Search results for: evaluation accuracy

Authors: Zi-Ang Li, Mu-Xuan Tao

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During the process of the industrialization of steel structure housing, a composite structural system with separated gravity and lateral resistant systems has been applied in engineering practices, which consists of composite frame with hinged beam-column joints, steel brace and RC shear wall. As an attempt in steel structural system area, seismic performance evaluation of the separated composite structure is important for further application in steel housing. This paper focuses on the seismic performance comparison of the separated composite structural system and traditional steel frame-shear wall system under the same inter-story drift ratio (IDR) provision limit. The same architectural layout of a high-rise building is designed as two different structural systems at the same IDR level, and finite element analysis using pushover method is carried out. Static pushover analysis implies that the separated structural system exhibits different lateral deformation mode and failure mechanism with traditional steel frame-shear wall system. Different indexes are adopted and discussed in seismic performance evaluation, including IDR, safe factor (SF), shear wall damage, etc. The performance under maximum considered earthquake (MCE) demand spectrum shows that the shear wall damage of two structural systems are similar; the separated composite structural system exhibits less plastic hinges; and the SF index value of the separated composite structural system is higher than the steel frame shear wall structural system.

Keywords: finite element analysis, new composite structural system, seismic performance evaluation, static pushover analysis

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Authors: Rosa Figueroa, Christopher Flores

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Text categorization is the problem of assigning a new document to a set of predetermined categories, on the basis of a training set of free-text data that contains documents whose category membership is known. To train a classification model, it is necessary to extract characteristics in the form of tokens that facilitate the learning and classification process. In text categorization, the feature extraction process involves the use of word sequences also known as N-grams. In general, it is expected that documents belonging to the same category share similar features. The Smith-Waterman (SW) algorithm is a dynamic programming algorithm that performs a local sequence alignment in order to determine similar regions between two strings or protein sequences. This work explores the use of SW algorithm as an alternative to feature extraction in text categorization. The dataset used for this purpose, contains 2,610 annotated documents with the classes Obese/Non-Obese. This dataset was represented in a matrix form using the Bag of Word approach. The score selected to represent the occurrence of the tokens in each document was the term frequency-inverse document frequency (TF-IDF). In order to extract features for classification, four experiments were conducted: the first experiment used SW to extract features, the second one used unigrams (single word), the third one used bigrams (two word sequence) and the last experiment used a combination of unigrams and bigrams to extract features for classification. To test the effectiveness of the extracted feature set for the four experiments, a Support Vector Machine (SVM) classifier was tuned using 20% of the dataset. The remaining 80% of the dataset together with 5-Fold Cross Validation were used to evaluate and compare the performance of the four experiments of feature extraction. Results from the tuning process suggest that SW performs better than the N-gram based feature extraction. These results were confirmed by using the remaining 80% of the dataset, where SW performed the best (accuracy = 97.10%, weighted average F-measure = 97.07%). The second best was obtained by the combination of unigrams-bigrams (accuracy = 96.04, weighted average F-measure = 95.97) closely followed by the bigrams (accuracy = 94.56%, weighted average F-measure = 94.46%) and finally unigrams (accuracy = 92.96%, weighted average F-measure = 92.90%).

Keywords: comorbidities, machine learning, obesity, Smith-Waterman algorithm

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Authors: Saad Alkentar, Abdulkareem Assalem

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Recognizing small targets has always posed a significant challenge in image analysis. Over long distances, the image signal-to-noise ratio tends to be low, limiting the amount of useful information available to detection systems. Consequently, visual target recognition becomes an intricate task to tackle. In this study, we introduce a Track Before Detect (TBD) approach that leverages target trajectory information (coordinates) to effectively distinguish between noise and potential targets. By reframing the problem as a multivariate time series classification, we have achieved remarkable results. Specifically, our TBD method achieves an impressive 97% accuracy in separating target signals from noise within a mere half-second time span (consisting of 10 data points). Furthermore, when classifying the identified targets into our predefined categories—airplane, drone, and bird—we achieve an outstanding classification accuracy of 96% over a more extended period of 1.5 seconds (comprising 30 data points).

Keywords: small targets, drones, trajectory information, TBD, multivariate time series

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Authors: Luca Vascelli, Silvia Iacomini, Giada Gueli, Francesca Cavallini, Carlo Cavallini, Federica Berardo

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The study was conducted to evaluate the effect of training on Big 6 + 6 motor skills to promote daily living skills. Precision teaching (PT) suggests that improved speed of the component behaviors can lead to better performance of composite skills. This study assessed the effects of the repeated timed practice of component motor skills on speed and accuracy of composite skills related to daily living skills. An 18 years old adolescent with intellectual disability participated. A pre post probe single-subject design was used. The results suggest that the participant was able to perform the component skills at his individual aims (endurance was assessed). The speed and accuracy of composite skills were increased; stability and retention were also measured for the composite skill after the training.

Keywords: big 6+6, daily living skills, intellectual disability, precision teaching

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Authors: Abdullah Abu-Tineh, Youmen Chaaban

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This study examines the development of a professional development (PD) model for teacher growth and learning that is embedded into the school context. The School based Support Program (SBSP), designed for the Qatari context, targets the practices, knowledge and skills of both school leadership and teachers in an attempt to improve student learning outcomes. Key aspects of the model include the development of learning communities among teachers, strong leadership that supports school improvement activities, and the use of research-based PD to improve teacher practices and student achievement. This paper further presents findings from an evaluation of this PD program. Based on an adaptation of Guskey’s evaluation of PD models, 100 teachers at the participating schools were selected for classroom observations and 40 took part in in-depth interviews to examine changed classroom practices. The impact of the PD program on student learning was also examined. Teachers’ practices and their students’ achievement in English, Arabic, mathematics and science were measured at the beginning and at the end of the intervention.

Keywords: initiative, professional development, school based support Program (SBSP), school reform

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Authors: T. Nishimura, K. Doi, H. Fujimoto, T. Wada

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The Number of people with acquired visual impairments has increased in recent years. In specialized courses at schools for the blind and in Braille lessons offered by social welfare organizations, many people with acquired visual impairments cannot learn to read adequately Braille. One of the reasons is that the common Braille patterns for people visual impairments who already has mature Braille reading skill being difficult to read for Braille reading beginners. In addition, there is the scanty knowledge of Braille book manufacturing companies regarding what Braille patterns would be easy to read for beginners. Therefore, it is required to investigate a suitable Braille patterns would be easy to read for beginners. In order to obtain knowledge regarding suitable Braille patterns for beginners, this study aimed to elucidate the relationship between readability of paper-based Braille and its patterns. This study focused on character spacing, which readily affects Braille reading ability, to determine a suitable character spacing ratio (ratio of character spacing to dot spacing) for beginners. Specifically, considering beginners with acquired visual impairments who are unfamiliar with reading Braille, we quantitatively evaluated the effect of character spacing ratio on Braille readability through an evaluation experiment using sighted subjects with no experience of reading Braille. In this experiment, ten sighted adults took the blindfold were asked to read test piece (three Braille characters). Braille used as test piece was composed of five dots. They were asked to touch the Braille by sliding their forefinger on the test piece immediately after the test examiner gave a signal to start the experiment. Then, they were required to release their forefinger from the test piece when they perceived the Braille characters. Seven conditions depended on character spacing ratio was held (i.e., 1.2, 1.4, 1.5, 1.6, 1.8, 2.0, 2.2 [mm]), and the other four depended on the dot spacing (i.e., 2.0, 2.5, 3.0, 3.5 [mm]). Ten trials were conducted for each conditions. The test pieces are created using by NISE Graphic could print Braille adjusted arbitrary value of character spacing and dot spacing with high accuracy. We adopted the evaluation indices for correct rate, reading time, and subjective readability to investigate how the character spacing ratio affects Braille readability. The results showed that Braille reading beginners could read Braille accurately and quickly, when character spacing ratio is more than 1.8 and dot spacing is more than 3.0 mm. Furthermore, it is difficult to read Braille accurately and quickly for beginners, when both character spacing and dot spacing are small. For this study, suitable character spacing ratio to make reading easy for Braille beginners is revealed.

Keywords: Braille, character spacing, people with visual impairments, readability

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Authors: Pattaka Sa-Ngimnet

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That the University as we have known it is no longer serving the needs of the vast majority of students and potential students has been a topic of much discussion. Institutions of higher education, in this age of global culture, are in a process of metamorphosis. Technology is being used to allow more students, older students, working students and disabled students, who cannot attend conventional classes, to have greater access to higher education through the internet. But change must come about only after much evaluation and experimentation or education will simply become a commodity as, in some cases, it already has. This paper will be concerned with the meaning and methods of change and evaluation as they are applied to institutions of higher education. Organization’s generally have different goals and different approaches in order to be successful. However, the means of reaching those goals requires rational and effective planning. Any plans for successful change in any institution must take into account both effectiveness and efficiency and the differences between them. “Effectiveness” refers to an adequate means of achieving an objective. “Efficiency” refers to the ability to achieve an objective without waste of time or resources (The Free Dictionary). So an effective means may not be efficient and an efficient means may not be effective. The goal is to reach a synthesis of effectiveness and efficiency that will maximize both to the extent each is limited by the other. This focus of this paper then is to determine how an educational institution can become either successful or oppressive depending on the kinds of planning, evaluating and changes that operate by and on the administration. If the plan is concerned only with efficiency, the institution can easily become oppressive and lose sight of its purpose of educating students. If it is overly concentrated on effectiveness, the students may receive a superior education in the short run but the institution will face operating difficulties. In becoming only goal oriented, institutions also face problems. Simply stated, if the institution reaches its goals, the stake holders may become satisfied and fail to change and keep up with the needs of the times. So goals should be seen only as benchmarks in a process of becoming even better in providing quality education. Constant and consistent evaluation is the key to making all these factors come together in a successful process of planning, testing and changing the plans as needed. The focus of the evaluation has to be considered. Evaluations must take into account progress and needs of students, methods and skills of instructors, resources available from the institution and the styles and objectives of administrators. Thus the role of evaluation is pivotal in providing for the maximum of both effective and efficient change in higher education institutions.

Keywords: change, effectiveness, efficiency, education

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Authors: Chung-Yuan Wang, Min Hsu, Bo-Ya Juan, Hsiv Ching Lin, Hsveh Min Lin, Hsiu-Fang Yeh

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The success of Taiwan's National Health Insurance (NHI) system attracts widespread praise from the international society. However, the availability of medical care in a emote area is limited. Without the convenient public transportation system and mature social welfare policy, these people are difficult to regain their health and prevent disability. Preterm children have more risk to get development delay. Preterm children in a remote area have the human right to get rehabilitation resources as those in the city area. Therefore, the aim of this study was to show the importance of development screening to preterm children in a remote area and a tract the government to notice the issue. In Pingtung, children who are suspected development delay would be suggested to take a skillful screening evaluation in our hospital. Those preterm children (within 1-year-old) visited our pediatric clinic would also be referred to take the development evaluation. After the physiatrist’s systemic evaluation, the subjects would be scheduled to take the development evaluation. Gross motor, fine motor, speech comprehension/expression and mental study were included. The evaluation was in-charged by a physical therapist, occupational therapy, speech therapist and pediatric psychologist. The tools were Peabody developmental scale, Bayley Scales of Infant and Toddler Development (Bayley-III) and Wechsler Preschool & Primary Scale of Intelligence-Revised (WPPSI-R). In 2013, 459 children received the service in our hospital. Among these children, fifty-seven were noted with preterm baby history (gestation within 37 weeks). Thirty-six of these preterm children, who had never receive development evaluation, were included in this study. Thirty-six subjects (twenty-six male and ten female) were included. Nineteen subjects were found development delay. Six subjects were found suspected development delay. In gross motor, six subjects were development delay and eight were suspected development delay. In fine motor, five subjects were development delay and three were suspected development delay. In speech, sixteen subjects were development delay and six were suspected development delay. In our study, through the provision of development evaluation service, 72.2% preterm baby were found their development delay or suspected delay. They need further early intervention rehabilitation service. We made their parents realize that when development delay was recognized at the early stage, they are often reversible. No only the patients but also their families were improved their health status. The number of the subjects was limited in our study. Further study might be needed. Compared with 770 physical therapist (PT) and 370 occupational therapy (OT) in Taipei, there are only 108 PT and 54 OT in Pingtung. Further, there are much fewer therapists working on the field of pediatric rehabilitation. Living healthy is a human's right, no matter where does he live. For those development delay children in remote area, particularly preterm children, early detection, and early intervention rehabilitation service could play an important role in decreasing their disability and improving their quality of life. Through this study, we suggest the government to add more national resources on the development evaluation to preterm children in a remote area.

Keywords: development, early intervention, preterm children, rehabilitation

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Authors: Anes Enakoa, Yawei Liang

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Question Answering (QA) system is one of the most important and demanding tasks in the field of Natural Language Processing (NLP). In QA systems, the answer generation task generates a list of candidate answers to the user's question, in which only one answer is correct. Answer selection is one of the main components of the QA, which is concerned with selecting the best answer choice from the candidate answers suggested by the system. However, the selection process can be very challenging especially in Arabic due to its particularities. To address this challenge, an approach is proposed to answer questions with multiple answer choices for Arabic QA systems based on Textual Entailment (TE) recognition. The developed approach employs a Support Vector Machine that considers lexical, semantic and syntactic features in order to recognize the entailment between the generated hypotheses (H) and the text (T). A set of experiments has been conducted for performance evaluation and the overall performance of the proposed method reached an accuracy of 67.5% with C@1 score of 80.46%. The obtained results are promising and demonstrate that the proposed method is effective for TE recognition task.

Keywords: information retrieval, machine learning, natural language processing, question answering, textual entailment

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Authors: Christian Kapuku, Seung-Young Kho

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An accurate representation of the transportation system serving the region is one of the important aspects of transportation modeling. Such representation often requires developing an abstract model of the system elements, which also requires important amount of data, surveys and time. However, in some cases such as in developing countries, data deficiencies, time and budget constraints do not always allow such accurate representation, leaving opportunities to assumptions that may negatively affect the quality of the analysis. With the emergence of Internet open source data especially in the mapping technologies as well as the advances in Geography Information System, opportunities to tackle these issues have raised. Therefore, the objective of this paper is to demonstrate such application through a practical case of the development of the transportation network for the city of Kinshasa. The GIS geo-referencing was used to construct the digitized map of Transportation Analysis Zones using available scanned images. Centroids were then dynamically placed at the center of activities using an activities density map. Next, the road network with its characteristics was built using OpenStreet data and other official road inventory data by intersecting their layers and cleaning up unnecessary links such as residential streets. The accuracy of the final network was then checked, comparing it with satellite images from Google and Bing. For the validation, the final network was exported into Emme3 to check for potential network coding issues. Results show a high accuracy between the built network and satellite images, which can mostly be attributed to the use of open source data.

Keywords: geographic information system (GIS), network construction, transportation database, open source data

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Authors: Farzan Farhangian, Behnam Shakibafar, Bobda Cedric, Rene Jr. Landry

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Among the air navigation technologies, many of them are capable of increasing aviation sustainability as well as accuracy improvement in Alternative Positioning, Navigation, and Timing (APNT), especially avionics Distance Measuring Equipment (DME), Very high-frequency Omni-directional Range (VOR), etc. The integration of these air navigation solutions could make a robust and efficient accuracy in air mobility, air traffic management and autonomous operations. Designing a proper RF front-end, power amplifier and software-defined transponder could pave the way for reaching an optimized avionics navigation solution. In this article, the possibility of reaching an optimum front-end to be used with single low-cost Software-Defined Radio (SDR) has been investigated in order to reach a software-defined DME architecture. Our software-defined approach uses the firmware possibilities to design a real-time software architecture compatible with a Multi Input Multi Output (MIMO) BladeRF to estimate an accurate time delay between a Transmission (Tx) and the reception (Rx) channels using the synchronous scheduled communication. We could design a novel power amplifier for the transmission channel of the DME to pass the minimum transmission power. This article also investigates designing proper pair pulses based on the DO-178B avionics standard. Various guidelines have been tested, and the possibility of passing the certification process for each standard term has been analyzed. Finally, the performance of the DME was tested in the laboratory environment using an IFR6000, which showed that the proposed architecture reached an accuracy of less than 0.23 Nautical mile (Nmi) with 98% probability.

Keywords: avionics, DME, software defined radio, navigation

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Authors: Mehrnaz Alibeikloo, Hadi Khabbaz, Behzad Fatahi

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The spectral random field method is one of the widely used methods to obtain more reliable and accurate results in geotechnical problems involving material variability. Karhunen-Loeve (K-L) expansion method was applied to perform random field discretization of cross-correlated creep parameters. Karhunen-Loeve expansion method is based on eigenfunctions and eigenvalues of covariance function adopting Kernel integral solution. In this paper, the accuracy of Karhunen-Loeve expansion was investigated to predict long-term settlement of soft soils adopting elastic visco-plastic creep model. For this purpose, a parametric study was carried to evaluate the effect of K-L expansion terms and spatial correlation length on the reliability of results. The results indicate that small values of spatial correlation length require more K-L expansion terms. Moreover, by increasing spatial correlation length, the coefficient of variation (COV) of creep settlement increases, confirming more conservative and safer prediction.

Keywords: Karhunen-Loeve expansion, long-term settlement, reliability analysis, spatial correlation length

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Authors: Shi-Yu Xu

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The top three risk factors that have contributed to building collapses during past earthquake events in Taiwan are: "irregular floor plans or elevations," "insufficient columns in single-bay buildings," and the "weak-story problem." Fortunately, these unsound structural characteristics can be directly identified from the floor plans. However, due to the vast number of old buildings, conducting manual inspections to identify these compromised structural features in all existing structures would be time-consuming and prone to human errors. This study aims to develop an algorithm that utilizes artificial intelligence techniques to automatically pinpoint the structural components within a building's floor plans. The obtained spatial information will be utilized to construct a digital structural model of the building. This information, particularly regarding the distribution of columns in the floor plan, can then be used to conduct preliminary seismic assessments of the building. The study employs various image processing and pattern recognition techniques to enhance detection efficiency and accuracy. The study enables a large-scale evaluation of structural vulnerability for numerous old buildings, providing ample time to arrange for structural retrofitting in those buildings that are at risk of significant damage or collapse during earthquakes.

Keywords: structural vulnerability detection, object recognition, seismic capacity assessment, old buildings, artificial intelligence

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Authors: Eugene Y. J. Aw, J. W. Koh, S. H. Chew, K. E. Chua, P. L. Goh, Grace H. B. Foo, M. L. Leong

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This paper presents the evaluation of various soil testing methods such as the four-probe soil electrical resistivity method and cone penetration test (CPT) that can complement a newly developed novel rapid soil classification scheme using computer vision, to improve the accuracy and productivity of on-site classification of excavated soil. In Singapore, excavated soils from the local construction industry are transported to Staging Grounds (SGs) to be reused as fill material for land reclamation. Excavated soils are mainly categorized into two groups (“Good Earth” and “Soft Clay”) based on particle size distribution (PSD) and water content (w) from soil investigation reports and on-site visual survey, such that proper treatment and usage can be exercised. However, this process is time-consuming and labor-intensive. Thus, a rapid classification method is needed at the SGs. Four-probe soil electrical resistivity and CPT were evaluated for their feasibility as suitable additions to the computer vision system to further develop this innovative non-destructive and instantaneous classification method. The computer vision technique comprises soil image acquisition using an industrial-grade camera; image processing and analysis via calculation of Grey Level Co-occurrence Matrix (GLCM) textural parameters; and decision-making using an Artificial Neural Network (ANN). It was found from the previous study that the ANN model coupled with ρ can classify soils into “Good Earth” and “Soft Clay” in less than a minute, with an accuracy of 85% based on selected representative soil images. To further improve the technique, the following three items were targeted to be added onto the computer vision scheme: the apparent electrical resistivity of soil (ρ) measured using a set of four probes arranged in Wenner’s array, the soil strength measured using a modified mini cone penetrometer, and w measured using a set of time-domain reflectometry (TDR) probes. Laboratory proof-of-concept was conducted through a series of seven tests with three types of soils – “Good Earth”, “Soft Clay,” and a mix of the two. Validation was performed against the PSD and w of each soil type obtained from conventional laboratory tests. The results show that ρ, w and CPT measurements can be collectively analyzed to classify soils into “Good Earth” or “Soft Clay” and are feasible as complementing methods to the computer vision system.

Keywords: computer vision technique, cone penetration test, electrical resistivity, rapid and non-destructive, soil classification

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Authors: Sergey Ermolin, Olga Ermolin

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A Deep Convolution Neural Network with Triplet Loss is used to identify duplicate images in real-estate advertisements in the presence of image artifacts such as watermarking, cropping, hue/brightness adjustment, and others. The effects of batch normalization, spatial dropout, and various convergence methodologies on the resulting detection accuracy are discussed. For comparative Return-on-Investment study (per industry request), end-2-end performance is benchmarked on both Nvidia Titan GPUs and Intel’s Xeon CPUs. A new real-estate dataset from San Francisco Bay Area is used for this work. Sufficient duplicate detection accuracy is achieved to supplement other database-grounded methods of duplicate removal. The implemented method is used in a Proof-of-Concept project in the real-estate industry.

Keywords: visual recognition, convolutional neural networks, triplet loss, spatial batch normalization with dropout, duplicate removal, advertisement technologies, performance benchmarking

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Authors: Awad Alhwiti

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The purpose of this study was to investigate attitudes students in Tabuk University towards the study in the deanship of the preparation year according to the study stream (scientific, literature) and gender (male, female).The sample of the study consisted of (219) males, (120) of them are in the scientific stream and (99) from the literature stream. Moreover, (238) females, (172) of them are in the scientific stream and (66) from the literature stream. The researcher developed valid and reliable instrument to measure their attitudes towards the study in the deanship of the preparation year. The scale of the study consisted of a group of paragraphs which take positive numbers from (1) to (13) in the meter, and a group of paragraphs which take negative number from (14) to (34) in the scale. The findings of the study showed that (13) items of the scale had a high degree of evaluation, while two items had an average evaluation degree. Meanwhile, (19) items had a low evaluation degree, and the trends in general where it came from (19) paragraphs negative, and (14) paragraphs positive. As the total means of Tabuk students attitudes towards the study in the deanship of the preparation year was (1.92) with a standard deviation of (0.64) with an average evaluation degree. The findings showed that there were significant statistical difference at the level of (α = 0.05) in the samples’ attitudes towards the study in the preparation year attributed to study stream (scientific, literature) on the favor of the scientific stream. While, there were no significant statistical difference at the level of (α = 0.05) in the samples’ attitudes towards the study in the preparation year attributed to and gender (male, female).

Keywords: students attitudes, preparation year deanship, Tabuk University, education technology

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Authors: Amol M. Jadhav, Sharad S. Chudhari, S. S. Khedkar

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This review presents a through survey of research paper work on the experimental analysis, FEM Analysis & simulation of the metal spinning process. In this literature survey all the papers being taken from Elsevier publication and most of the from journal of material processing technology. In a last two decade or so, metal spinning process gradually used as chip less formation for the production of engineering component in a small to medium batch quantities. The review aims to provide include into the experimentation, FEM analysis of various components, simulation of metal spinning process and act as guide for research working on metal spinning processes. The review of existing work has several gaps in current knowledge of metal spinning processes. The evaluation of experiment is thickness strain, the spinning force, the twisting angle, the surface roughness of the conventional & shear metal spinning process; the evaluation of FEM of metal spinning to path definition with sufficient fine mesh to capture behavior of work piece; The evaluation of feed rate of roller, direction of roller,& type of roller stimulated. The metal spinning process has the more flexible to produce a wider range of product shape & to form more challenge material.

Keywords: metal spinning, FEM analysis, simulation of metal spinning, mechanical engineering

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Authors: Erica Siqueira, Adriana Bin, Rachel Stefanuto

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The paper aims to identify and to discuss the impact and results of ex-ante, mid-term and ex-post evaluation initiatives in Brazilian Social Enterprises from the point of view of the entrepreneurs and investors, highlighting the processes involved in these activities and their aftereffects. The study was conducted using a descriptive methodology, primarily qualitative. A multiple-case study was used, and, for that, semi-structured interviews were conducted with ten entrepreneurs in the (i) social finance, (ii) education, (iii) health, (iv) citizenship and (v) green tech fields, as well as three representatives of various impact investments, which are (i) venture capital, (ii) loan and (iii) equity interest areas. Convenience (non-probabilistic) sampling was adopted to select both businesses and investors, who voluntarily contributed to the research. The evaluation is still incipient in most of the studied business cases. Some stand out by adopting well-known methodologies like Global Impact Investing Report System (GIIRS), but still, have a lot to improve in several aspects. Most of these enterprises use nonexperimental research conducted by their own employees, which is ordinarily not understood as 'golden standard' to some authors in the area. Nevertheless, from the entrepreneur point of view, it is possible to identify that most of them including those routines in some extent in their day-by-day activities, despite the difficulty they have of the business in general. In turn, the investors do not have overall directions to establish evaluation initiatives in respective enterprises; they are funding. There is a mechanism of trust, and this is, usually, enough to prove the impact for all stakeholders. The work concludes that there is a large gap between what the literature states in regard to what should be the best practices in these businesses and what the enterprises really do. The evaluation initiatives must be included in some extension in all enterprises in order to confirm social impact that they realize. Here it is recommended the development and adoption of more flexible evaluation mechanisms that consider the complexity involved in these businesses’ routines. The reflections of the research also suggest important implications for the field of Social Enterprises, whose practices are far from what the theory preaches. It highlights the risk of the legitimacy of these enterprises that identify themselves as 'social impact', sometimes without the proper proof based on causality data. Consequently, this makes the field of social entrepreneurship fragile and susceptible to questioning, weakening the ecosystem as a whole. In this way, the top priorities of these enterprises must be handled together with the results and impact measurement activities. Likewise, it is recommended to perform further investigations that consider the trade-offs between impact versus profit. In addition, research about gender, the entrepreneur motivation to call themselves as Social Enterprises, and the possible unintended consequences from these businesses also should be investigated.

Keywords: evaluation practices, impact, results, social enterprise, social entrepreneurship ecosystem

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Authors: Syazreen N. Shair, Saiful A. Ishak, Aida Y. Yusof, Azizah Murad

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In this paper, we forecast age-specific Malaysian mortality rates and life expectancy at births by gender and ethnic groups including Malay, Chinese and Indian. Two mortality forecasting models are adopted the original Lee-Carter model and its recent modified version, the product ratio coherent model. While the first forecasts the mortality rates for each subpopulation independently, the latter accounts for the relationship between sub-populations. The evaluation of both models is performed using the out-of-sample forecast errors which are mean absolute percentage errors (MAPE) for mortality rates and mean forecast errors (MFE) for life expectancy at births. The best model is then used to perform the long-term forecasts up to the year 2030, the year when Malaysia is expected to become an aged nation. Results suggest that in terms of overall accuracy, the product ratio model performs better than the original Lee-Carter model. The association of lower mortality group (Chinese) in the subpopulation model can improve the forecasts of high mortality groups (Malay and Indian).

Keywords: coherent forecasts, life expectancy at births, Lee-Carter model, product-ratio model, mortality rates

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Authors: Rose Shayeghi, Pejman Hosseinioun

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The Multiple Intelligences theory characterizes human intelligence as a multifaceted entity that exists in all human beings with varying degrees. The most important contribution of this theory to the field of English Language Teaching (ELT) is its role in identifying individual differences and designing more learner-centered programs. The present study aims at investigating the relationship between different elements of multiple intelligence and grammar scores. To this end, 63 female Iranian EFL learner selected from among intermediate students participated in the study. The instruments employed were a Nelson English language test, Michigan Grammar Test, and Teele Inventory for Multiple Intelligences (TIMI). The results of Pearson Product-Moment Correlation revealed a significant positive correlation between grammatical accuracy and linguistic as well as interpersonal intelligence. The results of Stepwise Multiple Regression indicated that linguistic intelligence contributed to the prediction of grammatical accuracy.

Keywords: multiple intelligence, grammar, ELT, EFL, TIMI

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Authors: Degale Desta, Cheng Jian

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The most important factor in identifying a person is their face. Even identical twins have their own distinct faces. As a result, identification and face recognition are needed to tell one person from another. A face recognition system is a verification tool used to establish a person's identity using biometrics. Nowadays, face recognition is a common technique used in a variety of applications, including home security systems, criminal identification, and phone unlock systems. This system is more secure because it only requires a facial image instead of other dependencies like a key or card. Face detection and face identification are the two phases that typically make up a human recognition system.The idea behind designing and creating a face recognition system using deep learning with Azure ML Python's OpenCV is explained in this paper. Face recognition is a task that can be accomplished using deep learning, and given the accuracy of this method, it appears to be a suitable approach. To show how accurate the suggested face recognition system is, experimental results are given in 98.46% accuracy using Fast-RCNN Performance of algorithms under different training conditions.

Keywords: deep learning, face recognition, identification, fast-RCNN

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Authors: Muhammet Baldan, Emel Timuçin

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Molecular solubility prediction plays a crucial role in various fields, such as drug discovery, environmental science, and material science. In this study, we compare the performance of five machine learning algorithms—linear regression, support vector machines (SVM), random forests, gradient boosting machines (GBM), and neural networks—for predicting molecular solubility using the AqSolDB dataset. The dataset consists of 9981 data points with their corresponding solubility values. MACCS keys (166 bits), RDKit properties (20 properties), and structural properties(3) features are extracted for every smile representation in the dataset. A total of 189 features were used for training and testing for every molecule. Each algorithm is trained on a subset of the dataset and evaluated using metrics accuracy scores. Additionally, computational time for training and testing is recorded to assess the efficiency of each algorithm. Our results demonstrate that random forest model outperformed other algorithms in terms of predictive accuracy, achieving an 0.93 accuracy score. Gradient boosting machines and neural networks also exhibit strong performance, closely followed by support vector machines. Linear regression, while simpler in nature, demonstrates competitive performance but with slightly higher errors compared to ensemble methods. Overall, this study provides valuable insights into the performance of machine learning algorithms for molecular solubility prediction, highlighting the importance of algorithm selection in achieving accurate and efficient predictions in practical applications.

Keywords: random forest, machine learning, comparison, feature extraction

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Authors: N. Adjlane, N. Haddad

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The American foulbrood is one of the most serious diseases that may affect brood of larvae and pupae stages. The causative organism is a gram positive bacterium Paaenibacillus larvae. American foulbrood infected apiaries suffer from severe economic losses, resulting from significant decreases in honeybee populations and honey production. The aim of this study was to detect Paenibacillus larvae in the remains collected at the bottom of the hive from the suspected hives by direct PCR and culture growth. A total of 56 suspected beehive wax debris samples collected in 40 different apiaries located in the central region of Algeria. MYPGP the culture medium is used during all the identifications of the bacterium. After positive results on samples, biochemical confirmation tests (test of catalase, presence hydrolysis of casein) and microscopic (gram stain) are used in order to verify the accuracy of the initial results. The QIAamp DNA Mini Kit is used to identify the DNA of Paaenibacillus larvae. Paaenibacillus larvae were identified in 14 samples out of 16 by the PCR. A suspected culture-negative sample was found positive through evaluation with PCR. This research is for the bacterium Paaenibacillus larvae in the debris of the colony is an effective method for diagnosis of the pathology of American foulbrood.

Keywords: Paenibacillus larvae, honeybee, PCR, microbiological method

Procedia PDF Downloads 397

Authors: Kai-Chieh Lin, Chih-Fu Wu, Hsiang Ling Hsu, Yung-Hsiang Tu, Chia-Chen Wu

Abstract:

With the rapid development of computer technology, the design of computers and keyboards moves towards a trend of slimness. The change of mobile input devices directly influences users’ behavior. Although multi-touch applications allow entering texts through a virtual keyboard, the performance, feedback, and comfortableness of the technology is inferior to traditional keyboard, and while manufacturers launch mobile touch keyboards and projection keyboards, the performance has not been satisfying. Therefore, this study discussed the design factors of slim pressure-sensitive keyboards. The factors were evaluated with an objective (accuracy and speed) and a subjective evaluation (operability, recognition, feedback, and difficulty) depending on the shape (circle, rectangle, and L-shaped), thickness (flat, 3mm, and 6mm), and force (35±10g, 60±10g, and 85±10g) of the keyboard. Moreover, MANOVA and Taguchi methods (regarding signal-to-noise ratios) were conducted to find the optimal level of each design factor. The research participants, by their typing speed (30 words/ minute), were divided in two groups. Considering the multitude of variables and levels, the experiments were implemented using the fractional factorial design. A representative model of the research samples were established for input task testing. The findings of this study showed that participants with low typing speed primarily relied on vision to recognize the keys, and those with high typing speed relied on tactile feedback that was affected by the thickness and force of the keys. In the objective and subjective evaluation, a combination of keyboard design factors that might result in higher performance and satisfaction was identified (L-shaped, 3mm, and 60±10g) as the optimal combination. The learning curve was analyzed to make a comparison with a traditional standard keyboard to investigate the influence of user experience on keyboard operation. The research results indicated the optimal combination provided input performance to inferior to a standard keyboard. The results could serve as a reference for the development of related products in industry and for applying comprehensively to touch devices and input interfaces which are interacted with people.

Keywords: input performance, mobile device, slim keyboard, tactile feedback

Procedia PDF Downloads 291

Authors: Mohamed Wahba

Abstract:

Objective: To build a comparative arm for product (X) in specific gene mutated advanced gastrointestinal cancer using real world evidence to fulfill HTA requirements in drug evaluation. Methods: Data for product (X) were collected from phase II clinical trial while real world data for (Y) and (Z) were collected from US database. Real-world (RW) cohorts were matched to clinical trial base line characteristics using weighting by odds method. Outcomes included progression-free survival (PFS) and overall survival (OS) rates. Study location and participants: Internationally (product X, n=80) and from USA (Product Y and Z, n=73) Results: Two comparisons were made: trial cohort 1 (X) versus real-world cohort 1 (Z), trial cohort 2 (X) versus real-world cohort 2 (Y). For first line, the median OS was 9.7 months (95% CI 8.6- 11.5) and the median PFS was 5.2 months (95% CI 4.7- not reached) for real-world cohort 1. For second line, the median OS was 10.6 months (95% CI 4.7- 27.3) for real-world cohort 2 and the median PFS was 5.0 months (95% CI 2.1- 29.3). For OS analysis, results were statistically significant but not for PFS analysis. Conclusion: This study provided the clinical comparative outcomes needed for HTA evaluation.

Keywords: real world evidence, pharmacoeconomics, HTA agencies, oncology

Procedia PDF Downloads 79

Authors: Yuqing Chen, Ying Xu, Renfa Li

Abstract:

The development of matrix completion theory provides new approaches for data gathering in Wireless Sensor Networks (WSN). The existing matrix completion algorithms for WSN mainly consider how to reduce the sampling number without considering the real-time performance when recovering the data matrix. In order to guarantee the recovery accuracy and reduce the recovery time consumed simultaneously, we propose a new ALM algorithm to recover the weather monitoring data. A lot of experiments have been carried out to investigate the performance of the proposed ALM algorithm by using different parameter settings, different sampling rates and sampling models. In addition, we compare the proposed ALM algorithm with some existing algorithms in the literature. Experimental results show that the ALM algorithm can obtain better overall recovery accuracy with less computing time, which demonstrate that the ALM algorithm is an effective and efficient approach for recovering the real world weather monitoring data in WSN.

Keywords: wireless sensor network, matrix completion, singular value thresholding, augmented Lagrange multiplier

Procedia PDF Downloads 369

Authors: Dua Hişam, Serhat İkizoğlu

Abstract:

Identifying the problem behind balance disorder is one of the most interesting topics in the medical literature. This study has considerably enhanced the development of artificial intelligence (AI) algorithms applying multiple machine learning (ML) models to sensory data on gait collected from humans to classify between normal people and those suffering from Vestibular System (VS) problems. Although AI is widely utilized as a diagnostic tool in medicine, AI models have not been used to perform feature extraction and identify VS disorders through training on raw data. In this study, three machine learning (ML) models, the Random Forest Classifier (RF), Extreme Gradient Boosting (XGB), and K-Nearest Neighbor (KNN), have been trained to detect VS disorder, and the performance comparison of the algorithms has been made using accuracy, recall, precision, and f1-score. With an accuracy of 95.28 %, Random Forest Classifier (RF) was the most accurate model.

Keywords: vestibular disorder, machine learning, random forest classifier, k-nearest neighbor, extreme gradient boosting

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Authors: Cristian P. Topa, Esteban A. Valencia, Victor H. Hidalgo, Marco A. Martinez

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Wind tunnel experiments for aerodynamic profiles display numerous advantages, such as: clean steady laminar flow, controlled environmental conditions, streamlines visualization, and real data acquisition. However, the experiment instrumentation usually is expensive, and hence, each test implies a incremented in design cost. The aim of this work is to select and implement a low-cost static pressure data acquisition system for a NACA 2412 airfoil in an open cycle wind tunnel. This work compares wind tunnel experiment with Computational Fluid Dynamics (CFD) simulation and parametric analysis. The experiment was evaluated at Reynolds of 1.65 e⁵, with increasing angles from -5° to 15°. The comparison between the approaches show good enough accuracy, between the experiment and CFD, additional parametric analysis results differ widely from the other methods, which complies with the lack of accuracy of the lateral approach due its simplicity.

Keywords: wind tunnel, low cost instrumentation, experimental testing, CFD simulation

Procedia PDF Downloads 166

Authors: Ekaterina Leusheva, Valentin Morenov

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Well drilling in hard rocks is coupled with high energy demands which negates the speed of the process and thus reduces overall effectiveness. Aim of this project is to develop the technique of experimental research, which would allow to select optimal washing fluid composition while adding special hardness reducing detergent reagents. Based on the analysis of existing references and conducted experiments, technique dealing with quantitative evaluation of washing fluid weakening influence on drilled rocks was developed, which considers laboratory determination of three mud properties (density, surface tension, specific electrical resistance) and three rock properties (ultimate stress, dynamic strength, micro-hardness). Developed technique can be used in the well drilling technologies and particularly while creating new compositions of drilling muds for increased destruction effectiveness of hard rocks. It can be concluded that given technique introduces coefficient of hard rocks destruction effectiveness that allows quantitative evaluation of different drilling muds on the drilling process to be taken. Correct choice of drilling mud composition with hardness reducing detergent reagents will increase drilling penetration rate and drill meterage per bit.

Keywords: detergent reagents, drilling mud, drilling process stimulation, hard rocks

Procedia PDF Downloads 535

Authors: Zhaohui Tian

Abstract:

China’s growing and deepening engagement in Africa has attracted numerous controversial debates on Chinese-African social-racial relations both in the media and academia. Most research tends to discuss this issue and the tensions involved at the state level, but limited attention has been given to the individual relating processes of those two racial groups from an intercultural politeness evaluation angle. Thus, taking Kenya as a country focus and putting it under recent perspectives on pragmatics and politeness, this study explores the Chinese-Kenyan workplace relating experience in Chinese-owned companies with the aim to offer new insights on Chinese-African social-racial tensions. The original data were collected through 25 interviews from 29 Chinese and Kenyan participants working in different Chinese companies and industries, some of which had been later on converted into 182 short story data in order to better capture the process and content dimensions of their experiences using Spencer &Kádár’s politeness evaluation model. Both interview and story data were analysed in MAXQDA to understand the personal relating process and the criteria they were drawing from when making evaluative judgements of their relations. The result particular draws attention to tensions around goals, rights, and obligations, and social-moral dimensions that had been underrepresented in intercultural and pragmatics literature. The study offers alternative empirical insights into Chinese-Kenyan relations from an intercultural politeness management perspective and the possible mismatches of the evaluative criteria that potentially cause tension in this context.

Keywords: chinese-kenyan, evaluation, relating, workplace

Procedia PDF Downloads 89