Search results for: injecting drug user
Commenced in January 2007
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Edition: International
Paper Count: 4201

Search results for: injecting drug user

1141 Evaluating the Hepato-Protective Activities of Combination of Aqueous Extract of Roots of Tinospora cordifolia and Rhizomes of Curcuma longa against Paracetamol Induced Hepatic Damage in Rats

Authors: Amberkar Mohanbabu Vittalrao, Avin, Meena Kumari Kamalkishore, Padmanabha Udupa, Vinaykumar Bavimane, Honnegouda

Abstract:

Objective: To evaluate the hepato-protective activity of Tinospora cordiofolia (Tc) against paracetamol induced hepatic damage in rats. Methods: The plant stem (test drug) was procured locally, shade dried, powdered and extracted with water. Silymarin was used as standard hepatoprotective drugs and 2% gum acacia as a control (vehicle) against paracetamol (PCT) induced hepatotoxicity. Results and Discussion: The hepato-protective activity of aqueous stem extract was assessed by paracetamol induced hepatotoxicity preventive model in rats. Alteration in the levels of biochemical markers of hepatic damage like AST, ALT, ALP and lipid peroxides were tested in both paracetamol treated and untreated groups. Paracetamol (3g/kg) had enhanced the AST, ALT, ALP and the lipid peroxides in the serum. Treatment of silymarin and aqueous stem extract of Tc (200 and 400mg/kg) extract showed significant hepatoprotective activity by altering biochemical marker levels to the near normal. Preliminary phytochemical tests were done. Aqueous Tc extract showed presence of phenolic compound and flavonoids. Our findings suggested that Tc extract possessed hepatoprotective activity in a dose dependent manner. Conclusions: Tc was found to possess significant hepatoprotective property when treated with PCT. This was evident by decreasing the liver enzymes significantly when treated with PCT as compared to PCT only treated group (P < 0.05). Hence Tinospora cardiofolia could be a good, promising, preventive agent against PCT induced hepatotoxicity.

Keywords: Tinospora cardiofolia, hepatoprotection, paracetamol, silymarin

Procedia PDF Downloads 187
1140 Durian Marker Kit for Durian (Durio zibethinus Murr.) Identity

Authors: Emma K. Sales

Abstract:

Durian is the flagship fruit of Mindanao and there is an abundance of several cultivars with many confusing identities/ names. The project was conducted to develop procedure for reliable and rapid detection and sorting of durian planting materials. Moreover, it is also aimed to establish specific genetic or DNA markers for routine testing and authentication of durian cultivars in question. The project developed molecular procedures for routine testing. SSR primers were also screened and identified for their utility in discriminating durian cultivars collected. Results of the study showed the following accomplishments; 1. Twenty (29) SSR primers were selected and identified based on their ability to discriminate durian cultivars, 2. Optimized and established standard procedure for identification and authentication of Durian cultivars 3. Genetic profile of durian is now available at Biotech Unit. Our results demonstrate the relevance of using molecular techniques in evaluating and identifying durian clones. The most polymorphic primers tested in this study could be useful tools for detecting variation even at the early stage of the plant especially for commercial purposes. The process developed combines the efficiency of the microsatellites development process with the optimization of non-radioactive detection process resulting in a user-friendly protocol that can be performed in two (2) weeks and easily incorporated into laboratories about to start microsatellite development projects. This can be of great importance to extend microsatellite analyses to other crop species where minimal genetic information is currently available. With this, the University can now be a service laboratory for routine testing and authentication of durian clones.

Keywords: DNA, SSR analysis, genotype, genetic diversity, cultivars

Procedia PDF Downloads 432
1139 Predictability of Pupil Mydriasis as a Biomarker for Diabetes

Authors: Naveen Kumar Challa, Pavan Verıkıcherla, Madhubalan, Ashısh Sharma

Abstract:

Aim: Aim of the study was to find whether any difference exists in pupil mydriasis measured with Orbscan in non-diabetic and type 2 diabetic patients at various intervals after installation of Tropicamide 0.8% and Phenylephrine 5%. Methods: the Observational study conducted at a tertiary care eye hospital during September 2014 to March 2015. 240 eyes from 120 patients (40 non-diabetic, 80 diabetic) were dilated with Tropicamide 0.8% and Phenylephrine 5%. One drop of a drug was installed twice. The second drop is installed at 20 minutes after installation of the first drop. In two groups’ pupil diameter was measured before installation of drops and also at 15, 30, 45 and 60 minutes after installation of the first drop using both Orbscan. Result: Mean age of the non-diabetic group is 48.67 ± 7.93 years; Diabetic group is 59.97 ± 8.77 years. Mean duration of Diabetes was 7.01 ± 5.05 years. Mean pupil diameter measured with Orbscan before installation of the drops and also at 15, 30, 45 and 60 minutes after installation of first drop in non-diabetic group was 4.18 ± 0.64mm, 6.15 ± 0.41mm, 7.76 ±0.34, 9.59 ± 0.30, and 9.97 ± 0.10 mm respectively and for the diabetic group it was 4.00 ± 0.56 mm, 5.53 ± 0.52 mm, 7.018 ± 0.58mm, 8.25±0.51mm and 9.18 ± 0.46mm respectively. The mean difference between the mean pupil diameters of the non-diabetic and diabetic group shows a significant difference (P< 0.01) at all intervals except before dilatation. There is a significant negative correlation (r = 0.78 – 0.92) between the duration of diabetes and pupil dilatation at all intervals after installation of the drops. There is also significant difference (P< 0.005) in the mean values of pupil diameter between non retinopathy diabetic subjects and diabetic retinopathy subjects at all intervals after installation of drops. Conclusion: People attending eye clinic, whose pupil mydriasis values falls below the normal may be referred for diabetic evaluation. If normative data is established for the pupil size in Indian population using Orbscan then the values fall under normative data could be a predictor for diabetes. This would in turn help ophthalmologist to detect the diabetes at an early stage and prevent the complications resulting from the diabetes.

Keywords: diabetes mellitus, pupil diameter, orbscan, tropicamide

Procedia PDF Downloads 505
1138 Automatic Multi-Label Image Annotation System Guided by Firefly Algorithm and Bayesian Method

Authors: Saad M. Darwish, Mohamed A. El-Iskandarani, Guitar M. Shawkat

Abstract:

Nowadays, the amount of available multimedia data is continuously on the rise. The need to find a required image for an ordinary user is a challenging task. Content based image retrieval (CBIR) computes relevance based on the visual similarity of low-level image features such as color, textures, etc. However, there is a gap between low-level visual features and semantic meanings required by applications. The typical method of bridging the semantic gap is through the automatic image annotation (AIA) that extracts semantic features using machine learning techniques. In this paper, a multi-label image annotation system guided by Firefly and Bayesian method is proposed. Firstly, images are segmented using the maximum variance intra cluster and Firefly algorithm, which is a swarm-based approach with high convergence speed, less computation rate and search for the optimal multiple threshold. Feature extraction techniques based on color features and region properties are applied to obtain the representative features. After that, the images are annotated using translation model based on the Net Bayes system, which is efficient for multi-label learning with high precision and less complexity. Experiments are performed using Corel Database. The results show that the proposed system is better than traditional ones for automatic image annotation and retrieval.

Keywords: feature extraction, feature selection, image annotation, classification

Procedia PDF Downloads 571
1137 Film Review of 'Heroic Saviours and Survivors': The Representation of Sex Trafficking in Popular Films in India

Authors: Nisha James, Shubha Ranganathan

Abstract:

One of the most poignant forms of organized crime against women, which has rarely made it to the world of Indian cinema, is that of sex trafficking, i.e. the forcible involvement of women in the sex trade through fraud or coercion (Hughes, 2005). In the space of Indian cinema, much of the spotlight has been on the sensational drug trafficking and gang mafia of Bombay. During our research on sex trafficking, the rehabilitated women interviewed often expressed strong criticism about mass media’s naive portrayal of prostitutes as money-minting, happy and sexually driven women. They argued that this unrealistic portrayal ignored the fact that this was not a reality for the majority of trafficked women. Given the gravity of sex trafficking as a human rights issue, it is, therefore, refreshing to see three recent films on sex trafficking in Indian Languages – Naa Bangaaru Talli (2014, Telugu), Mardaani (2014, Hindi) and Lakshmi (2014, Hindi). This paper reviews these three films to explore the portrayal of the everyday reality of trafficking for women. Film analysis was used to understand the representation of psychological issues in the media. The strength of these movies starts with their inspirations which are of true stories and that they are all aimed at bringing awareness about the issue of sex trafficking, which is a rising social evil in Indian society though none of the three films move to portray the next phase of rehabilitation and reintegration of victims, which is a very complex and important process in the life of a survivor. According to findings, survivors of sex trafficking find the rehabilitation and reintegration into society to be a slow and tough part of their life as they continuously face stigma and social exclusion and have to strive to live against all odds of non-acceptance starting from their family.

Keywords: film review, Indian films, sex trafficking, survivors

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1136 Protective Effect of the Histamine H3 Receptor Antagonist DL77 in Behavioral Cognitive Deficits Associated with Schizophrenia

Authors: B. Sadek, N. Khan, D. Łażewska, K. Kieć-Kononowicz

Abstract:

The effects of the non-imidazole histamine H3 receptor (H3R) antagonist DL77 in passive avoidance paradigm (PAP) and novel object recognition (NOR) task in MK801-induced cognitive deficits associated with schizophrenia (CDS) in adult male rats, and applying donepezil (DOZ) as a reference drug were investigated. The results show that acute systemic administration of DL77 (2.5, 5, and 10 mg/kg, i.p.) significantly improved MK801-induced (0.1 mg/kg, i.p.) memory deficits in PAP. The ameliorating activity of DL77 (5 mg/kg, i.p.) in MK801-induced deficits was partly reversed when rats were pretreated with the centrally-acting H2R antagonist zolantidine (ZOL, 10 mg/kg, i.p.) or with the antimuscarinic antagonist scopolamine (SCO, 0.1 mg/kg, i.p.), but not with the CNS penetrant H1R antagonist pyrilamine (PYR, 10 mg/kg, i.p.). Moreover, the memory enhancing effect of DL77 (5 mg/kg, i.p.) in MK801-induced memory deficits in PAP was strongly reversed when rats were pretreated with a combination of ZOL (10 mg/kg, i.p.) and SCO (1.0 mg/kg, i.p.). Furthermore, the significant ameliorative effect of DL77 (5 mg/kg, i.p.) on MK801-induced long-term memory (LTM) impairment in NOR test was comparable to the DOZ-provided memory-enhancing effect, and was abrogated when animals were pretreated with the histamine H3R agonist R-(α)-methylhistamine (RAMH, 10 mg/kg, i.p.). However, DL77(5 mg/kg, i.p.) failed to provide procognitive effect on MK801-induced short-term memory (STM) impairment in NOR test. In addition, DL77 (5 mg/kg) did not alter anxiety levels and locomotor activity of animals naive to elevated-plus maze (EPM), demonstrating that improved performances with DL77 (5 mg/kg) in PAP or NOR are unrelated to changes in emotional responding or spontaneous locomotor activity. These results provide evidence for the potential of H3Rs for the treatment of neurodegenerative disorders related to impaired memory function, e.g. CDS.

Keywords: histamine H3 receptor, antagonist, learning, memory impairment, passive avoidance paradigm, novel object recognition

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1135 Face Recognition Using Body-Worn Camera: Dataset and Baseline Algorithms

Authors: Ali Almadan, Anoop Krishnan, Ajita Rattani

Abstract:

Facial recognition is a widely adopted technology in surveillance, border control, healthcare, banking services, and lately, in mobile user authentication with Apple introducing “Face ID” moniker with iPhone X. A lot of research has been conducted in the area of face recognition on datasets captured by surveillance cameras, DSLR, and mobile devices. Recently, face recognition technology has also been deployed on body-worn cameras to keep officers safe, enabling situational awareness and providing evidence for trial. However, limited academic research has been conducted on this topic so far, without the availability of any publicly available datasets with a sufficient sample size. This paper aims to advance research in the area of face recognition using body-worn cameras. To this aim, the contribution of this work is two-fold: (1) collection of a dataset consisting of a total of 136,939 facial images of 102 subjects captured using body-worn cameras in in-door and daylight conditions and (2) evaluation of various deep-learning architectures for face identification on the collected dataset. Experimental results suggest a maximum True Positive Rate(TPR) of 99.86% at False Positive Rate(FPR) of 0.000 obtained by SphereFace based deep learning architecture in daylight condition. The collected dataset and the baseline algorithms will promote further research and development. A downloadable link of the dataset and the algorithms is available by contacting the authors.

Keywords: face recognition, body-worn cameras, deep learning, person identification

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1134 An Explanatory Study into the Information-Seeking Behaviour of Egyptian Beggars

Authors: Essam Mansour

Abstract:

The key purpose of this study is to provide first-hand information about beggars in Egypt, especially from the perspective of their information seeking behaviour including their information needs. The researcher tries to investigate the information-seeking behaviour of Egyptian beggars with regard to their thoughts, perceptions, motivations, attitudes, habits, preferences as well as challenges that may impede their use of information. The research methods used were an adapted form of snowball sampling of a heterogeneous demographic group of participants in the beggary activity in Egypt. This sampling was used to select focus groups to explore a range of relevant issues. Data on the demographic characteristics of the Egyptian beggars showed that they tend to be men, mostly with no formal education, with an average age around 30s, labeled as low-income persons, mostly single and mostly Muslims. A large number of Egyptian beggars were seeking for information to meet their basic needs as well as their daily needs, although some of them were not able to identify their information needs clearly. The information-seeking behaviour profile of a very large number of Egyptian beggars indicated a preference for informal sources of information over formal ones to solve different problems and meet the challenges they face during their beggary activity depending on assistive devices, such as mobile phones. The high degree of illiteracy and the lack of awareness about the basic rights of information as well as information needs were the most important problems Egyptian beggars face during accessing information. The study recommended further research to be conducted about the role of the library in the education of beggars. It also recommended that beggars’ awareness about their information rights should be promoted through educational programs that help them value the role of information in their life.

Keywords: user studies, information-seeking behaviour, information needs, information sources, beggars, Egypt

Procedia PDF Downloads 300
1133 Anticancer Effect of Resveratrol-Loaded Gelatin Nanoparticles in NCI-H460 Non-Small Cell Lung Carcinoma Cell Lines

Authors: N. Rajendra Prasad

Abstract:

Resveratrol (RSV), a grape phytochemical, has drawn greater attention because of its beneficial ef-fects against cancer. However, RSV has some draw-backs such as unstabilization, poor water solubility and short biological half time, which limit the utili-zation of RSV in medicine, food and pharmaceutical industries. In this study, we have encapsulated RSV in gelatin nanoparticles (GNPs) and studied its anti-cancer efficacy in NCI-H460 lung cancer cells. SEM and DLS studies have revealed that the prepared RSV-GNPs possess spherical shape with a mean diameter of 294 nm. The successful encapsulation of RSV in GNPs has been achieved by the cross-linker glutaraldehyde probably through Schiff base reaction and hydrogen bond interaction. Spectrophotometric analysis revealed that the max-imum of 93.6% of RSV has been entrapped in GNPs. In vitro drug release kinetics indicated that there was an initial burst release followed by a slow and sustained release of RSV from GNPs. The prepared RSV-GNPs exhibited very rapid and more efficient cellular uptake than free RSV. Further, RSV-GNPs treatment showed greater antiproliferative efficacy than free RSV treatment in NCI-H460 cells. It has been found that greater ROS generation, DNA damage and apoptotic incidence in RSV-GNPs treated cells than free RSV treatment. Erythrocyte aggregation assay showed that the prepared RSV-GNPs formulation elicit no toxic response. HPLC analysis revealed that RSV-GNPs was more bioavailable and had a longer half-life than free RSV. Hence, GNPs carrier system might be a promising mode for controlled delivery and for improved therapeutic index of poorly water soluble RSV.

Keywords: resveratrol, coacervation, anticancer gelatin nanoparticles, lung cancer, controlled release

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1132 3D Multiuser Virtual Environments in Language Teaching

Authors: Hana Maresova, Daniel Ecler

Abstract:

The paper focuses on the use of 3D multi-user virtual environments (MUVE) in language teaching and presents the results of four years of research at the Faculty of Education, Palacký University in Olomouc (Czech Republic). In the form of an experiment, mother tongue language teaching in the 3D virtual worlds Second Life and Kitely (experimental group) and parallel traditional teaching on identical topics representing teacher's interpretation using a textbook (control group) were implemented. The didactic test, which was presented to the experimental and control groups in an identical form before and after the instruction, verified the effect of the instruction in the experimental group by comparing the results obtained by both groups. Within the three components of mother-tongue teaching (vocabulary, literature, style and communication education), the students in the literature group achieved partially better results (statistically significant in the case of items devoted to the area of visualization of the learning topic), while in the case of grammar and style education the respondents of the control group achieved better results. On the basis of the results obtained, we can conclude that the most appropriate use of MUVE can be seen in the teaching of those topics that provide the possibility of dramatization, experiential learning and group involvement and cooperation, on the contrary, with regard to the need to divide students attention between the topic taught and the control of avatar and movement in virtual reality as less suitable for teaching in the area of memorization of the topic or concepts.

Keywords: distance learning, 3D virtual environments, online teaching, language teaching

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1131 Fast Approximate Bayesian Contextual Cold Start Learning (FAB-COST)

Authors: Jack R. McKenzie, Peter A. Appleby, Thomas House, Neil Walton

Abstract:

Cold-start is a notoriously difficult problem which can occur in recommendation systems, and arises when there is insufficient information to draw inferences for users or items. To address this challenge, a contextual bandit algorithm – the Fast Approximate Bayesian Contextual Cold Start Learning algorithm (FAB-COST) – is proposed, which is designed to provide improved accuracy compared to the traditionally used Laplace approximation in the logistic contextual bandit, while controlling both algorithmic complexity and computational cost. To this end, FAB-COST uses a combination of two moment projection variational methods: Expectation Propagation (EP), which performs well at the cold start, but becomes slow as the amount of data increases; and Assumed Density Filtering (ADF), which has slower growth of computational cost with data size but requires more data to obtain an acceptable level of accuracy. By switching from EP to ADF when the dataset becomes large, it is able to exploit their complementary strengths. The empirical justification for FAB-COST is presented, and systematically compared to other approaches on simulated data. In a benchmark against the Laplace approximation on real data consisting of over 670, 000 impressions from autotrader.co.uk, FAB-COST demonstrates at one point increase of over 16% in user clicks. On the basis of these results, it is argued that FAB-COST is likely to be an attractive approach to cold-start recommendation systems in a variety of contexts.

Keywords: cold-start learning, expectation propagation, multi-armed bandits, Thompson Sampling, variational inference

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1130 Sustainable Affordable Housing Development in Indonesia

Authors: Gina Cynthia Raphita Hasibuan

Abstract:

The housing sector in Indonesia is in critical condition where majority of low-income citizens live in substandard dwellings, and the number housing backlog is increasing every year. The housing problem becomes more urgent when the term 'sustainability' is considered, and sustainable affordable housing is yet to gain its successful implementation. Global urbanization develops fastest in developing countries like Indonesia where informal settlements are rapidly escalating, hence, making sustainable affordable housing strategies very critical in this context. The problem in developing countries like Indonesia lies on the institutional capacity of newly-established local governments having greater power to determine a development policy but apparently still lacking institutional capability and coordination with the central government and collaborative governance are still not established yet. The concept of upgrading informal settlements are seen changed over time and inconsistent. Despite much research on theme such as sustainable housing concept within Indonesian context, there has been a dearth of research examining the role of collaborative governance, as the current approach still shows fragmented approach between the stakeholders and the lack of community participation as the end user, and thus this research attempts to fill the gap on the aforementioned problems. By using case study with multi-methods conducted in Jakarta, this research has an overall aim to critically assess the role of collaborative governance in addressing sustainable affordable housing in Indonesia and to understand informal settlements and interventions in Indonesia rather than imposing a framework from western perspectives.

Keywords: affordable housing, collaborative governance, sustainability, urban planning

Procedia PDF Downloads 369
1129 A Deep Learning Approach to Online Social Network Account Compromisation

Authors: Edward K. Boahen, Brunel E. Bouya-Moko, Changda Wang

Abstract:

The major threat to online social network (OSN) users is account compromisation. Spammers now spread malicious messages by exploiting the trust relationship established between account owners and their friends. The challenge in detecting a compromised account by service providers is validating the trusted relationship established between the account owners, their friends, and the spammers. Another challenge is the increase in required human interaction with the feature selection. Research available on supervised learning (machine learning) has limitations with the feature selection and accounts that cannot be profiled, like application programming interface (API). Therefore, this paper discusses the various behaviours of the OSN users and the current approaches in detecting a compromised OSN account, emphasizing its limitations and challenges. We propose a deep learning approach that addresses and resolve the constraints faced by the previous schemes. We detailed our proposed optimized nonsymmetric deep auto-encoder (OPT_NDAE) for unsupervised feature learning, which reduces the required human interaction levels in the selection and extraction of features. We evaluated our proposed classifier using the NSL-KDD and KDDCUP'99 datasets in a graphical user interface enabled Weka application. The results obtained indicate that our proposed approach outperformed most of the traditional schemes in OSN compromised account detection with an accuracy rate of 99.86%.

Keywords: computer security, network security, online social network, account compromisation

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1128 A Study on Abnormal Behavior Detection in BYOD Environment

Authors: Dongwan Kang, Joohyung Oh, Chaetae Im

Abstract:

Advancement of communication technologies and smart devices in the recent times is leading to changes into the integrated wired and wireless communication environments. Since early days, businesses had started introducing environments for mobile device application to their operations in order to improve productivity (efficiency) and the closed corporate environment gradually shifted to an open structure. Recently, individual user's interest in working environment using mobile devices has increased and a new corporate working environment under the concept of BYOD is drawing attention. BYOD (bring your own device) is a concept where individuals bring in and use their own devices in business activities. Through BYOD, businesses can anticipate improved productivity (efficiency) and also a reduction in the cost of purchasing devices. However, as a result of security threats caused by frequent loss and theft of personal devices and corporate data leaks due to low security, companies are reluctant about adopting BYOD system. In addition, without considerations to diverse devices and connection environments, there are limitations in detecting abnormal behaviors such as information leaks which use the existing network-based security equipment. This study suggests a method to detect abnormal behaviors according to individual behavioral patterns, rather than the existing signature-based malicious behavior detection and discusses applications of this method in BYOD environment.

Keywords: BYOD, security, anomaly behavior detection, security equipment, communication technologies

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1127 Effect of Saffron Extract and Aerobic Exercises on Troponin T and Heart-Type Fatty Acid Binding Protein in Men with Type 2 Diabetes

Authors: Ahmad Abdi, M. Golzadeh Gangeraj, Alireza Barari, S. Shirali, S. Amini

Abstract:

Aims: Diabetes is one of the common metabolic diseases in the world that has the dire adverse effects such as nephropathy, retinopathy and cardiovascular problems. Pharmaceutical and non-pharmaceutical strategies for control and treatment of diabetes are provided. Exercise and nutrition as non-drug strategies for the prevention and control of diabetes are considered. Exercises may increase oxidative stress and myocardium injury, thus it is necessary to take nutrition strategies to help diabetic athletes. Methods: This study was a semi-experimental research. Therefore, 24 men with type 2 diabetes were selected and randomly divided in four groups (1. control, 2. saffron extract, 3. aerobic exercises, 4. compound aerobic exercises and saffron extract). Saffron extract with 100 mg/day was used. Aerobic exercises, three days a week, for eight weeks, with 55-70% of maximum heart rate were performed. At the end, levels of Heart-type fatty acid-binding protein (HFABP) and Troponin T were measured. Data were analyzed by Paired t, One-way ANOVA and Tukey tests. Results: The serum Troponin T increased significantly in saffron extract, aerobic exercises and compound saffron extract -aerobic exercises in type 2 diabetic men(P=0.024, P =0.013, P=0.005 respectively). Saffron extract consumption (100 mg/day) and aerobic exercises did not significantly influence the serum HFABP (P =0.365, P =0.188 respectively). But serum HFABP decreased significantly in compound saffron extract -aerobic exercises group (P =0.003). Conclusions: Raised cardiac Troponin T and HFABP concentration accepted as the standard biochemical markers for the diagnosis of cardiac injury. Saffron intake may beneficially protect the myocardium from injuries. Compound saffron extract -aerobic exercises can decrease levels of Troponin T and HFABP in men with type 2 diabetes.

Keywords: Saffron, aerobic exercises, type 2 diabetes, HFABP, troponin T

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1126 Knowledge Based Behaviour Modelling and Execution in Service Robotics

Authors: Suraj Nair, Aravindkumar Vijayalingam, Alexander Perzylo, Alois Knoll

Abstract:

In the last decade robotics research and development activities have grown rapidly, especially in the domain of service robotics. Integrating service robots into human occupied spaces such as homes, offices, hospitals, etc. has become increasingly worked upon. The primary motive is to ease daily lives of humans by taking over some of the household/office chores. However, several challenges remain in systematically integrating such systems in human shared work-spaces. In addition to sensing and indoor-navigation challenges, programmability of such systems is a major hurdle due to the fact that the potential user cannot be expected to have knowledge in robotics or similar mechatronic systems. In this paper, we propose a cognitive system for service robotics which allows non-expert users to easily model system behaviour in an underspecified manner through abstract tasks and objects associated with them. The system uses domain knowledge expressed in the form of an ontology along with logical reasoning mechanisms to infer all the missing pieces of information required for executing the tasks. Furthermore, the system is also capable of recovering from failed tasks arising due to on-line disturbances by using the knowledge base and inferring alternate methods to execute the same tasks. The system is demonstrated through a coffee fetching scenario in an office environment using a mobile robot equipped with sensors and software capabilities for autonomous navigation and human-interaction through natural language.

Keywords: cognitive robotics, reasoning, service robotics, task based systems

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1125 Adsorption of Dyes and Iodine: Reaching Outstanding Kinetics with CuII-Based Metal–Organic Nanoballs

Authors: Eder Amayuelas, Begoña Bazán, M. Karmele Urtiaga, Gotzone Barandika, María I. Arriortua

Abstract:

Metal Organic Frameworks (MOFs) have attracted great interest in recent years, taking a lead role in the field of catalysis, drug delivery, sensors and absorption. In the past decade, promising results have been reported specifically in the field of adsorption, based on the topology and chemical features of this type of porous material. Thus, its application in industry and environment for the adsorption of pollutants is presented as a response to an increasingly important need. In this area, organic dyes are nowadays widely used in many industries including medicine, textile, leather, printing and plastics. The consequence of this fact is that dyes are present as emerging pollutants in soils and water where they remain for long periods of time due to their high stability, with a potential risk of toxicity in wildlife and in humans. On the other hand, the presence of iodine in soils, water and gas as a nuclear activity pollutant product or its extended use as a germicide is still a problem in many countries, which indicates the imperative need for its removal. In this context, this work presents the characterization as an adsorbent of the activated compound αMOP@Ei2-1 obtained from the already reported [Cu₂₄(m-BDC)₂₄(DMF)₂₀(H₂O)₄]•24DMF•40H₂O (MOP@Ei2-1), where m-BDC is the 1,3-benzenedicarboxylic ligand and DMF is N,N′-dimethylformamide. The structure of MOP@Ei2-1 consists of Cu24 clusters arranged in such a way that 12 paddle-wheels are connected through m-BDC ligands. The clusters exhibit an internal cavity where crystallization molecules of DMF and water are located. Adsorption of dyes and iodine as pollutant examples has been carried out, focusing attention on the kinetics of the rapid process.

Keywords: adsorption, organic dyes, iodine, metal organic frameworks

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1124 Modelling the Tensile Behavior of Plasma Sprayed Freestanding Yttria Stabilized Zirconia Coatings

Authors: Supriya Patibanda, Xiaopeng Gong, Krishna N. Jonnalagadda, Ralph Abrahams

Abstract:

Yttria stabilized zirconia (YSZ) is used as a top coat in thermal barrier coatings in high-temperature turbine/jet engine applications. The mechanical behaviour of YSZ depends on the microstructural features like crack density and porosity, which are a result of coating method. However, experimentally ascertaining their individual effect is difficult due to the inherent challenges involved like material synthesis and handling. The current work deals with the development of a phenomenological model to replicate the tensile behavior of air plasma sprayed YSZ obtained from experiments. Initially, uniaxial tensile experiments were performed on freestanding YSZ coatings of ~300 µm thick for different crack densities and porosities. The coatings exhibited a nonlinear behavior and also a huge variation in strength values. With the obtained experimental tensile curve as a base and crack density and porosity as prime variables, a phenomenological model was developed using ABAQUS interface with new user material defined employing VUMAT sub routine. The relation between the tensile stress and the crack density was empirically established. Further, a parametric study was carried out to investigate the effect of the individual features on the non-linearity in these coatings. This work enables to generate new coating designs by varying the key parameters and predicting the mechanical properties with the help of a simulation, thereby minimizing experiments.

Keywords: crack density, finite element method, plasma sprayed coatings, VUMAT

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1123 A Practice of Zero Trust Architecture in Financial Transactions

Authors: Liwen Wang, Yuting Chen, Tong Wu, Shaolei Hu

Abstract:

In order to enhance the security of critical financial infrastructure, this study carries out a transformation of the architecture of a financial trading terminal to a zero trust architecture (ZTA), constructs an active defense system for cybersecurity, improves the security level of trading services in the Internet environment, enhances the ability to prevent network attacks and unknown risks, and reduces the industry and security risks brought about by cybersecurity risks. This study introduces the SDP technology of ZTA, adapts and applies it to a financial trading terminal to achieve security optimization and fine-grained business grading control. The upgraded architecture of the trading terminal moves security protection forward to the user access layer, replaces VPN to optimize remote access, and significantly improves the security protection capability of Internet transactions. The study achieves 1. deep integration with the access control architecture of the transaction system; 2. no impact on the performance of terminals and gateways, and no perception of application system upgrades; 3. customized checklist and policy configuration; 4. introduction of industry-leading security technology such as single-packet authorization (SPA) and secondary authentication. This study carries out a successful application of ZTA in the field of financial trading and provides transformation ideas for other similar systems while improving the security level of financial transaction services in the Internet environment.

Keywords: zero trust, trading terminal, architecture, network security, cybersecurity

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1122 Machine Learning Strategies for Data Extraction from Unstructured Documents in Financial Services

Authors: Delphine Vendryes, Dushyanth Sekhar, Baojia Tong, Matthew Theisen, Chester Curme

Abstract:

Much of the data that inform the decisions of governments, corporations and individuals are harvested from unstructured documents. Data extraction is defined here as a process that turns non-machine-readable information into a machine-readable format that can be stored, for instance, in a database. In financial services, introducing more automation in data extraction pipelines is a major challenge. Information sought by financial data consumers is often buried within vast bodies of unstructured documents, which have historically required thorough manual extraction. Automated solutions provide faster access to non-machine-readable datasets, in a context where untimely information quickly becomes irrelevant. Data quality standards cannot be compromised, so automation requires high data integrity. This multifaceted task is broken down into smaller steps: ingestion, table parsing (detection and structure recognition), text analysis (entity detection and disambiguation), schema-based record extraction, user feedback incorporation. Selected intermediary steps are phrased as machine learning problems. Solutions leveraging cutting-edge approaches from the fields of computer vision (e.g. table detection) and natural language processing (e.g. entity detection and disambiguation) are proposed.

Keywords: computer vision, entity recognition, finance, information retrieval, machine learning, natural language processing

Procedia PDF Downloads 92
1121 Easymodel: Web-based Bioinformatics Software for Protein Modeling Based on Modeller

Authors: Alireza Dantism

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Presently, describing the function of a protein sequence is one of the most common problems in biology. Usually, this problem can be facilitated by studying the three-dimensional structure of proteins. In the absence of a protein structure, comparative modeling often provides a useful three-dimensional model of the protein that is dependent on at least one known protein structure. Comparative modeling predicts the three-dimensional structure of a given protein sequence (target) mainly based on its alignment with one or more proteins of known structure (templates). Comparative modeling consists of four main steps 1. Similarity between the target sequence and at least one known template structure 2. Alignment of target sequence and template(s) 3. Build a model based on alignment with the selected template(s). 4. Prediction of model errors 5. Optimization of the built model There are many computer programs and web servers that automate the comparative modeling process. One of the most important advantages of these servers is that it makes comparative modeling available to both experts and non-experts, and they can easily do their own modeling without the need for programming knowledge, but some other experts prefer using programming knowledge and do their modeling manually because by doing this they can maximize the accuracy of their modeling. In this study, a web-based tool has been designed to predict the tertiary structure of proteins using PHP and Python programming languages. This tool is called EasyModel. EasyModel can receive, according to the user's inputs, the desired unknown sequence (which we know as the target) in this study, the protein sequence file (template), etc., which also has a percentage of similarity with the primary sequence, and its third structure Predict the unknown sequence and present the results in the form of graphs and constructed protein files.

Keywords: structural bioinformatics, protein tertiary structure prediction, modeling, comparative modeling, modeller

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1120 How Validated Nursing Workload and Patient Acuity Data Can Promote Sustained Change and Improvements within District Health Boards. the New Zealand Experience

Authors: Rebecca Oakes

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In the New Zealand public health system, work has been taking place to use electronic systems to convey data from the ‘floor to the board’ that makes patient needs, and therefore nursing work, visible. For nurses, these developments in health information technology puts us in a very new and exciting position of being able to articulate the work of nursing through a language understood at all levels of an organisation, the language of acuity. Nurses increasingly have a considerable stake-hold in patient acuity data. Patient acuity systems, when used well, can assist greatly in demonstrating how much work is required, the type of work, and when it will be required. The New Zealand Safe Staffing Unit is supporting New Zealand nurses to create a culture of shared governance, where nursing data is informing policies, staffing methodologies and forecasting within their organisations. Assisting organisations to understand their acuity data, strengthening user confidence in using electronic patient acuity systems, and ensuring nursing and midwifery workload is accurately reflected is critical to the success of the safe staffing programme. Nurses and midwives have the capacity via an acuity tool to become key informers of organisational planning. Quality patient care, best use of health resources and a quality work environment are essential components of a safe, resilient and well resourced organisation. Nurses are the key informers of this information. In New Zealand a national level approach is paving the way for significant changes to the understanding and use of patient acuity and nursing workload information.

Keywords: nursing workload, patient acuity, safe staffing, New Zealand

Procedia PDF Downloads 363
1119 Molecular Mechanism on Inflammation and Antioxidant Role of Pterocarpus Marsupiumin in Experimental Hyperglycaemia

Authors: Leelavinothan Pari , Ayyasamy Rathinam

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Diabetes mellitus (DM) is a major and growing public health problem throughout the world. Pterocarpus marsupium (Roxb.) (Family: Fabaceae) is widely used as a traditional medicine to treat various diseases including diabetes. However, the molecular mechanism of Pterocarpus marsupium has not been investigated so far. Two fractions (2.5% and 5%) of extract from the medicinal plant, Pterocarpus marsupium (PME) were conducted in a dose dependent manner in streptozotocin (45 mg/kg b.w.) induced type 2 diabetic rats. Each fraction of PME was administered to diabetic rats intragastrically at a dose of 50, 100 and 200 mg/kg b.w for 45 days. The effective dose 200 mg/kg b.w of 5% fraction was more pronounced in reducing the levels of blood glucose (95.65 mg/dL) and glycosylated hemoglobin (HbA1c) (0.41 mg/g Hb), and increasing the plasma insulin (16.20 µU/mL) level. Moreover, PME (200 mg/kg b.w) significantly ameliorated lipid peroxidation products (thiobarbituric reactive substances, lipid hydroperoxides) enzymatic (superoxide dismutase, catalase and glutathione peroxidase) and non-enzymatic antioxidants (Vitamin C, Vitamin E and reduced glutathione) levels. The altered activities of the key enzymes of lipid metabolism along with the lipid profile in diabetic rats were significantly reverted to near normal levels by the administration of PME 5% 200 mg/kg b.w fraction. PME (200 mg/kg b.w) has the ability to reduce the inflammatory cytokines, such as TNF-α, IL-6 mRNA, as well as protein expression and apoptotic marker, such as caspase-3 enzyme in diabetic hepatic tissue. The above biochemical findings were also supported by histological studies such as improvement in pancreas and liver. Pterocarpus marsupium could effectively reduce the hyperglycemia, oxidative-stress, inflammation and hyperlipedimea in diabetic rats; hence it could be a useful drug in the management of diabetes without any side effects.

Keywords: diabetes mellitus, streptozotocin, Pterocarpus marsupium, lipid peroxidation, Antioxidants, inflammatory cytokines

Procedia PDF Downloads 357
1118 A High Content Screening Platform for the Accurate Prediction of Nephrotoxicity

Authors: Sijing Xiong, Ran Su, Lit-Hsin Loo, Daniele Zink

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The kidney is a major target for toxic effects of drugs, industrial and environmental chemicals and other compounds. Typically, nephrotoxicity is detected late during drug development, and regulatory animal models could not solve this problem. Validated or accepted in silico or in vitro methods for the prediction of nephrotoxicity are not available. We have established the first and currently only pre-validated in vitro models for the accurate prediction of nephrotoxicity in humans and the first predictive platforms based on renal cells derived from human pluripotent stem cells. In order to further improve the efficiency of our predictive models, we recently developed a high content screening (HCS) platform. This platform employed automated imaging in combination with automated quantitative phenotypic profiling and machine learning methods. 129 image-based phenotypic features were analyzed with respect to their predictive performance in combination with 44 compounds with different chemical structures that included drugs, environmental and industrial chemicals and herbal and fungal compounds. The nephrotoxicity of these compounds in humans is well characterized. A combination of chromatin and cytoskeletal features resulted in high predictivity with respect to nephrotoxicity in humans. Test balanced accuracies of 82% or 89% were obtained with human primary or immortalized renal proximal tubular cells, respectively. Furthermore, our results revealed that a DNA damage response is commonly induced by different PTC-toxicants with diverse chemical structures and injury mechanisms. Together, the results show that the automated HCS platform allows efficient and accurate nephrotoxicity prediction for compounds with diverse chemical structures.

Keywords: high content screening, in vitro models, nephrotoxicity, toxicity prediction

Procedia PDF Downloads 298
1117 Acoustic Modeling of a Data Center with a Hot Aisle Containment System

Authors: Arshad Alfoqaha, Seth Bard, Dustin Demetriou

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A new multi-physics acoustic modeling approach using ANSYS Mechanical FEA and FLUENT CFD methods is developed for modeling servers mounted to racks, such as IBM Z and IBM Power Systems, in data centers. This new approach allows users to determine the thermal and acoustic conditions that people are exposed to within the data center. The sound pressure level (SPL) exposure for a human working inside a hot aisle containment system inside the data center is studied. The SPL is analyzed at the noise source, at the human body, on the rack walls, on the containment walls, and on the ceiling and flooring plenum walls. In the acoustic CFD simulation, it is assumed that a four-inch diameter sphere with monopole acoustic radiation, placed in the middle of each rack, provides a single-source representation of all noise sources within the rack. Ffowcs Williams & Hawkings (FWH) acoustic model is employed. The target frequency is 1000 Hz, and the total simulation time for the transient analysis is 1.4 seconds, with a very small time step of 3e-5 seconds and 10 iterations to ensure convergence and accuracy. A User Defined Function (UDF) is developed to accurately simulate the acoustic noise source, and a Dynamic Mesh is applied to ensure acoustic wave propagation. Initial validation of the acoustic CFD simulation using a closed-form solution for the spherical propagation of an acoustic point source is performed.

Keywords: data centers, FLUENT, acoustics, sound pressure level, SPL, hot aisle containment, IBM

Procedia PDF Downloads 157
1116 Inhibitory Attributes of Saudi Honey Against Hospital Acquired Methicillin Resistant Staph. aureus (MRSA) and Acinetobacter baumannii

Authors: Al-Hindi Rashad, Alotibi Ibrahim

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The aim of this study was to examine the antibacterial activity of the peroxide components of some locally produced honeys: Toran, Zaitoon (Olive), Shaflah, Saha, Jizan, Rabea Aja, Fakhira, Sedr Aljanoob, Tenhat, Karath and Bareq against two of the drug resistant bacteria; i.e., methicillin resistant Staph. aureus (MRSA, ATCC 43330) and Acinetobacter baumannii. Measurement of the antibacterial activity of honey samples by using the agar well diffusion method was adopted as follows: by using turbidity standard McFaraland 0.5, suspensions of bacterial strains MRSA ATCC 43330 and Acinetobacter baumannii were prepared. By the spreading plate method, 100 µl of the suspension was inoculated onto Muller-Hinton agar medium. On the inoculated agar medium, five wells were made using a sterile cork borer (diameter 5 mm).100 µl of honey dilutions (10%, 30%, 50%, 70% and 100%) were used. The study indicated that the highly effective activity was in some local honey samples such as Toran honey against MRSA, and Shafalah honey against MRSA and Acinetobacter baumannii which showed bactericidal effects at concentrations 70 % to 100 % as well. The majority of local honey samples recorded bacteriostatic effects on MRSA and Acinetobacter baumannii at consternations 50 % and above. In conclusion this investigation indicated that in regard to the majority inhibitory effect on microorganisms, the existing of H2O2 in honey samples together with phenolic content greatly provide a strong antibacterial activities among different types of honey, because in some previous studies the H2O2 content of honey interacts with phenolic content and showed better inhibitory effect than in absent of H2O2.

Keywords: antibacterial activity, honey, hospital acquired, Saudi Arabia

Procedia PDF Downloads 474
1115 A Machine Learning Approach for Performance Prediction Based on User Behavioral Factors in E-Learning Environments

Authors: Naduni Ranasinghe

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E-learning environments are getting more popular than any other due to the impact of COVID19. Even though e-learning is one of the best solutions for the teaching-learning process in the academic process, it’s not without major challenges. Nowadays, machine learning approaches are utilized in the analysis of how behavioral factors lead to better adoption and how they related to better performance of the students in eLearning environments. During the pandemic, we realized the academic process in the eLearning approach had a major issue, especially for the performance of the students. Therefore, an approach that investigates student behaviors in eLearning environments using a data-intensive machine learning approach is appreciated. A hybrid approach was used to understand how each previously told variables are related to the other. A more quantitative approach was used referred to literature to understand the weights of each factor for adoption and in terms of performance. The data set was collected from previously done research to help the training and testing process in ML. Special attention was made to incorporating different dimensionality of the data to understand the dependency levels of each. Five independent variables out of twelve variables were chosen based on their impact on the dependent variable, and by considering the descriptive statistics, out of three models developed (Random Forest classifier, SVM, and Decision tree classifier), random forest Classifier (Accuracy – 0.8542) gave the highest value for accuracy. Overall, this work met its goals of improving student performance by identifying students who are at-risk and dropout, emphasizing the necessity of using both static and dynamic data.

Keywords: academic performance prediction, e learning, learning analytics, machine learning, predictive model

Procedia PDF Downloads 132
1114 Induction of HIV-1 Resistance: The New Approaches Based on Gene Modification and Stem Cell Engineering

Authors: Alieh Farshbaf

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Introduction: Current anti-retroviral drugs have some restrictions for treatment of HIV-1 infection. The efficacy of retroviral drugs is not same in different infected patients and the virus rebound from latent reservoirs after stopping them. Recently, the engineering of stem cells and gene therapy provide new approaches to eliminate some drug problems by induction of resistance to HIV-1. Literature review: Up to now, AIDS-restriction genes (ARGs) were suitable candidate for gene and cell therapies, such as cc-chemokine receptor-5 (CCR5). In this manner, CCR5 provide effective cure in Berlin and Boston patients by inducing of HIV-1 resistance with allogeneic stem cell transplantation. It is showed that Zinc Finger Nuclease (ZFN) could induce HIV-1 resistance in stem cells of infected patients by homologous recombination or non-end joining mechanism and eliminate virus loading after returning the modified cells. Then, gene modification by HIV restriction factors, as TRIM5, introduced another gene candidate for HIV by interfering in infection process. These gene modifications/editing provided by stem cell futures that improve treatment in refractory disease such as HIV-1. Conclusion: Although stem cell transplantation has some complications, but in compare to retro-viral drugs demonstrated effective cure by elimination of virus loading. On the other hand, gene therapy is cost-effective for an infected patient than retroviral drugs payment in a person life-long. The results of umbilical cord blood stem cell transplantation showed that gene and cell therapy will be applied easier than previous treatment of AIDS with high efficacy.

Keywords: stem cell, AIDS, gene modification, cell engineering

Procedia PDF Downloads 286
1113 Improving Self-Administered Medication Adherence for Older Adults: A Systematic Review

Authors: Mathumalar Loganathan, Lina Syazana, Bryony Dean Franklin

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Background: The therapeutic benefit of self-administered medication for long-term use is limited by an average 50% non-adherence rate. Patient forgetfulness is a common factor in unintentional non-adherence. With a growing ageing population, strategies to improve self-administration of medication adherence are essential. Our aim was to review systematically the effects of interventions to optimise self-administration of medication. Method: Database searched were MEDLINE, EMBASE, PsynINFO, CINAHL from 1980 to 31 October 2013. Search terms included were ‘self-administration’, ‘self-care’, ‘medication adherence’, and ‘intervention’. Two independent reviewers undertook screening and methodological quality assessment, using the Downs and Black rating scale. Results: The search strategy retrieved 6 studies that met the inclusion and exclusion criteria. Three intervention strategies were identified: self-administration medication programme (SAMP), nursing education and medication packaging (pill calendar). A nursing education programme focused on improving patients’ behavioural self-management of drug prescribing. This was the most studied area and three studies highlighting an improvement in self-administration of medication. Conclusion: Results are mixed and there is no one interventional strategy that has proved to be effective. Nevertheless, self-administration of medication programme seems to show most promise. A multi-faceted approach and clearer policy guideline are likely to be required to improve prescribing for these vulnerable patients. Mixed results were found for SAMP. Medication packaging (pill calendar) was evaluated in one study showing a significant improvement in self-administration of medication. A meta-analysis could not be performed due to heterogeneity in the outcome measures.

Keywords: self-administered medication, intervention, prescribing, older patients

Procedia PDF Downloads 305
1112 A Framework for Enhancing Mobile Development Software for Rangsit University, Thailand

Authors: Thossaporn Thossansin

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This paper presents the developing of a mobile application for students who are studying in a Faculty of Information Technology, Rangsit University (RSU), Thailand. RSU enhanced the enrollment process by leveraging its information systems, which allows students to download RSU APP. This helps students to access RSU’s information that is important for them. The reason to have a mobile application is to give support students’ ability to access the system at anytime, anywhere and anywhere. The objective of this paper was to develop an application on iOS platform for students who are studying in Faculty of Information Technology, Rangsit University, Thailand. Studies and learns student’s perception for a new mobile app. This paper has targeted a group of students who is studied in year 1-4 in the faculty of information technology, Rangsit University. This new application has been developed by the department of information technology, Rangsit University and it has generally called as RSU APP. This is a new mobile application development for RSU, which has useful features and functionalities in giving support to students. The core module has consisted of RSU’s announcement, calendar, event, activities, and ebook. The mobile app has developed on iOS platform that is related to RSU’s policies in giving free Tablets for the first year students. The user satisfaction is analyzed from interview data that has 81 interviews and Google application such as google form is taken into account for 122 interviews. Generally, users were satisfied to-use application with the most satisfaction at the level of 4.67. SD is 0.52, which found the most satisfaction in that users can learn and use quickly. The most satisfying is 4.82 and SD is 0.71 and the lowest satisfaction rating in its modern form, apps lists. The satisfaction is 4.01, and SD is 0.45.

Keywords: mobile application, development of mobile application, framework of mobile development, software development for mobile devices

Procedia PDF Downloads 306