Search results for: data reduction

Authors: Kunihisa Kakumoto

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Purpose: The global environmental problem is now raised in the global dimension. The sprawl phenomenon over the natural limitation is to be made a forecast beforehand in an algorithmic way so that the condition of our social life can hopefully be protected under the natural limitation. The sustainable condition in the globe is now to be found to keep the balance between the capacity of nature and the possibility of our social lives. The amount of water on the earth is limited. Therefore, on the reason, sustainable conditions are strongly dependent on the capacity of water. The amount of water can be considered in relation to the area of the green planting because a certain volume of the water can be obtained in the forest, where the green planting can be preserved. We can find the sustainable conditions of the water in relation to the green planting area. The reduction of CO₂ by green planting is also possible. Possible Measure and the Methods: Until now, by the opportunity of many international conferences, the concept of the solar community as one prototype has been introduced by technical papers. The algorithmic trial calculation on the basic concept of the solar community can be taken into consideration. The concept of the solar community is based on the collected data of the solar model house. According to the algorithmic results of the prototype, the simulation work in the globe can be performed as the algorithmic conversion results. This algorithmic study can be simulated by the amount of water, also in relation to the green planting area. Additionally, the submission of CO₂ in the solar community and the reduction of CO₂ by green planting can be calculated. On the base of these calculations in the solar community, the sustainable conditions on the globe can be simulated as the conversion results in an algorithmic way. The digital formation in the solar community can also be taken into consideration by this opportunity. Conclusion: For the finding of sustainable conditions around the globe, the solar community as one prototype has been taken into consideration. The role of the water is very important because the capacity of the water supply is very limited. But, at present, the cycle of the social community is not composed by the point of the natural mechanism. The simulative calculation of this study can be shown by the limitation of the total water supply. According to this process, the total capacity of the water supply and the capable residential number of the population and the areas can be taken into consideration by the algorithmic calculation. For keeping enough water, the green planting areas are very important. The planting area is also very important to keep the balance of CO₂. The simulative calculation can be performed by the relation between the submission and the reduction of CO₂ in the solar community. For the finding of this total balance and the sustainable conditions, the green planting area and the total amount of water can be recognized by the algorithmic simulative calculation. The study for the finding of sustainable conditions can be performed by the simulative calculations on the algorithmic model in the solar community as one prototype. The example of one prototype can be in balance. The activity of the social life must be in the capacity of the natural mechanism. The capable capacity of the natural environment in our world is very limited.

Keywords: the solar community, the sustainable condition, the natural limitation, the algorithmic calculation

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Authors: Sarra Senhadji, Imene Benzeguimi, Zohra Yagoub

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Big Data represents the recent technology of manipulating voluminous and unstructured data sets over multiple sources. Therefore, NOSQL appears to handle the problem of unstructured data. Association rules mining is one of the popular techniques of data mining to extract hidden relationship from transactional databases. The algorithm for finding association dependencies is well-solved with Map Reduce. The goal of our work is to reduce the time of generating of frequent itemsets by using Map Reduce and NOSQL database oriented document. A comparative study is given to evaluate the performances of our algorithm with the classical algorithm Apriori.

Keywords: Apriori, Association rules mining, Big Data, Data Mining, Hadoop, MapReduce, MongoDB, NoSQL

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Authors: Melaku Tsehay

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The Consortium of Christian Relief and Development Associations (CCRDA), and the CORE Group Polio Partners (CGPP) Secretariat have been working with Global Alliance for Vac-cines and Immunization (GAVI) to improve the immunization data quality in Afar and Somali Regional States. The main aim of this study was to compare the quality of immunization data before and after the above interventions in health facilities in the pastoralist communities in Ethiopia. To this end, a comparative-cross-sectional study was conducted on 51 health facilities. The baseline data was collected in May 2019, while the end line data in August 2021. The WHO data quality self-assessment tool (DQS) was used to collect data. A significant improvment was seen in the accuracy of the pentavalent vaccine (PT)1 (p = 0.012) data at the health posts (HP), while PT3 (p = 0.010), and Measles (p = 0.020) at the health centers (HC). Besides, a highly sig-nificant improvment was observed in the accuracy of tetanus toxoid (TT)2 data at HP (p < 0.001). The level of over- or under-reporting was found to be < 8%, at the HP, and < 10% at the HC for PT3. The data completeness was also increased from 72.09% to 88.89% at the HC. Nearly 74% of the health facilities timely reported their respective immunization data, which is much better than the baseline (7.1%) (p < 0.001). These findings may provide some hints for the policies and pro-grams targetting on improving immunization data qaulity in the pastoralist communities.

Keywords: data quality, immunization, verification factor, pastoralist region

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Authors: Javed Iqbal

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Filling of Xiangjiaba Reservoir Lake in Southwest China triggered and re-activated numerous landslides due to water fluctuation. In order to understand the relationship between reservoirs and slope instability, a typical reservoir landslide (Dasha landslide) at right bank of Jinsha River was selected as a case study for in-depth investigations. The detailed field investigations were carried out in order to identify the landslide with respect to its surroundings and to find out the slip-surface. Boreholes were drilled in order to find out the subsurface lithology and the depth of failure of Dasha landslide. The in-situ geotechnical tests were performed, and the soil samples from exposed slip surface were retrieved for geotechnical laboratory analysis. Finally, stability analysis was done using 3D strength reduction method under different conditions of reservoir water level fluctuations and rainfall conditions. The in-depth investigations show that the Dasha landslide is a bedding rockslide which was once activated in 1986. The topography of Dasha landslide is relatively flat, while the back scarp and local terrain are relatively steep. The landslide area is about 29 × 104 m², and the maximum thickness of the landslide deposits revealed by drilling is about 40 m with the average thickness being about 20 m, and the volume is thus estimated being about 580 × 10⁴ m³. Bedrock in the landslide area is composed of Suining Formation of Jurassic age. The main rock type is silty mudstone with sandstone, and bedding orientation is 300~310° ∠ 7~22°. The factor of safety (FOS) of Dasha landslide obtained by 3D strength reduction cannot meet the minimum safety requirement under the working condition of reservoir level fluctuation as designed, with effect of rainfall and rapid drawdown.

Keywords: Dasha landslide, Xiangjiaba reservoir, strength reduction method, bedding rockslide

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Authors: Ali H. Daraji, Jack M. Hale, Ye Jianqiao

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With the extensive use of high specific strength structures to optimise the loading capacity and material cost in aerospace and most engineering applications, much effort has been expended to develop intelligent structures for active vibration reduction and structural health monitoring. These structures are highly flexible, inherently low internal damping and associated with large vibration and long decay time. The modification of such structures by adding lightweight piezoelectric sensors and actuators at efficient locations integrated with an optimal control scheme is considered an effective solution for structural vibration monitoring and controlling. The size and location of sensor and actuator are important research topics to investigate their effects on the level of vibration detection and reduction and the amount of energy provided by a controller. Several methodologies have been presented to determine the optimal location of a limited number of sensors and actuators for small-scale structures. However, these studies have tackled this problem directly, measuring the fitness function based on eigenvalues and eigenvectors achieved with numerous combinations of sensor/actuator pair locations and converging on an optimal set using heuristic optimisation techniques such as the genetic algorithms. This is computationally expensive for small- and large-scale structures subject to optimise a number of s/a pairs to suppress multiple vibration modes. This paper proposes an efficient method to determine optimal locations for a limited number of sensor/actuator pairs for active vibration reduction of a flexible structure based on finite element method and Hamilton’s principle. The current work takes the simplified approach of modelling a structure with sensors at all locations, subjecting it to an external force to excite the various modes of interest and noting the locations of sensors giving the largest average percentage sensors effectiveness measured by dividing all sensor output voltage over the maximum for each mode. The methodology was implemented for a cantilever plate under external force excitation to find the optimal distribution of six sensor/actuator pairs to suppress the first six modes of vibration. It is shown that the results of the optimal sensor locations give good agreement with published optimal locations, but with very much reduced computational effort and higher effectiveness. Furthermore, it is shown that collocated sensor/actuator pairs placed in these locations give very effective active vibration reduction using optimal linear quadratic control scheme.

Keywords: optimisation, plate, sensor effectiveness, vibration control

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Authors: M. Gangadharappa, M. Ravi Kumar, H. N. Reddappa

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The mechanical properties and morphological analysis of Al6061-Red mud particulate composites were investigated. The compositions of the composite include a matrix of Al6061 and the red mud particles of 53-75 micron size as reinforcement ranging from 0% to 12% at an interval of 2%. Stir casting technique was used to fabricate Al6061-Red mud composites. Density measurement, estimation of percentage porosity, tensile properties, fracture toughness, hardness value, impact energy, percentage elongation and percentage reduction in area. Further, the microstructures and SEM examinations were investigated to characterize the composites produced. The result shows that a uniform dispersion of the red mud particles along the grain boundaries of the Al6061 alloy. The tensile strength and hardness values increases with the addition of Red mud particles, but there is a slight decrease in the impact energy values, values of percentage elongation and percentage reduction in area as the reinforcement increases. From these results of investigation, we concluded that the red mud, an industrial waste can be used to enhance the properties of Al6061 alloy for engineering applications.

Keywords: Al6061, red mud, tensile strength, hardness and microstructures

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Authors: Eman Merza, Stephen Pearson, Glen Lichtwark, Peter Malliaras

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The Achilles tendon (AT) exhibits volume changes related to fluid flow under acute load which may be linked to changes in stiffness. Fluid flow provides a mechanical signal for cellular activity and may be one mechanism that facilitates tendon adaptation. This study aimed to investigate whether isometric intervention involving a high level of load duration and intensity could maximize the immediate reduction in AT volume and stiffness compared to interventions involving a lower level of load duration and intensity. Sixteen healthy participants (12 males, 4 females; age= 24.4 ± 9.4 years; body mass= 70.9 ± 16.1 kg; height= 1.7 ± 0.1 m) performed three isometric interventions of varying levels of load duration (2 s and 8 s) and intensity (35% and 75% maximal voluntary isometric contraction) over a 3 week period. Freehand 3D ultrasound was used to measure free AT volume (at rest) and length (at 35%, 55%, and 75% of maximum plantarflexion force) pre- and post-interventions. The slope of the force-elongation curve over these force levels represented individual stiffness (N/mm). Large reductions in free AT volume and stiffness resulted in response to long-duration high-intensity loading whilst less reduction was produced with a lower load intensity. In contrast, no change in free AT volume and a small increase in AT stiffness occurred with lower load duration. These findings suggest that the applied load on the AT must be heavy and sustained for a long duration to maximize immediate volume reduction, which might be an acute response that enables optimal long-term tendon adaptation via mechanotransduction pathways.

Keywords: Achilles tendon, volume, stiffness, free tendon, 3d ultrasound

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Authors: Helan Satish, M. Ramasubba Reddy

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The simulation of an endocardial cell for gene mutation in the cardiac sodium ion channel NaV1.5, encoded by SCN5A gene, is discussed. The characterization of Brugada Syndrome by loss of function effect on SCN5A mutation due to L812Q mutant present in the DII-S4 transmembrane region of the NaV1.5 channel protein and its effect in an endocardial cell is studied. Ten Tusscher model of human ventricular action potential is modified to incorporate the changes contributed by L812Q mutant in the endocardial cells. Results show that BrS-associated SCN5A mutation causes reduction in the inward sodium current by modifications in the channel gating dynamics such as delayed activation, enhanced inactivation, and slowed recovery from inactivation in the endocardial cell. A decrease in the inward sodium current was also observed, which affects depolarization phase (Phase 0) that leads to reduction in the spike amplitude of the cardiac action potential.

Keywords: SCN5A gene mutation, sodium channel, Brugada syndrome, cardiac arrhythmia, action potential

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Authors: Maria Paula Santos, Ana Lucas

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Organizations support their operations and decision making on the data they have at their disposal, so the quality of these data is remarkably important and Data Quality (DQ) is currently a relevant issue, the literature being unanimous in pointing out that poor DQ can result in large costs for organizations. The literature review identified and described 24 Critical Success Factors (CSF) for Data Quality Management (DQM) that were presented to a panel of experts, who ordered them according to their degree of importance, using the Delphi method with the Q-sort technique, based on an online questionnaire. The study shows that the five most important CSF for DQM are: definition of appropriate policies and standards, control of inputs, definition of a strategic plan for DQ, organizational culture focused on quality of the data and obtaining top management commitment and support.

Keywords: critical success factors, data quality, data quality management, Delphi, Q-Sort

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Authors: Mehrshad Khosraviani, Sepehr Najjarpour

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Considering the usage of graph-based approaches in systems and synthetic biology, and the various types of ‎the graphs employed by them, a comprehensive graph library based ‎on the three-tier architecture (3TA) was previously introduced for full representation of the biological systems. Although proposing a 3TA-based graph library, three following reasons motivated us to redesign the graph ‎library based on the service-oriented architecture (SOA): (1) Maintaining the accuracy of the data related to an input graph (including its edges, its ‎vertices, its topology, etc.) without involving the end user:‎ Since, in the case of using 3TA, the library files are available to the end users, they may ‎be utilized incorrectly, and consequently, the invalid graph data will be provided to the ‎computer algorithms. However, considering the usage of the SOA, the operation of the ‎graph registration is specified as a service by encapsulation of the library files. In other words, overall control operations needed for registration of the valid data will be the ‎responsibility of the services. (2) Partitioning of the library product into some different parts: Considering 3TA, a whole library product was provided in general. While here, the product ‎can be divided into smaller ones, such as an AND/OR graph drawing service, and each ‎one can be provided individually. As a result, the end user will be able to select any ‎parts of the library product, instead of all features, to add it to a project. (3) Reduction of the complexities: While using 3TA, several other libraries must be needed to add for connecting to the ‎database, responsibility of the provision of the needed library resources in the SOA-‎based graph library is entrusted with the services by themselves. Therefore, the end user ‎who wants to use the graph library is not involved with its complexity. In the end, in order to ‎make ‎the library easier to control in the system, and to restrict the end user from accessing the files, ‎it was preferred to use the service-oriented ‎architecture ‎‎(SOA) over the three-tier architecture (3TA) and to redevelop the previously proposed graph library based on it‎.

Keywords: Bio-Design Automation, Biological System, Graph Library, Service-Oriented Architecture, Systems and Synthetic Biology

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Authors: Salah Al-Din I. Badran, Samad Ahmadi, Ismail Shahin

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A blind source separation method is proposed; in this method, we use a non-uniform filter bank and a novel normalisation. This method provides a reduced computational complexity and increased convergence speed comparing to the full-band algorithm. Recently, adaptive sub-band scheme has been recommended to solve two problems: reduction of computational complexity and increase the convergence speed of the adaptive algorithm for correlated input signals. In this work, the reduction in computational complexity is achieved with the use of adaptive filters of orders less than the full-band adaptive filters, which operate at a sampling rate lower than the sampling rate of the input signal. The decomposed signals by analysis bank filter are less correlated in each subband than the input signal at full bandwidth, and can promote better rates of convergence.

Keywords: blind source separation, computational complexity, subband, convergence speed, mixture

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Authors: Alida Sandison, Louise A. Stroud

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Narcissism is a personality configuration which has both normal and pathological personality expressions. Narcissism is highly complex, and is linked to a broad field of research. There are both dimensional and categorical conceptualisations of narcissism, and a variety of theoretical formulations that have been put forward to understand the narcissistic personality configuration. Currently, Kernberg’s Object Relations theory is well supported for this purpose. The complexity and particular defense mechanisms at play in the narcissistic personality make it a difficult personality configuration worth further research. Psychobiography as a methodology allows for the exploration of the lived life, and is thus a useful methodology to surmount these inherent challenges. Narcissism has been a focus of academic interest for a long time, and although there is a lot of research done in this area, to the researchers' knowledge, narcissistic dynamics have never been explored within a psychobiographical format. Thus, the primary aim of the research was to explore and describe narcissism in the life of Howard Hughes, with the objective of gaining further insight into narcissism through the use of this unconventional research approach. Hughes was chosen as subject for the study as he is renowned as an eccentric billionaire who had his revolutionary effect on the world, but was concurrently disturbed within his personal pathologies. Hughes was dynamic in three different sectors, namely motion pictures, aviation and gambling. He became more and more reclusive as he entered into middle age. From his early fifties he was agoraphobic, and the social network of connectivity that could reasonably be expected from someone in the top of their field was notably distorted. Due to his strong narcissistic personality configuration, and the interpersonal difficulties he experienced, Hughes represents an ideal figure to explore narcissism. The study used a single case study design, and purposive sampling to select Hughes. Qualitative data was sampled, using secondary data sources. Given that Hughes was a famous figure, there is a plethora of information on his life, which is primarily autobiographical. This includes books written about his life, and archival material in the form of newspaper articles, interviews and movies. Gathered data were triangulated to avoid the effect of author bias, and increase the credibility of the data used. It was collected using Yin’s guidelines for data collection. Data was analysed using Miles and Huberman strategy of data analysis, which consists of three steps, namely, data reduction, data display, and conclusion drawing and verification. Patterns which emerged in the data highlighted the defense mechanisms used by Hughes, in particular that of splitting and projection, in defending his sense of self. These defense mechanisms help us to understand the high levels of entitlement and paranoia experienced by Hughes. Findings provide further insight into his sense of isolation and difference, and the consequent difficulty he experienced in maintaining connections with others. Findings furthermore confirm the effectiveness of Kernberg’s theory in understanding narcissism observing an individual life.

Keywords: Howard Hughes, narcissism, narcissistic defenses, object relations

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Authors: Seok-Tae Yoon, Jae-Yeong Choi, Gyu-Mok Jeon, Yong-Jin Cho, Jong-Chun Park

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Conventional submarines obtain propulsive force by using an electric propulsion system consisting of a diesel generator, battery, motor, and propeller. In the underwater, the submarine uses the electric power stored in the battery. After that, when a certain amount of electric power is consumed, the submarine floats near the sea water surface and recharges the electric power by using the diesel generator. The voyage carried out while charging the power is called a snorkel, and the high-temperature exhaust gas from the diesel generator forms a heat distribution on the sea water surface. The heat distribution is detected by weapon system equipped with thermo-detector and that is the main cause of reducing the survivability of the submarine. In this paper, an experimental study was carried out to establish optimal operating conditions of a submarine for reduction of infrared signature radiated from the sea water surface. For this, a hot gas generating system and a round acrylic water tank with adjustable water level were made. The control variables of the experiment were set as the mass flow rate, the temperature difference between the water and the hot gas in the water tank, and the water level difference between the air outlet and the water surface. The experimental instrumentation used a thermocouple of T-type to measure the released air temperature on the surface of the water, and a thermography system to measure the thermal energy distribution on the water surface. As a result of the experiment study, we analyzed the correlation between the final released temperature of the exhaust pipe exit in a submarine and the depth of the snorkel, and presented reasonable operating conditions for the infrared signature reduction of submarine.

Keywords: experiment study, flow rate, infrared signature, snorkeling, thermography

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Authors: Sanaz Moayer, Fang Huang, Scott Gardner

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In the highly leveraged business world of today, an organisation’s success depends on how it can manage and organize its traditional and intangible assets. In the knowledge-based economy, knowledge as a valuable asset gives enduring capability to firms competing in rapidly shifting global markets. It can be argued that ability to create unique knowledge assets by configuring ICT and human capabilities, will be a defining factor for international competitive advantage in the mid-21st century. The concept of KM is recognized in the strategy literature, and increasingly by senior decision-makers (particularly in large firms which can achieve scalable benefits), as an important vehicle for stimulating innovation and organisational performance in the knowledge economy. This thinking has been evident in professional services and other knowledge intensive industries for over a decade. It highlights the importance of social capital and the value of the intellectual capital embedded in social and professional networks, complementing the traditional focus on creation of intellectual property assets. Despite the growing interest in KM within professional services there has been limited discussion in relation to multinational resource based industries such as mining and petroleum where the focus has been principally on global portfolio optimization with economies of scale, process efficiencies and cost reduction. The Australian minerals and metals mining industry, although traditionally viewed as capital intensive, employs a significant number of knowledge workers notably- engineers, geologists, highly skilled technicians, legal, finance, accounting, ICT and contracts specialists working in projects or functions, representing potential knowledge silos within the organisation. This silo effect arguably inhibits knowledge sharing and retention by disaggregating corporate memory, with increased operational and project continuity risk. It also may limit the potential for process, product, and service innovation. In this paper the strategic application of knowledge management incorporating contemporary ICT platforms and data mining practices is explored as an important enabler for knowledge discovery, reduction of risk, and retention of corporate knowledge in resource based industries. With reference to the relevant strategy, management, and information systems literature, this paper highlights possible connections (currently undergoing empirical testing), between an Strategic Knowledge Management (SKM) framework incorporating supportive Data Mining (DM) practices and competitive advantage for multinational firms operating within the Australian resource sector. We also propose based on a review of the relevant literature that more effective management of soft and hard systems knowledge is crucial for major Australian firms in all sectors seeking to improve organisational performance through the human and technological capability captured in organisational networks.

Keywords: competitive advantage, data mining, mining organisation, strategic knowledge management

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Authors: Ashis Pradhan, Mohan P. Pradhan

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Pattern Matching is useful for recognizing character in a digital image. OCR is one such technique which reads character from a digital image and recognizes them. Line segmentation is initially used for identifying character in an image and later refined by morphological operations like binarization, erosion, thinning, etc. The work discusses a recognition technique that defines a set of morphological operators based on its orientation in a character. These operators are further categorized into groups having similar shape but different orientation for efficient utilization of memory. Finally the characters are recognized in accordance with the occurrence of frequency in hierarchy of significant pattern of those morphological operators and by comparing them with the existing database of each character.

Keywords: binary image, morphological patterns, frequency count, priority, reduction data set and recognition

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Authors: Etim, Victoria Enefiok, Dada, Oluseyi Akintunde, Bassey Okon

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Phonological disorder is a serious and disturbing issue to many parents and teachers. Efforts towards resolving the problem have been undermined by other specific disabilities which were hidden to many regular and special education teachers. It is against this background that this study was motivated to provide data on the prevalence of phonological disorders in children with specific language impairment (CWSLI) as the first step towards critical intervention. The study was a survey of 15 CWSLI from St. Louise Inclusive schools, Ikot Ekpene in Akwa Ibom State of Nigeria. Phonological Processes Diagnostic Scale (PPDS) with 17 short sentences, which cut across the five phonological processes that were examined, were validated by experts in test measurement, phonology and special education. The respondents were made to read the sentences with emphasis on the targeted sounds. Their utterances were recorded and analyzed in the language laboratory using Praat Software. Data were also collected through friendly interactions at different times from the clients. The theory of generative phonology was adopted for the descriptive analysis of the phonological processes. Data collected were analyzed using simple percentage and composite bar chart for better understanding of the result. The study found out that CWSLI exhibited the five phonological processes under investigation. It was revealed that 66.7%, 80%, 73.3%, 80%, and 86.7% of the respondents have severe deficit in fricative stopping, velar fronting, liquid gliding, final consonant deletion and cluster reduction, respectively. It was therefore recommended that a nationwide survey should be carried out to have national statistics of CWSLI with phonological deficits and develop intervention strategies for effective therapy to remediate the disorder.

Keywords: language disorders, phonology, phonological processes, specific language impairment

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Authors: Marriette Sakah, Samuel Gyamfi, Morkporkpor Delight Sedzro, Christoph Kuhn

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Ghana is experiencing rapid economic development and its cities command an increasingly dominant role as centers of both production and consumption. Cities run on energy and are extremely vulnerable to energy scarcity, energy price escalations and health impacts of very poor air quality. The overriding concern in Ghana and other West African states is bridging the gap between energy demand and supply. Energy efficiency presents a cost-effective solution for supply challenges by enabling more coverage with current power supply levels and reducing the need for investment in additional generation capacity and grid infrastructure. In Ghana, major issues for energy policy formulation in residential applications include lack of disaggregated electrical energy consumption data and lack of thorough understanding with regards to socio-economic influences on energy efficiency investment. This study uses a bottom up approach to estimate baseline electricity end-use as well as the energy consumption of best available technologies to enable estimation of energy-efficiency resource in terms of relative reduction in total energy use for Tema city, Ghana. A ground survey was conducted to assess the probable consumer behavior in response to energy efficiency initiatives to enable estimation of the amount of savings that would occur in response to specific policy interventions with regards to funding and incentives provision targeted at households. Results show that 16% - 54% reduction in annual electricity consumption is reasonably achievable depending on the level of incentives provision. The saved energy could supply 10000 - 34000 additional households if the added households use only best available technology. Political support and consumer awareness are necessary to translate energy efficiency resources into real energy savings.

Keywords: achievable energy savings, energy efficiency, Ghana, household appliances

Procedia PDF Downloads 198

Authors: Usman Ahmed Khan

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Urbanization directly affects the existing infrastructure, landscape modification, environmental contamination, and traffic pollution, especially if there is a lack of urban planning. Recently, the rapid urban sprawl has resulted in less developed green areas and has devastating environmental consequences. This study was aimed to study the past urban expansion rates and measure LST from satellite data. The land use land cover (LULC) maps of years 1996, 2010, 2013, and 2017 were generated using landsat satellite images. Four main classes, i.e., water, urban, bare land, and vegetation, were identified using unsupervised classification with iterative self-organizing data analysis (isodata) technique. The LST from satellite thermal data can be derived from different procedures: atmospheric, radiometric calibrations and surface emissivity corrections, classification of spatial changeability in land-cover. Different methods and formulas were used in the algorithm that successfully retrieves the land surface temperature to help us study the thermal environment of the ground surface. To verify the algorithm, the land surface temperature and the near-air temperature were compared. The results showed that, From 1996-2017, urban areas increased to about a considerable increase of about 48%. Few areas of the city also shown in a reduction in LST from the year 1996-2017 that actually began their transitional phase from rural to urban LULC. The mean temperature of the city increased averagely about 1ºC each year in the month of October. The green and vegetative areas witnessed a decrease in the area while a higher number of pixels increased in urban class.

Keywords: LST, LULC, isodata, urbanization

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Authors: Xiaoling Ren, Guidong Yang

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As one of the largest industrial synthetic chemicals in the world, ammonia has the advantages of high energy density, easy liquefaction, and easy transportation, which is widely used in agriculture, chemical industry, energy storage, and other fields. The industrial Haber-Bosch method process for ammonia synthesis is generally conducted under severe conditions. It is essential to develop a green, sustainable strategy for ammonia production to meet the growing demand. In this direction, photocatalytic nitrogen reduction has huge advantages over the traditional, well-established Haber-Bosch process, such as the utilization of natural sun light as the energy source and significantly lower pressure and temperature to affect the reaction process. However, the high activation energy of nitrogen and the low efficiency of photo-generated electron-hole separation in the photocatalyst result in low ammonia production yield. Many researchers focus on improving the catalyst. In addition to modifying the catalyst, improving the dispersion of the catalyst and making full use of active sites are also means to improve the overall catalytic activity. Few studies have been carried out on this, which is the aim of this work. In this work, by making full use of the nitrogen activation ability of WO3-x with defective sites, small size WO3-x photocatalyst with high dispersibility was constructed, while the growth of WO3-x was restricted by using a high specific surface area mesoporous SBA-15 molecular sieve with the regular pore structure as a template. The morphology of pure SBA-15 and WO3-x/SBA-15 was characterized byscanning electron microscopy (SEM). Compared with pure SBA-15, some small particles can be found in the WO3-x/SBA-15 material, which means that WO3-x grows into small particles under the limitation of SBA-15, which is conducive to the exposure of catalytically active sites. To elucidate the chemical nature of the material, the X-ray diffraction (XRD) analysis was conducted. The observed diffraction pattern inWO3-xis in good agreement with that of the JCPDS file no.71-2450. Compared with WO3-x, no new peaks appeared in WO3-x/SBA-15.It can be concluded that WO3-x/SBA-15 was synthesized successfully. In order to provide more active sites, the mass content of WO3-x was optimized. Then the photocatalytic nitrogen reduction performances of above samples were performed with methanol as a hole scavenger. The results show that the overall ammonia production performance of WO3-x/SBA-15 is improved than pure bulk WO3-x. The above results prove that making full use of active sites is also a means to improve overall catalytic activity.This work provides material basis for the design of high-efficiency photocatalytic nitrogen reduction catalysts.

Keywords: ammonia, photocatalytic, nitrogen reduction, WO3-x, high dispersibility

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Authors: A. M. Nasr, W. R. Azzam, K. E. Ebeed

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For bored piles, careful cleaning must be used to reduce the amount of material trapped in the drilled hole; otherwise, the debris' presence might cause the soft toe effect, which would affect the axial resistance. There isn't much comprehensive research on bored piles with debris. In order to investigate the behavior of a single pile, a pile composite foundation, a two pile group, a three pile group and a four pile group investigation conducts, forty-eight numerical tests in which the debris is simulated using foam rubber.1m pile diameter and 10m length with spacing 3D and depth of foundation 1m used in this study. It is found that the existence of debris causes a reduction of bearing capacity by 64.58% and 33.23% for single pile and pile composite foundation, respectively, 23.27% and 24.24% for the number of defective piles / total number of pile =1/2 and 1 respectively for two group pile, 10.23%, 19.42% and 28.47% for the number of defective piles / total number of pile =1/3,2/3 and 1 respectively for three group pile and, this reduction increase with the increase in a number of defective piles / a total number of piles and 7.1%, 13.32%,19.02% and 26.36 for the number of defective piles / total number of pile =1/4,2/4,3/4 and 1 respectively for four group pile and decreases with an increase of number of pile duo to interaction effect.

Keywords: debris, Foundation, defective, interaction, board pile

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Authors: Omolara Lade, David Oloke

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Ibadan City suffers serious water supply problems; cases of dry taps are common in virtually every part of the City. The scarcity of piped water has made communities find alternative water sources; groundwater sources being a ready source. These wells are prone to pollution due to the close proximity of septic tanks to wells, disposal of solid or liquid wastes in pits, abandoned boreholes or even stream channels and landfills. Storms and floods in Ibadan have increased with consequent devastating effects claiming over 120 lives and displacing 600 people on August 2011 alone. In this study, an analysis of the water demand and sources of supply for the city was carried out through questionnaire survey and collection of data from City’s main water supply - Water Corporation of Oyo State (WCOS), groundwater sources were explored and 30 years rainfall data were collected from Meteorological station in Ibadan. 1067 questionnaire were administered at household level with a response rate of 86.7 %. A descriptive analysis of the survey revealed that 77.1 % of the respondents did not receive water at all from WCOS while 83.8 % depend on groundwater sources. Analysis of data from WCOS revealed that main water supply is inadequate as < 10 % of the population water demand was met. Rainfall intensity is highest in June with a mean value of 188 mm, which can be harvested at community—based level and used to complement the population water demand. Rainwater harvesting if planned, and managed properly will become a valuable alternative source of managing urban flood and alleviating water scarcity in the city.

Keywords: Ibadan, rainwater harvesting, sustainable water, urban flooding

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Authors: A. Ikhlef

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Image noise in computed tomography, is mainly caused by the statistical noise, system noise reconstruction algorithm filters. Since last few years, low dose x-ray imaging became more and more desired and looked as a technical differentiating technology among CT manufacturers. In order to achieve this goal, several technologies and techniques are being investigated, including both hardware (integrated electronics and photon counting) and software (artificial intelligence and machine learning) based solutions. From a hardware point of view, electronic noise could indeed be a potential driver for low and ultra-low dose imaging. We demonstrated that the reduction or elimination of this term could lead to a reduction of dose without affecting image quality. Also, in this study, we will show that we can achieve this goal using conventional electronics (low cost and affordable technology), designed carefully and optimized for maximum detective quantum efficiency. We have conducted the tests using large imaging objects such as 30 cm water and 43 cm polyethylene phantoms. We compared the image quality with conventional imaging protocols with radiation as low as 10 mAs (<< 1 mGy). Clinical validation of such results has been performed as well.

Keywords: computed tomography, electronic noise, scintillation detector, x-ray detector

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Authors: M. H. Rajikin, S. M. M. Syairah, A. R. Sharaniza

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Effects of nicotine on pre-partum body weight and preimplantation embryonic development has been reported previously. Present study was conducted to determine the effects of annatto (Bixa orellana)-derived delta-tocotrienol (TCT) (with presence of 10% gamma-TCT isomer) on the nicotine-induced reduction in body weight and 8-cell embryonic growth in mice. Twenty four 6-8 weeks old (23-25g) female balb/c mice were randomly divided into four groups (G1-G4; n=6). Those groups were subjected to the following treatments for 7 consecutive days: G1 (control) were gavaged with 0.1 ml tocopherol stripped corn oil, G2 was subcutaneously (s.c.) injected with 3 mg/kg/day of nicotine, G3 received concurrent treatment of nicotine (3 mg/kg/day) and 60 mg/kg/day of δ-TCT mixture (contains 90% delta & 10% gamma isomers) and G4 was given 60 mg/kg/day of δ-TCT mixture alone. Body weights were recorded daily during the treatment. On Day 8, females were superovulated with 5 IU Pregnant Mare’s Serum Gonadotropin (PMSG) for 48 hours followed with 5 IU human Chorionic Gonadotropin (hCG) before mated with males at the ratio of 1:1. Females were sacrificed by cervical dislocation for embryo collection 48 hours post-coitum. Collected embryos were cultured in vitro. Results showed that throughout Day 1 to Day 7, the body weight of nicotine treated group (G2) was significantly lower (p<0.05) than that of G1, G3 and G4. Intervention with δ-TCT mixture (G3) managed to increase the body weight close to the control group. This is also observed in the group treated with δ-TCT mixture alone (G4). The development of 8-cell embryos following in vitro culture (IVC) was totally inhibited in G2. Intervention with δ-TCT mixture (G3) resulted in the production of 8-cell embryos, although it was not up to that of the control group. Treatment with δ-TCT mixture alone (G4) caused significant increase in the average number of produced 8-cell embryo compared to G1. Present data indicated that δ-TCT mixture was able to reverse the body weight loss in nicotine treated mice and the development of 8-cell embryos was also improved.

Keywords: δ-tocotrienol, body weight, nicotine, preimplantation embryonic development

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Authors: Antonella Falanga, Armando Cartenì

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Today, an unprecedented amount of data coming from several sources, including mobile devices, sensors, tracking systems, and online platforms, characterizes our lives. The term “big data” not only refers to the quantity of data but also to the variety and speed of data generation. These data hold valuable insights that, when extracted and analyzed, facilitate informed decision-making. The 4Vs of big data - velocity, volume, variety, and value - highlight essential aspects, showcasing the rapid generation, vast quantities, diverse sources, and potential value addition of these kinds of data. This surge of information has revolutionized many sectors, such as business for improving decision-making processes, healthcare for clinical record analysis and medical research, education for enhancing teaching methodologies, agriculture for optimizing crop management, finance for risk assessment and fraud detection, media and entertainment for personalized content recommendations, emergency for a real-time response during crisis/events, and also mobility for the urban planning and for the design/management of public and private transport services. Big data's pervasive impact enhances societal aspects, elevating the quality of life, service efficiency, and problem-solving capacities. However, during this transformative era, new challenges arise, including data quality, privacy, data security, cybersecurity, interoperability, the need for advanced infrastructures, and staff training. Within the transportation sector (the one investigated in this research), applications span planning, designing, and managing systems and mobility services. Among the most common big data applications within the transport sector are, for example, real-time traffic monitoring, bus/freight vehicle route optimization, vehicle maintenance, road safety and all the autonomous and connected vehicles applications. Benefits include a reduction in travel times, road accidents and pollutant emissions. Within these issues, the proper transport demand estimation is crucial for sustainable transportation planning. Evaluating the impact of sustainable mobility policies starts with a quantitative analysis of travel demand. Achieving transportation decarbonization goals hinges on precise estimations of demand for individual transport modes. Emerging technologies, offering substantial big data at lower costs than traditional methods, play a pivotal role in this context. Starting from these considerations, this study explores the usefulness impact of big data within transport demand estimation. This research focuses on leveraging (big) data collected during the COVID-19 pandemic to estimate the evolution of the mobility demand in Italy. Estimation results reveal in the post-COVID-19 era, more than 96 million national daily trips, about 2.6 trips per capita, with a mobile population of more than 37.6 million Italian travelers per day. Overall, this research allows us to conclude that big data better enhances rational decision-making for mobility demand estimation, which is imperative for adeptly planning and allocating investments in transportation infrastructures and services.

Keywords: big data, cloud computing, decision-making, mobility demand, transportation

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Authors: Djamila Benhaddouche, Abdelkader Benyettou

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In this paper, we used data mining to extract biomedical knowledge. In general, complex biomedical data collected in studies of populations are treated by statistical methods, although they are robust, they are not sufficient in themselves to harness the potential wealth of data. For that you used in step two learning algorithms: the Decision Trees and Support Vector Machine (SVM). These supervised classification methods are used to make the diagnosis of thyroid disease. In this context, we propose to promote the study and use of symbolic data mining techniques.

Keywords: biomedical data, learning, classifier, algorithms decision tree, knowledge extraction

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Authors: Usama Ahmed

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Data mining is the process of analyze data which are used to predict helpful information. It is the field of research which solve various type of problem. In data mining, classification is an important technique to classify different kind of data. Diabetes is most common disease. This paper implements different classification technique using Waikato Environment for Knowledge Analysis (WEKA) on diabetes dataset and find which algorithm is suitable for working. The best classification algorithm based on diabetic data is Naïve Bayes. The accuracy of Naïve Bayes is 76.31% and take 0.06 seconds to build the model.

Keywords: data mining, classification, diabetes, WEKA

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Authors: Onu Theresa Chinyere

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The study evaluates the perceived effect of climate change on nutritional status of women in Nigeria. Five research questions and two hypotheses were formulated to guide the study. The study adopted a survey and experimental study research design. One thousand two hundred and fifty one (1,250) respondents were selected from different State in Nigeria using multistage sampling technique. The instruments used to collect data were questionnaire and personal interview on socio economic characteristics of respondents, while Anthropometric data (height and weight) were also used. The data was analyzed using t-test statistic, decided at 50% level of significance. The study found that most states in Nigeria experience high winds, warmer and frequent hot days and night over most land areas, droughts and tides during climate change events. The respondent unanimously agree that climate change causes reduction in food yields, decline in food availability/supply, negatively affecting soil quality, carbon fertilization, decreases flexibilities in technology choices to strengthen food production. The Anthropometric analysis shows that out of 1250 women sampled, 560 (44.8%) maintain normal weight, while 405 (32.40%) women were found to be underweight, since their body mass index is less that 18.5. There were few cases of obesity among the surveyed women since only 80 out of 1250 which represent 6.4% of the women were obese. Bases on the findings, the following recommendations were made-local fertilizer should be encouraged to boost foods yield especially during climate change: women should imbibe the culture of preservation or reservoir that will help in mitigating the effects of climate on food intake and nutritional status, especially during the crisis period, among others.

Keywords: climate change, nutrition anthropometric analysis, obesity culture, environment and women among others

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Authors: Carlos V. Gonzalez

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Background: Providers of in-home and community based services strive for the elimination of preventable harm to the people under their care as well as to the employees who support them. Traditional models of safety and protection from harm have assumed that the absence of incidents of harm is a good indicator of safe practices. However, this model creates an illusion of safety that is easily shaken by sudden and inadvertent harmful events. As an alternative, we have developed and implemented an evidence-based resilient model of safety known as C.O.P.E. (Caring, Observing, Predicting and Evaluating). Within this model, safety is not defined by the absence of harmful incidents, but by the presence of continuous monitoring, anticipation, learning, and rapid response to events that may lead to harm. Objective: The objective was to evaluate the effectiveness of the C.O.P.E. model for the reduction of harm to individuals with mental disabilities who receive home and community based services. Methods: Over the course of 2 years we counted the number of incidents of harm and near misses. We trained employees on strategies to eliminate incidents before they fully escalated. We trained employees to track different levels of patient status within a scale from 0 to 10. Additionally, we provided direct support professionals and supervisors with customized smart phone applications to track and notify the team of changes in that status every 30 minutes. Finally, the information that we collected was saved in a private computer network that analyzes and graphs the outcome of each incident. Result and conclusions: The use of the COPE model resulted in: A reduction in incidents of harm. A reduction the use of restraints and other physical interventions. An increase in Direct Support Professional’s ability to detect and respond to health problems. Improvement in employee alertness by decreasing sleeping on duty. Improvement in caring and positive interaction between Direct Support Professionals and the person who is supported. Developing a method to globally measure and assess the effectiveness of prevention from harm plans. Future applications of the COPE model for the reduction of harm to people who receive home and community based services are discussed.

Keywords: harm, patients, resilience, safety, mental illness, disability

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Authors: Asifa Amara, Prachi Singh, Kanishka, Debargho Pathak, Akshat Kumar, Jayakumar Eravelly

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Today's generation is totally dependent on technology that uses data as its fuel. The present study is all about innovations and developments in data science and gives an idea about how efficiently to use the data provided. This study will help to understand the core concepts of data science. The concept of artificial intelligence was introduced by Alan Turing in which the main principle was to create an artificial system that can run independently of human-given programs and can function with the help of analyzing data to understand the requirements of the users. Data science comprises business understanding, analyzing data, ethical concerns, understanding programming languages, various fields and sources of data, skills, etc. The usage of data science has evolved over the years. In this review article, we have covered a part of data science, i.e., machine learning. Machine learning uses data science for its work. Machines learn through their experience, which helps them to do any work more efficiently. This article includes a comparative study image between human understanding and machine understanding, advantages, applications, and real-time examples of machine learning. Data science is an important game changer in the life of human beings. Since the advent of data science, we have found its benefits and how it leads to a better understanding of people, and how it cherishes individual needs. It has improved business strategies, services provided by them, forecasting, the ability to attend sustainable developments, etc. This study also focuses on a better understanding of data science which will help us to create a better world.

Keywords: data science, machine learning, data analytics, artificial intelligence

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Authors: Shady Adib, Vladimir Vinogradov, Peter Gosling

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Digital Twin (DT) technology is a new technology that appeared in the early 21st century. The DT is defined as the digital representation of living and non-living physical assets. By connecting the physical and virtual assets, data are transmitted smoothly, allowing the virtual asset to fully represent the physical asset. Although there are lots of studies conducted on the DT concept, there is still limited information about the ability of the DT models for monitoring and detecting unexpected changes in structural behaviour in real time. This is due to the large computational efforts required for the analysis and an excessively large amount of data transferred from sensors. This paper aims to develop the DT concept to be able to detect the abnormal changes in structural behaviour in real time using advanced modelling techniques, deep learning algorithms, and data acquisition systems, taking into consideration model uncertainties. finite element (FE) models were first developed offline to be used with a reduced basis (RB) model order reduction technique for the construction of low-dimensional space to speed the analysis during the online stage. The RB model was validated against experimental test results for the establishment of a DT model of a two-dimensional truss. The established DT model and deep learning algorithms were used to identify the location of damage once it has appeared during the online stage. Finally, the RB model was used again to identify the damage severity. It was found that using the RB model, constructed offline, speeds the FE analysis during the online stage. The constructed RB model showed higher accuracy for predicting the damage severity, while deep learning algorithms were found to be useful for estimating the location of damage with small severity.

Keywords: data acquisition system, deep learning, digital twin, model uncertainties, reduced basis, reduced order model

Procedia PDF Downloads 81