Therefore, this research project has been guided by two questions: What were the factors that motivated the transformation of the institutionality of international cooperation in Ecuador from 2007 to 2017? and, what were the implications of this transformation in terms of the international role of the country? This paper seeks to answer these questions through Role Theory within a Constructivist meta-theoretical perspective, considering that in this case, changes at the institutional level in the field of cooperation, responded not only to material motivations but also to interests built on the basis of a specific state identity. The latter was only possible to affirm through specific roles such as ‘sovereign recipient of cooperation’ as well as ‘donor of international cooperation’. However, the performance of these roles was problematic as they were not easily accepted by the other actors in the international arena or in the domestic level. In terms of methodology, these dynamics are analyzed in a qualitative way mainly through interpretive analysis of the discourse of high-level decision-makers from Ecuador and other cooperation actors. Complementary to this, document-based research of relevant information as well as interviews have been conducted. Finally, it is concluded that even if material factors such as infrastructure needs, trade and investment interests, as well as reinforcement of state control and monitoring of cooperation flows, motivated the institutional transformation of international cooperation in Ecuador; the essential basis of these changes was the search for a new identity for the country to be projected in the international arena. This identity started to be built but continues to be unstable. Therefore, it is important to potentiate the achievements of the new international cooperation policies, and review their weaknesses, so that non-reimbursable cooperation funds received as well as ‘South-South cooperation’ actions, contribute effectively to national objectives.

Keywords: Ecuador, international cooperation, Role Theory, state identity

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Authors: I. T. Adebayo, J. R. Aworemi, V. A. Ogundele, O. J. Babalola, J. O. Ajayi

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The behavior of road users is a critical element in road safety. However, despite the proven effectiveness of the seat belt in reducing injury severity, some drivers still do not use the seat belt. The study, therefore, examined seat belt usage among drivers in Ogbomoso, Oyo State, Nigeria. Face-to-face surveys were conducted to elicit data on seat belt usage and road behaviors on 54,038 drivers plying the General-Lautech Road in Ogbomoso over a period of six months. Data collected were analyzed using both descriptive and inferential statistics. Findings revealed that seat belt usage was moderate among private car drivers in the morning (52.75 percent) and much lower in the evening (37.67 percent), while less than 30 percent of the commercial bus/taxi drivers used the seat during both periods. The paired T-test revealed a significant difference in seat belt usage by all the drivers in the morning and in the evening, as indicated with a T value of 113.977 and the level of significance p < 0.05. The study concluded that there is a significant difference in the usage of the seat belt by both private car and commercial bus/taxi drivers in Ogbomoso as most drivers made use of the seat belt, especially in the morning, to avoid being delayed when flagged down and fined for non-compliance with seat belt usage by the road traffic law enforcement agents. However, most of the drivers cited inadequate/lack of enforcement of compulsory use of seat belts by the relevant agencies and discomfort as the major reasons for not using the seat belt while driving.

Keywords: drivers, road , seat belt, traffic psychology

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Authors: Talha Ahmed, Ishtiaq Hassan

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Urban areas or metropolitan is portrayed by the very high density of population due to the result of these economic activities. Some critical elements, such as urban expansion and climate change, are driving changes in cities with exposure to the incidence and impacts of pluvial floods. Urban communities are recurrently developed by huge spaces by which water cannot enter impermeable surfaces, such as man-made permanent surfaces and structures, which do not cause the phenomena of infiltration and percolation. Urban sprawl can result in increased run-off volumes, flood stage and flood extents during heavy rainy seasons. The flood risks require a thorough examination of all aspects affecting to severe an event in order to accurately estimate their impacts and other risk factors associated with them. For risk evaluation and its impact due to urbanization, an integrated hydrological modeling approach is used on the study area in Islamabad (Pakistan), focusing on a natural water body that has been adopted in this research. The vulnerability of the physical elements at risk in the research region is analyzed using GIS and SOBEK. The supervised classification of land use containing the images from 1980 to 2020 is used. The modeling of DEM with selected return period is used for modeling a hydrodynamic model for flood event inundation. The selected return periods are 50,75 and 100 years which are used in flood modeling. The findings of this study provided useful information on high-risk places and at-risk properties.

Keywords: urbanization, flood, flood risk, GIS

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Authors: Ivan Ramos Sampe Immanuel, Linung Kresno Adikusumo, Liston Sitanggang

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Achieving the production targets of oil and gas in an upstream oil and gas company represents a complex undertaking necessitating collaborative engagement from a multidisciplinary team. In addition to conducting exploration activities and executing well intervention programs, an upstream oil and gas enterprise must assess the feasibility of attaining predetermined production goals. The monitoring of production performance serves as a critical activity to ensure organizational progress towards the established oil and gas performance targets. Subsequently, decisions within the upstream oil and gas management team are informed by the received information pertaining to the respective production performance. To augment the decision-making process, the implementation of a production performance dashboard emerges as a viable solution, providing an integrated and centralized tool. The deployment of a production performance dashboard manifests as an instrumental mechanism fostering a user-friendly interface for monitoring production performance, while concurrently preserving the intrinsic characteristics of granular data. The integration of diverse data sources into a unified production performance dashboard establishes a singular veritable source, thereby enhancing the organization's capacity to uphold a consolidated and authoritative foundation for its business requisites. Additionally, the heightened accessibility of the production performance dashboard to business users constitutes a compelling substantiation of its consequential impact on facilitating the monitoring of organizational targets.

Keywords: production, performance, dashboard, data analytics

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Authors: Robin C. Ladwig

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The future of work becomes less predictable, which requires increasing the adaptability of organizations to social and work changes. Society is transforming regarding gender identity in the sense that more people come forward to identify as trans and gender diverse (TGD). Organizations are ill-equipped to provide a safe and encouraging work environment by lacking inclusive organizational structures. The qualitative multi-method research about TGD inclusivity in the workplace explores the enablers and barriers for TGD individuals to satisfactory engage in the work environment and organizational culture. Furthermore, these TGD insights are analyzed about their organizational implications and awareness from a leadership and management perspective. The semi-structured online interviews with TGD individuals and the photo-elicit open-ended questionnaire addressed to leadership and management in diversity, career development, and human resources have been analyzed with a critical grounded theory approach. Findings demonstrated the significance of TGD voices, the support of leadership and management, as well as the synergy between voices and leadership. Hence, it indicates practical implications such as the revision of exclusive language used in policies, data collection, or communication and reconsideration of organizational decision-making by leaders to include TGD voices.

Keywords: future of work, occupational identity, organisational decision-making, trans and gender diverse identity

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Authors: Halimah Abdul Manaf, Ahmad Martadha Mohamed, Zainal M. Zan, Nur Rusydina Khadzali

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Strengthening accountability among civil servants has been at the centre of government transformation ever since the country is striving to become a developed nation by the year 2020. One critical area that has become the loci of attention is increasing the accountability of local government by delivering services that are preferred by the communities. This article explores the practices of citizen participation and political accountability in local government in Malaysia. The existing literature has identified a mismatch between the demands of the community and the actual services delivered by the local government. Based upon this framework, this research attempts to examine the linkages between citizen participation and political accountability in selected local governments in Malaysia. This study employs quantitative method involving 1155 respondents who were randomly selected from local government personnel as well as local citizens. The instruments in the questionnaires were adopted from Wang and Wart (2007) who have also studied local government accountability. The findings reveal that respondents are satisfied with the services provided to the community. However, three areas of concerned are the inadequacy of citizens’ participation in programs, immediate actions on complaints as well as the slow response to repair dilapidated basic infrastructures such as roads, park, and recreations. It is recommended that local governments in Malaysia continue to engage the citizens in the decision making process so that the needs and demands of the citizens can be adequately fulfilled.

Keywords: citizen participation, political accountability, local government, Malaysia

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Authors: Desislav Andreev, Veselin Stanev

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Linux operating system continues to gain popularity with every passed year. This is due to its open-source license and a great number of distributions, covering users’ needs. At first glance it seems that Linux can be integrated in every type of systems – it is already present in personal computers, smartphones and even in some embedded systems like Raspberry Pi. However, Linux still does not meet the performance and security requirements to run effectively on a real-time system. Real-time systems are very time-restricted – their processes have to execute and finish at strict time intervals. The Completely Fair Scheduler present in Linux does not have such scheduling capabilities and it is not able to ensure that critical-time processes will execute on time. One of the ways to solve this problem is implementing an Adaptive Partition Scheduler solution similar to that present in QNX Neutrino operating system. This type of scheduling divides the CPU in multiple adaptive partitions where each partition holds a percentage of CPU usage called budget, which allows optimal usage of the CPU resources and also provides protection against cyber attacks such as Denial of Service. This approach will also benefit systems, where functional safety is highly demanded, such as the instrumental clusters in the Automotive industry. The purpose of this paper is to present a concept of Adaptive Partition Scheduler designed for Linux-based operating systems.

Keywords: adaptive partitions, Linux kernel modules, real-time systems, scheduling

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Authors: Angela Maria Fasnacht

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Detection of anomalies due to contaminants’ presence, also known as early detection systems in water treatment plants, has become a critical point that deserves an in-depth study for their improvement and adaptation to current requirements. The design of these systems requires a detailed analysis and processing of the data in real-time, so it is necessary to apply various statistical methods appropriate to the data generated, such as Spearman’s Correlation, Factor Analysis, Cross-Correlation, and k-fold Cross-validation. Statistical analysis and methods allow the evaluation of large data sets to model the behavior of variables; in this sense, statistical treatment or analysis could be considered a vital step to be able to develop advanced models focused on machine learning that allows optimized data management in real-time, applied to early detection systems in water treatment processes. These techniques facilitate the development of new technologies used in advanced sensors. In this work, these methods were applied to identify the possible correlations between the measured parameters and the presence of the glyphosate contaminant in the single-pass system. The interaction between the initial concentration of glyphosate and the location of the sensors on the reading of the reported parameters was studied.

Keywords: glyphosate, emergent contaminants, machine learning, probes, sensors, predictive

Procedia PDF Downloads 111