Search results for: mobile data patterns

Authors: V. R. Sadasivam, M. Vipin, P. Vineeth, M. Sajith, G. Sathiskumar, R. Manikandan, N. Vijayarangan

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Global positioning system technology is what leads to such things as navigation systems, GPS tracking devices, GPS surveying and GPS mapping. All that GPS does is provide a set of coordinates which represent the location of GPS units with respect to its latitude, longitude and elevation on planet Earth. It also provides time, which is accurate. The tracking devices themselves come in different flavors. They will contain a GPS receiver, and GPS software, along with some way of transmitting the resulting coordinates. GPS in mobile tend to use radio waves to transmit their location to another GPS device. The purpose of this prototype “Mobi Navi Tour for Rescue Operation” timely communication, and lightning fast decision-making with a group of people located in different places with a common goal. Timely communication and tracking the people are a critical issue in many situations, environments. Expedited can find missing person by sending the location and other related information to them through mobile. Information must be drawn from the caller and entered into the system by the administrator or a group leader and transferred to the group leader. This system will locate the closest available person, a group of people working in an organization/company or vehicle to determine availability and their position to track them. Misinformation cannot lead to the wrong decision in the rapidly paced environment in a normal and an abnormal situation. In “Mobi Navi Tour for Rescue Operation” we use Google Cloud Messaging for android (GCM) which is a service that helps developers send data from servers to their android applications on android devices. The service provides a simple, lightweight mechanism that servers can use to tell mobile applications to contact the server directly, to fetch updated application or user data.

Keywords: android, gps, tour, communication, service

Procedia PDF Downloads 381

Authors: Vemula Amalakrishna, S. Pushpavanam

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Change and motion characterize and persistently reshape the world around us, on scales from molecular to global. The subtle interplay between change (Reaction) and motion (Diffusion) gives rise to an astonishing intricate spatial or temporal pattern. These pattern formation in nature has been intellectually appealing for many scientists since antiquity. Periodic precipitation patterns, also known as Liesegang patterns (LP), are one of the stimulating examples of such self-assembling reaction-diffusion (RD) systems. LP formation has a great potential in micro and nanotechnology. So far, the research on LPs has been concentrated mostly on how these patterns are forming, retrieving information to build a universal mathematical model for them. Researchers have developed various theoretical models to comprehensively construct the geometrical diversity of LPs. To the best of our knowledge, simulation studies of LPs assume an arbitrary value of RD parameters to explain experimental observation qualitatively. In this work, existing models were studied to understand the mechanism behind this phenomenon and challenges pertaining to models were understood and explained. These models are not computationally effective due to the presence of discontinuous precipitation rate in RD equations. To overcome the computational challenges, smoothened Heaviside functions have been introduced, which downsizes the computational time as well. Experiments were performed using a conventional LP system (AgNO₃-K₂Cr₂O₇) to understand the effects of different gels and temperatures on formed LPs. The model is extended for real parameter values to compare the simulated results with experimental data for both 1-D (Cartesian test tubes) and 2-D(cylindrical and Petri dish).

Keywords: reaction-diffusion, spatio-temporal patterns, nucleation and growth, supersaturation

Procedia PDF Downloads 139

Authors: Pegah Farokhzad

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Family is a basic unit of the society and the main source of human development. The initial aim of the family is psychological and social support of its members and has special developmental stages. Researches show the families who have less cohesion, have more conflicts and maladjustments and the members of such families are not able to communicate effectively. Family is a system in which any inter communication is related to child rearing patterns and can affect it. Even the child rearing styles in childhood can determine the family communications in adulthood. Therefore, the aim of the present research was to examine the relationship between child-rearing styles including authoritative, authoritarian and permissive with dimensions of family communication patterns including the conversation and conformity. The research design was a correlational and the population consisted of the psychology students of Roudehen Islamic Azad University who were studying in academic year 2013-2014. A sample of 324 students were selected randomly from the population. The research tools were the Baumrind Child-rearing Questionnaires and Family Communication Patterns Inventory, The Revised Scale of Koerner and Fitzpatrick. The results were: (a) There was a positive and significant relationship between conversation orientation and authoritative style. (b) There was no significant relationship between conversation orientation and other child-rearing styles. (c) There was a negative significant relationship between conformity orientation and authoritative style. (d) There was a positive significant relationship between conformity orientation with authoritarian and permissive styles. (e) There was a significant relationship between 3 dimensions of child-rearing and communication patterns.

Keywords: child-rearing styles, family relationship patterns, university students, Iran

Procedia PDF Downloads 487

Authors: R. Fegas, S. Zerkout, S. Taberkokt, M. Righezza

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The present work demonstrate the potential of Betacyclodextrine (BCD) for the chiral analysis of a drug .Various separation mechanisms were applied and several parameters affecting the separation were studied, including the type and concentration of chiral selector, and pH of buffer. A simple and sensitive high-performance liquid chromatography (HPLC) method was developed as an assay for fexofenadine enantiomers in pharmaceutical preparation. Fexofenadine enantiomers were separated using a mobile phase of 0.25mM NaH2PO4–acetonitrile (65:35, v/v) – Betacyclodextrine on achiral phenyl-urea column at a flow rate of 1ml/min and measurement at 220nm. The chiral mechanism of separation was mainly based on specific interaction between the solute and the stationary phase. The retention was directly controlled by mobile phase composition but not the selectivity which results of the two mechanisms, electrostatic interactions and partition mechanism.

Keywords: fexofenadine enantiomer, HPLC, achiral phenyl-urea column

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Authors: Christina Tay

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This paper investigates the impact of Information and Communication Technology (ICT) on bilateral trade in goods. Empirical analysis is performed on the United States and 34 partnering countries from 2000 to 2013. Our econometric model fits the data well, explaining 52% of the variation in trade flows for goods trade, 53.2% of the variation in trade flows for goods export and 48% of the variation in trade flows for goods import. For every 10% increase in fixed broadband Internet subscribers per 100 people increases, goods trade by 7.9% and for every 5% increase in fixed broadband Internet subscribers per 100 people, goods export increases by 11%. For every 1% increase in fixed telephone line penetration per 100 people, goods trade increases by 26.3%, goods export increases by 24.4% and goods import increases by 24.8%. For every 1% increase in mobile-cellular telephone subscriptions, goods trade decreases by 29.6% and goods export decreases by 27.1%, whilst for every 0.01% increase in mobile-cellular telephone subscriptions, goods import decreases by 34.3%. For every 1% increase in the percentage of population who used the Internet from any location in the last 12 months Internet, goods trade increases by 32.5%, goods export increases by 38.9%, goods import increases by 33%. All our trade determinants as well as our ICT variables have significances on goods exports for the US. We can also draw from our study that the US relies more rather heavily on ICT for its goods export compared to goods import.

Keywords: bilateral trade, fixed broadband, fixed telephone, goods trade, information and communicative technologies, Internet, mobile-cellular phone

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Authors: Sherif K. El Dyasti, Esam A. Hagras, Adel E. El-Hennawy

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This paper addresses the performance of antenna array beam-forming on Chip-Interleaved Code Division Multiple Access (CI_CDMA) system based on Minimum Mean Square Error (MMSE) detector in aeronautical mobile radio channel. Multipath fading, Doppler shifts caused by the speed of the aircraft, and Multiple Access Interference (MAI) are the most important reasons that affect and reduce the performance of aeronautical system. In this paper, we suggested the CI-CDMA with antenna array to combat this fading and improve the bit error rate (BER) performance. We further evaluate the performance of the proposed system in the four standard scenarios in aeronautical mobile radio channel.

Keywords: aeronautical channel, CI-CDMA, beamforming, communication, information

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Authors: Sherrene Bogle, Verlia Bogle, Tyrone Anderson

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In recent years, organizations have become increasingly interested in the possibility of analyzing social media as a means of gaining meaningful feedback about their products and services. The aspect based sentiment analysis approach is used to predict the sentiment for Twitter datasets for Digicel and Lime, the main mobile companies in Jamaica, using supervised learning classification techniques. The results indicate an average of 82.2 percent accuracy in classifying tweets when comparing three separate classification algorithms against the purported baseline of 70 percent and an average root mean squared error of 0.31. These results indicate that the analysis of sentiment on social media in order to gain customer feedback can be a viable solution for mobile companies looking to improve business performance.

Keywords: machine learning, sentiment analysis, social media, supervised learning

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Authors: Wilayat Ali, Li Sheng, Waleed Ahmed

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The ability of the robot to make simultaneously map of the environment and localize itself with respect to that environment is the most important element of mobile robots. To solve SLAM many algorithms could be utilized to build up the SLAM process and SLAM is a developing area in Robotics research. Robot Operating System (ROS) is one of the frameworks which provide multiple algorithm nodes to work with and provide a transmission layer to robots. Manyof these algorithms extensively in use are Hector SLAM, Gmapping and Cartographer SLAM. This paper describes a ROS-based Simultaneous localization and mapping (SLAM) library Google Cartographer mapping, which is open-source algorithm. The algorithm was applied to create a map using laser and pose data from 2d Lidar that was placed on a mobile robot. The model robot uses the gazebo package and simulated in Rviz. Our research work's primary goal is to obtain mapping through Cartographer SLAM algorithm in a static indoor environment. From our research, it is shown that for indoor environments cartographer is an applicable algorithm to generate 2d maps with LIDAR placed on mobile robot because it uses both odometry and poses estimation. The algorithm has been evaluated and maps are constructed against the SLAM algorithms presented by Turtlebot2 in the static indoor environment.

Keywords: SLAM, ROS, navigation, localization and mapping, gazebo, Rviz, Turtlebot2, slam algorithms, 2d indoor environment, cartographer

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Authors: Luis Fernando Pinedo-Lomeli, Rosa Martha Lopez-Gutierrez, Jose Antonio Michel-Macarty, Cesar Cruz-Hernandez, Liliana Cardoza-Avendaño, Humberto Cruz-Hernandez

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Robots are working in industry and services performing repetitive or dangerous tasks, however, when flexible movement capabilities and complex tasks are required, the use of many robots is needed. Also, productivity can be improved by reducing times to perform tasks. In the last years, a lot of effort has been invested in research and development of collective control of mobile robots. This interest is justified as there are many advantages when two or more robots are collaborating in a particular task. Some examples are: cleaning toxic waste, transportation and manipulation of objects, exploration, and surveillance, search and rescue. In this work a study of collective movements of mobile robots is presented. A solution of collisions avoidance is developed. This solution is levered on a communication implementation that allows coordinate movements in different paths were avoiding obstacles.

Keywords: synchronization, communication, robots, legos

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Authors: Adarsh Shroff

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Big data is a collection of dataset so large and complex that it becomes difficult to process using data base management tools. To perform operations like search, analysis, visualization on big data by using data mining; which is the process of extraction of patterns or knowledge from large data set. In recent years, the data mining applications become stale and obsolete over time. Incremental processing is a promising approach to refreshing mining results. It utilizes previously saved states to avoid the expense of re-computation from scratch. This project uses i2MapReduce, an incremental processing extension to Map Reduce, the most widely used framework for mining big data. I2MapReduce performs key-value pair level incremental processing rather than task level re-computation, supports not only one-step computation but also more sophisticated iterative computation, which is widely used in data mining applications, and incorporates a set of novel techniques to reduce I/O overhead for accessing preserved fine-grain computation states. To optimize the mining results, evaluate i2MapReduce using a one-step algorithm and three iterative algorithms with diverse computation characteristics for efficient mining.

Keywords: big data, map reduce, incremental processing, iterative computation

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Authors: Maha Awad M. Almuttairi

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This research aimed to measure the impact of the use of a mobile learning (iTunes U) app for the development of metacognition skills delivered in the enrichment program offered to gifted students at the secondary level in Jeddah. The author targeted a group of students on an experimental scale to evaluate the achievement. The research sample consisted of a group of 38 gifted female students. The scale of evaluation of the metacognition skills used to measure the performance of students in the enrichment program was as follows: Satisfaction scale for the assessment of the technique used and the final product form after completion of the program. Appropriate statistical treatment used includes Paired Samples T-Test Cronbach’s alpha formula and eta squared formula. It was concluded in the results the difference of α≤ 0.05, which means the performance of students in the skills of metacognition in favor of using iTunes U. In light of the conclusion of the experiment, a number of recommendations and suggestions were present; the most important benefit of mobile learning applications is to provide enrichment programs for gifted students in the Kingdom of Saudi Arabia, as well as conducting further research on mobile learning and gifted student teaching.

Keywords: enrichment program, gifted students, metacognition skills, mobile learning

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Authors: Paraskevi Theodorou, Apostolos Meliones

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In the context of the development process of two assistive navigation mobile apps for blind and visually impaired people (BVI) an extensive qualitative analysis of the requirements of potential users has been conducted. The analysis was based on interviews with BVIs and aimed to elicit not only their needs with respect to autonomous navigation but also their preferences on specific features of the apps under development. The elicited requirements were structured into four main categories, namely, requirements concerning the capabilities, functionality and usability of the apps, as well as compatibility requirements with respect to other apps and services. The main categories were then further divided into nine sub-categories. This classification, along with its content, aims to become a useful tool for the researcher or the developer who is involved in the development of digital services for BVI.

Keywords: accessibility, assistive mobile apps, blind and visually impaired people, user requirements analysis

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Authors: Rasha Shoumar

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Background: Since the onset of the Syria crisis in 2011, Jordan has hosted many Syrian refugees, many of which are residing in urban and rural areas. Vulnerability of refugees has increased due to the COVID-19 pandemic, adding to their already existing challenge in access to medical services, rendering them vulnerable to the complications of untreated medical conditions and amplifying their risk for severe COVID-19 disease. To improve health outcomes and access to health care services in a COVID-19 context, IOM (The International Organization for Migration) provided health services including awareness raising, direct primary health care through mobile teams and referrals to secondary services were extended to the vulnerable populations of refugees. Method: 6 community health volunteers were trained and deployed to different governorates to provide COVID-19 and non-communicable disease awareness and collect data rated to non-communicable disease and access to medical health services. Primary health care services were extended to 7 governorates through a mobile medical team, providing medical management. The collected Data was reviewed and analyzed. Results: 2150 refugees in rural areas were reached out by community health volunteers, out of which 78 received their medications through the Ministry of Health, 121 received their medications through different non-governmental organizations, 665 patients couldn’t afford buying any medications, 1286 patients were occasionally buying their medications when they were able to afford it. 853 patients received medications and follow up through IOM mobile clinics, the most common conditions were hypertension, diabetes, hyperlipidemia, anemia, heart disease, thyroid disease, asthma, seizures, and psychiatric conditions. 709 of these patients had more than 3 of the comorbidities. Multiple cases were referred for secondary and tertiary lifesaving interventions. Conclusion: Non communicable diseases are highly prevalent among refugee population in Jordan, access to medical services have proven to be a challenge in rural areas especially during the COVID-19 era, many of the patients have multiple uncontrolled medical conditions placing them at risk for complications and risk for severe COVID-19 disease. Deployment of mobile clinics to rural areas plays an essential role in managing such medical conditions, thus improving the continuum of health care approach, physical and mental wellbeing of refugees and reducing the risk for severe COVID-19 disease among this group, taking us one step forward toward universal health access.

Keywords: COVID-19, refugees, mobile clinics, primary health care

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Authors: Zainab Mutlaq Ibrahim, Mohamed Bader-El-Den, Mihaela Cocea

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Students' textual feedback can hold unique patterns and useful information about learning process, it can hold information about advantages and disadvantages of teaching methods, assessment components, facilities, and other aspects of teaching. The results of analysing such a feedback can form a key point for institutions’ decision makers to advance and update their systems accordingly. This paper proposes a data mining framework for analysing end of unit general textual feedback using part of speech feature (PoS) with four machine learning algorithms: support vector machines, decision tree, random forest, and naive bays. The proposed framework has two tasks: first, to use the above algorithms to build an optimal model that automatically classifies the whole data set into two subsets, one subset is tailored to assessment practices (assessment related), and the other one is the non-assessment related data. Second task to use the same algorithms to build an optimal model for whole data set, and the new data subsets to automatically detect their sentiment. The significance of this paper is to compare the performance of the above four algorithms using part of speech feature to the performance of the same algorithms using n-grams feature. The paper follows Knowledge Discovery and Data Mining (KDDM) framework to construct the classification and sentiment analysis models, which is understanding the assessment domain, cleaning and pre-processing the data set, selecting and running the data mining algorithm, interpreting mined patterns, and consolidating the discovered knowledge. The results of this paper experiments show that both models which used both features performed very well regarding first task. But regarding the second task, models that used part of speech feature has underperformed in comparison with models that used unigrams and bigrams.

Keywords: assessment, part of speech, sentiment analysis, student feedback

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Authors: Marina Karaseva

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The beginning of our century became a new digital epoch in the educational situation. Last decade the newest stage of this process had been initialized by the touch-screen mobile devices with program applications for them. The touch possibilities for learning fundamentals of music are of especially importance for music majors. The phenomenon of touching, firstly, makes it realistic to play on the screen as on music instrument, secondly, helps students to learn music theory while listening in its sound elements by music ear. Nowadays we can detect several levels of such mobile applications: from the basic ones devoting to the elementary music training such as intervals and chords recognition, to the more advanced applications which deal with music perception of non-major and minor modes, ethnic timbres, and complicated rhythms. The main purpose of the proposed paper is to disclose the main tendencies in this process and to demonstrate the most innovative features of music theory applications on the base of iOS and Android systems as the most common used. Methodological recommendations how to use these digital material musicologically will be done for the professional music education of different levels. These recommendations are based on more than ten year ‘iTheory’ teaching experience of the author. In this paper, we try to logically classify all types of ‘iTheory’mobile applications into several groups, according to their methodological goals. General concepts given below will be demonstrated in concrete examples. The most numerous group of programs is formed with simulators for studying notes with audio-visual links. There are link-pair types as follows: sound — musical notation which may be used as flashcards for studying words and letters, sound — key, sound — string (basically, guitar’s). The second large group of programs is programs-tests containing a game component. As a rule, their basis is made with exercises on ear identification and reconstruction by voice: sounds and intervals on their sounding — harmonical and melodical, music modes, rhythmic patterns, chords, selected instrumental timbres. Some programs are aimed at an establishment of acoustical communications between concepts of the musical theory and their musical embodiments. There are also programs focused on progress of operative musical memory (with repeating of sounding phrases and their transposing in a new pitch), as well as on perfect pitch training In addition a number of programs improvisation skills have been developed. An absolute pitch-system of solmisation is a common base for mobile programs. However, it is possible to find also the programs focused on the relative pitch system of solfegе. In App Store and Google Play Market online store there are also many free programs-simulators of musical instruments — piano, guitars, celesta, violin, organ. These programs may be effective for individual and group exercises in ear training or composition classes. Great variety and good sound quality of these programs give now a unique opportunity to musicians to master their music abilities in a shorter time. That is why such teaching material may be a way to effective study of music theory.

Keywords: ear training, innovation in music education, music theory, mobile devices

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Authors: Nelson Kimeli Kemboi Yego, Juma Kasozi, Joseph Nkruzinza, Francis Kipkogei

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The study investigated the low uptake of health insurance in Kenya despite efforts to achieve universal health coverage through various health insurance schemes. Unsupervised machine learning techniques were employed to identify patterns in health insurance uptake based on sociodemographic factors among Kenyan households. The aim was to identify key demographic groups that are underinsured and to provide insights for the development of effective policies and outreach programs. Using the 2021 FinAccess Survey, the study clustered Kenyan households based on their health insurance uptake and sociodemographic features to reveal patterns in health insurance uptake across the country. The effectiveness of k-prototypes clustering, hierarchical clustering, and agglomerative hierarchical clustering in clustering based on sociodemographic factors was compared. The k-prototypes approach was found to be the most effective at uncovering distinct and well-separated clusters in the Kenyan sociodemographic data related to health insurance uptake based on silhouette, Calinski-Harabasz, Davies-Bouldin, and Rand indices. Hence, it was utilized in uncovering the patterns in uptake. The results of the analysis indicate that inclusivity in health insurance is greatly related to affordability. The findings suggest that targeted policy interventions and outreach programs are necessary to increase health insurance uptake in Kenya, with the ultimate goal of achieving universal health coverage. The study provides important insights for policymakers and stakeholders in the health insurance sector to address the low uptake of health insurance and to ensure that healthcare services are accessible and affordable to all Kenyans, regardless of their socio-demographic status. The study highlights the potential of unsupervised machine learning techniques to provide insights into complex health policy issues and improve decision-making in the health sector.

Keywords: health insurance, unsupervised learning, clustering algorithms, machine learning

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Authors: Jianan Sun, Ziwen Ye

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Multidimensional computerized adaptive testing (MCAT) is a popular research topic in psychometrics. It is important for practitioners to clearly know the item-trait patterns of administered items when a test like MCAT is operated. Item-trait pattern recognition refers to detecting which latent traits in a psychological test are measured by each of the specified items. If the item-trait patterns of the replenished items in MCAT item pool are well detected, the interpretability of the items can be improved, which can further promote the abilities of the examinees who attending the MCAT to be accurately estimated. This research explores to solve the item-trait pattern recognition problem of the replenished items in MCAT item pool from the perspective of statistical variable selection. The popular multidimensional item response theory model, multidimensional two-parameter logistic model, is assumed to fit the response data of MCAT. The proposed method uses the least absolute shrinkage and selection operator (LASSO) to detect item-trait patterns of replenished items based on the essential information of item responses and ability estimates of examinees collected from a designed MCAT procedure. Several advantages of the proposed method are outlined. First, the proposed method does not strictly depend on the relative order between the replenished items and the selected operational items, so it allows the replenished items to be mixed into the operational items in reasonable order such as considering content constraints or other test requirements. Second, the LASSO used in this research improves the interpretability of the multidimensional replenished items in MCAT. Third, the proposed method can exert the advantage of shrinkage method idea for variable selection, so it can help to check item quality and key dimension features of replenished items and saves more costs of time and labors in response data collection than traditional factor analysis method. Moreover, the proposed method makes sure the dimensions of replenished items are recognized to be consistent with the dimensions of operational items in MCAT item pool. Simulation studies are conducted to investigate the performance of the proposed method under different conditions for varying dimensionality of item pool, latent trait correlation, item discrimination, test lengths and item selection criteria in MCAT. Results show that the proposed method can accurately detect the item-trait patterns of the replenished items in the two-dimensional and the three-dimensional item pool. Selecting enough operational items from the item pool consisting of high discriminating items by Bayesian A-optimality in MCAT can improve the recognition accuracy of item-trait patterns of replenished items for the proposed method. The pattern recognition accuracy for the conditions with correlated traits is better than those with independent traits especially for the item pool consisting of comparatively low discriminating items. To sum up, the proposed data-driven method based on the LASSO can accurately and efficiently detect the item-trait patterns of replenished items in MCAT.

Keywords: item-trait pattern recognition, least absolute shrinkage and selection operator, multidimensional computerized adaptive testing, variable selection

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Authors: Mohammed A. Zidan, Alaa Sagheer, Nasser Metwally

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Real-time learning is an important goal that most of artificial intelligence researches try to achieve it. There are a lot of problems and applications which require low cost learning such as learn a robot to be able to classify and recognize patterns in real time and real-time recall. In this contribution, we suggest a model of quantum competitive learning based on a series of quantum gates and additional operator. The proposed model enables to recognize any incomplete patterns, where we can increase the probability of recognizing the pattern at the expense of the undesired ones. Moreover, these undesired ones could be utilized as new patterns for the system. The proposed model is much better compared with classical approaches and more powerful than the current quantum competitive learning approaches.

Keywords: competitive learning, quantum gates, quantum gates, winner-take-all

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Authors: K. Sathishkumar, V. Thiagarasu

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Due to recent advances in DNA microarray technology, it is now feasible to obtain gene expression profiles of tissue samples at relatively low costs. Many scientists around the world use the advantage of this gene profiling to characterize complex biological circumstances and diseases. Microarray techniques that are used in genome-wide gene expression and genome mutation analysis help scientists and physicians in understanding of the pathophysiological mechanisms, in diagnoses and prognoses, and choosing treatment plans. DNA microarray technology has now made it possible to simultaneously monitor the expression levels of thousands of genes during important biological processes and across collections of related samples. Elucidating the patterns hidden in gene expression data offers a tremendous opportunity for an enhanced understanding of functional genomics. However, the large number of genes and the complexity of biological networks greatly increase the challenges of comprehending and interpreting the resulting mass of data, which often consists of millions of measurements. A first step toward addressing this challenge is the use of clustering techniques, which is essential in the data mining process to reveal natural structures and identify interesting patterns in the underlying data. This work presents an analysis of several clustering algorithms proposed to deals with the gene expression data effectively. The existing clustering algorithms like Support Vector Machine (SVM), K-means algorithm and evolutionary algorithm etc. are analyzed thoroughly to identify the advantages and limitations. The performance evaluation of the existing algorithms is carried out to determine the best approach. In order to improve the classification performance of the best approach in terms of Accuracy, Convergence Behavior and processing time, a hybrid clustering based optimization approach has been proposed.

Keywords: microarray technology, gene expression data, clustering, gene Selection

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Authors: Gaurav Prabhudesai, Shaurya Kaushal, Pulkit Dubey, B. D. Pant

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The current race of miniaturization of circuits, systems, modules and networks has resulted in portable and mobile wireless systems having tremendous capabilities with small volume and weight. The power drivers or the power pack, electrically driving these modules have also reduced in proportion. Normally, the power packs in these mobile or fixed systems are batteries, rechargeable or non-rechargeable, which need regular replacement or recharging. Another approach to power these modules is to utilize the ambient energy available for electrical driving to make the system self-sustained. The current paper presents an overview of the different MEMS (Micro-Electro-Mechanical Systems) based techniques used for the harvesting of vibration energy to electrically drive a WSN (wireless sensor network) or a mobile module. This kind of system would have enormous applications, the most significant one, may be in cell phones.

Keywords: energy harvesting, WSN, MEMS, piezoelectrics

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Authors: Ewa Bednorz, Marek Polrolniczak, Bartosz Czernecki, Arkadiusz Marek Tomczyk

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This study is meant as a contribution to the research of the upwelling phenomenon, which is one of the most pronounced examples of the sea-atmosphere coupling. The aim is to confirm the atmospheric forcing of the sea waters circulation and sea surface temperature along the variously oriented Baltic Sea coasts and to find out macroscale and regional circulation patterns triggering upwelling along different sections of this relatively small and semi-closed sea basin. The mean daily sea surface temperature data from the summer seasons (June–August) of the years 1982–2017 made the basis for the detection of upwelling cases. For the atmospheric part of the analysis, monthly indices of the Northern Hemisphere macroscale circulation patterns were used. Besides, in order to identify the local direction of airflow, the daily zonal and meridional regional circulation indices were constructed and introduced to the analysis. Finally, daily regional circulation patterns over the Baltic Sea region were distinguished by applying the principal component analysis to the gridded mean daily sea level pressure data. Within the Baltic Sea, upwelling is the most frequent along the zonally oriented northern coast of the Gulf of Finland, southern coasts of Sweden, and along the middle part of the western Gulf of Bothnia coast. Among the macroscale circulation patterns, the Scandinavian type (SCAND), with a primary circulation center located over Scandinavia, has the strongest impact on the horizontal flow of surface sea waters in the Baltic Sea, which triggers upwelling. An anticyclone center over Scandinavia in the positive phase of SCAND enhances the eastern airflow, which increases upwelling frequency along southeastern Baltic coasts. It was proved in the study that the zonal circulation has a stronger impact on upwelling occurrence than the meridional one, and it could increase/decrease a chance of upwelling formation by more than 70% in some coastal sections. Positive and negative phases of six distinguished regional daily circulation patterns made 12 different synoptic situations which were analyzed in the terms of their influence on the upwelling formation. Each of them revealed some impact on the frequency of upwelling in some coastal section of the Baltic Sea; however, two kinds of synoptic situations seemed to have the strongest influence, namely, the first kind representing pressure patterns enhancing the zonal flow and the second kind representing synoptic patterns with a cyclone/anticyclone centers over southern Scandinavia. Upwelling occurrence appeared to be particularly strongly reliant on the atmospheric conditions in some specific coastal sections, namely: the Gulf of Finland, the south eastern Baltic coasts (Polish and Latvian-Lithuanian section), and the western part of the Gulf of Bothnia. Concluding, it can be stated that atmospheric conditions strongly control the occurrence of upwelling within the Baltic Sea basin. Both local and macroscale circulation patterns expressed by the location of the pressure centers influence the frequency of this phenomenon; however, the impact strength varies, depending on the coastal region. Acknowledgment: This research was funded by the National Science Centre, Poland, grant number 2016/21/B/ST10/01440.

Keywords: Baltic Sea, circulation patterns, coastal upwelling, synoptic conditions

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Authors: Ajda Osifo, Amanda Radwan

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Mobile-assisted language learning (MALL) or m-learning which is defined as learning with mobile devices that can be utilized in any place that is equipped with unbroken transmission signals, has created new opportunities and challenges for educational use. It introduced a new learning model combining new types of mobile devices, wireless communication services and technologies with teaching and learning. Recent advancements in the mobile world such as the Apple IOS devices (IPhone, IPod Touch and IPad), Android devices and other smartphone devices and environments (such as Windows Phone 7 and Blackberry), allowed learning to be more flexible inside and outside the classroom, making the learning experience unique, adaptable and tailored to each user. Creativity, learner autonomy, collaboration and digital practices of language learners are encouraged as well as innovative pedagogical applications, like the flipped classroom, for such practices in classroom contexts are enhanced. These developments are gradually embedded in daily life and they also seem to be heralding the sustainable move to paperless classrooms. Since mobile technologies are increasingly viewed as a main platform for delivery, we as educators need to design our activities, materials and learning environments in such a way to ensure that learners are engaged and feel comfortable. For the purposes of our session, several core MALL applications that work on the Apple IPad/IPhone will be explored; the rationale and steps needed to successfully implement these applications will be discussed and student examples will be showcased. The focus of the session will be on the following points: 1-Our current pedagogical approach, 2-The rationale and several core MALL apps, 3-Possible Challenges for Teachers and Learners, 4-Future implications. This session is aimed at instructors who are interested in integrating MALL apps into their own classroom planning.

Keywords: MALL, educational technology, iPads, apps

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Authors: Danuvasin Charoen

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The study investigates the business process and business model of GRABTAXI. The paper also discusses how the company implemented strategies to gain competitive advantages. The data is derived from the analysis of secondary data and the in-depth interviews among staffs, taxi drivers, and key customers. The findings indicated that the company’s competitive advantages come from being the first mover, emphasising on the ease of use and tangible benefits of application, and using network effect strategy.

Keywords: taxi, mobile application, innovative business model, Thailand

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Authors: Muhammad Akbar Hussain, Muhammad Mehdi Hussain, Waqar Haider

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There are tens of thousands of undetected and uncatalogued pieces of space debris in the Low Earth Orbit (LEO). They are not only difficult to be detected and tracked, their sheer number puts active satellites and humans in orbit around Earth into danger. With the entry of more governments and private companies into harnessing the Earth’s orbit for communication, research and military purposes, there is an ever-increasing need for not only the detection and cataloguing of these pieces of space debris, it is time to take measures to take them out and clean up the space around Earth. Current optical and radar-based Space Situational Awareness initiatives are useful mostly in detecting and cataloguing larger pieces of debris mainly for avoidance measures. Smaller than 10 cm pieces are in a relatively dark zone, yet these are deadly and capable of destroying satellites and human missions. A network of mobile observatories, connected to each other in real time and working in unison as a single instrument, may be able to detect small pieces of debris and achieve effective triangulation to help create a comprehensive database of their trajectories and parameters to the highest level of precision. This data may enable ground-based laser systems to help deorbit individual debris. Such a network of observatories can join current efforts in detection and removal of space debris in Earth’s orbit.

Keywords: space debris, low earth orbit, mobile observatories, triangulation, seamless operability

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Authors: Jisoo Song

Abstract:

Today’s mobile applications are communicating with servers more and more in order to access external services or information. Also, server-side code changes are more frequent than client-side code changes in a mobile application. The frequent changes lead to an increase in testing cost increase. To reduce costs, UI based test automation can be one of the solutions. It is a common automation technique in system-level testing. However, it can be unsuitable for mobile applications. When you automate tests based on UI elements for mobile applications, there are some limitations such as the overhead of script maintenance or the difficulty of finding invisible defects that UI elements cannot represent. To overcome these limitations, we present a new automation technique based on Rest API. You can automate system-level tests through test scripts that you write. These scripts call a series of Rest API in a user’s action sequence. This technique does not require testers to know the internal implementation details, only input and expected output of Rest API. You can easily modify test cases by modifying Rest API input values and also find problems that might not be evident from the UI level by validating output values. For example, when an application receives price information from a payment server and user cannot see it at UI level, Rest API based scripts can check whether price information is correct or not. More than 10 mobile applications at our company are being tested automatically based on Rest API scripts whenever application source code, mostly server source code, is built. We are finding defects right away by setting a script as a build job in CI server. The build job starts when application code builds are completed. This presentation will also include field cases from our company.

Keywords: case studies at SK Planet, introduction of rest API based test automation, limitations of UI based test automation

Procedia PDF Downloads 426

Authors: Jiwon Lee, Si-hwan Jang, Sanghyun Joo

Abstract:

The popularity of emoticons are on the rise since the mobile messengers are generalized. At the same time, few problems of emoticons are also occurred due to innate characteristics of emoticons. Too many emoticons make difficult people to select one which is well-suited for user's intention. On the contrary to this, sometimes user cannot find the emoticon which expresses user's exact intention. Poor information delivery of emoticon is another problem due to a major part of current emoticons are focused on emotion delivery. In this situation, we propose a new concept of emoticons, editable emoticons, to solve above drawbacks of emoticons. User can edit the components inside the proposed editable emoticon and send it to express his exact intention. By doing so, the number of editable emoticons can be maintained reasonable, and it can express user's exact intention. Further, editable emoticons can be used as information deliverer according to user's intention and editing skills. In this paper, we propose the concept of editable emoticons and schema based editable emoticon description method. The proposed description method is 200 times superior to the compared screen capturing method in the view of transmission bandwidth. Further, the description method is designed to have compatibility since it follows MPEG-UD international standard. The proposed editable emoticons can be exploited not only mobile applications, but also various fields such as education and medical field.

Keywords: description schema, editable emoticon, emoticon transmission, mobile applications

Procedia PDF Downloads 275

Authors: Nosheen Fatima Warraich

Abstract:

One of the most often used models in information system (IS) research is the technology acceptance model (TAM). This meta-analysis aims to measure the relationship between TAM variables, Perceived Ease of Use (PEOU), and Perceived Usefulness (PU) with users’ attitudes and behavioral intention (BI) in mobile and digital libraries context. It also examines the relationship of external variables (information quality and system quality) with TAM variables (PEOU and PU) in digital libraries settings. This meta-analysis was performed through PRISMA-P guidelines. Four databases (Google Scholar, Web of Science, Scopus, and LISTA) were utilized for searching, and the search was conducted according to defined criteria. The findings of this study revealed a large effect size of PU and PEOU with BI. There was also a large effect size of PU and PEOU with attitude. A medium effect size was found between SysQ -> PU, InfoQ-> PU, and SysQ -> PEOU. However, there was a small effect size between InfoQ and PEOU. It fills the literature gap and also confirms that TAM is a valid model for the acceptance and use of technology in mobile and digital libraries context. Thus, its findings would be helpful for developers and designers in designing and developing mobile library apps. It will also be beneficial for library authorities and system librarians in designing and developing digital libraries in academic settings.

Keywords: technology acceptance model (tam), perceived ease of use, perceived usefulness, information quality, system quality, meta-analysis, systematic review, digital libraries, and mobile library apps.

Procedia PDF Downloads 51

Authors: A. B. R. Hazarika

Abstract:

In the present paper, Quantum dots of ZnS are used to study the faster microwave propagation in space and on earth which will be difficult to bypass as quantum key encryption-decryption is difficult to decode. The present study deals with Quantum internet protocol which is much faster, safer and secure in microwave propagation than the present Internet Protocol v6, which forms the aspect of our study. Assimilation of hardware, Quantum dots with Quantum protocol theory beautifies the aspect of the study. So far to author’s best knowledge, the study on mobile telephony with Quantum dots long-term evolution (QDLTE) has not been studied earlier, which forms the aspect of the study found that the Bitrate comes out to be 102.4 Gbps.

Keywords: encryption, decryption, internet protocol, microwave, mobile telephony, quantum key encryption, quantum dots

Procedia PDF Downloads 151

Authors: Heeyong Noh, Seongryong Kang, Sungjoo Lee

Abstract:

As the world becomes increasingly interconnected, firms have tried to explore market opportunities not only in the domestic market but also abroad. In particular, transactions of intangible assets in the global market now take on great importance. Accordingly, technology transfer activities such as patent licensing, copyright transfer, or workforce trainings which are considered significant to leverage an organization’s internal capabilities, are occurring more frequently and briskly across the world than ever before. Though a number of studies have addressed the issues regarding technology transfer, most of them have focused on university-industry technology transfer. Of course, some have investigated international technology transfer phenomenon but used patent citations data as a proxy. In order to understand the phenomena more clearly, it would be necessary to collect and analyze data that can measure technology transfer activities between firms more directly. Therefore, this study aims to examine the patterns of international trade in technology by employing data about international technology in-licensing activities in Korean firms. We also investigate the effect of international technology in-licensing strategy on a firm’s innovation performance. The research findings are expected to help R&D managers understand how firms have absorbed technological knowledge from foreign firms in the form of licensing and further develop effective international collaboration strategies. In addition, significant implications can be offered for political decision-making regarding technology trade within increasing international interconnections.

Keywords: international technology trade, technology trade effect, technology transfer, R&D managers

Procedia PDF Downloads 349

Authors: Seung Hwan Park, Cheng-Sool Park, Jun Seok Kim, Youngji Yoo, Daewoong An, Jun-Geol Baek

Abstract:

Depending on the big data analysis becomes important, yield prediction using data from the semiconductor process is essential. In general, yield prediction and analysis of the causes of the failure are closely related. The purpose of this study is to analyze pattern affects the final test results using a die map based clustering. Many researches have been conducted using die data from the semiconductor test process. However, analysis has limitation as the test data is less directly related to the final test results. Therefore, this study proposes a framework for analysis through clustering using more detailed data than existing die data. This study consists of three phases. In the first phase, die map is created through fail bit data in each sub-area of die. In the second phase, clustering using map data is performed. And the third stage is to find patterns that affect final test result. Finally, the proposed three steps are applied to actual industrial data and experimental results showed the potential field application.

Keywords: die-map clustering, feature extraction, pattern recognition, semiconductor manufacturing process

Procedia PDF Downloads 380