Search results for: decentralized data management

Authors: Faranak Omidian

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This study has been carried out to examine the status of architecture department at bachelor's level of engineering architecture in Islamic Azad University of Dezful in 2012-13 academic year. The present research is a descriptive cross sectional study and in terms of measurement, it is descriptive and analytical, which was done based on 7 steps and in 7 areas with 32 criteria and 169 indicators. The sample includes 201 students, 14 faculty members, 72 graduates and 39 employers. Simple random sampling method, complete enumeration method, network sampling (snowball sampling) were used for students, faculty members and graduates respectively. All sample responded to the questions. After data collection, the findings were ranked on Likert scale from desirable to undesirable with the scores ranging from 1 to 3.The results showed that the department with a score of 1.88 in regard to objectives, organizational status, management and organizations, with a score of 2 in relation to students, with a score of 1.8 in regard to faculty members was in a relatively desirable status. Regarding training courses and curriculum, it gained a score of 2.33 which indicates the desirable status of the department in this regard. It gained scores of 1.75, 2, and 1.8 with respect to educational and research facilities and equipment, teaching and learning strategies, and graduates respectively, all of which shows the relatively desirable status of the department. The results showed that the department of architecture, with an average score of 2.14 in all evaluated areas, was in a desirable situation. Therefore, although the department generally has a desirable status, it needs to put in more effort to tackle its weaknesses and shortages and corrects its defects in order to promote educational quality, taking to the desirable level.

Keywords: internal evaluation, architecture department in Islamic, Azad University, Dezful

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Authors: Nattabhorn Leamcharaskul

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This study aims to examine determining factors of the dynamics of poverty in Thailand by using panel data of 3,567 households in 2007-2017. Four techniques of estimation are employed to analyze the situation of poverty across households and time periods: the multinomial logit model, the sequential logit model, the quantile regression model, and the difference in difference model. Households are categorized based on their experiences into 5 groups, namely chronically poor, falling into poverty, re-entering into poverty, exiting from poverty and never poor households. Estimation results emphasize the effects of demographic and socioeconomic factors as well as unexpected events on the economic status of a household. It is found that remittances have positive impact on household’s economic status in that they are likely to lower the probability of falling into poverty or trapping in poverty while they tend to increase the probability of exiting from poverty. In addition, not only receiving a secondary source of household income can raise the probability of being a never poor household, but it also significantly increases household income per capita of the chronically poor and falling into poverty households. Public work programs are recommended as an important tool to relieve household financial burden and uncertainty and thus consequently increase a chance for households to escape from poverty.

Keywords: difference in difference, dynamic, multinomial logit model, panel data, poverty, quantile regression, remittance, sequential logit model, Thailand, transfer

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Authors: Sajid Aman

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Jobs in the banking sector in Pakistan are perceived as very tough, due to which employee turnover is very high. However, the managerial role is very important in influencing employees’ attitudes toward their turnout. This paper explores the manager’s role in influencing employees’ effectiveness on the job. The paper adopted a pragmatic approach by combining both qualitative and quantitative data. The study employed an exploratory sequential strategy under a mixed-method research design. Qualitative data was analyzed using thematic analysis. Five major themes, such as the manager’s attitude towards employees, his leadership style, listening to employee’s personal problems, provision of personal loans without interest and future career prospects, emerged as key factors increasing employee’s effectiveness in the banking sector. The quantitative data revealed that a manager’s attitude, leadership style, availability to listen to employees’ personal problems, and future career prospects and listening to employee’s personal problems are strongly associated with employees’ effectiveness at the job. However, personal loan without interest was noted as having no significant association with employee’s effectiveness at the job. The study concludes manager’s role is more important in the effectiveness of the employees at their job in the banking sector. It is suggested that managers should have a positive attitude towards employees and give time to listening to employee’s problems, even personal ones.

Keywords: banking sector, employee’s effectiveness, manager’s role, leadership style

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Authors: Sinsze Koo, Benjin Luo, Matthew Henry

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In order to increase the performance of an automatic transmission, the automatic transmission fluid is required to be warm up to an optimal operating temperature. In a conventional vehicle, cold starts result in friction loss occurring in the gear box and engine. The stop and go nature of city driving dramatically affect the warm-up of engine oil and automatic transmission fluid and delay the time frame needed to reach an optimal operating temperature. This temperature phenomenon impacts both engine and transmission performance but also increases fuel consumption and CO2 emission. The aim of this study is to develop know-how of the thermal behavior in order to identify thermal impacts and functional principles in automatic transmissions. Thermal behavior was studied using models and simulations, developed using GT-Suit, on a one-dimensional thermal and flow transport. A power train of a conventional vehicle was modeled in order to emphasis the thermal phenomena occurring in the various components and how they impact the automatic transmission performance. The simulation demonstrates the thermal model of a transmission fluid cooling system and its component parts in warm-up after a cold start. The result of these analyses will support the future designs of transmission systems and components in an attempt to obtain better fuel efficiency and transmission performance. Therefore, these thermal analyses could possibly identify ways that improve existing thermal management techniques with prioritization on fuel efficiency.

Keywords: thermal management, automatic transmission, hybrid, and systematic approach

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Authors: A. Benatiallah, D. Benatiallah, F. Abaidi, B. Nasri, A. Harrouz, S. Mansouri

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The region of Adrar is located in the south-western Algeria and covers a total area of 443.782 km², occupied by a population of 432,193 inhabitants. The main activity of population is agriculture, mainly based on the date palm cultivation occupies a total area of 23,532 ha. Adrar region climate is a continental desert characterized by a high variation in temperature between months (July, August) it exceeds 48°C and coldest months (December, January) with 16°C. Rainfall is very limited in frequency and volume with an aridity index of 4.6 to 5 which corresponds to a type of arid climate. Geologically Adrar region is located on the edge North West and is characterized by a Precambrian basement cover stolen sedimentary deposit of Phanerozoic age transgressive. The depression is filled by Touat site Paleozoic deposits (Cambrian to Namurian) of a vast sedimentary basin extending secondary age of the Saharan Atlas to the north hamada Tinhirt Tademaït and the plateau of south and Touat Gourara west to Gulf of Gabes in the Northeast. In this work we have study geothermal potential of Adrar region from the borehole data eatable in various sites across the area of 400,000 square kilometres; from these data we developed a GIS (Adrar_GIS) that plots data on the various points and boreholes in the region specifying information on available geothermal potential has variable depths.

Keywords: sig, geothermal, potenteil, temperature

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Authors: Feng Huang, Carlos G. Ochoa, Haitao Zhao

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Poyang Lake, the largest freshwater lake in China, is located at the middle-lower reaches of the Yangtze River basin. It has great value in socioeconomic development and is internationally recognized as an important lacustrine and wetland ecosystem with abundant biodiversity. Impacted by ongoing climate change and anthropogenic activities, especially the regulation of the Three Gorges Reservoir since 2003, Poyang Lake has experienced significant water regime evolution, resulting in challenges for the management of water resources and the environment. Quantifying the contribution of hydrologic and topographic changes to water regime alteration is necessary for policymakers to design effective adaption strategies. Long term hydrologic data were collected and the back-propagation neural networks were constructed to simulate the lake water level. The impacts of hydrologic and topographic changes were differentiated through scenario analysis that considered pre-impact and post-impact hydrologic and topographic scenarios. The lake water regime was characterized by hydrologic indicators that describe monthly water level fluctuations, hydrologic features during flood and drought seasons, and frequency and rate of hydrologic variations. The results revealed different contributions of hydrologic and topographic changes to different features of the lake water regime.Noticeable changes were that the water level declined dramatically during the period of reservoir impoundment, and the drought was enhanced during the dry season. The hydrologic and topographic changes exerted a synergistic effect or antagonistic effect on different lake water regime features. The findings provide scientific reference for lacustrine and wetland ecological protection associated with water regime alterations.

Keywords: back-propagation neural network, scenario analysis, water regime, Poyang Lake

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Authors: Liliana Rusu

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The goal of the proposed work is to provide a more comprehensive picture of the wind and wave climate in the Romanian nearshore, using the results provided by numerical models. The Romanian coastal environment is located in the western side of the Black Sea, the more energetic part of the sea, an area with heavy maritime traffic and various offshore operations. Information about the wind and wave climate in the Romanian waters is mainly based on observations at Gloria drilling platform (70 km from the coast). As regards the waves, the measurements of the wave characteristics are not so accurate due to the method used, being also available for a limited period. For this reason, the wave simulations that cover large temporal and spatial scales represent an option to describe better the wave climate. To assess the wind climate in the target area spanning 1992–2016, data provided by the NCEP-CFSR (U.S. National Centers for Environmental Prediction - Climate Forecast System Reanalysis) and consisting in wind fields at 10m above the sea level are used. The high spatial and temporal resolution of the wind fields is good enough to represent the wind variability over the area. For the same 25-year period, as considered for the wind climate, this study characterizes the wave climate from a wave hindcast data set that uses NCEP-CFSR winds as input for a model system SWAN (Simulating WAves Nearshore) based. The wave simulation results with a two-level modelling scale have been validated against both in situ measurements and remotely sensed data. The second level of the system, with a higher resolution in the geographical space (0.02°×0.02°), is focused on the Romanian coastal environment. The main wave parameters simulated at this level are used to analyse the wave climate. The spatial distributions of the wind speed, wind direction and the mean significant wave height have been computed as the average of the total data. As resulted from the amount of data, the target area presents a generally moderate wave climate that is affected by the storm events developed in the Black Sea basin. Both wind and wave climate presents high seasonal variability. All the results are computed as maps that help to find the more dangerous areas. A local analysis has been also employed in some key locations corresponding to highly sensitive areas, as for example the main Romanian harbors.

Keywords: numerical simulations, Romanian nearshore, waves, wind

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Authors: Nadia Yaghoobi, Seyed Majid Esmaeilzadeh

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Due to advancements in wireless communication, new sensor capabilities have been created. In addition to the automation industry, the Internet of Things (IoT) has been used in environmental issues and has provided the possibility of communication between different devices for data collection and exchange. Water quality depends on many factors which are essential for maintaining the minimum sustainability of water. Regarding the great dependence of fishes on the quality of the aquatic environment, water quality can directly affect their activity. Therefore, monitoring water quality is an important issue to consider, especially in the fish farming industry. The conventional method of water quality testing is to collect water samples manually and send them to a laboratory for testing and analysis. This time-consuming method is a waste of manpower and is not cost-effective. The water quality measurement system implemented in this project monitors water quality in real-time through various sensors (parameters: water temperature, water level, dissolved oxygen, humidity and ambient temperature, water turbidity, PH). The Wi-Fi module, ESP8266, transmits data collected by sensors wirelessly to ThingSpeak and the smartphone app. Also, with the help of these instantaneous data, water temperature and water level can be controlled by using a heater and a water pump, respectively. This system can have a detailed study of the pollution and condition of water resources and can provide an environment for safe fish farming.

Keywords: dissolved oxygen, IoT, monitoring, ThingSpeak, water level, water quality, WiFi module

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Authors: Shobha U. Jadhav, R. S. Saler

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Onion is most Important Vegetable crop grown throughout the world. Onion suffers from pest and fungal diseases but the fungicides cause pollution and disturb microbial balance of soil. Under integrated fungal disease management programme cost effective and eco- friendly component like plant extract are used to control plant pathogens. Alternaria porri, Fusarium oxysporium, Stemphylium vesicarium are soil borne pathogens of onion. Effect of three different plant extract (Datura metel, Pongamia pinnata, Ipomoea palmata) at five different concentration Viz, 10,25,50,75 and 100 percentage on these pathogens was studied by food poisoning techniquie. Detura metal gave 94.73% growth of Alternaria porri at 10% extract concentraton and 26.31% growth in 100% extract concentration. As compared to Fusarium oxysporium, and Stemphylium vesicarium, Alternaria porri give good inhibitory response. In Pongamia pinnata L. at 10% extract concentration 84.21% growth and at 100% extract concentration 36.84% growth of Stemphylium vesicarium was observed. Stemphylium vesicarium give good in inhibitory response as compared to Alternaria porri and Fusarium oxysporium. Ipomoea palmata in 10% extract concentration 92% growth and in 100% extract concentration 40% growth of Fusarium oxysporium was recorded. Fusarium oxysporium give good inhibitory response as compared to Alternaria porri and, Stemphylium vesicarium.

Keywords: pathogen, onion, plant extract, Allium cepa L.

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Authors: İ. Çelik, Goksel Demirer

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Turkey is the third largest producer of pistachio (Pistacia vera L.) after Iran and United States. Harvested pistachio nuts are covered with organic hull which is removed by de-hulling process. Most of the pistachio by-products which are produced during de-hulling process are considered as agricultural waste and often mixed with soil, to a lesser extent are used as feedstuff by local livestock farmers and a small portion is used as herbal medicine. Due to its high organic and phenolic content as well as high solids concentration, pistachio processing wastes create significant waste management problems unless they are properly managed. However, there is not a well-established waste management method compensating the waste generated during the processing of pistachios. This study investigated the anaerobic treatability and biogas generation potential of pistachio hull waste. The effect of pre-treatment on biogas generation potential was investigated. For this purpose, Biochemical Methane Potential (BMP) Assays were conducted for two Chemical Oxygen Demand (COD) concentrations of 22 and 33 g tCOD l-1 at the absence and presence of chemical and thermal pre-treatment methods. The results revealed anaerobic digestion of the pistachio de-hulling wastes and subsequent biogas production as a renewable energy source are possible. The observed percent COD removal and methane yield values of the pre-treated pistachio de-hulling waste samples were significantly higher than the raw pistachio de-hulling waste. The highest methane yield was observed as 213.4 ml CH4/g COD.

Keywords: pistachio de-hulling waste, biogas, renewable energy, pre-treatment

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Authors: Antarip Bhattacharya, Dhritiman Maitra

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Primary hyperparathyroidism (PHPT) is the most common cause of hypercalcemia due to autonomous production of parathormone (PTH) and the third most common endocrine disorder. Upto 2% of postmenopausal women could have this condition. Primary hyperparathyroidism is characterized by hypercalcemia with a high or insufficiently suppressed level of parathyroid hormone and is caused by a solitary parathyroid adenoma in 85-90% of patients. PHPT may also be caused by parathyroid hyperplasia (involving multiple glands) or parathyroid carcinoma. Associated morbidities and sequelae include decreased bone mineral density, fractures, kidney stones, hypertension, cardiac comorbidities and psychiatric disorder which entail huge costs for treatment. In the year 2021, by virtue of running a Breast and Endocrine Surgery clinic in a Tier 1 city at a tertiary care hospital, the opportunity to be associated with patients of hyperparathyroidism came our way. Here, we shall describe the spectrum of clinical presentations and customisation of treatment for parathyroid diseases with reference to the above patients. A retrospective analysis of the data of all patients presenting with symptoms of parathyroid diseases was made and classified according to the cause. 13 patients had presented with symptoms of hyperparathyroidism and each case presented with unique symptoms and necessitated detailed evaluation. The treatment or surgery offered to each patient was tailored to his/her individual disease and led to favourable outcomes. Diseases affecting parathyroid are not as rare as we believe. Each case merits detailed clinical evaluation, investigations and tailoring of suitable treatment with regard to medical management and extent of surgery. Intra-operative frozen section/iOPTH monitoring are really useful adjuncts for intra-operative decision making.

Keywords: hyperparathyroidism, parathyroid adenoma, parathyroid surgery, PTH

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Authors: Siti Noor Baiti Binti Mustafa

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Energy management studies regarding energy efficiency investments in Malaysia has yet to address the lack of empirical research that examines pro- sustainability behavior of managers in the industrial sector and how it influences energy efficiency investment decision-making. This study adopts the Theory of Planned Behavior (TPB) to examine the relationship between personal attitude, subjective norms, and perceived behavioral control (PBC), the intention of energy efficiency investments, and how perceptions of Non-Energy Benefits (NEB) influence these intentions among managers in the industrial sector in Malaysia. Managers from various sub-sectors in the industrial sector were selected from a sample of companies that are participants of the Government-led program named the Energy Audit Conditional Grant (EACG) that aimed to promote energy efficiency. Data collection was conducted through an online semi-structured, open-ended questionnaire and then later interviewed. The results of this explorative sequential qualitative study showed that perceived behavioral control was a significant predictor of energy efficiency investment intentions as compared to factors such as attitude and subjective norms. The level of awareness and perceptions towards NEB further played a significant factor in influencing energy efficiency investment decision-making as well. Various measures and policy recommendations are provided together with insights on factors that influence decision-makers intention to invest in energy efficiency, whilst new knowledge on NEB perceptions will be useful to enhance the attractiveness of energy-efficient investments.

Keywords: energy efficiency investments, non-energy benefits, theory of planned behavior, personal attitude, subjective norms, perceived behavioral control, Malaysia industrial sector

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Authors: Guofan Shao, Lina Tang, Hao Zhang

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The values of image classification accuracy are affected by class size distributions and classification schemes, making it difficult to compare the performance of classification algorithms across different remote sensing data sources and classification systems. Based on the term efficacy from medicine and pharmacology, we have developed the metrics of image classification efficacy at the map and class levels. The novelty of this approach is that a baseline classification is involved in computing image classification efficacies so that the effects of class statistics are reduced. Furthermore, the image classification efficacies are interpretable and comparable, and thus, strengthen the assessment of image data classification methods. We use real-world and hypothetical examples to explain the use of image classification efficacies. The metrics of image classification efficacy meet the critical need to rectify the strategy for the assessment of image classification performance as image classification methods are becoming more diversified.

Keywords: accuracy assessment, efficacy, image classification, machine learning, uncertainty

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Authors: Lucas M. Furlan, Cesar A. Moreira, Jepherson F. Sales, Guilherme T. Bueno, Manuel E. Ferreira, Carla V. S. Coelho, Vania Rosolen

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Located in the western part of the State of Minas Gerais, Brazil, the study area consists of a savanna environment, represented by sedimentary plateau and a soil cover composed by lateritic and hydromorphic soils - in the latter, occurring the deferruginization and concentration of high-alumina clays, exploited as refractory material. In the hydromorphic topographic depressions (wetlands) the hydropedogical relationships are little known, but it is observed that in times of rainfall, the depressed region behaves like a natural seasonal reservoir - which suggests that the wetlands on the surface of the plateau are places of recharge of the aquifer. The aquifer recharge areas are extremely important for the sustainable social, economic and environmental development of societies. The understanding of hydrodynamics in relation to the functioning of the ferruginous and hydromorphic lateritic soils system in the savanna environment is a subject rarely explored in the literature, especially its understanding through the joint application of geoprocessing by UAV (Unmanned Aerial Vehicle) and electrical tomography. The objective of this work is to understand the hydrogeological dynamics in a wetland (with an area of 426.064 m²), in the Brazilian savanna,as well as the understanding of the subsurface architecture of hydromorphic depressions in relation to the recharge of aquifers. The wetland was compartmentalized in three different regions, according to the geoprocessing. Hydraulic conductivity studies were performed in each of these three portions. Electrical tomography was performed on 9 lines of 80 meters in length and spaced 10 meters apart (direction N45), and a line with 80 meters perpendicular to all others. With the data, it was possible to generate a 3D cube. The integrated analysis showed that the area behaves like a natural seasonal reservoir in the months of greater precipitation (December – 289mm; January – 277,9mm; February – 213,2mm), because the hydraulic conductivity is very low in all areas. In the aerial images, geotag correction of the images was performed, that is, the correction of the coordinates of the images by means of the corrected coordinates of the Positioning by Precision Point of the Brazilian Institute of Geography and Statistics (IBGE-PPP). Later, the orthomosaic and the digital surface model (DSM) were generated, which with specific geoprocessing generated the volume of water that the wetland can contain - 780,922m³ in total, 265,205m³ in the region with intermediate flooding and 49,140m³ in the central region, where a greater accumulation of water was observed. Through the electrical tomography it was possible to identify that up to the depth of 6 meters the water infiltrates vertically in the central region. From the 8 meters depth, the water encounters a more resistive layer and the infiltration begins to occur horizontally - tending to concentrate the recharge of the aquifer to the northeast and southwest of the wetland. The hydrodynamics of the area is complex and has many challenges in its understanding. The next step is to relate hydrodynamics to the evolution of the landscape, with the enrichment of high-alumina clays, and to propose a management model for the seasonal reservoir.

Keywords: electrical tomography, hydropedology, unmanned aerial vehicle, water resources management

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Authors: Kanamon Suwantada

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The purpose of this research is to understand customer’s expectations towards homestays and to establish the precise strategies to increase numbers of tourists for homestay business in Amphawa district, Samutsongkram, Thailand. The researcher aims to ensure that each host provides experiences to travelers who are looking for and determining new targets for homestay business in Amphawa as well as creating sustainable homestay using marketing strategies to increase customers. The methods allow interview and questionnaire to gain both overview data from the tourists and qualitative data from the homestay owner’s perspective to create a GAP analysis. The data was collected from 200 tourists, during 15th May - 30th July, 2011 from homestay in Amphawa Community. The questionnaires were divided into three sections: the demographic profile, customer information and influencing on purchasing position, and customer expectation towards homestay. The analysis, in fact, will be divided into two methods which are percentage and correlation analyses. The result of this research revealed that homestay had already provided customers with reasonable prices in good locations. Antithetically, activities that they offered still could not have met the customer’s requirements. Homestay providers should prepare additional activities such as village tour, local attraction tour, village daily life experiences, local ceremony participation, and interactive conversation with local people. Moreover, the results indicated that a price was the most important factor for choosing homestay.

Keywords: ecotourism, homestay, marketing, sufficiency economic philosophy

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Authors: Siti Nurhidayah Naqiah Abdull Rani, Herlina Abdul Rahim, Rashidah Ghazali, Noramli Abdul Razak

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Near infrared (NIR) spectroscopy has always been of great interest in the food and agriculture industries. The development of prediction models has facilitated the estimation process in recent years. In this study, 110 crude palm oil (CPO) samples were used to build a free fatty acid (FFA) prediction model. 60% of the collected data were used for training purposes and the remaining 40% used for testing. The visible peaks on the NIR spectrum were at 1725 nm and 1760 nm, indicating the existence of the first overtone of C-H bands. Principal component regression (PCR) was applied to the data in order to build this mathematical prediction model. The optimal number of principal components was 10. The results showed R2=0.7147 for the training set and R2=0.6404 for the testing set.

Keywords: palm oil, fatty acid, NIRS, regression

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Authors: Haifeng Wang, Haili Zhang

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Most movie recommendation systems have been developed for customers to find items of interest. This work introduces a predictive model usable by small and medium-sized enterprises (SMEs) who are in need of a data-based and analytical approach to stock proper movies for local audiences and retain more customers. We used classification models to extract features from thousands of customers’ demographic, behavioral and social information to predict their movie genre preference. In the implementation, a Gaussian kernel support vector machine (SVM) classification model and a logistic regression model were established to extract features from sample data and their test error-in-sample were compared. Comparison of error-out-sample was also made under different Vapnik–Chervonenkis (VC) dimensions in the machine learning algorithm to find and prevent overfitting. Gaussian kernel SVM prediction model can correctly predict movie genre preferences in 85% of positive cases. The accuracy of the algorithm increased to 93% with a smaller VC dimension and less overfitting. These findings advance our understanding of how to use machine learning approach to predict customers’ preferences with a small data set and design prediction tools for these enterprises.

Keywords: computational social science, movie preference, machine learning, SVM

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Authors: Muhammad Yahaya Ubale

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Substantial rate of urbanization as well as economic growth is the tasks and prospects of sustainability. Objectives of the paper are: to ascertain the fate of sustainability in urbanized cities and; to identify the challenges of land use array in urbanized cities. Methodology engaged in this paper employed the use of secondary data where articles, conference proceedings, seminar papers and literature materials were effectively used. The paper established the fact that while one thinks globally, it is reciprocal to act locally if at all sustainability should be achieved. The speed and scale of urbanization must be equal to natural and cost-effective deliberations. It also discovered a podium that allows a city to work together as an ideal conglomerate, engaging all city departments as a source of services, engaging residents, businesses, and contractors. It also revealed that city should act as a leader and partner within an urban region, engaging senior government officials, utilities, rural settlements, private sector stakeholders, NGOs, and academia. Cities should assimilate infrastructure system design and management to enhance efficiency of resource flows in an urban area. They should also coordinate spatial development; integrate urban forms and urban flows, combine land use, urban design, urban density, and other spatial attributes with infrastructural development. Finally, by 2050, urbanized cities alone could be consuming 140 billion tons of minerals, ores, fossil fuels and biomass annually (three times its current rate of consumption), sustainability can be accomplished through land use control, limited access to finite resources, facilities, utilities and services as well as property right and user charge.

Keywords: sustainability, land use array, urbanized cities, fate of sustainability and perseverance

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Authors: Ahmad Tijani Surajudeen, Muhammad Zahiri Awang Mat, Aliy Abdulwahid Adebisi

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With arrival of Islam in the South-Western Nigeria in the late fifteenth and early sixteenth centuries, various masājid established in different parts of the area played vital roles towards the betterment and unity of the Muslims. However, despite the fact that the masājid in the South-Western part of Nigeria contributed immensely to the spiritual and educational enhancement of the Muslims, it has not fully captured the holistic educational roles as a unique model used by the Prophet (S.A.W). Therefore, the primary objective of this paper is to investigate and broaden the roles of masjid towards its compartmentalized and holistic contributions among the Muslims in the south-western Nigeria. The findings from the paper have identified five holistic roles of masjid, namely, spiritual, intellectual, physical, social and emotional contributions which have been exemplified in the prophetic model of masjid. The paper has argued that the five factors must be unreservedly unified towards the betterment of the Muslims and enhancement of Islamic education and Arabic Language in the South-Western Nigeria. However, the challenges of masjid management in the South-Western Nigeria are the main hindrance in achieving the holistic roles of masjid. It is thereby suggested that, the management of masjid should take the identified prophetic model of masjid into account in order to positively improve the affairs of Muslims as well as promoting the teaching and learning of Islamic education and Arabic language among the Muslims in the South-Western Nigeria.

Keywords: worship, Islamic education, Arabic language, prophetic holistic model

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Authors: M. C. Schloesser

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The purpose of this paper is to explore the use and impact of business analytics in European football. Despite good evidence from other major sports leagues, research on this topic in Europe is currently very scarce. This research relies on expert interviews on the use and objective of business analytics. Along with revenue data over 16 seasons spanning from 2004/05 to 2019/20 from Manchester City FC, we conducted a time series analysis to detect a structural breakpoint on the different revenue streams, i.e., sponsorship and ticketing, after analytical tools have been implemented. We not only find that business analytics have indeed been applied at Manchester City FC and revenue increase is the main objective of their utilization but also that business analytics is indeed a good means to increase revenues if applied sufficiently. We can thereby support findings from other sports leagues. Consequently, professional sports organizations are advised to apply business analytics if they aim to increase revenues. This research has shown that analytical practices do, in fact, support revenue growth and help to work more efficiently. As the knowledge of analytical practices is very confidential and not publicly available, we had to select one club as a case study which can be considered a research limitation. Other practitioners should explore other clubs or leagues. Further, there are other factors that can lead to increased revenues that need to be considered. Additionally, sports organizations need resources to be able to apply and utilize business analytics. Consequently, findings might only apply to the top teams of the European football leagues. Nonetheless, this paper combines insights and results on usage, objectives, and impact of business analytics in European professional football and thereby fills a current research gap.

Keywords: business analytics, expert interviews, revenue management, time series analysis

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Authors: Fatemeh Torabi, Jamal El-Den, Narumon Sriratanviriyakul

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Perpetual changes in the workplace and daily business activities bring a need for imbedding organizational knowledge sharing within the organizations’ culture, routines and processes. Organizations should adapt to the changing in the environment in order to survive. Accordingly, the management should promote a knowledge sharing culture which might result in knowledge accumulation, hence better response to these changing environmental conditions. Researchers in the field of strategy and marketing stressed that employees’, as well as the overall performance of the organization, would improve as a result of implementing a knowledge-oriented culture. The research investigated the significant impact of knowledge sharing on market response and the competitiveness of organizations. A knowledge sharing framework was developed based on current literary frameworks with additional constructs such as employees’ learning commitments, experiences and prior knowledge. Linear regression was used to analyze the relationships among dependent and independent variables. The research’s results indicated strong positive correlation between the dependent and independent variables, especially in organizational market sharing. We anticipate that this correlation would improve organizational knowledge sharing related practices and the associated knowledge entities. The research posits the introduced framework could be a solid ground for further investigations on how some organizational factors would influence the organization’s response to the market as well as on competitiveness. Final results support all hypotheses. Finding of this research show that knowledge sharing intention had the significant and positive effect on market response and competitiveness of organizations.

Keywords: knowledge management, knowledge sharing, market response, organizational competitiveness

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Authors: Lok Raj Joshi, Naveen Prakash Shah, Sharad Kumar Sharma, I. Ratna Bhattarai, Rajendra Basnet, Deepak Dahal, Bahagwan Maharjan, Seraphine Kaminsa

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Context: Tuberculosis (TB) is a significant health issue in Nepal, a country with a high burden of the disease. Despite efforts to control TB, there is still a gap in the notification of TB cases, which hinders effective control and treatment. This paper aims to address this notification gap and proposes strategies to improve TB control in Nepal. Research Aim: The aim of this research is to understand and address the tuberculosis notification gap in Nepal. The focus is on enhancing the healthcare system, involving the private sector and communities, raising awareness, and addressing social determinants to achieve sustainable TB control. Methodology: The research methodology involved a review of existing epidemiological data and research studies related to TB in Nepal. Additionally, consultation with an expert group from the TB control program in Nepal provided insights into the current state of TB control and challenges in addressing the notification gap. Findings: The findings reveal that only 55% of TB cases were reported in 2022, indicating a significant notification gap. Of the reported cases, only 32% and 19% were referred by the private sector and community, respectively. Furthermore, 20% of diagnosed cases were not treated in the initial phase. The estimated number of cases of multidrug-resistant TB (MDR TB) was 2,800, suggesting a low diagnosis rate. Among the diagnosed MDR TB cases, only 60% were receiving treatment. Additionally, it was observed that 20% of diagnosed MDR TB cases were from India and not enrolling in TB treatment in Nepal, indicating a high rate of defaulters. Theoretical Importance: The study highlights the importance of adopting a holistic strategy to address the notification gap in TB cases in Nepal. It emphasizes the need to enhance healthcare infrastructure, raise awareness, involve the private sector and local communities, establish effective methods to trace initial defaulters, implement TB interventions in border regions, and mitigate the social stigma associated with the disease. Data Collection and Analysis Procedures: Data for this study was collected through a review of existing epidemiological data and research studies. The data were then analyzed to identify patterns, trends, and gaps in TB case notification in Nepal.

Keywords: TB, tuberculosis, private sector, community, migrants, nepal

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Authors: Hamid Reza Behnood, Esmaeel Ayati, Tom Brijs, Mohammadali Pirayesh Neghab

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Investment projects in road safety planning can benefit from an effectiveness evaluation regarding their expected safety outcomes. The objective of this study is to develop a decision support system (DSS) to support policymakers in taking the right choice in road safety planning based on the efficiency of previously implemented safety measures in a set of regions in Iran. The measures considered for each region in the study include performance indicators about (1) police operations, (2) treated black spots, (3) freeway and highway facility supplies, (4) speed control cameras, (5) emergency medical services, and (6) road lighting projects. To this end, inefficiency measure is calculated, defined by the proportion of fatality rates in relation to the combined measure of road safety performance indicators (i.e., road safety measures) which should be minimized. The relative inefficiency for each region is modeled by the Data Envelopment Analysis (DEA) technique. In a next step, a fuzzy decision-making system is constructed to convert the information obtained from the DEA analysis into a rule-based system that can be used by policy makers to evaluate the expected outcomes of certain alternative investment strategies in road safety.

Keywords: performance indicators, road safety, decision support system, data envelopment analysis, fuzzy reasoning

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Authors: Olugbade Damola, Adekomi Adebimbo, Sofowora Olaniyi Alaba

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One of the major problems facing education in Nigeria is the provision of quality Science and Technology education. Inadequate teaching facilities, non-usage of innovative teaching strategies, ineffective classroom management, lack of students’ motivation and poor integration of ICT has resulted in the increase in percentage of students who failed Basic Science and Technology in Junior Secondary Certification Examination for National Examination Council in Nigeria. To address these challenges, the Federal Government came up with a road map on education. This was with a view of enhancing quality education through integration of modern technology into teaching and learning, enhancing quality assurance through proper monitoring and introduction of innovative methods of teaching. This led the researcher to investigate how MOODLE LMS could be used to enhance students’ learning outcomes in BST. A sample of 120 students was purposively selected from four secondary schools in Ogbomoso. The experimental group was taught using MOODLE LMS, while the control group was taught using the conventional method. Data obtained were analyzed using mean, standard deviation and t-test. The result showed that MOODLE LMS was an effective learning platform in teaching BST in junior secondary schools (t=4.953, P<0.05). Students’ attitudes towards BST was also enhanced through MOODLE LMS (t=15.632, P<0.05). The use of MOODLE LMS significantly enhanced students’ retention (t=6.640, P<0.05). In conclusion, the Federal Government efforts at enhancing quality assurance through integration of modern technology and e-learning in Secondary schools proved to have yielded good result has students found MOODLE LMS to be motivating and interactive. Attendance was improved.

Keywords: basic science and technology, MOODLE LMS, performance, quality assurance

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Authors: Amin Khamoosh, Hamed Faramarzifar

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In the capital of Iran, Tehran, numerous buildings constructed when extreme climates were not prevalent now face the need for rehabilitation, typically within their first decade. Our data delves into the performance metrics and economic advantages of sustainable rehabilitation practices compared to traditional methods. With a focus on the scarcity of water resources, we specifically scrutinize water-efficient techniques throughout construction, rehabilitation, and usage. Examining design elements that optimize natural light while efficiently managing heat transmission is crucial, given the reliance on water for cooling devices in this region. The data aims to present a comprehensive strategy, addressing immediate structural concerns while harmonizing with Iran's unique environmental conditions.

Keywords: sustainable rehabilitation, concrete buildings, iran, solar energy, water-efficient techniques

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Authors: Baba Mbaye

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In collaborative filtering recommendation systems, a user receives suggested items based on the opinions and evaluations of a community of users. This type of recommendation system uses only the information (notes in numerical values) contained in a usage matrix as input data. This matrix can be constructed based on users' behaviors or by offering users to declare their opinions on the items they know. The cold start problem leads to very poor performance for new users. It is a phenomenon that occurs at the beginning of use, in the situation where the system lacks data to make recommendations. There are three types of cold start problems: cold start for a new item, a new system, and a new user. We are interested in this article at the cold start for a new user. When the system welcomes a new user, the profile exists but does not have enough data, and its communities with other users profiles are still unknown. This leads to recommendations not adapted to the profile of the new user. In this paper, we propose an approach that improves cold start by using the notions of similarity and semantic proximity between users profiles during cold start. We will use the cold-metadata available (metadata extracted from the new user's data) useful in positioning the new user within a community. The aim is to look for similarities and semantic proximities with the old and current user profiles of the system. Proximity is represented by close concepts considered to belong to the same group, while similarity groups together elements that appear similar. Similarity and proximity are two close but not similar concepts. This similarity leads us to the construction of similarity which is based on: a) the concepts (properties, terms, instances) independent of ontology structure and, b) the simultaneous representation of the two concepts (relations, presence of terms in a document, simultaneous presence of the authorities). We propose an ontology, OIVCSRS (Ontology of Improvement Visitor Cold Start in Recommender Systems), in order to structure the terms and concepts representing the meaning of an information field, whether by the metadata of a namespace, or the elements of a knowledge domain. This approach allows us to automatically attach the new user to a user community, partially compensate for the data that was not initially provided and ultimately to associate a better first profile with the cold start. Thus, the aim of this paper is to propose an approach to improving cold start using semantic technologies.

Keywords: visitor cold start, recommender systems, collaborative filtering, semantic filtering

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Authors: Gaya Tridinanti

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Enhanching English vocabulary in early childhood is the main problem often faced by teachers. Thus, the purpose of this study was to determine the enhancement of children’s English vocabulary acquisition by using digital storytelling. This type of research was an action research. It consisted of a series of four activities done in repeated cycles: planning, implementation, observation, and reflection. The subject of the study consisted of 30 students of B group (5-6 years old) attending Happy Kids Kindergarten Palembang, Indonesia. This research was conducted in three cycles. The methods used for data collection were observation and documentation. Descriptive qualitative and quantitative methods were also used to analyse the data. The research showed that the digital storytelling learning activities could enhance the children’s English vocabulary acquisition. It is based on the data in which the enhancement in pre-cycle was 37% and 51% in Cycle I. In Cycle II it was 71% and in Cycle III it was 89.3%. The results showed an enhancement of about 14% from the pre-cycle to Cycle I, 20% from Cycle I to Cycle II, and enhancement of about 18.3% from Cycle II to Cycle III. The conclusion of this study suggests that digital storytelling learning method could enhance the English vocabulary acquisition of B group children at the Happy Kids Kindergarten Palembang. Therefore, digital storytelling can be considered as an alternative to improve English language learning in the classroom.

Keywords: acquisition, enhancing, digital storytelling, English vocabulary

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Authors: Ismail Seçer

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The purpose of this study is to analyze the predictive effect of anxiety sensitivity on obsessive compulsive symptoms. The sample of the study consists of 542 students selected with appropriate sampling method from the secondary and high schools in Erzurum city center. Obsessive Compulsive Inventory and Anxiety Sensitivity Index were used in the study to collect data. The data obtained through the study was analyzed with structural equation modeling. As a result of the study, it was determined that there is a significant relationship between obsessive Compulsive Disorder (OCD) and anxiety sensitivity. Anxiety sensitivity has direct and indirect meaningful effects on the latent variable of OCD in the sub-dimensions of doubting-checking, obsessing, hoarding, washing, ordering, and mental neutralizing, and also anxiety sensitivity is a significant predictor of obsessive compulsive symptoms.

Keywords: obsession, compulsion, structural equation, anxiety sensitivity

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Authors: Hilman Agil Satria, Rezky Naufan Hendrawan

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Indonesia is vulnerable to geological hazard because of its location in subduction zone and have tropical climate. Landslide is one of the most happened geological hazard in Indonesia, based on Indonesia Geospasial data, at least 194 landslides recorded in 2013. In fact, research location is placed as the third city that most happened landslide in Indonesia. Landslide caused damage of many houses and wrecked the road. The purpose of this research is to make a landslide zone therefore can be used as one of mitigation consideration. The location is in Bruno, Porworejo district Central Java Province Indonesia at 109.903 – 109.99 and -7.59 – -7.50 with 10 Km x 10 Km wide. Based on geological mapping result, the research location consist of Late Miocene sandstone and claystone, and Pleistocene volcanic breccia and tuff. Those landslide happened in the lithology that close with fault zone. This location has so many geological structures: joints, faults and folds. There are 3 thrust faults, 1 normal faults, 4 strike slip faults and 6 folds. This geological structure movement is interpreted as the main factor that has triggered landslide in this location. This research use field data as well as samples of rock, joint, slicken side and landslide location which is combined with DEM SRTM to analyze geomorphology. As the final result of combined data will be presented as geological map, geological structure map and landslide zone map. From this research we can assume that there is correlation between geological structure and landslide locations.

Keywords: geological structure, landslide, Porworejo, Indonesia

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Authors: Chien-kuo Chang, Bo-wei Wu, Yi-yun Tang, Min-chiu Wu

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This paper proposes a power equipment diagnosis system based on partial discharge (PD), which is characterized by increasing the readability of experimental data and the convenience of operation. This system integrates a variety of analysis programs of different data formats and different programming languages and then establishes a set of interfaces that can follow and expand the structure, which is also helpful for subsequent maintenance and innovation. This study shows a case of using the developed Convolutional Neural Networks (CNN) to integrate with this system, using the designed model architecture to simplify the complex training process. It is expected that the simplified training process can be used to establish an adaptive deep learning experimental structure. By selecting different test data for repeated training, the accuracy of the identification system can be enhanced. On this platform, the measurement status and partial discharge pattern of each equipment can be checked in real time, and the function of real-time identification can be set, and various training models can be used to carry out real-time partial discharge insulation defect identification and insulation state diagnosis. When the electric power equipment entering the dangerous period, replace equipment early to avoid unexpected electrical accidents.

Keywords: partial discharge, convolutional neural network, partial discharge analysis platform, adaptive deep learning

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