Search results for: data reliability

Authors: Triano Nurhikmat

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Along with the progress of science and technology, the development of the industrialized world in Indonesia took place very rapidly. This leads to a process of industrialization of society Indonesia faster with the establishment of the company and the workplace are diverse. Development of the industry relates to the activity of the worker. Where in these work activities do not cover the possibility of an impending crash on either the workers or on a construction project. The cause of the occurrence of industrial accidents was the fault of electrical damage, work procedures, and error technique. The method of an association rule is one of the main techniques in data mining and is the most common form used in finding the patterns of data collection. In this research would like to know how relations of the association between the incidence of any industrial accidents. Therefore, by using methods of analysis association rule patterns associated with combination obtained two iterations item set (2 large item set) when every factor of industrial accidents with a West Jakarta so industrial accidents caused by the occurrence of an electrical value damage = 0.2 support and confidence value = 1, and the reverse pattern with value = 0.2 support and confidence = 0.75.

Keywords: association rule, data mining, industrial accidents, rules

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Authors: Salam Alzubaidi, G. Fantoni, F. Failli, M. Frosolini

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The dynamic facility layout problem is a really critical issue in the competitive industrial market; thus, solving this problem requires robust design and effective simulation systems. The sustainable simulation requires inputting reliable and accurate data into the system. So this paper describes an automated system integrated into the real environment to measure the duration of the material handling operations, collect the data in real-time, and determine the variances between the actual and estimated time schedule of the operations in order to update the simulation software and redesign the facility layout periodically. The automated method- time measurement system collects the real data through using Radio Frequency-Identification (RFID) and Internet of Things (IoT) technologies. Hence, attaching RFID- antenna reader and RFID tags enables the system to identify the location of the objects and gathering the time data. The real duration gathered will be manipulated by calculating the moving average duration of the material handling operations, choosing the shortest material handling path, and then updating the simulation software to redesign the facility layout accommodating with the shortest/real operation schedule. The periodic simulation in real-time is more sustainable and reliable than the simulation system relying on an analysis of historical data. The case study of this methodology is in cooperation with a workshop team for producing mechanical parts. Although there are some technical limitations, this methodology is promising, and it can be significantly useful in the redesigning of the manufacturing layout.

Keywords: dynamic facility layout problem, internet of things, method time measurement, radio frequency identification, simulation

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Authors: Mohamed Boualem Salah

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The size and shape of soil particles reflect the formation history of the grains. In turn, the macro scale behavior of the soil mass results from particle level interactions which are affected by particle shape. Sphericity, roundness and smoothness characterize different scales associated to particle shape. New experimental data and data from previously published studies are gathered into two databases to explore the effects of particle shape on packing as well as small and large-strain properties of sandy soils. Data analysis shows that increased particle irregularity (angularity and/or eccentricity) leads to: an increase in emax and emin, a decrease in stiffness yet with increased sensitivity to the state of stress, an increase in compressibility under zero-lateral strain loading, and an increase in critical state friction angle φcs and intercept Γ with a weak effect on slope λ. Therefore, particle shape emerges as a significant soil index property that needs to be properly characterized and documented, particularly in clean sands and gravels. The systematic assessment of particle shape will lead to a better understanding of sand behavior.

Keywords: angularity, eccentricity, shape particle, behavior of soil

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Authors: Sheilla Atieno Odhiambo, Simona Vasile, Alexandra De Raeve, Ann Schwarz

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Strain sensing seams have been developed by integrating conductive sewing threads in different types of seams design on a fabric typical for sports clothing using sewing technology. The aim is to have a simple integrated textile strain sensor that can be applied to sports clothing to monitor the movements of the upper body parts of the user during sports. Different types of commercially available sewing threads were used as the bobbin thread in the production of different architectural seam sensors. These conductive sewing threads have been integrated into seams in particular designs using specific seam types. Some of the threads are delicate and needed to be laid into the seam with as little friction as possible and less tension; thus, they could only be sewn in as the bobbin thread and not the needle thread. Stitch type 304; 406; 506; 601;602; 605. were produced. The seams were made on a fabric of 80% polyamide 6.6 and 20% elastane. The seams were cycled(stretch-release-stretch) for five cycles and up to 44 cycles following EN ISO 14704-1: 2005 (modified), using a tensile instrument and the changes in the resistance of the seams with time were recorded using Agilent meter U1273A. Both experiments were conducted simultaneously on the same seam sample. Sensing functionality, among which is sensor gauge and reliability, were evaluated on the promising sensor seams. The results show that the sensor seams made from HC Madeira 40 conductive yarns performed better inseam stitch 304 and 602 compared to the other combination of stitch type and conductive sewing threads. These sensing seams 304, 406 and 602 will further be interconnected to our developed processing and communicating unit and further integrated into a sports clothing prototype that can track body posture. This research is done within the framework of the project SmartSeam.

Keywords: conductive sewing thread, sensing seams, smart seam, sewing technology

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Authors: Fatma Tezel Sahin, Zeynep Nur Aydin Kilic, Aysegul Akinci Cosgun

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Family involvement activities are a significant place in increasing the success in preschool education and maintaining the education. It is necessary that both of the parents be in the family involvement activities. However, while mother involvement is obtained in the family involvement activities, father involvement is neglected. For that reason, the current study aims at determining the views of teachers with regard to father involvement in the preschool education programs. The working group of the study consisted of 23 preschool teachers. The study is a descriptive survey. The data were obtained through individual interviews. As a data collection instrument, “Teacher Interview Form” was used. The data were analysed through content analysis method. The data regarding the views of the teachers were given as frequency and percentage values. At the end of the research, a great majority of the teachers stated that they were proficient in applying family involvement studies. They also pointed out that they held more family meetings in order to obtain family involvement and then they implemented involvement activities both in the class and out of the class for parents. They expressed that they observed more mother involvement in these activities that fathers. Parents expressed that the reasons why fathers involved in these activities less compared to mothers were the working conditions of fathers and that it was regarded as a task of mothers. Depending on the results of the research, it is likely to recommend that fathers should be informed about the involvement in family activities and that some applications and opportunities should be supplied for the fathers in preschool education institutions in order to encourage them.

Keywords: preschool education, parent involvement, father involvement, teacher views

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Authors: Perpetual Nwakaego Ibe

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The Millennium Development Goals (MDGs), were an integrated project formed to eradicate many unnatural situations the citizens of the third world country may found themselves in. The MDGs, to be a sustainable project for the future depends 100% on the actions of governments, multilateral institutions and civil society. This paper first looks at the political views on the MDGs and relates it to the current electoral situations around the country by underlining the drastic changes over the few months. The second part of the paper presents ICT in tertiary institutions as one of the solutions in terms of the success of the MDGs. ICT is vital in all phases of educational process and development of the cloud connectivity is an added advantage of Information and Communication Technology (ICT) for sharing a common data bank for research purposes among UNICEF, RED CROSS, NPS, INEC, NMIC, and WHO. Finally, the paper concludes with areas that needs twigging and recommendations for the tertiary institutions committed to delivering an ambitious set of goals. A combination of observation, and document materials for data gathering was employed as the methodology for carrying out this research.

Keywords: MDG, ICT, data bank, database

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Authors: Mohd Ruzlin Mohd Mokhtar

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At present, most operators who are working on projects for utilities such as power, water, oil, gas, telecommunication and sewerage are using technologies e.g. Total station, Global Positioning System (GPS), Electromagnetic Locator (EML) and Ground Penetrating Radar (GPR) to perform underground utility mapping. With the increase in popularity of Horizontal Directional Drilling (HDD) method among the local authorities and asset owners, most of newly installed underground utilities need to use the HDD method. HDD method is seen as simple and create not much disturbance to the public and traffic. Thus, it was the preferred utilities installation method in most of areas especially in urban areas. HDDs were installed much deeper than exiting utilities (some reports saying that HDD is averaging 5 meter in depth). However, this impacts the accuracy or ability of existing underground utility mapping technologies. In most of Malaysia underground soil condition, those technologies were limited to maximum of 3 meter depth. Thus, those utilities which were installed much deeper than 3 meter depth could not be detected by using existing detection tools. The accuracy and reliability of existing underground utility mapping technologies or work procedure were in doubt. Thus, a mitigation action plan is required. While installing new utility using Horizontal Directional Drilling (HDD) method, a more accurate underground utility mapping can be achieved by using Gyro OMU compared to existing practice using e.g. EML and GPR. Gyro OMU is a method to accurately identify the location of HDD thus this mapping can be used or referred to avoid those cost of breakdown due to future HDD works which can be caused by inaccurate underground utility mapping.

Keywords: Gyro Orientation Measurement Unit (Gyro OMU), Horizontal Directional Drilling (HDD), Ground Penetrating Radar (GPR), Electromagnetic Locator (EML)

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Authors: Averalda van Graan, Joelaine Chetty, Malory Links, Agness Mwangwela, Sitilitha Masangwi, Dalitso Chimwala, Shiban Ghosh, Elizabeth Marino-Costello

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Food composition data is becoming increasingly important as dealing with food insecurity and malnutrition in its persistent form of under-nutrition is now coupled with increasing over-nutrition and its related ailments in the developing world, of which Malawi is not spared. In the absence of a food composition database (FCDB) inherent to our dietary patterns, efforts were made to develop a country-specific FCDB for nutrition practice, research, and programming. The main objective was to develop a multi-user, country-specific food composition database, and table from existing published and unpublished scientific literature. A multi-phased approach guided by the project framework was employed. Phase 1 comprised a scoping mission to assess the nutrition landscape for compilation activities. Phase 2 involved training of a compiler and data collection from various sources, primarily; institutional libraries, online databases, and food industry nutrient data. Phase 3 subsumed evaluation and compilation of data using FAO and IN FOODS standards and guidelines. Phase 4 concluded the process with quality assurance. 316 Malawian food items categorized into eight food groups for 42 components were captured. The majority were from the baby food group (27%), followed by a staple (22%) and animal (22%) food group. Fats and oils consisted the least number of food items (2%), followed by fruits (6%). Proximate values are well represented; however, the percent missing data is huge for some components, including Se 68%, I 75%, Vitamin A 42%, and lipid profile; saturated fat 53%, mono-saturated fat 59%, poly-saturated fat 59% and cholesterol 56%. A multi-phased approach following the project framework led to the development of the first Malawian FCDB and table. The table reflects inherent Malawian dietary patterns and nutritional concerns. The FCDB can be used by various professionals in nutrition and health. Rising over-nutrition, NCD, and changing diets challenge us for nutrient profiles of processed foods and complete lipid profiles.

Keywords: analytical data, dietary pattern, food composition data, multi-phased approach

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Authors: Sultan Ghaleb Aldaihani

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- The environment in which educational leadership takes place is becoming increasingly complex due to factors like globalization and rapid technological change. - This is creating a "leadership gap" where the complexity of the environment outpaces the ability of leaders to effectively respond. - Educational leadership involves guiding teachers and the broader school system towards improved student learning and achievement. 2. Implications of Artificial Intelligence (AI) in Educational Leadership: - AI has great potential to enhance education, such as through intelligent tutoring systems and automating routine tasks to free up teachers. - AI can also have significant implications for educational leadership by providing better information and data-driven decision-making capabilities. - Computer-adaptive testing can provide detailed, individualized data on student learning that leaders can use for instructional decisions and accountability. 3. Enhancing Decision-Making Processes: - Statistical models and data mining techniques can help identify at-risk students earlier, allowing for targeted interventions. - Probability-based models can diagnose students likely to drop out, enabling proactive support. - These data-driven approaches can make resource allocation and decision-making more effective. 4. Improving Efficiency and Productivity: - AI systems can automate tasks and change processes to improve the efficiency of educational leadership and administration. - Integrating AI can free up leaders to focus more on their role's human, interactive elements.

Keywords: Education, Leadership, Technology, Artificial Intelligence

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Authors: Riktesh Srivastava

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Online Shopping have established an astonishing evolution in the last few years. And it is now apparent that B2C architecture is becoming progressively imperative channel for even traditional brick and mortar type traders as well. In this completion knowing customers and predicting behavior are extremely important. More important, when any customer logs onto the B2C architecture, the traces of their buying patterns can be stored and used for future predictions. Such a prediction is called Customer Lifetime Value (CLV). Earlier, we used Net Present Value to do so, however, it ignores two important aspects of B2C architecture, “market risks” and “big amount of customer data”. Now, we use RFM- Recency, Frequency and Monetary Value to estimate the CLV, and as the term exemplifies, market risks, is well sheltered. Big Data Analysis is also roofed in RFM, which gives real exploration of the Big Data and lead to a better estimation for future cash flow from customers. In the present paper, 6 factors (collected from varied sources) are used to determine as to what attracts the customers to the B2C architecture. For these 6 factors, RFM is computed for 3 years (2013, 2014 and 2015) respectively. CLV and Revenue are the two parameters defined using RFM analysis, which gives the clear picture of the future predictions.

Keywords: CLV, RFM, revenue, recency, frequency, monetary value

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Authors: Saqib Ali

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Sources are classified into two depending upon the factor of reviving. These sources, which cannot be revived into their original shape once they are consumed, are considered as nonrenewable energy resources, i.e., (coal, fuel) Moreover, those energy resources which are revivable to the original condition even after being consumed are known as renewable energy resources, i.e., (wind, solar, hydel) Renewable energy is a cost-effective way to generate clean and green electrical energy Now a day’s majority of the countries are paying heed to energy generation from RES Pakistan is mostly relying on conventional energy resources which are mostly nonrenewable in nature coal, fuel is one of the major resources, and with the advent of time their prices are increasing on the other hand RES have great potential in the country with the deployment of RES greater reliability and an effective power system can be obtained In this thesis, a similar concept is being used and a hybrid power system is proposed which is composed of intermixing of renewable and nonrenewable sources The Source side is composed of solar, wind, fuel cells which will be used in an optimal manner to serve load The goal is to provide an economical, reliable, uninterruptable power supply. This is achieved by optimal controller (PI, PD, PID, FOPID) Optimization techniques are applied to the controllers to achieve the desired results. Advanced algorithms (Particle swarm optimization, Flower Pollination Algorithm) will be used to extract the desired output from the controller Detailed comparison in the form of tables and results will be provided, which will highlight the efficiency of the proposed system.

Keywords: distributed generation, demand-side management, hybrid power system, micro grid, renewable energy resources, supply-side management

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Authors: Mohammed Kachtali, Imad Fenjiro, Jamal Alkarkouri

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Wind erosion is a serious environmental problem in arid and semi-arid regions. Indeed, wind erosion easily removes the finest particles of the soil surface, which also contribute to losing soil fertility. The siltation of infrastructures and cultivated areas and the negative impact on health are additional consequences of wind erosion. In Morocco, wind erosion constitutes the main factor of silting up in coast and Sahara. The aim of our study is to use an equation of wind erosion in order to estimate the soil loses by wind erosion in the coast of Gharb (North of Morocco). The used equation in our model includes the geographic data, climatic data of 30 years and edaphic data collected from area study which contained 11 crossing of 4 stations. Our results have shown that the values of wind erosion are higher and very different between some crossings (p < 0.001). This difference is explained by topography, soil texture, and climate. In conclusion, wind erosion is higher in Gharb coast and varies from station to another; this problem required several methods of control and mitigation.

Keywords: Gharb coast, modeling, silting, wind erosion

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Authors: I. Alhajri, G. Zahedi, R. Alazmi, A. Akbari

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In this paper, an Artificial Neural Network (ANN) was developed to predict Asphaltene Precipitation (AP) during the injection of carbon dioxide into crude oil reservoirs. In this study, the experimental data from six different oil fields were collected. Seventy percent of the data was used to develop the ANN model, and different ANN architectures were examined. A network with the Trainlm training algorithm was found to be the best network to estimate the AP. To check the validity of the proposed model, the model was used to predict the AP for the thirty percent of the data that was unevaluated. The Mean Square Error (MSE) of the prediction was 0.0018, which confirms the excellent prediction capability of the proposed model. In the second part of this study, the ANN model predictions were compared with modified Hirschberg model predictions. The ANN was found to provide more accurate estimates compared to the modified Hirschberg model. Finally, the proposed model was employed to examine the effect of different operating parameters during gas injection on the AP. It was found that the AP is mostly sensitive to the reservoir temperature. Furthermore, the carbon dioxide concentration in liquid phase increases the AP.

Keywords: artificial neural network, asphaltene, CO2 injection, Hirschberg model, oil reservoirs

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Authors: Zainuddin Zakaria, Sun Woh Lye

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Despite the continuous advancements in automated conflict resolution tools, there is still a low rate of adoption of automation from Air Traffic Control Officers (ATCOs). Trust or acceptance in these tools and conformance to the individual ATCO preferences in strategy execution for conflict resolution are two key factors that impact their use. This paper proposes a methodology to unearth and classify ATCO conflict resolution strategies from simulator data of trained and qualified ATCOs. The methodology involves the extraction of ATCO executive control actions and the establishment of a system of strategy resolution classification based on ATCO radar commands and prevailing flight parameters in deconflicting a pair of aircraft. Six main strategies used to handle various categories of conflict were identified and discussed. It was found that ATCOs were about twice more likely to choose only vertical maneuvers in conflict resolution compared to horizontal maneuvers or a combination of both vertical and horizontal maneuvers.

Keywords: air traffic control strategies, conflict resolution, simulator data, strategy classification system

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Authors: Emberga Terhemb Opara Alexander, Selemo Alexader, Onyekwuru Samuel

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The aeromagnetic data have been used to re-evaluate parts of the Upper Benue Trough Nigeria using spectral analysis technique in order to appraise the mineral accumulation potential of the area. The regional field was separated with a first order polynomial using polyfit program. The residual data was subdivided into 24 spectral blocks using OASIS MONTAJ software program. Two prominent magnetic depth source layers were identified. The deeper source depth values obtained ranges from 1.56km to 2.92km with an average depth of 2.37km as the magnetic basement depth while for the shallower sources, the depth values ranges from -1.17km to 0.98km with an average depth of 0.55km. The shallow depth source is attributed to the volcanic rocks that intruded the sedimentary formation and this could possibly be responsible for the mineralization found in parts of the study area.

Keywords: spectral analysis, Upper Benue Trough, magnetic basement depth, aeromagnetic

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Authors: Fathi M. O. Hamed, Salma F. Elkofhaifee

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The aim of this work is to detect geometrical shape objects in an image. In this paper, the object is considered to be as a circle shape. The identification requires find three characteristics, which are number, size, and location of the object. To achieve the goal of this work, this paper presents an algorithm that combines from some of statistical approaches and image analysis techniques. This algorithm has been implemented to arrive at the major objectives in this paper. The algorithm has been evaluated by using simulated data, and yields good results, and then it has been applied to real data.

Keywords: image processing, median filter, projection, scale-space, segmentation, threshold

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Authors: Mohamed Ahmed Kenawi Abdallah

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Chemical composition, cooking loss, shrinkage value, texture coefficient indices, Feder value, microbial examination, and sensory evaluation were done in order to examine the effect of adding 15% germinated quinoa seeds flour as extender to chicken wings meat to produce low fat chicken burger, packaged in two different packing materials and stored frozen for nine months. The data indicated reduction in the moisture content, crude either extract, and increase in the ash content, pH value, and total acidity for the samples extended by quinoa flour compared with the control one. The data showed that the extended samples with quinoa flour had the lowest values of TBA, cooking loss, and shrinkage value compared with the control ones. The data also revealed that, the sample contained quinoa flour had total bacterial count and psychrophilic bacterial count lower than the control sample. In addition, it has higher evaluation values for overall acceptability than the control one.

Keywords: chicken wings, low fat chicken burger, quinoa flour, vacuum packaging.

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Authors: Sergio Paez Moncaleano, Alvaro Mauricio Montenegro

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This paper presents a novel statistical methodology for measuring and founding constructs in Latent Regression Analysis. This approach uses the qualities of Factor Analysis in binary data with interpretations on Item Response Theory (IRT). In addition, based on the fundamentals of submodel theory and with a convergence of many ideas of IRT, we propose an algorithm not just to solve the dimensionality problem (nowadays an open discussion) but a new research field that promises more fear and realistic qualifications for examiners and a revolution on IRT and educational research. In the end, the methodology is applied to a set of real data set presenting impressive results for the coherence, speed and precision. Acknowledgments: This research was financed by Colciencias through the project: 'Multidimensional Item Response Theory Models for Practical Application in Large Test Designed to Measure Multiple Constructs' and both authors belong to SICS Research Group from Universidad Nacional de Colombia.

Keywords: item response theory, dimensionality, submodel theory, factorial analysis

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Authors: Anthony Oppong Kyekyeku, Sussana Antwi-Boasiako, Emmanuel De-Graft Johnson Owusu Ansah

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In this observational study, the performance of a known conventional storage system was tested and evaluated for fitness for its intended purpose. The system has a scope extended for the storage of dry cocoa beans. System sensitivity, reproducibility and uncertainties are not known in details. This study discusses the system performance in the context of existing literature on factors that influence the quality of cocoa beans during storage. Controlled conditions were defined precisely for the system to give reliable base line within specific established procedures. Minitab® 17 and R statistical software (R-3.3.1) were used for the statistical analyses. The approach to the storage system testing was to observe and compare through laboratory test methods the quality of the cocoa beans samples before and after storage. The samples were kept in Kilner jars and the temperature of the storage environment controlled and monitored over a period of 408 days. Standard test methods use in international trade of cocoa such as the cut test analysis, moisture determination with Aqua boy KAM III model and bean count determination were used for quality assessment. The data analysis assumed the entire population as a sample in order to establish a reliable baseline to the data collected. The study concluded a statistically significant mean value at 95% Confidence Interval (CI) for the performance data analysed before and after storage for all variables observed. Correlational graphs showed a strong positive correlation for all variables investigated with the exception of All Other Defect (AOD). The weak relationship between the before and after data for AOD had an explained variability of 51.8% with the unexplained variability attributable to the uncontrolled condition of hidden infestation before storage. The current study concluded with a high-performance criterion for the storage system.

Keywords: benchmarking performance data, cocoa beans, hidden infestation, storage system validation

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Authors: Gurjeet Singh, Rabindra K. Panda

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Soil moisture is a key hydrologic state variable and is intrinsically linked to the Earth's water, climate and carbon cycles. On ecological point of view, the soil moisture is a fundamental natural resource providing the transpirable water for plants. Soil moisture varies both temporally and spatially due to spatiotemporal variation in rainfall, vegetation cover, soil properties and topography. Satellite derived soil moisture provides spatio-temporal extensive data. However, the spatial resolution of a typical satellite (L-band radiometry) is of the order of tens of kilometers, which is not good enough for developing efficient agricultural water management schemes at the field scale. In the present study, the soil moisture from radiometer data has been disaggregated using blending approach to achieve higher resolution soil moisture data. The radiometer estimates of soil moisture at a 40 km resolution have been disaggregated to 10 km, 5 km and 1 km resolutions. The disaggregated soil moisture was compared with the observed data, consisting of continuous sensor based soil moisture profile measurements, at three monitoring sites and extensive spatial near-surface soil moisture measurements, concurrent with satellite monitoring in the 500 km2 study watershed in the Eastern India. The estimated soil moisture status at different spatial scales can help in developing efficient agricultural water management schemes to increase the crop production and water use efficiency.

Keywords: disaggregation, eastern India, radiometers, soil moisture, water use efficiency

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Authors: D. Subedi, D. Sharma

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Current transformers (CTs) are used to transform large primary currents to a small secondary current. Since most standard equipment’s are not designed to handle large primary currents the CTs have an important part in any electrical system for the purpose of Metering and Protection both of which are integral in Power system. Now a days due to advancement in solid state technology, the operation times of the protective relays have come to a few cycles from few seconds. Thus, in such a scenario it becomes important to study the transient response of the current transformers as it will play a vital role in the operating of the protective devices. This paper shows the steady state and transient behavior of current transformers and how it changes with change in connected burden. The transient and steady state response will be captured using the data acquisition software LabVIEW. Analysis is done on the real time data gathered using LabVIEW. Variation of current transformer characteristics with changes in burden will be discussed.

Keywords: accuracy, accuracy limiting factor, burden, current transformer, instrument security factor

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Authors: Jaballah Jamil

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KLD (Peter Kinder, Steve Lydenberg and Amy Domini) research & analytics is an independent intermediary of social performance information that adopts an investor-pay model. KLD rating agency does not have an explicit monitoring on the rated firm which suggests that KLD ratings may not include private informations. Moreover, the incapacity of KLD to predict accurately the extra-financial rating of Enron casts doubt on the reliability of KLD ratings. Therefore, we first investigate whether KLD ratings affect investors' perception by studying the effect of KLD rating changes on firms' financial performances. Second, we study the impact of the Enron scandal on investors' perception of KLD rating changes by comparing the effect of KLD rating changes on firms' financial performances before and after the failure of Enron. We propose an empirical study that relates a number of equally-weighted portfolios returns, excess stock returns and book-to-market ratio to different dimensions of KLD social responsibility ratings. We first find that over the last two decades KLD rating changes influence significantly and negatively stock returns and book-to-market ratio of rated firms. This finding suggests that a raise in corporate social responsibility rating lowers the firm's risk. Second, to assess the Enron scandal's effect on the perception of KLD ratings, we compare the effect of KLD rating changes before and after the Enron scandal. We find that after the Enron scandal this significant effect disappears. This finding supports the view that the Enron scandal annihilates the KLD's effect on Socially Responsible Investors. Therefore, our findings may question results of recent studies that use KLD ratings as a proxy for Corporate Social Responsibility behavior.

Keywords: KLD social rating agency, investors' perception, investment decision, financial performance

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Authors: Will Brown

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Martin Heidegger is considered to be one of the leading philosophical lights of the 20th century with his lecture/essay 'The Question Concerning Technology' proving to be an invaluable text in the study of technology and the understanding of how technology influences the world it is set upon. However, this text has not as of yet been applied to the rapid rise and proliferation of ‘smart’ cities. This article is premised upon the application of the aforementioned text and the smart city in order to provide a fresh, if not critical analysis and interpretation of this phenomena. The first section below provides a brief literature review of smart urbanism in order to lay the groundwork necessary to apply Heidegger’s work to the smart city, from which a framework is developed to interpret the infusion of digital sensing technologies and the urban milieu. This framework is comprised of four concepts put forward in Heidegger’s text: circumscribing, bringing-forth, challenging, and standing-reserve. A concluding chapter is based upon the notion of enframement, arguing that once the rubric of data collection is placed within the urban system, future systems will require the capability to harvest data, resulting in an ever-renewing smart city.

Keywords: air quality sensing, big data, Martin Heidegger, smart city

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Authors: María José López Rey, Mar Chaves Carrillo, Manuela Caballero Guisado

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The data presented here are part of a broader investigation on active population aging. The work was carried out in November 2020 in Extremadura, a region of southern Spain. This R + D + I project, called "Active aging scenarios in Extremadura: intervention proposals," was carried out by a team of professors, researchers from the University of Extremadura. The project has been financed by the European Regional Development Funds and the Government of Extremadura. Here, we focus on aspects that have to do with the experience of health, especially during the COVID-19 pandemic, and how this has affected the population related to the main sociodemographic variables. In an exercise of methodological triangulation, thus providing robustness to the analysis, primary data, obtained from the survey designed ad hoc, are combined with other secondary data from various sources and studies carried out in Spain (Sociological Research Centre, and National Institute of Statistics). The survey was carried out on a representative sample of the population over 55 years old, coming from Extremadura. Among the findings, we must highlight the practical invariability of perceptions based on the main sociodemographic variables, as well as some differences indicated by the variables sex and age.

Keywords: aging, health, COVID-19, perceptions

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Authors: Ammarah Irum, Muhammad Ali Tahir

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Document-level sentiment analysis in Urdu is a challenging Natural Language Processing (NLP) task due to the difficulty of working with lengthy texts in a language with constrained resources. Deep learning models, which are complex neural network architectures, are well-suited to text-based applications in addition to data formats like audio, image, and video. To investigate the potential of deep learning for Urdu sentiment analysis, we implemented five different deep learning models, including Bidirectional Long Short Term Memory (BiLSTM), Convolutional Neural Network (CNN), Convolutional Neural Network with Bidirectional Long Short Term Memory (CNN-BiLSTM), and Bidirectional Encoder Representation from Transformer (BERT). In this study, we developed a hybrid deep learning model called BiLSTM-Single Layer Multi Filter Convolutional Neural Network (BiLSTM-SLMFCNN) by fusing BiLSTM and CNN architecture. The proposed and baseline techniques are applied on Urdu Customer Support data set and IMDB Urdu movie review data set by using pre-trained Urdu word embedding that are suitable for sentiment analysis at the document level. Results of these techniques are evaluated and our proposed model outperforms all other deep learning techniques for Urdu sentiment analysis. BiLSTM-SLMFCNN outperformed the baseline deep learning models and achieved 83%, 79%, 83% and 94% accuracy on small, medium and large sized IMDB Urdu movie review data set and Urdu Customer Support data set respectively.

Keywords: urdu sentiment analysis, deep learning, natural language processing, opinion mining, low-resource language

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Authors: Kika Ioannou Kazamia

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This paper examines the action research cycle of the second phase of longitudinal research on sustainable interior design practices, between two groups of stakeholders, designers and clients. During this phase of the action research, the second step - the change stage - of Lewin’s change management model has been utilized to change values, approaches, and attitudes toward sustainable design practices among the participants. Affective domain learning theory is utilized to attach new values. Learning with the use of information technology, collaborative learning, and problem-based learning are the learning methods implemented toward the acquisition of the objectives. Learning methods, and aims, require the design of interventions with participants' involvement in activities that would lead to the acknowledgment of the benefits of sustainable practices. Interventions are steered to measure participants’ decisions for the worth and relevance of ideas, and experiences; accept or commit to a particular stance or action. The data collection methods used in this action research are observers’ reports, participants' questionnaires, and interviews. The data analyses use both quantitative and qualitative methods. The main beneficial aspect of the quantitative method was to provide the means to separate many factors that obscured the main qualitative findings. The qualitative method allowed data to be categorized, to adapt the deductive approach, and then examine for commonalities that could reflect relevant categories or themes. The results from the data indicate that during the second phase, designers and clients' participants altered their behaviours.

Keywords: design, change, sustainability, learning, practices

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Authors: Bahadir Aydin

Abstract:

Today it is difficult to reach accurate knowledge because of mass data. This huge data makes the environment more and more caotic. Data is a main piller of intelligence. There is a close tie between knowledge and intelligence. Information gathered from different sources can be modified, interpreted and classified by using knowledge development process. This process is applied in order to attain intelligence. Within this process the effect of knowledge is crucial. Knowledge is classified as explicit and tacit knowledge. Tacit knowledge can be seen as "only the tip of the iceberg”. This tacit knowledge accounts for much more than we guess in all intelligence cycle. If the concept of intelligence scrutinized, it can be seen that it contains risks, threats as well as success. The main purpose for all organization is to be succesful by eliminating risks and threats. Therefore, there is a need to connect or fuse existing information and the processes which can be used to develop it. By the help of process the decision-maker can be presented with a clear holistic understanding, as early as possible in the decision making process. Planning, execution and assessments are the key functions that connects to information to knowledge. Altering from the current traditional reactive approach to a proactive knowledge development approach would reduce extensive duplication of work in the organization. By new approach to this process, knowledge can be used more effectively.

Keywords: knowledge, intelligence cycle, tacit knowledge, KIDW

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Authors: Jeff Clarine, Chang-Shyh Peng, Daisy Sang

Abstract:

Bioassay is the measurement of the potency of a chemical substance by its effect on a living animal or plant tissue. Bioassay data and chemical structures from pharmacokinetic and drug metabolism screening are mined from and housed in multiple databases. Bioassay prediction is calculated accordingly to determine further advancement. This paper proposes a four-step preprocessing of datasets for improving the bioassay predictions. The first step is instance selection in which dataset is categorized into training, testing, and validation sets. The second step is discretization that partitions the data in consideration of accuracy vs. precision. The third step is normalization where data are normalized between 0 and 1 for subsequent machine learning processing. The fourth step is feature selection where key chemical properties and attributes are generated. The streamlined results are then analyzed for the prediction of effectiveness by various machine learning algorithms including Pipeline Pilot, R, Weka, and Excel. Experiments and evaluations reveal the effectiveness of various combination of preprocessing steps and machine learning algorithms in more consistent and accurate prediction.

Keywords: bioassay, machine learning, preprocessing, virtual screen

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Authors: Malraj Bharatha Kiriella

Abstract:

The purpose of this paper is to investigate the determinants of tourism foreign direct investment (TFDI) to selected developing countries during 1978-2017. The study used pooled panel data to estimate an econometric model. The findings show that market size and institutional barriers are determining factors for TFDI in countries, while other variables of positive country conditions, FDI-related government policy, tourism-related infrastructure and labor conditions are insignificant. The result shows that institutional effects are positive, while market size negatively affects TFDI inflows. The research is limited to eight developing countries. The results can be used to support government policy on TFDI. The paper makes the following contributions: First, it provides important insight and understanding into the TFDI decision-making process in developing countries. Second, both TFDI theory and evidence are minimal, and an econometric model developed on the basis of available literature has been empirically tested.

Keywords: determinants, developing countries, FDI in tourism, panel data

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Authors: Shilpa Murthy, Hazlina Binti Abu Bakar, Juliet Mathew, Chandrashekhar Thummala Hlly Sreerama Reddy, Pathiyil Ravi Shankar

Abstract:

Simulation is defined as a technique that replaces or expands real experiences with guided experiences that interactively imitate real-world processes or systems. Simulation enables learners to train in a safe and non-threatening environment. For decades, simulation has been considered an integral part of clinical teaching and learning strategy in medical education. The several types of simulation used in medical education and the clinical environment can be applied to several models, including full-body mannequins, task trainers, standardized simulated patients, virtual or computer-generated simulation, or Hybrid simulation that can be used to facilitate learning. Simulation allows healthcare practitioners to acquire skills and experience while taking care of patient safety. The recent COVID pandemic has also led to an increase in simulation use, as there were limitations on medical student placements in hospitals and clinics. The learning is tailored according to the educational needs of students to make the learning experience more valuable. Simulation in the pre-clinical years has challenges with resource constraints, effective curricular integration, student engagement and motivation, and evidence of educational impact, to mention a few. As instructors, we may have more reliance on the use of simulation for pre-clinical students while the students’ confidence levels and perceived competence are to be evaluated. Our research question was whether the implementation of simulation-based learning positively influences preclinical medical students' confidence levels and perceived competence. This study was done to align the teaching activities with the student’s learning experience to introduce more low-fidelity simulation-based teaching sessions for pre-clinical years and to obtain students’ input into the curriculum development as part of inclusivity. The study was carried out at International Medical University, involving pre-clinical year (Medical) students who were started with low-fidelity simulation-based medical education from their first semester and were gradually introduced to medium fidelity, too. The Student Satisfaction and Self-Confidence in Learning Scale questionnaire from the National League of Nursing was employed to collect the responses. The internal consistency reliability for the survey items was tested with Cronbach’s alpha using an Excel file. IBM SPSS for Windows version 28.0 was used to analyze the data. Spearman’s rank correlation was used to analyze the correlation between students’ satisfaction and self-confidence in learning. The significance level was set at p value less than 0.05. The results from this study have prompted the researchers to undertake a larger-scale evaluation, which is currently underway. The current results show that 70% of students agreed that the teaching methods used in the simulation were helpful and effective. The sessions are dependent on the learning materials that are provided and how the facilitators engage the students and make the session more enjoyable. The feedback provided inputs on the following areas to focus on while designing simulations for pre-clinical students. There are quality learning materials, an interactive environment, motivating content, skills and knowledge of the facilitator, and effective feedback.

Keywords: low-fidelity simulation, pre-clinical simulation, students satisfaction, self-confidence

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