Search results for: panel data analysis

Authors: Iliya Bitrus Abaje

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This study examines the evidence of climate change scenario in Kaduna State from the analysis of temperature and rainfall data (1976-2015) from three meteorological stations along a geographic transect from the southern part to the northern part of the State. Different statistical methods were used in determining the changes in both the temperature and rainfall series. The result of the linear trend lines revealed a mean increase in average temperature of 0.73oC for the 40 years period of study in the State. The plotted standard deviation for the temperature anomalies generally revealed that years of temperatures above the mean standard deviation (hotter than the normal conditions) in the last two decades (1996-2005 and 2006-2015) were more than those below (colder than the normal condition). The Cramer’s test and student’s t-test generally revealed an increasing temperature trend in the recent decades. The increased in temperature is an evidence that the earth’s atmosphere is getting warmer in recent years. The linear trend line equation of the annual rainfall for the period of study showed a mean increase of 316.25 mm for the State. Findings also revealed that the plotted standard deviation for the rainfall anomalies, and the 10-year non-overlapping and 30-year overlapping sub-periods analysis in all the three stations generally showed an increasing trend from the beginning of the data to the recent years. This is an evidence that the study area is now experiencing wetter conditions in recent years and hence climate change. The study recommends diversification of the economic base of the populace with emphasis on moving away from activities that are sensitive to temperature and rainfall extremes Also, appropriate strategies to ameliorate the scourge of climate change at all levels/sectors should always take into account the recent changes in temperature and rainfall amount in the area.

Keywords: anomalies, linear trend, rainfall, temperature

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Authors: Hasik Lee, Seung-Young Kho

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Nowadays, automatic fare collection (AFC) system is widely used in many countries. However, smart card data from many of cities does not contain alighting information which is necessary to build OD matrices. Therefore, in order to utilize smart card data, destinations of passengers should be estimated. In this paper, kernel density estimation was used to forecast probabilities of alighting stations of bus passengers and applied to smart card data in Seoul, Korea which contains boarding and alighting information. This method was also validated with actual data. In some cases, stochastic method was more accurate than deterministic method. Therefore, it is sufficiently accurate to be used to build OD matrices.

Keywords: destination estimation, Kernel density estimation, smart card data, validation

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Authors: Javed Mohammed

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Right now, bio-medical infrastructure lags well behind the curve. Our healthcare system is dispersed and disjointed; medical records are a bit of a mess; and we do not yet have the capacity to store and process the crazy amounts of data coming our way from widespread whole-genome sequencing. And then there are privacy issues. Despite these infrastructure challenges, some researchers are plunging into bio medical Big Data now, in hopes of extracting new and actionable knowledge. They are doing delving into molecular-level data to discover bio markers that help classify patients based on their response to existing treatments; and pushing their results out to physicians in novel and creative ways. Computer scientists and bio medical researchers are able to transform data into models and simulations that will enable scientists for the first time to gain a profound under-standing of the deepest biological functions. Solving biological problems may require High-Performance Computing HPC due either to the massive parallel computation required to solve a particular problem or to algorithmic complexity that may range from difficult to intractable. Many problems involve seemingly well-behaved polynomial time algorithms (such as all-to-all comparisons) but have massive computational requirements due to the large data sets that must be analyzed. High-throughput techniques for DNA sequencing and analysis of gene expression have led to exponential growth in the amount of publicly available genomic data. With the increased availability of genomic data traditional database approaches are no longer sufficient for rapidly performing life science queries involving the fusion of data types. Computing systems are now so powerful it is possible for researchers to consider modeling the folding of a protein or even the simulation of an entire human body. This research paper emphasizes the computational biology's growing need for high-performance computing and Big Data. It illustrates this article’s indispensability in meeting the scientific and engineering challenges of the twenty-first century, and how Protein Folding (the structure and function of proteins) and Phylogeny Reconstruction (evolutionary history of a group of genes) can use HPC that provides sufficient capability for evaluating or solving more limited but meaningful instances. This article also indicates solutions to optimization problems, and benefits Big Data and Computational Biology. The article illustrates the Current State-of-the-Art and Future-Generation Biology of HPC Computing with Big Data.

Keywords: high performance, big data, parallel computation, molecular data, computational biology

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Authors: Tassadit Issaadi Hamitouche, Nicolas Gillard, Jean Petit, Valerie Lavaste, Celine Mayousse

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Water is a fundamental resource for the industry. It is taken from the environment either from municipal distribution networks or from various natural water sources such as the sea, ocean, rivers, aquifers, etc. Once used, water is discharged into the environment, reprocessed at the plant or treatment plants. These withdrawals and discharges have a direct impact on natural water resources. These impacts can apply to the quantity of water available, the quality of the water used, or to impacts that are more complex to measure and less direct, such as the health of the population downstream from the watercourse, for example. Based on the analysis of data (meteorological, river characteristics, physicochemical substances), we wish to predict water stress episodes and anticipate prefectoral decrees, which can impact the performance of plants and propose improvement solutions, help industrialists in their choice of location for a new plant, visualize possible interactions between companies to optimize exchanges and encourage the pooling of water treatment solutions, and set up circular economies around the issue of water. The development of a system for the collection, processing, and use of data related to water resources requires the functional constraints specific to the latter to be made explicit. Thus the system will have to be able to store a large amount of data from sensors (which is the main type of data in plants and their environment). In addition, manufacturers need to have 'near-real-time' processing of information in order to be able to make the best decisions (to be rapidly notified of an event that would have a significant impact on water resources). Finally, the visualization of data must be adapted to its temporal and geographical dimensions. In this study, we set up an infrastructure centered on the TICK application stack (for Telegraf, InfluxDB, Chronograf, and Kapacitor), which is a set of loosely coupled but tightly integrated open source projects designed to manage huge amounts of time-stamped information. The software architecture is coupled with the cross-industry standard process for data mining (CRISP-DM) data mining methodology. The robust architecture and the methodology used have demonstrated their effectiveness on the study case of learning the level of a river with a 7-day horizon. The management of water and the activities within the plants -which depend on this resource- should be considerably improved thanks, on the one hand, to the learning that allows the anticipation of periods of water stress, and on the other hand, to the information system that is able to warn decision-makers with alerts created from the formalization of prefectoral decrees.

Keywords: data mining, industry, machine Learning, shortage, water resources

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Authors: A. Rahim Baharudin, Nor Arinee binti Mat Saaud, Muhammad Afiq Azman, Farah Adiba A. Sani

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Objectives: This paper shares the case study on the engineering analysis, data analysis, and real-time data comparison for qualifying the stand wires' minimum breaking load and safe working load upon loadout operation for a new project and, at the same time, eliminate the risk due to discrepancies and unalignment of COMPANY Technical Standards to Industry Standards and Practices. This paper demonstrates “Lean Construction” for COMPANY’s Project by sustaining fit-for-purpose Technical Requirements of Loadout Strand Wire Factor of Safety (F.S). The case study utilizes historical engineering data from a few loadout operations by skidding methods from different projects. It is also demonstrating and qualifying the skidding wires' minimum breaking load and safe working load used for loadout operation for substructure and other facilities for the future. Methods: Engineering analysis and comparison of data were taken as referred to the international standard and internal COMPANY standard requirements. Data was taken from nine (9) previous projects for both topsides and jacket facilities executed at the several local fabrication yards where load out was conducted by three (3) different service providers with emphasis on four (4) basic elements: i) Industry Standards for Loadout Engineering and Operation Reference: COMPANY internal standard was referred to superseded documents of DNV-OS-H201 and DNV/GL 0013/ND. DNV/GL 0013/ND and DNVGL-ST-N001 do not mention any requirements of Strand Wire F.S of 4.0 for Skidding / Pulling Operations. ii) Reference to past Loadout Engineering and Execution Package: Reference was made to projects delivered by three (3) major offshore facilities operators. Strand Wire F.S observed ranges from 2.0 MBL (Min) to 2.5 MBL (Max). No Loadout Operation using the requirements of 4.0 MBL was sighted from the reference. iii) Strand Jack Equipment Manufacturer Datasheet Reference: Referring to Strand Jack Equipment Manufactured Datasheet by different loadout service providers, it is shown that the Designed F.S for the equipment is also ranging between 2.0 ~ 2.5. Eight (8) Strand Jack Datasheet Model was referred to, ranging from 15 Mt to 850 Mt Capacity; however, there are NO observations of designed F.S 4.0 sighted. iv) Site Monitoring on Actual Loadout Data and Parameter: Max Load on Strand Wire was captured during 2nd Breakout, which is during Static Condition of 12.9 MT / Strand Wire (67.9% Utilization). Max Load on Strand Wire for Dynamic Conditions during Step 8 and Step 12 is 9.4 Mt / Strand Wire (49.5% Utilization). Conclusion: This analysis and study demonstrated the adequacy of strand wires supplied by the service provider were technically sufficient in terms of strength, and via engineering analysis conducted, the minimum breaking load and safe working load utilized and calculated for the projects were satisfied and operated safely for the projects. It is recommended from this study that COMPANY’s technical requirements are to be revised for future projects’ utilization.

Keywords: construction, load out, minimum breaking load, safe working load, strand jacking, skidding

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Authors: Naushaba Naseem Ahmed

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Economic development does not merely depend upon the level of development but also on its distributive aspect. As it is a serious issue, the fruit of development is not equally distributed among the different section of peoples and different part of the country this cause the regional disparities in the levels of social economic development. Different part of the country has different resource endowments in term of natural, human and capital. If there is the uniform condition to grow, these areas that have better resources, are favourably placed grow comparatively faster as other areas. Thus with the very stage of development, gap between resourceful and less resourceful area goes on widening. This paper is an attempt to highlight the levels of disparities in term of economic development with the help of selected variables. Principal component analysis, correlation, and coefficient of variation are the techniques which were used in paper and employed published data for analysis. The result shows that Western region of Uttar Pradesh is more developed followed by Central Region. There will be urgent need in investment and developmental policies for the backward region like Bundelkhand region of Uttar Pradesh.

Keywords: coefficient of variation, correlation, economic development, principal component analysis

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Authors: Anit S. Malhotra, Ajay Duseja, Neelam Chadha

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Endothelial dysfunction is a precursor to atherosclerosis, and flow-mediated dilatation (FMD) in the brachial artery is the commonest method to evaluate endothelial function in humans. Non-alcoholic fatty liver disease (NAFLD) is one of the most common liver disorders encountered in clinical practice. An earlier meta-analysis had quantitatively assessed the degree of endothelial dysfunction using FMD. However, the largest study investigating the relation of FMD with NAFLD was published after that meta-analysis. In addition, that meta-analysis did not include some studies, including one from our centre. Therefore, an updating the previous meta-analysis was considered important. We searched PubMed, Cochrane Library, Embase, Scopus, SCI, Google Scholar, conference proceedings, and references of included studies till June 2017 to identify observational studies evaluating endothelial function using FMD in patients with non-alcoholic fatty liver disease. Data was analyzed using MedCalc. Fourteen studies were found eligible for inclusion in the meta-analysis. Patients with NAFLD had lower brachial artery FMD as compared to controls, standardized mean difference (random effects model) being –1.279%; 95% confidence interval (CI), –1.478 to –0.914. The effect size became smaller after addition of the recent study with the largest sample size was included compared with the earlier meta-analysis. In conclusion, patients with NAFLD had low FMD values indicating that they are at a higher risk of cardiovascular disease although our results suggest the effect size is not as large as reported previously.

Keywords: endothelial dysfunction, flow-mediated dilatation, meta-analysis, non-alcoholic fatty liver disease

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Authors: Karla Kristine Bay, Jovie Ann Gabin, Allana Joyce Sasotona

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This research employed an Interpretative Phenomenological Analysis to explore the experiences of Children in Conflict with the Law (CICL) which gave light to their concept of ‘friends’. Derived from this context are the following objectives of the study: 1) determining the differentiation of the forms of friends of the CICL; 2) presenting the process of attachment towards detachment in the formation of friendship; and 3) discussing the experiences, and reflections of the CICL on the ‘self’ out of their encounter with friendship. Using the data gathered from the individual drawings of the CICL of their representations of the self, family, friends, community, and Bahay Kalinga as subjects in the meaning-making process utilizing Filipino Psychology methods of pagtatanong-tanong (interview), and pakikipagkwentuhan (conversation), data analysis produced a synthesis of seventeen individual cases. Overall results generated three superordinate themes on the differentiation of the forms of friends which include friends with good influences, friends with bad influences, and friends within the family. While two superordinate themes were produced on the process of attachment towards detachment, namely social, emotional, and psychological experiences on the process of attachment, and emotional and psychological experiences on the process of detachment. Lastly, two superordinate themes were created on the experiences, and reflections of the CICL on the ‘self’ out of their encounter with friendship. This consists of the recognition of the ‘self’ as a responsible agent in developing healthy relationships between the self and others, and reconstruction of the self from the collective experiences of healing, forgiveness, and acceptance. These findings, together with supporting theories discussed the impact of friendship on the emergence of criminal behavior and other dispositions; springing from the child’s dissociation from the family that led to finding belongingness from an external group called friends.

Keywords: children in conflict with the law, criminal behavior, friends, interpretative phenomenological analysis

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Authors: Supasak Ngaoprasertwong

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The purpose of this research was to develop a model for Muay Thai competition management for promoting sport tourism in the next decade. Moreover, the model was appropriately initiated for practical use. This study also combined several methodologies, both quantitative research and qualitative research, to entirely cover all aspects of data, especially the tourists’ satisfaction toward Muay Thai competition. The data were collected from 400 tourists watching Muay Thai competition in 4 stadiums to create the model for Muay Thai competition to support the sport tourism in the next decade. Besides, Ethnographic Delphi Futures Research (EDFR) was applied to gather the data from certain experts in boxing industry or having significant role in Muay Thai competition in both public sector and private sector. The first step of data collection was an in-depth interview with 27 experts associated with Muay Thai competition, Muay Thai management, and tourism. The second step and the third step of data collection were conducted to confirm the experts’ opinions toward various elements. When the 3 steps of data collection were completely accomplished, all data were assembled to draft the model. Then the model was proposed to 8 experts to conduct a brainstorming to affirm it. According to the results of quantitative research, it found that the tourists were satisfied with personnel of competition at high level (x=3.87), followed by facilities, services, and safe high level (x=3.67). Furthermore, they were satisfied with operation in competition field at high level (x=3.62).Regarding the qualitative methodology including literature review, theories, concepts and analysis of qualitative research development of the model for Muay Thai competition to promote the sport tourism in the next decade, the findings indicated that there were 2 data sets as follows: The first one was related to Muay Thai competition to encourage the sport tourism and the second one was associated with Muay Thai stadium management to support the sport tourism. After the brain storming, “EE Muay Thai Model” was finally developed for promoting the sport tourism in the next decade (2015-2024).

Keywords: Muay Thai competition management, Muay Thai sport tourism, Muay Thai, Muay Thai for sport tourism management

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Authors: Vinay Mishra, Meena Malkani

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Objectives: To study the effect of physical maternal nutritional markers (viz. weight, height, gestational weight gain, BMI) and third-trimester haemoglobin concentration on anthropometry and cord blood haemoglobin of their newborn. Methods: Study area: Post-natal ward of a tertiary care hospital in an urban area. Study population: All post-partum women and their newborns. Sample size: 100. Maternal and neonatal data and anthropometric measurements were recorded in semi-structured case proforma. Data analysis: The data obtained was analysed using SPSS 20 software.The comparison between the groups was done using One-Way Analysis of Variance for two groups. For more than two groups comparisons further posthoc analysis was done using Tukey test. Pearson correlation coefficient was used for correlating the variables. A P value less than 0.05 was considered significant. Results: 1. Out of the 100 studied mothers, 52% were anaemic. 2. Cord blood haemoglobin values decreased significantly with the order of birth. 3. Cord blood haemoglobin of normal-weight newborns is significantly higher as compared to that of LBW newborns. 4. Cord blood haemoglobin has strong statistical significance with maternal anaemia. 5. Pre-pregnancy weight and gestational weight gain significantly influence the neonates anthropometry. Conclusions: 1. Birth order has a prominent inverse effect on the cord blood haemoglobin. 2. Majority of the expectant mothers are anaemic and give birth to LBW babies with reduced anthropometric markers. 3. Pre-pregnancy weight, height and gestational weight gain has a very significant impact on the neonatal anthropometry. 4. Thus, maternal nutrition during gestation and during the crucial periods of growth in the pre-child bearing age group has a very significant impact on foetal development.

Keywords: maternal nutrition, anthropometry, cord blood hemoglobin, newborn

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Authors: M. Mesrouk, A. Hadj Arab

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This work allows highlight the effect of dust on the absorption of the optical spectrum on the photovoltaic module, the effect of the particles dust presence on the photovoltaic modules have been a microscopic scale studied with COMSOL Multi-physic software simulation. In this paper, we have supposed the dust layer as a diffraction network repetitive optical structure characterized by the spacing between particle which represented by 'd' and the simulated structure (air-dust particle-glass). In this study we can observe the relationship between the wavelength and the particle spacing, the simulation shows us that the maximum wavelength transmission value corresponding, λ0 = 400nm, which represent the spacing value between the particles dust, d = 400 nm. In fact, we can observe that while increase dust layer density the wavelength transmission value decrease, there is a relationship between the density and wavelength value which can be absorbed in a dusty photovoltaic panel.

Keywords: dust effect, photovoltaic module, spectral absorption, wavelength transmission

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Authors: Jae Won Shin

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We develop an evaluated nuclear data based photonuclear reaction model of GEANT4 for a more accurate simulation of photon-induced neutron production. The evaluated photonuclear data libraries from the ENDF/B-VII.1 are taken as input. Incident photon energies up to 140 MeV which is the threshold energy for the pion production are considered. For checking the validity of the use of the data-based model, we calculate the photoneutron production cross-sections and yields and compared them with experimental data. The results obtained from the developed model are found to be in good agreement with the experimental data for (γ,xn) reactions.

Keywords: ENDF/B-VII.1, GEANT4, photoneutron, photonuclear reaction

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Authors: Ajith K. A. Gedara, Iva Chianella, Jose L. Endrino, Qi Zhang

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The olive seed is a by-product of the olive oil production industry. Biuret test and ferric chloride test revealed that water or alkali NaOH extractions of olive seed flour are rich in proteins and tannins. Both protein and tannins are well-known bio-based wood adhesives in the wood-based panel industry. In general, tannins-based adhesives show better mechanical and physical properties than protein wood adhesives. This paper explores different methods of extracting tannins from olive seed flour against the tannins yield and their applications as bio-based adhesives in wood-based panels. Once investigated, the physical and the mechanical properties of wood-based panels made using bio-adhesives based tannins extracted from olive seed flour revealed that the resulting products seemed to satisfy the Japanese Industrial Standards JIS A 5908:2015.

Keywords: bio-adhesives, olive seed flour, tannins, wood-based panels

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Authors: ZhangRun, Yi-Fang Chiang, Li-Shia Huang

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The purpose of this study was to explore the impact of emotional story marketing on the fundraising effectiveness of non-profit organizations and to further clarify the communication effectiveness of emotional story types by using "social distance" which reflects individual differences, as an intervening variable in two experiments. The quasi-experimental design of the development experiment (positive warmth of the story v.s. negative sadness of the story) × social distance (near v.s. far) to clarify the effects of social distance. In this study, we designed the experimental advertising situation ourselves, and data were collected through a questionnaire survey. A total of 391 questionnaires were distributed, and data analysis and hypothesis verification were conducted through variance analysis. According to the analysis results of this study, the use of positive emotional appeals in the design of non-profit organization advertisements on issues related to the loss of children will increase the willingness of listeners to donate. For those with close social distance, there is no significant difference between the positive and "warm" emotional story ads and the negative and "sad" emotional story ads. For those with far social distance, there is a significant difference between the positive and "warm" emotional story ads and the negative and "sad" emotional story ads, with the positive and "warm" emotional appeals improving their willingness to donate. Therefore, this study suggests that NPOs should use more positive and warm emotional stories in their advertising design to enhance the fundraising effectiveness of NPO story marketing.

Keywords: story marketing, emotional appeal, social distance, willingness to donate

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Authors: Quoc Ngoc Phan, Hieu Van Nguyen, Minh Hong Nguyen

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This study presents an integrated approach using Mercury Injection Capillary Pressure (MICP) and petrographic analysis to assess the seal quality of the inter-bedded shale formations which are considered the intra-formation top seals of hydrocarbon bearing zones in Green Dragon structure. Based on the hydrocarbon column height (HCH) at leak point derived from capillary pressure data, four seal types were identified. Furthermore, the results of scanning electron microscopy (SEM) and X-ray diffraction (XRD) analysis were interpreted to clarify the influence of clay minerals on seal capacity. The result of the study indicated that the inter-bedded shale formations are the good sealing quality with a majority of analyzed samples ranked type A and B seals in the sample set. Both seal types occurred mainly in mudstones with pore radius estimated less than 0.251 µm. Overall, type A and B seals contained a large amount of authigenic clay minerals such as illite, chlorite which showed the complexity of morphological arrangement in pore space. Conversely, the least common seal type C and D were presented in moderately compacted sandstones with more open pore radius. It is noticeable that there was a reduction of illite and chlorite in clay mineral fraction of these seal type. It is expected that the integrated analysis approach using Mercury Injection Capillary Pressure and petrographic data employed in this study can be applied to assess the sealing quality of future well sites in Green Dragon or other structures.

Keywords: seal capacity, hydrocarbon height column, seal type, SEM, XRD

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Authors: Rashi Bhalla, Russel Pears, M. Asif Naeem

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In this 'Information Explosion Era' analyzing data 'a critical commodity' and mining knowledge from vertically distributed data stream incurs huge communication cost. However, an effort to decrease the communication in the distributed environment has an adverse influence on the classification accuracy; therefore, a research challenge lies in maintaining a balance between transmission cost and accuracy. This paper proposes a method based on Bayesian inference to reduce the communication volume in a heterogeneous distributed environment while retaining prediction accuracy. Our experimental evaluation reveals that a significant reduction in communication can be achieved across a diverse range of dataset types.

Keywords: big data, bayesian inference, distributed data stream mining, heterogeneous-distributed data

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Authors: Triveni Gogoi, Rima Chatterjee

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Shear wave velocity (Vs) estimation is an important approach in the seismic exploration and characterization of a hydrocarbon reservoir. There are varying methods for prediction of S-wave velocity, if recorded S-wave log is not available. But all the available methods for Vs prediction are empirical mathematical models. Shear wave velocity can be estimated using P-wave velocity by applying Castagna’s equation, which is the most common approach. The constants used in Castagna’s equation vary for different lithologies and geological set-ups. In this study, multiple regression analysis has been used for estimation of S-wave velocity. The EMERGE module from Hampson-Russel software has been used here for generation of S-wave log. Both single attribute and multi attributes analysis have been carried out for generation of synthetic S-wave log in Upper Assam basin. Upper Assam basin situated in North Eastern India is one of the most important petroleum provinces of India. The present study was carried out using four wells of the study area. Out of these wells, S-wave velocity was available for three wells. The main objective of the present study is a prediction of shear wave velocities for wells where S-wave velocity information is not available. The three wells having S-wave velocity were first used to test the reliability of the method and the generated S-wave log was compared with actual S-wave log. Single attribute analysis has been carried out for these three wells within the depth range 1700-2100m, which corresponds to Barail group of Oligocene age. The Barail Group is the main target zone in this study, which is the primary producing reservoir of the basin. A system generated list of attributes with varying degrees of correlation appeared and the attribute with the highest correlation was concerned for the single attribute analysis. Crossplot between the attributes shows the variation of points from line of best fit. The final result of the analysis was compared with the available S-wave log, which shows a good visual fit with a correlation of 72%. Next multi-attribute analysis has been carried out for the same data using all the wells within the same analysis window. A high correlation of 85% has been observed between the output log from the analysis and the recorded S-wave. The almost perfect fit between the synthetic S-wave and the recorded S-wave log validates the reliability of the method. For further authentication, the generated S-wave data from the wells have been tied to the seismic and correlated them. Synthetic share wave log has been generated for the well M2 where S-wave is not available and it shows a good correlation with the seismic. Neutron porosity, density, AI and P-wave velocity are proved to be the most significant variables in this statistical method for S-wave generation. Multilinear regression method thus can be considered as a reliable technique for generation of shear wave velocity log in this study.

Keywords: Castagna's equation, multi linear regression, multi attribute analysis, shear wave logs

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Authors: Pinyada Santisarun, Yaowaret Tharawoot, Songyut Akkakoson

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This paper reports on a literature review sub-study of a larger research project which has been designed to identify the rhetorical organization of a travel writing genre, together with the use of lexical choices, syntactical structures, and graphological features, based on a randomly-selected corpus of Thailand travel listicles. Conducted as a library-based overview, this study aims to specify theoretical and practical elements for the said larger study. The materials for the review have been retrieved from various Internet sources, covering both public search engines and library databases. Generally, the article focuses on answering questions about the ‘what’ and the ‘how’ of such background elements widely discussed in the literature as the meaning of listicles, how the travel listicles’ patterns and regularities can be categorized to form a new genre, the effect of computer-mediated communication on the travel world, the travel language, and the current situation concerning the importance of travel listicles. The theoretical and practical data derived from this study provide valuable insights into the way in which the genre analysis and lexico-syntactical examination of Thailand travel listicles in the present authors’ larger research project can be properly conducted. The data gained can be added to the expanding body of knowledge in the field of the ESP genre.

Keywords: computer-mediated communication, digital writing, genre-based analysis, online travel writing, tourism language

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Authors: Harold Jideofor

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The application of Project Management (PM) tools and techniques in the public sector is gradually becoming an important issue in developing economies, especially in a country like Nigeria where projects of different size and structures are undertaken. The paper examined the application of the project management practice in the public sector in Nigeria. The PM lifecycles, tools, and techniques were presented. The study was carried out in Lagos because of its metropolitan nature and rapidly growing economy. Twenty-three copies of questionnaire were administered to 23 public institutions in Lagos to generate primary data. The descriptive analysis techniques using percentages and table presentations coupled with the coefficient of correlation were used for data analysis. The study revealed that application of PM tools and techniques is an essential management approach that tends to achieve specified objectives within specific time and budget limits through the optimum use of resources. Furthermore, the study noted that there is a lack of in-depth knowledge of PM tools and techniques in public sector institutions sampled, also a high cost of the application was also observed by the respondents. The study recommended among others that PM tools and techniques should be applied gradually especially in old government institutions where resistance to change is perceived to be high.

Keywords: project management, public sector, practice, Nigeria

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Authors: Ouafae Baida, Najma Hamzaoui, Maha Akbib, Abdelfettah Sedqui, Abdelouahid Lyhyaoui

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Numerous scientific works present various methods to analyze the data for several domains, specially the comparison of classifications. In our recent work, we presented a new approach to help the user choose the best classification method from the results obtained by every method, by basing itself on the distances between the trees of classification. The result of our approach was in the form of a dendrogram contains methods as a succession of connections. This approach is much needed in phylogeny analysis. This discipline is intended to analyze the sequences of biological macro molecules for information on the evolutionary history of living beings, including their relationship. The product of phylogeny analysis is a phylogenetic tree. In this paper, we recommend the use of a new method of construction the phylogenetic tree based on comparison of different classifications obtained by different molecular genes.

Keywords: hierarchical classification, classification methods, structure of tree, genes, phylogenetic analysis

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Authors: Khaja Moiduddin, Sherif Mohammed Elseufy, Hisham Alkhalefah

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Recent advances in three-dimensional (3D) printing, medical imaging, and implant design may alter how craniomaxillofacial surgeons construct individualized treatments using patient data. By utilizing medical image data, medical professionals can obtain detailed information about a patient's injuries, enabling them to conduct a thorough preoperative assessment while ensuring the implant's accuracy. However, selecting the right implant material requires careful consideration of various mechanical properties. This study aims to compare the two commonly used implant material for cranial reconstruction which includes titanium (Ti6Al4V) and Polyetheretherketone (PEEK). Biomechanical analysis was performed to study the implant behavior, by keeping the implant design and fixation constant in both cases. A finite element model was created and analyzed under loading conditions. The finite element analysis proves that although Ti6Al4V is stronger than PEEK but, its mechanical strength is adequate to bear the loads of the adjacent bone tissue.

Keywords: cranial reconstruction, titanium implants, PEEK, finite element model

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Authors: Xu Jiaqiao

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Text sentiment analysis is an important branch of natural language processing. This technology is widely used in public opinion analysis and web surfing recommendations. At present, the mainstream sentiment analysis methods include three parts: sentiment analysis based on a sentiment dictionary, based on traditional machine learning, and based on deep learning. This paper mainly analyzes and compares the advantages and disadvantages of the SVM method of traditional machine learning and the Long Short-term Memory (LSTM) method of deep learning in the field of Chinese sentiment analysis, using Chinese comments on Sina Microblog as the data set. Firstly, this paper classifies and adds labels to the original comment dataset obtained by the web crawler, and then uses Jieba word segmentation to classify the original dataset and remove stop words. After that, this paper extracts text feature vectors and builds document word vectors to facilitate the training of the model. Finally, SVM and LSTM models are trained respectively. After accuracy calculation, it can be obtained that the accuracy of the LSTM model is 85.80%, while the accuracy of SVM is 91.07%. But at the same time, LSTM operation only needs 2.57 seconds, SVM model needs 6.06 seconds. Therefore, this paper concludes that: compared with the SVM model, the LSTM model is worse in accuracy but faster in processing speed.

Keywords: sentiment analysis, support vector machine, long short-term memory, Chinese microblog comments

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Authors: Benny Sand, Yotam Lurie, Shlomo Mark

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Medical Internet of Things (MIoT), AI, and data privacy are linked forever in a gordian knot. This paper explores the conflicts of interests between the stakeholders regarding data privacy in the MIoT arena. While patients are at home during healthcare hospitalization, MIoT can play a significant role in improving the health of large parts of the population by providing medical teams with tools for collecting data, monitoring patients’ health parameters, and even enabling remote treatment. While the amount of data handled by MIoT devices grows exponentially, different stakeholders have conflicting understandings and concerns regarding this data. The findings of the research indicate that medical teams are not concerned by the violation of data privacy rights of the patients' in-home healthcare, while patients are more troubled and, in many cases, are unaware that their data is being used without their consent. MIoT technology is in its early phases, and hence a mixed qualitative and quantitative research approach will be used, which will include case studies and questionnaires in order to explore this issue and provide alternative solutions.

Keywords: MIoT, data privacy, stakeholders, home healthcare, information privacy, AI

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Authors: Lakhoua Najeh

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Introduction: In most situations, an industrial system already existing, conditioned by its history, its culture and its context are in difficulty facing the necessity to restructure itself in an organizational and technological environment in perpetual evolution. This is why all operations of restructuring first of all require a diagnosis based on a functional analysis. After a presentation of the functionality of a supervisory system for complex processes, we present the concepts of industrial automation and supervisory control and data acquisition (SCADA). Methods: This global analysis exploits the various available documents on the one hand and takes on the other hand in consideration the various testimonies through investigations, the interviews or the collective workshops; otherwise, it also takes observations through visits as a basis and even of the specific operations. The exploitation of this diagnosis enables us to elaborate the project of restructuring thereafter. Leaving from the system analysis for the restructuring of industrial systems, and after a technical diagnosis based on visits, an analysis of the various technical documents and management as well as on targeted interviews, a focusing retailing the various levels of analysis has been done according a general methodology. Results: The methodology adopted in order to contribute to the restructuring of industrial systems by its participative and systemic character and leaning on a large consultation a lot of human resources that of the documentary resources, various innovating actions has been proposed. These actions appear in the setting of the TQM gait requiring applicable parameter quantification and a treatment valorising some information. The new management environment will enable us to institute an information and communication system possibility of migration toward an ERP system. Conclusion: Technological advancements in process monitoring, control and industrial automation over the past decades have contributed greatly to improve the productivity of virtually all industrial systems throughout the world. This paper tries to identify the principles characteristics of a process monitoring, control and industrial automation in order to provide tools to help in the decision-making process.

Keywords: automation, supervision, SCADA, TQM

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Authors: Nada Azhar

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As a developing country, The Kingdom of Saudi Arabia (KSA) needs to make the best possible use of its workforce for social and economic reasons. The workforce is diverse, calling for appropriate diversity management (DM). The thesis focuses on the banking sector in KSA. To date, there have been no studies on DM in the banking sector in this country. Many organizations have introduced specific policies and programmes to improve the recruitment, inclusion, promotion, and retention of diverse employees, in addition to the legal requirements existing in many countries. However, Western-centric models of DM may not be applicable, at least not in their entirety, in other regions. The aim of the study is to devise a framework for understanding gender, age and disability DM in the banking sector in KSA in order to enhance DM in this sector. A sample of 24 managers, 2 from each of the 12 banks, was interviewed to obtain their views on DM in the banking sector in KSA. Thematic analysis was used to analyze the data. These themes were used to develop the questionnaire, which was administered to 10 managers in each of the 12 banks. After analysis of these data, and completion of the study, the research will make a theoretical contribution to the knowledge on DM and a practical contribution to the management of diversity in Saudi banks. This paper concerns a work in progress.

Keywords: age, disability, diversity, gender, Kingdom of Saudi Arabia

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Authors: Deepak Singh, Rail Kuliev

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The abstract highlights the critical importance of optimizing data integration and management strategies in the upstream oil and gas industry. With its complex and dynamic nature generating vast volumes of data, efficient data integration and management are essential for informed decision-making, cost reduction, and maximizing operational performance. Challenges such as data silos, heterogeneity, real-time data management, and data quality issues are addressed, prompting the proposal of several strategies. These strategies include implementing a centralized data repository, adopting industry-wide data standards, employing master data management (MDM), utilizing real-time data integration technologies, and ensuring data quality assurance. Training and developing the workforce, “reskilling and upskilling” the employees and establishing robust Data Management training programs play an essential role and integral part in this strategy. The article also emphasizes the significance of data governance and best practices, as well as the role of technological advancements such as big data analytics, cloud computing, Internet of Things (IoT), and artificial intelligence (AI) and machine learning (ML). To illustrate the practicality of these strategies, real-world case studies are presented, showcasing successful implementations that improve operational efficiency and decision-making. In present study, by embracing the proposed optimization strategies, leveraging technological advancements, and adhering to best practices, upstream oil and gas companies can harness the full potential of data-driven decision-making, ultimately achieving increased profitability and a competitive edge in the ever-evolving industry.

Keywords: master data management, IoT, AI&ML, cloud Computing, data optimization

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Authors: Farhad Asadi, Mohammad Javad Mollakazemi, Aref Ghafouri

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Recent research in neural networks science and neuroscience for modeling complex time series data and statistical learning has focused mostly on learning from high input space and signals. Local linear models are a strong choice for modeling local nonlinearity in data series. Locally weighted projection regression is a flexible and powerful algorithm for nonlinear approximation in high dimensional signal spaces. In this paper, different learning scenario of one and two dimensional data series with different distributions are investigated for simulation and further noise is inputted to data distribution for making different disordered distribution in time series data and for evaluation of algorithm in locality prediction of nonlinearity. Then, the performance of this algorithm is simulated and also when the distribution of data is high or when the number of data is less the sensitivity of this approach to data distribution and influence of important parameter of local validity in this algorithm with different data distribution is explained.

Keywords: local nonlinear estimation, LWPR algorithm, online training method, locally weighted projection regression method

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Authors: Chanida Tangjai Benchalak Muangmeesri, Dechrit Maneetham

Abstract:

Collection of marine garbage in the modern world, where technology is vital to existence. Consequently, technology can assist in reducing the duplicate labor in the subject of collecting trash in the water that must be done the same way repeatedly owing to the consequence of suffering an emerging disease or COVID-19. This is due to the rapid advancement of technology. As a result, solid trash and plastic garbage are increasing. Agricultural gardens, canals, ponds, and water basins are all sources of water. Building boat-like instruments for rubbish collection in the water will be done this time. It has two control options, boat control via remote control and boat control via an Internet of Things system. A solar panel with a power output of 40 watts powers the system being able to store so accurate and precise waste collection, allowing for thorough water cleaning. The primary goals are to keep the water's surface clean and assess its quality to support the aquatic ecology.

Keywords: automatic boat, water treatment, cleaning machine, iot

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Authors: Ibrahim Mohammed, Suleiman Taofiq, Muhammad Naziru Yahya

Abstract:

Geoelectrical measurements using Schlumberger Vertical Electrical Sounding (VES) method were carried out in Waziri Umaru Federal Polytechnic, Birnin Kebbi, Nigeria, with the aim of determining the groundwater potential in the area. Twelve (12) Vertical Electric Sounding (VES) data were collected using Terrameter (ABEM SAS 300c) and analyzed using computer software (IPI2win), which gives an automatic interpretation of the apparent resistivity. The results of the interpretation of VES data were used in the characterization of three to five geo-electric layers from which the aquifer units were delineated. Data analysis indicated that water bearing formation exists in the third and fourth layers having resistivity range of 312 to 767 Ωm and 9.51 to 681 Ωm, respectively. The thickness of the formation ranges from 14.7 to 41.8 m, while the depth is from 8.22 to 53.7 m. Based on the result obtained from the interpretation of the data, five (5) VES stations were recommended as the most viable locations for groundwater exploration in the study area. The VES stations include VES A4, A5, A6, B1, and B2. The VES results of the entire area indicated that the water bearing formation occurs at maximum depth of 53.7 m at the time of this survey.

Keywords: aquifer, depth, groundwater, resistivity, Schlumberger

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Authors: Isaac Kayode Ogunlade

Abstract:

Data acquisition (DAQ) is the process by which physical phenomena from the real world are transformed into an electrical signal(s) that are measured and converted into a digital format for processing, analysis, and storage by a computer. The DAQ is designed using PIC18F4550 microcontroller, communicating with Personal Computer (PC) through USB (Universal Serial Bus). The research deployed initial knowledge of data acquisition system and embedded system to develop a weather data acquisition device using LM35 sensor to measure weather parameters and the use of Artificial Intelligence(Artificial Neural Network - ANN)and statistical approach(Autoregressive Integrated Moving Average – ARIMA) to predict precipitation (rainfall). The device is placed by a standard device in the Department of Meteorology, Federal University of Technology, Akure (FUTA) to know the performance evaluation of the device. Both devices (standard and designed) were subjected to 180 days with the same atmospheric condition for data mining (temperature, relative humidity, and pressure). The acquired data is trained in MATLAB R2012b environment using ANN, and ARIMAto predict precipitation (rainfall). Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Correction Square (R2), and Mean Percentage Error (MPE) was deplored as standardize evaluation to know the performance of the models in the prediction of precipitation. The results from the working of the developed device show that the device has an efficiency of 96% and is also compatible with Personal Computer (PC) and laptops. The simulation result for acquired data shows that ANN models precipitation (rainfall) prediction for two months (May and June 2017) revealed a disparity error of 1.59%; while ARIMA is 2.63%, respectively. The device will be useful in research, practical laboratories, and industrial environments.

Keywords: data acquisition system, design device, weather development, predict precipitation and (FUTA) standard device

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