Search results for: one side class algorithm

Authors: Hoyeon Park, Yunhwan Keon, Kyoung-Jae Kim

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Location Based Social Network services (LBSNs) is a new term that combines location based service and social network service (SNS). Unlike traditional SNS, LBSNs emphasizes empirical elements in the user's actual physical location. Point-of-Interest (POI) is the most important factor to implement LBSNs recommendation system. POI information is the most popular spot in the area. In this study, we would like to recommend POI to users in a specific area through recommendation system using collaborative filtering. The process is as follows: first, we will use different data sets based on Seoul and New York to find interesting results on human behavior. Secondly, based on the location-based activity information obtained from the personalized LBSNs, we have devised a new rating that defines the user's preference for the area. Finally, we have developed an automated rating algorithm from massive raw data using distributed systems to reduce advertising costs of LBSNs.

Keywords: location-based social network services, point-of-interest, recommender systems, business analytics

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Authors: Merad Boudia Omar Rafik, Feham Mohammed

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Data aggregation in wireless sensor networks (WSNs) provides a great reduction of energy consumption. The limited resources of sensor nodes make the choice of an encryption algorithm very important for providing security for data aggregation. Asymmetric cryptography involves large ciphertexts and heavy computations but solves, on the other hand, the problem of key distribution of symmetric one. The latter provides smaller ciphertexts and speed computations. Also, the recent researches have shown that achieving the end-to-end confidentiality and the end-to-end integrity at the same is a challenging task. In this paper, we propose (SA-SPKC), a novel security protocol which addresses both security services for WSNs, and where only the base station can verify the individual data and identify the malicious node. Our scheme is based on stateful public key encryption (StPKE). The latter combines the best features of both kinds of encryption along with state in order to reduce the computation overhead. Our analysis

Keywords: secure data aggregation, wireless sensor networks, elliptic curve cryptography, homomorphic encryption

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Authors: Amit Kumar Bhandary, Prithviraj Gupta, Siddhartha Mukherjee, Mahua Ghosh Chaudhuri, Rajib Dey

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Chromite ores are primarily used for extraction of chromium, which is an expensive metal. For low grade chromite ores (containing less than 40% Cr₂O₃), the chromium extraction is not usually economically viable. India possesses huge quantities of low grade chromite reserves. This deposit can be utilized after proper physical beneficiation. Magnetic separation techniques may be useful after reduction for the beneficiation of low grade chromite ore. The sample collected from the sukinda mines is characterized by XRD which shows predominant phases like maghemite, chromite, silica, magnesia and alumina. The raw ore is crushed and ground to below 75 micrometer size. The microstructure of the ore shows that the chromite grains surrounded by a silicate matrix and porosity observed the exposed side of the chromite ore. However, this ore may be utilized in refractory applications. Chromite ores contain Cr₂O₃, FeO, Al₂O₃ and other oxides like Fe-Cr, Mg-Cr have a high tendency to form spinel compounds, which usually show high refractoriness. Initially, the low grade chromite ore (containing 34.8% Cr₂O₃) was reduced at 1200 ⁰C for 80 minutes with 30% coke fines by weight, before being subjected to magnetic separation. The reduction by coke leads to conversion of higher state of iron oxides converted to lower state of iron oxides. The pre-reduced samples are then characterized by XRD. The magnetically inert mass was then reacted with 20% MgO by weight at 1450 ⁰C for 2 hours. The resultant product was then tested for various refractoriness parameters like apparent porosity, slag resistance etc. The results were satisfactory, indicating that the resultant spinel compounds are suitable for refractory applications for elevated temperature processes.

Keywords: apparent porosity, beneficiation, low-grade chromite, refractory, spinel compounds, slag resistance

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Authors: Tope Olubodun

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Background: Family planning practices help individuals and couples avoid unwanted pregnancies, regulate intervals between pregnancies, and determine the number of children in the family. Family planning is an effective intervention for promoting maternal health, but its acceptability and utilization are impeded by many factors in Southwest Nigeria. Aim: This study was conducted to assess women’s knowledge and practice of family planning in two rural communities in Ogun State, Southwest Nigeria, and to determine factors associated with the utilization of family planning among these women. Methods: This was a cross-sectional study conducted among 561 women of reproductive age selected by multistage sampling. The data collection was done using interviewer-administered questionnaires. Data obtained were analyzed using IBM SPSS Statistics version 20. Frequencies were generated, and chi-square test was used to explore associations. The level of significance was set at 0.05. Result: The majority of the respondents were aware of family planning 410 (73.1%). The method most commonly known was male condom 348 (62.0%), then pills 276 (49.2%) and injectables 231(41.3%). The commonest sources of information on family planning were health workers 158 (26.8%), outreaches 162 (27.5%) and TV/radio 136 (23.1%). Respondents that had used family planning, however, only constituted forty–five percent. The methods commonly used were injectables 104 (39.2%) and pills 85 (32.1%). Reasons for choosing not to use family planning include the desire for more children 78 (26.3%), because spouse does not support family planning 56 (18.9%), fear of unbearable side effects 44 (14.9%), and poor knowledge of the methods of family planning as well as where the services can be obtained 39 (13.2%). There is a statistically significant association between age, ethnicity, education, occupation, average monthly income, and use of family planning. Conclusion: Campaigns that promote male involvement in family planning, use of family planning for child spacing, and dispelling of fears is recommended to improve the practice of family planning among such a group of women.

Keywords: family planning, rural, knowledge, practice

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Authors: Aniqa Jabeen

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The aim of this study was to evaluate the effectiveness of Tc-99m MIBI (Technetium 99-methoxy-iso-butyl-isonitrile) scintigraphy to differentiate malignancies from benign lesions, which were detected on planar bone scans. Materials and Methods: 59 patients with bone lesions were enrolled in the study. The scintigraphic findings were compared with the clinical, radiological and the histological findings. Each patient initially underwent a three-phase bone scan with Tc-99m MDP (Methylene Diphosphonate) and if evidence of lesion found, the patient then underwent a dynamic and static MIBI scintigraphy after three to four days. The MDP and MIBI scans were evaluated visually and quantitatively. For quantitative analysis count ratios of lesions and contralateral normal side (L/C) were taken by region of interests drawn on scans. The Student T test was applied to assess the significant difference between benign and malignant lesions p-value < 0.05 was considered significant. Result: The MDP scans showed the increase tracer uptake, but there was no significant difference between benign and malignant uptake of the radiotracer. However significant difference (p-value 0.015), in uptake was seen in malignant (L/C = 3.51 ± 1.02) and benign lesion (L/C = 2.50±0.42) on MIBI scan. Three of thirty benign lesions did not show significant MIBI uptake. Seven malignant appeared as false negatives. Specificity of the scan was 86.66%, and its Negative Predictive Value (NPV) was 81.25% whereas the sensitivity of scan was 79.31%. In excluding the axial metastasis from the lesions, the sensitivity of MIBI scan increased to 91.66% and the NPV also increased to 92.85%. Conclusion: MIBI scintigraphy provides its usefulness by distinguishing malignant from benign lesions. MIBI also correctly identifies metastatic lesions. The negative predictive value of the scan points towards its ability to accurately diagnose the normal (benign) cases. However, biopsy remains the gold standard and a definitive diagnostic modality in musculoskeletal tumors. MIBI scan provides useful information in preoperative assessment and in distinguishing between malignant and benign lesions.

Keywords: benign, malignancies, MDP bone scan, MIBI scintigraphy

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Authors: P.Kiruthika, K. Ramani

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This paper presented the design and advancement of a single-phase 27-level Hybrid Multilevel DC-AC Converter interfacing with Photo Voltaic. In this context, the Multicarrier Pulse Width Modulation method can be implemented in 27-level Hybrid Multilevel Inverter for generating a switching pulse. Perturb & Observer algorithm can be used in the Maximum Power Point Tracking method for the Photo Voltaic system. By implementing Maximum Power Point Tracking with three separate solar panels as an input source to the 27-level Hybrid Multilevel Inverter. This proposed method can be simulated by using MATLAB/simulink. The result shown that the proposed method can achieve silky output wave forms, more flexibility in voltage range, and to reduce Total Harmonic Distortion in medium-voltage drives.

Keywords: Multi Carrier Pulse Width Modulation Technique (MCPWM), Multi Level Inverter (MLI), Maximum Power Point Tracking (MPPT), Perturb and Observer (P&O)

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Authors: Kyunghun Kang, Sangwoo Oh, Yongha Hwang

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PDMS (Polydimethylsiloxane)-based microfluidic device has been recently applied to area of biomedical research, tissue engineering, and diagnostics because PDMS is low cost, nontoxic, optically transparent, gas-permeable, and especially biocompatible. Generally, PDMS microfluidic devices are fabricated by conventional soft lithography. Microfabrication requires expensive cleanroom facilities and a lot of time; however, only two-dimensional or simple three-dimensional structures can be fabricated. In this study, we introduce fabricating method for complex three-dimensional microfluidic channels using soluble wax mold. Using the 3D printing technique, we firstly fabricated three-dimensional mold which consists of soluble wax material. The PDMS pre-polymer is cast around, followed by PDMS casting and curing. The three-dimensional casting mold was removed from PDMS by chemically dissolved with methanol and acetone. In this work, two preliminary experiments were carried out. Firstly, the solubility of several waxes was tested using various solvents, such as acetone, methanol, hexane, and IPA. We found the combination between wax and solvent which dissolves the wax. Next, side effects of the solvent were investigated during the curing process of PDMS pre-polymer. While some solvents let PDMS drastically swell, methanol and acetone let PDMS swell only 2% and 6%, respectively. Thus, methanol and acetone can be used to dissolve wax in PDMS without any serious impact. Based on the preliminary tests, three-dimensional PDMS microfluidic channels was fabricated using the mold which was printed out using 3D printer. With the proposed fabricating technique, PDMS-based microfluidic devices have advantages of fast prototyping, low cost, optically transparence, as well as having complex three-dimensional geometry. Acknowledgements: This research was supported by Supported by a Korea University Grant and Basic Science Research Program through the National Research Foundation of Korea(NRF).

Keywords: microfluidic channel, polydimethylsiloxane, 3D printing, casting

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Authors: Mubassir Hussain

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British Bangladeshis are one of the most marginalised and lowest socioeconomic groups in the UK. Their silent hardships have crystallised the stigma surrounding them. Understanding the intimate workings of this stigma can unravel its profound psychological impact, which has hindered their social and economic progress and slowly taken them out of the ‘victim’ mindset. Although community-based studies have been conducted to understand the nuances of British Bangladeshis’ stigma experiences, these examinations are broad and touch only the surface. They do not investigate the private family dynamics behind closed doors, how family members feel and engage with stigma or the use and justification of their responses. The main objectives of this qualitative research are to observe how attitudes towards stigma differ across generations, analyse the variety and frequency of reactions across age cohorts, gender, and social class, and examine how their actions and identities shape their responses. This data will be collected through embedded ethnography and analysed using qualitative software. Through this analysis, the research hypothesises that the older generation will engage more in the ‘isolation’, ‘not responding’, and ‘management of the self’ response categories, whereas the subsequent generations will employ ‘confrontation’, ‘demonstrating competence’, and ‘management of the self’ reactions. From these findings, the study anticipates an assortment of compelling and diverse responses and effects. Ultimately, the family members and community are responsible for their own futures and have the power to make these life-altering changes. Their collective experiences and values shape how individuals perceive and respond to stigma, racism, Islamophobia and discrimination through either silence, resilience or confrontation.

Keywords: British Bangladeshi, stigma, racism, discrimination, Islamophobia, responses

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Authors: Saba Gachpaz, Hamid Reza Heidari

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The sharp increase in population growth leads to more pressure on agricultural areas to satisfy the food supply. To achieve this, more resources should be consumed and, besides other environmental concerns, highlight sustainable agricultural development. Land-use management is a crucial factor in obtaining optimum productivity. Machine learning is a widely used technique in the agricultural sector, from yield prediction to customer behavior. This method focuses on learning and provides patterns and correlations from our data set. In this study, nine physical control factors, namely, soil classification, electrical conductivity, normalized difference water index (NDWI), groundwater level, elevation, annual precipitation, pH of water, annual mean temperature, and slope in the alluvial plain in Khuzestan (an agricultural hotspot in Iran) are used to decide the best agricultural land use for both rainfed and irrigated agriculture for ten different crops. For this purpose, each variable was imported into Arc GIS, and a raster layer was obtained. In the next level, by using training samples, all layers were imported into the python environment. A random forest model was applied, and the weight of each variable was specified. In the final step, results were visualized using a digital elevation model, and the importance of all factors for each one of the crops was obtained. Our results show that despite 62% of the study area being allocated to agricultural purposes, only 42.9% of these areas can be defined as a suitable class for cultivation purposes.

Keywords: land suitability, machine learning, random forest, sustainable agriculture

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Authors: M. Cabuk, M. Yavuz, T. A. Yesil, H. I. Unal

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Electrorheological (ER) fluids are a class of smart materials exhibiting reversible changes in their rheological and mechanical properties under an applied electric field (E). ER fluids generally are composed of polarisable solid particles dispersed in non-conducting oil. ER fluids are fluids which exhibit. The resistance to motion of the ER fluid can be controlled by adjusting the applied E, due to their fast and reversible changes in their rheological properties presence of E. In this study, a series of chitosan/expanded perlite (CS/EP) composites with different chitosan mass fractions (10%, 20%, and 50%) was used. Characterizations of the composites were carried out by Fourier Transform Infrared (FTIR), X-ray diffraction (XRD) and Scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM-EDX) techniques. Antisedimentation stability and dielectric properties of the composites were also determined. The effects of volume fraction, electric field strength, shear rate, shear stress, and temperature onto ER properties of the CS/EP composite particles dispersed in silicone oil (SO) were investigated in detail. Vibration damping behavior of the CS/EP composites were determined as a function of frequence, storage (Gʹ) and loss (Gʹ ʹ) moduli. It was observed that ER response of the CS/EP/SO ER fluids increased with increasing electric field strength and exhibited the typical shear thinning non-Newtonian viscoelastic behaviors with increasing shear rate. The maximum yield stress was obtained with 1250 Pa under E = 3 kV/mm. Further, the CS/EP/SO ER fluids were observed to sensitive to vibration control by showing reversible viscosity enhancements (Gʹ > Gʹ ʹ). Acknowledgements: The authors thank the TÜBİTAK (214Z199) for the financial support of this work.

Keywords: chitosan, electrorheology, perlite, vibration control

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Authors: Piyangkun Kukutapan, Siridech Boonsang

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The article proposes maximum power point tracking without mechanical sensor using Multilayer Perceptron Neural Network (MLPNN). The aim of article is to reduce the cost and complexity but still retain efficiency. The experimental is that duty cycle is generated maximum power, if it has suitable qualification. The measured data from DC generator, voltage (V), current (I), power (P), turnover rate of power (dP), and turnover rate of voltage (dV) are used as input for MLPNN model. The output of this model is duty cycle for driving the converter. The experiment implemented using Arduino Uno board. This diagram is compared to MPPT using MLPNN and P&O control (Perturbation and Observation control). The experimental results show that the proposed MLPNN based approach is more efficiency than P&O algorithm for this application.

Keywords: maximum power point tracking, multilayer perceptron netural network, optimal duty cycle, DC generator

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Authors: Derick M. Rakgoale, Topside E. Mathonsi, Vusumuzi Malele

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Cloud computing offers distributed online and on-demand computational services from anywhere in the world. Cloud computing services have grown immensely over the past years, especially in the past year due to the Coronavirus pandemic. Cloud computing has changed the working environment and introduced work from work phenomenon, which enabled the adoption of technologies to fulfill the new workings, including cloud services offerings. The increased cloud computing adoption has come with new challenges regarding data privacy and its integrity in the cloud environment. Previously advanced encryption algorithms failed to reduce the memory space required for cloud computing performance, thus increasing the computational cost. This paper reviews the existing encryption algorithms used in cloud computing. In the future, artificial neural networks (ANN) algorithm design will be presented as a security solution to ensure data integrity, confidentiality, privacy, and availability of user data in cloud computing. Moreover, MATLAB will be used to evaluate the proposed solution, and simulation results will be presented.

Keywords: cloud computing, data integrity, confidentiality, privacy, availability

Procedia PDF Downloads 135

Authors: B. J. Mahen, N. E. Lloyd-Gale, S. Johnson, W. P. Rakowicz, M. J. Harris, A. D. Miller

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Background: Migraine is a leading cause of disability in the world. Calcitonin gene-related peptide (CGRP) receptor antagonists offer an approach to migraine prophylaxis by inhibiting the inflammatory and vasodilatory effects of CGRP. In recent years, NICE licensed the use of three CGRP-receptor antagonists: Fremanezumab, Galcanezumab, and Erenumab. Here, we present the outcomes of CGRP-antagonist treatment in a cohort of patients who suffer from episodic or chronic migraine and have failed at least three oral prophylactic therapies. Methods: We offered CGRP antagonists to 86 patients who met the NICE criteria to start therapy. We recorded the number of headache days per month (HDPM) at 0 weeks, 3 months, and 12 months. Of those, 26 patients were switched to an alternative treatment due to poor response or side effects. Of the 112 total cases, 9 cases did not sufficiently maintain their headache diary, and 5 cases were not followed up at 3 months. We have therefore included 98 sets of data in our analysis. Results: Fremanezumab achieved a reduction in HDPM by 51.7% at 3 months (p<0.0001), with 63.7% of patients meeting NICE criteria to continue therapy. Patients trialed on Galcanezumab attained a reduction in HDPM by 47.0% (p=0.0019), with 51.6% of patients meeting NICE criteria to continue therapy. Erenumab, however, only achieved a reduction in HDPM by 17.0% (p=0.29), and this was not statistically significant. Furthermore, 34.4%, 9.7%, and 4.9% of patients taking Fremanezumab, Galcanezumab, and Erenumab, respectively, continued therapy beyond 12 months. Of those who attempted drug holidays following 12 months of treatment, migraine symptoms relapsed in 100% of cases. Conclusion: We observed a significant improvement in HDPM amongst episodic and chronic migraine patients following treatment with Fremanezumab or Galcanezumab.

Keywords: migraine, CGRP, fremanezumab, galcanezumab, erenumab

Procedia PDF Downloads 95

Authors: M. Assaad, J. Mäkiö, T. Mäkelä, M. Kankaanranta, N. Fachantidis, V. Dagdilelis, A. Reid, C. R. del Rio, E. V. Pavlysh, S. V. Piashkun

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To bring science and society together in Europe, thus increasing the continent’s international competitiveness, STEM (science, technology, engineering and mathematics) education must be more relatable to European youths in their everyday life. STIMEY (Science, Technology, Innovation, Mathematics, Engineering for the Young) project researches and develops a hybrid educational environment with multi-level components that is being designed and developed based on a well-researched pedagogical framework, aiming to make STEM education more attractive to young people aged 10 to 18 years in this digital era. This environment combines social media components, robotic artefacts, and radio to educate, engage and increase students’ interest in STEM education and careers from a young age. Additionally, it offers educators the necessary modern tools to deliver STEM education in an attractive and engaging manner in or out of class. Moreover, it enables parents to keep track of their children’s education, and collaborate with their teachers on their development. Finally, the open platform allows businesses to invest in the growth of the youths’ talents and skills in line with the economic and labour market needs through entrepreneurial tools. Thus, universities, schools, teachers, students, parents, and businesses come together to complete a circle in which STEM becomes part of the daily life of youths through a hybrid educational environment that also prepares them for future careers.

Keywords: e-learning, entrepreneurship, pedagogy, robotics, serious gaming, social media, STEM education

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Authors: Shravani Itkelwar, Deepak Tewari, Bhaskar Natarajan

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The energy consumption data plays a vital role in energy efficiency policy design, implementation, and impact assessment. Any demand-side energy management intervention's success relies on the availability of accurate, comprehensive, granular, and up-to-date data on energy consumption. The Building sector, including residential and commercial, is one of the largest consumers of energy in India after the Industrial sector. With economic growth and increasing urbanization, the building sector is projected to grow at an unprecedented rate, resulting in a 5.6 times escalation in energy consumption till 2047 compared to 2017. Therefore, energy efficiency interventions will play a vital role in decoupling the floor area growth and associated energy demand, thereby increasing the need for robust data. In India, multiple institutions are involved in the collection and dissemination of data. This paper focuses on energy consumption data management in the building sector in India for both residential and commercial segments. It evaluates the robustness of data available through administrative and survey routes to estimate the key performance indicators and identify critical data gaps for making informed decisions. The paper explores several issues in the data, such as lack of comprehensiveness, non-availability of disaggregated data, the discrepancy in different data sources, inconsistent building categorization, and others. The identified data gaps are justified with appropriate examples. Moreover, the paper prioritizes required data in order of relevance to policymaking and groups it into "available," "easy to get," and "hard to get" categories. The paper concludes with recommendations to address the data gaps by leveraging digital initiatives, strengthening institutional capacity, institutionalizing exclusive building energy surveys, and standardization of building categorization, among others, to strengthen the management of building sector energy consumption data.

Keywords: energy data, energy policy, energy efficiency, buildings

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Authors: Mariana Paz Sajon, Paula Cecilia Primogerio, Mariana Albarracin

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This study recovers an experience of teacher training carried out in an Undergraduate Business School from a private university in Buenos Aires, Argentina. The purpose of the project was to provide teachers with an opportunity to reflect on their teaching practices at the university. The aim of the study is to systematize lessons and challenges that emerge from this teacher training experience. A group of teachers who showed a willingness to learn teaching abilities was selected to work. They completed a formative journey working in learning communities starting from the immersion in different aspects of teaching and learning, class observations, and an individual and collaborative reflection exercise in a systematic way among colleagues. In this study, the productions of the eight teachers who are members of the learning communities are analyzed, framed in an e-portfolio that they prepared during the training journey. The analysis shows that after the process of shared reflection, traits related to powerful teaching and meaningful learning have appeared in the classes. For their part, teachers reflect having reached an awareness of their own practices, identifying strengths and opportunities for improvement, and the experience of sharing their own way and knowing the successes and failures of others was valued. It is an educational journey of pedagogical transformation of the teachers, which is infrequent in business education, which could lead to a change in teaching practices for the entire Business School. The present study involves theoretical and pedagogic aspects of education in a business school in Argentina and its flow-on implications for the workplace that may be transferred to other educational contexts.

Keywords: Argentina, learning community, meaningful learning, powerful teaching, reflective practice

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Authors: Jie Zhang, Qianyu Guo, Tieyi Zhang, Zhiyong Feng, Xiaohong Li

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With the widespread popularity of mobile devices and the development of artificial intelligence (AI), deep learning (DL) has been extensively applied in Android apps. Compared with traditional Android apps (traditional apps), deep learning based Android apps (DL-based apps) need to use more third-party application programming interfaces (APIs) to complete complex DL inference tasks. However, existing methods (e.g., FlowDroid) for detecting sensitive information leakage in Android apps cannot be directly used to detect DL-based apps as they are difficult to detect third-party APIs. To solve this problem, we design DLtrace; a new static information flow analysis tool that can effectively recognize third-party APIs. With our proposed trace and detection algorithms, DLtrace can also efficiently detect privacy leaks caused by sensitive APIs in DL-based apps. Moreover, using DLtrace, we summarize the non-sequential characteristics of DL inference tasks in DL-based apps and the specific functionalities provided by DL models for such apps. We propose two formal definitions to deal with the common polymorphism and anonymous inner-class problems in the Android static analyzer. We conducted an empirical assessment with DLtrace on 208 popular DL-based apps in the wild and found that 26.0% of the apps suffered from sensitive information leakage. Furthermore, DLtrace has a more robust performance than FlowDroid in detecting and identifying third-party APIs. The experimental results demonstrate that DLtrace expands FlowDroid in understanding DL-based apps and detecting security issues therein.

Keywords: mobile computing, deep learning apps, sensitive information, static analysis

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Authors: Anujendra, Parag Kumar Guha Thakurta

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The data transmission between mobile hosts and base stations (BSs) in Mobile networks are often vulnerable to failure. Thus, efficient link connectivity, in terms of the services of both base stations and communication channels of the network, is required in wireless mobile networks to achieve highly reliable data transmission. In addition, it is observed that the number of blocked hosts is increased due to insufficient number of channels during heavy load in the network. Under such scenario, the channels are allocated accordingly to offer a reliable communication at any given time. Therefore, a reliability-based channel allocation model with acceptable system performance is proposed as a MOO problem in this paper. Two conflicting parameters known as Resource Reuse factor (RRF) and the number of blocked calls are optimized under reliability constraint in this problem. The solution to such MOO problem is obtained through NSGA-II (Non-dominated Sorting Genetic Algorithm). The effectiveness of the proposed model in this work is shown with a set of experimental results.

Keywords: base station, channel, GA, pareto-optimal, reliability

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Authors: Sepehr Moradi

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This study investigates the contribution of individual Australian Superfine Merino Wool (ASFW) and Inner Mongolia Cashmere (IMC) fibres strength behaviour to the breaking force variation (CVBF) and minimum fibre diameter (CVₘFD) induced by actual single fibre lengths and the combination of length and diameter groups. Mid-side samples were selected for the ASFW (n = 919) and IMC (n = 691) since it is assumed to represent the average of the whole fleece. The average (LₘFD) varied for ASFW and IMC by 36.6 % and 33.3 % from shortest to longest actual single fibre length and -21.2 % and -21.7 % between longest-coarsest and shortest-finest groups, respectively. The tensile properties of single animal fibres were characterised using Single Fibre Analyser (SIFAN 4). After normalising for diversity in fibre diameter at the position of breakage, the parameters, which explain the strength behaviour within actual fibre lengths and combination of length-diameter groups, were the Intrinsic Fibre Strength (IFS) (MPa), Min IFS (MPa), Max IFS (MPa) and Breaking force (BF) (cN). The average strength of single fibres varied extensively within actual length groups and within a combination of length-diameter groups. IFS ranged for ASFW and IMC from 419 to 355 MPa (-15.2 % range) and 353 to 319 (-9.6 % range) and BF from 2.2 to 3.6 (63.6 % range) and 3.2 to 5.3 cN (65.6 % range) from shortest to longest groups, respectively. Single fibre properties showed no differences within actual length groups and within a combination of length-diameter groups, or was there a strong interaction between the strength of single fibre (P > 0.05) within remaining and removing length-diameter groups. Longer-coarser fibre fractionation had a significant effect on BF and IFS and all of the length groups showed a considerable variance in single fibre strength that is accounted for by diversity in the diameter variation along the fibre. There are many concepts for the improvement of the stress-strain properties of animal fibres as a means of raising a single fibre strength by simultaneous changes in fibre length and diameter. Fibre fractionation over a given length directly for single fibre strength or using the variation traits of fibre diameter is an important process used to increase the strength of the single fibre.

Keywords: single animal fibre fractionation, actual length groups, strength variation, length-diameter groups, diameter variation along fibre

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Authors: J. F. Pollo Gaspary, F. Peron Gaspary, E. M. Simão, R. Concatto Beltrame, G. Orengo de Oliveira, M. S. Ristow Ferreira, F. Sartori Thies, I. F. Minello, F. dos Santos de Oliveira

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Background: The immune system has evolved several mechanisms to protect the host against cancer, and it has now been suggested that the expansion of its functions may prevent tumor growth and control the symptoms of cancer patients. Two techniques, ozone therapy and pulsed electromagnetic fields (PEMF), are independently associated with an increase in the immune system functions and they maybe help palliative care of patients in these conditions. Case Report: A patient with rectal adenocarcinoma with metastases decides to interrupt the clinical chemotherapy protocol due to refractoriness and side effects. As a palliative care alternative treatment it is suggested to the patient the use of ozone therapy associated with PEMF techniques. Results: The patient reports an improvement in well-being, in autonomy and in pain control. Imaging tests confirm a pause in tumor growth despite more than 60 days without using classic treatment. These results associated with palliative care alternative treatment stimulate the return to the chemotherapy protocol. Discussion: This case illustrates that these two techniques can contribute to the control of tumor growth and refractory symptoms, such as pain, probably by enhancing the immune system. Conclusions: The potential use of the combination of these two therapies, ozone therapy and PEMF therapy, can contribute to palliation of cancer patients, alone or in combination with pharmacological therapies. The conduct of future investigations on this paradigm can elucidate how much these techniques contribute to the survival and well-being of these patients.

Keywords: cancer, complementary and alternative medicine , ozone therapy, palliative care, PEMF therapy

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Authors: Adrian Kong, William Chang, Rolando Valdes, Alec Rodriguez, Roberto Miki

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The Pneumask consists of a custom snorkel-specific adapter that attaches a snorkel-port of the mask to a 3D-printed filter. This full-face snorkel mask was designed for use as personal protective equipment (PPE) during the COVID-19 pandemic when there was a widespread shortage of PPE for medical personnel. Various clinical validation tests have been conducted, including the sealing capability of the mask, filter performance, CO2 buildup, and clinical usability. However, data regarding the filter efficiencies of Pneumask and multiple filter types have not been determined. Using an experimental system, we evaluated the filtration efficiency across various masks and filters during inhalation. Eighteen combinations of respirator models (5 P100 FFRs, 4 Dolfino Masks) and filters (2091, 7093, 7093CN, BB50T) were evaluated for their exposure to airborne particles sized 0.3 - 10.0 microns using an electronic airborne particle counter. All respirator model combinations provided similar performance levels for 1.0-micron, 3.0-micron, 5.0-micron, 10.0-microns, with the greatest differences in the 0.3-micron and 0.5-micron range. All models provided expected performances against all particle sizes, with Class P100 respirators providing the highest performance levels across all particle size ranges. In conclusion, the modified snorkel mask has the potential to protect providers who care for patients with COVID-19 from increased airborne particle exposure.

Keywords: COVID-19, PPE, mask, filtration, efficiency

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Authors: Triano Nurhikmat

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

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

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Authors: Αlexios Kotsakis, Stefanos Katsavounis, Dimitra Alexiou

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Networks can be utilized to represent project planning problems, using nodes for activities and arcs to indicate precedence relationship between them. For fixed activity duration, a simple algorithm calculates the amount of time required to complete a project, followed by the activities that comprise the critical path. Program Evaluation and Review Technique (PERT) generalizes the above model by incorporating uncertainty, allowing activity durations to be random variables, producing nevertheless a relatively crude solution in planning problems. In this paper, based on the findings of the relevant literature, which strongly suggests that a Beta distribution can be employed to model earthmoving activities, we utilize Monte Carlo simulation, to estimate the project completion time distribution and measure the influence of skewness, an element inherent in activities of modern technical projects. We also extract the activity criticality index, with an ultimate goal to produce more accurate planning estimations.

Keywords: beta distribution, PERT, Monte Carlo simulation, skewness, project completion time distribution

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Authors: Ullah Aman

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The practice of giving dowry was meant to assist a newly-wed couple to start their life together with ease; however, now it has turned into a commercial transaction in which monetary considerations receive priority over the personal merits of the bride. The present study was designed to explore the causes and consequences of dowry system and to measure the association between dowry and women prestige in district Swabi. A sample size of 378 household (female) Respondents was randomly selected through proportional allocation method. The data was interpreted into frequency and percentages while to measure the relationship between Dowry system and Women Prestige, Chi-Square statistic was applied. Result indicated that majority of the 316(83.6%) respondents stated that Family members are in favor of high dowry because high dowry is today’s women need which is disclosed by 302(79.9%) of the sample size. In addition to this, most 320(84.7%) of the respondents has opined that low dowry leads to broken families in the society. Moreover, a strong association (p=0.000) was determined between high dowry and women prestige. Similarly, a strong significant relation was found (p=0.000) between women prestige and low dowry mortifying women prestige in our society. The study concluded that dowry, deeply rooted in the society is an immorality which must be strictly banned in the country. It is a herculean task to completely eliminate dowry system from the nation but slowly and gradually efforts are being made in this direction. Dowry is a sure cause of promoting intense conflicts between the families, quarrels and inculcates greed in the society. Government and the builders of the social fabric should strictly work on it, banning this system for each and every class in Pakistan. Moreover, for curbing this mal practice we must put effort to bring social awareness to the society are some of the recommendation.

Keywords: Dowry, women, prestige, causes,

Procedia PDF Downloads 153

Authors: Haodong Huang, Zida Zhao, Shilong Sun, Chiyao Li, Wenfu Xu

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The control methods for legged robots based on deep reinforcement learning have seen widespread application; however, the inherent black-box nature of neural networks presents challenges in understanding the decision-making motives of the robots. To address this issue, we propose a fully interpretable deep reinforcement learning training method to elucidate the underlying principles of legged robot motion. We incorporate the dynamics of legged robots into the policy, where observations serve as inputs and actions as outputs of the dynamics model. By embedding the dynamics equations within the multi-layer perceptron (MLP) computation process and making the parameters trainable, we enhance interpretability. Additionally, Bayesian optimization is introduced to train these parameters. We validate the proposed fully interpretable motion control algorithm on a legged robot, opening new research avenues for motion control and learning algorithms for legged robots within the deep learning framework.

Keywords: deep reinforcement learning, interpretation, motion control, legged robots

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Authors: Nasiruddin Khan

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The increased use of caffeinated beverages and energy drink is posing threat to all ages and gender especially, younger adults. There is a lack of scientific evidence in Oman regarding caffeine and energy drink consumption. Our study aims to demonstrate the prevalence, pattern, knowledge and awareness, and side effects of caffeine intake among university students. This cross-sectional study including (N=365) apparently healthy male and female Omani university students aged 18-30 years, was carried out from February 2018-June 2018. A self-administered questionnaire with various sections was used to obtain information. The prevalence of caffeinated beverage consumption was commonly high among participants (97%). The males preferred Nescafe, coffee (both p < 0.001), espresso (p < 0.022), and soda (p < 0.008) while females consumed more tea (p < 0.029). The awareness about negative health impact of caffeine intake was significantly higher in females rather than males (p < 0.002). The overall prevalence of energy drink consumption was 42.1% (n=149), and higher in males (75%, p < 0.001). More males consumed 3-5 and > 5 cans/day while females used 1-2 cans/day. The starting age of energy drink use was higher in females (16-20 years (51.1%)) as compared to males (11-15 years (33.3%)). Females were more aware of caffeine as energy drink ingredient (p < 0.036) than males. The major source of information about enery drink was family and friends (58.3%). Red Bull was the commonly used brand (55.5%) among participants. Common reasons for high energy drink consumption were energy boost (68.4 %), taste (62.9%), reduce fatigue (52.1%), and better performance (47.3%). Females reported breathing problem, and abnormal heart beat (p < 0.004, 0.054, respectively), while more males reported irritability than females (p < 0.052). The prevalence of caffeinated beverage and energy drink consumption is high among participants. The awareness, and knowledge among university student is not satisfactory and needs immediate action to avoid excess use of such consumption.

Keywords: energy drink, caffeinated beverages, awareness, Oman

Procedia PDF Downloads 131

Authors: A. Ikhlef

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

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

Procedia PDF Downloads 127

Authors: J. Chamorro-Servent, S. Tassani, M. A. Gonzalez-Ballester, L. J. Roca, J. Romeu, O. Camara

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Electromagnetic and microwave imaging (MWI) have been used in medical imaging in the last years, being the most common applications of breast cancer and stroke detection or monitoring. In those applications, the subject or zone to observe is surrounded by a number of antennas, and the Nyquist criterium can be satisfied. Additionally, the space between the antennas (transmitting and receiving the electromagnetic fields) and the zone to study can be prepared in a homogeneous scenario. However, this may differ in other cases as could be intracardiac catheters, stomach monitoring devices, pelvic organ systems, liver ablation monitoring devices, or uterine fibroids’ ablation systems. In this work, we analyzed different MWI algorithms to find the most suitable method for dealing with an intrabody scenario. Due to the space limitations usually confronted on those applications, the device would have a cylindrical configuration of a maximum of eight transmitters and eight receiver antennas. This together with the positioning of the supposed device inside a body tract impose additional constraints in order to choose a reconstruction method; for instance, it inhabitants the use of well-known algorithms such as filtered backpropagation for diffraction tomography (due to the unusual configuration with probes enclosed by the imaging region). Finally, the difficulty of simulating a realistic non-homogeneous background inside the body (due to the incomplete knowledge of the dielectric properties of other tissues between the antennas’ position and the zone to observe), also prevents the use of Born and Rytov algorithms due to their limitations with a heterogeneous background. Instead, we decided to use a time-reversed algorithm (mostly used in geophysics) due to its characteristics of ignoring heterogeneities in the background medium, and of focusing its generated field onto the scatters. Therefore, a 2D time-reversed finite difference time domain was developed based on the time-reversed approach for microwave breast cancer detection. Simultaneously an in-silico testbed was also developed to compare ground-truth dielectric properties with corresponding microwave imaging reconstruction. Forward and inverse problems were computed varying: the frequency used related to a small zone to observe (7, 7.5 and 8 GHz); a small polyp diameter (5, 7 and 10 mm); two polyp positions with respect to the closest antenna (aligned or disaligned); and the (transmitters-to-receivers) antenna combination used for the reconstruction (1-1, 8-1, 8-8 or 8-3). Results indicate that when using the existent time-reversed method for breast cancer here for the different combinations of transmitters and receivers, we found false positives due to the high degrees of freedom and unusual configuration (and the possible violation of Nyquist criterium). Those false positives founded in 8-1 and 8-8 combinations, highly reduced with the 1-1 and 8-3 combination, being the 8-3 configuration de most suitable (three neighboring receivers at each time). The 8-3 configuration creates a region-of-interest reduced problem, decreasing the ill-posedness of the inverse problem. To conclude, the proposed algorithm solves the main limitations of the described intrabody application, successfully detecting the angular position of targets inside the body tract.

Keywords: FDTD, time-reversed, medical imaging, microwave imaging

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Authors: Heramb Somthankar, Anujoy Chakraborty

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This paper presents a classification study on yield prediction in semiconductor production using machine learning approaches. A complicated semiconductor production process is generally monitored continuously by signals acquired from sensors and measurement sites. A monitoring system contains a variety of signals, all of which contain useful information, irrelevant information, and noise. In the case of each signal being considered a feature, "Feature Selection" is used to find the most relevant signals. The open-source UCI SECOM Dataset provides 1567 such samples, out of which 104 fail in quality assurance. Feature extraction and selection are performed on the dataset, and useful signals were considered for further study. Afterward, common machine learning algorithms were employed to predict whether the signal yields pass or fail. The most relevant algorithm is selected for prediction based on the accuracy and loss of the ML model.

Keywords: deep learning, feature extraction, feature selection, machine learning classification algorithms, semiconductor production monitoring, signal processing, time-series analysis

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Authors: Tajinder Kaur, Anu Bala

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An image retrieval system is a computer system for browsing, searching, and retrieving images from a large database of digital images a new algorithm meant for content-based image retrieval (CBIR) is presented in this paper. The proposed method combines the color and texture features which are extracted the global and local information of the image. The local texture feature is extracted by using local binary patterns (LBP), which are evaluated by taking into consideration of local difference between the center pixel and its neighbors. For the global color feature, the color histogram (CH) is used which is calculated by RGB (red, green, and blue) spaces separately. In this paper, the combination of color and texture features are proposed for content-based image retrieval. The performance of the proposed method is tested on Corel 1000 database which is the natural database. The results after being investigated show a significant improvement in terms of their evaluation measures as compared to LBP and CH.

Keywords: color, texture, feature extraction, local binary patterns, image retrieval

Procedia PDF Downloads 366