Abstract: In this modern era of technology, the concept of Internet of Things is very popular in every domain. It is a widely distributed system of things in which the data collected from sensory devices is transmitted, analyzed locally/collectively then broadcasted to network where action can be taken remotely via mobile/web apps. Today’s mobile computing is also gaining importance as the services are provided during mobility. Through mobile computing, data are transmitted via computer without physically connected to a fixed point. The challenge is to provide services with high speed and security. Also, the data gathered from the mobiles must be processed in a secured way. Mobile computing is strongly influenced by internet of things. In this paper, we have discussed security issues and challenges of internet of things and mobile computing and we have compared both of them on the basis of similarities and dissimilarities.
Abstract: Check-in locations on social media provide information about an individual’s location. The millions of units of data generated from these sites provide knowledge for human activity. In this research, we used a geolocation service and users’ texts posted on Twitter social media to analyze human mobility. Our research will answer the questions; what are the movement patterns of a citizen? And, how far do people travel in the city? We explore the people trajectory of 201,118 check-ins and 22,318 users over a period of one month in Makassar city, Indonesia. To accommodate individual mobility, the authors only analyze the users with check-in activity greater than 30 times. We used sampling method with a systematic sampling approach to assign the research sample. The study found that the individual movement shows a high degree of regularity and intensity in certain places. The other finding found that the average distance an urban inhabitant can travel per day is as far as 9.6 km.
Abstract: To assist medical diagnosis, we propose a federation
of several existing and open medical ontologies and terminologies.
The goal is to merge the strengths of all these resources to provide
clinicians the access to a variety of shared knowledges that can
facilitate identification and association of human diseases and all of
their available characteristic signs such as symptoms and clinical
signs. This work results to an integration model loaded from target
known ontologies of the bioportal platform such as DOID, MESH,
and SNOMED for diseases selection, SYMP, and CSSO for all
existing signs.
Abstract: Software-defined networking (SDN) provides a solution
for scalable network framework with decoupled control and data
plane. However, this architecture also induces a particular distributed
denial-of-service (DDoS) attack that can affect or even overwhelm
the SDN network. DDoS attack detection problem has to date been
mostly researched as entropy comparison problem. However, this
problem lacks the utilization of SDN, and the results are not accurate.
In this paper, we propose a DDoS attack detection method, which
interprets DDoS detection as a signature matching problem and is
formulated as Earth Mover’s Distance (EMD) model. Considering
the feasibility and accuracy, we further propose to define the cost
function of EMD to be a generalized Kullback-Leibler divergence.
Simulation results show that our proposed method can detect DDoS
attacks by comparing EMD values with the ones computed in the case
without attacks. Moreover, our method can significantly increase the
true positive rate of detection.
Abstract: The purpose of this research is to improve the convenience of waiting for trains at level crossings and stations and to prevent accidents resulting from forcible entry into level crossings, by providing level crossing users and passengers with information that tells them when the next train will pass through or arrive. For this paper, we proposed methods for estimating operation by means of an average value method, variable response smoothing method, and exponential smoothing method, on the basis of open data, which has low accuracy, but for which performance schedules are distributed in real time. We then examined the accuracy of the estimations. The results showed that the application of an exponential smoothing method is valid.
Abstract: The stakeholders’ pressure on corporate managers to maintain firm’s profitability has created economic incentives for management to engage in earnings management practices. Therefore, this study examines the effects of audit quality and corporate governance on earnings management of quoted deposit money banks (DMBs) in Nigeria. This study specifically investigates the influence of audit tenure, audit fee, board independence, and board size on earnings management of DMBs. Explanatory research design was employed in carrying out the study while secondary data were sourced from the annual reports and accounts of all the 15 quoted DMBs in Nigerian Stock Exchange as at December 31, 2015 for a period of 10 years covering from 2006 to 2015. The data obtained for the study were analyzed using panel regression analysis approach. The findings reveal that board independence has a negative significant effect on earnings management at a 5% level of significance (p=0.002), while audit fee has a positive significant effect on earnings management at a 5% level of significance (p=0.013) and audit tenure has a negative significant effect on earnings management of DMBs at a 5% level of significance (p=0.003). Surprisingly, board size was statistically not significant at a 5% level of significance (p=0.086). The study concludes that high audit quality and sound corporate governance could improve the earnings quality of DMBs. Hence, the study recommends that the authorities saddled with the responsibility of banking supervision in Nigeria such the Securities and Exchange Commission (SEC) and CBN to advise the National Assembly in Nigeria to pass into law the three years professional requirement for audit tenure.
Abstract: Security of the smart home in terms of behavior activity pattern recognition is a totally dissimilar and unique issue as compared to the security issues of other scenarios. Sensor devices (low capacity and high capacity) interact and negotiate each other by detecting the daily behavior activity of individuals to execute common tasks. Once a device (e.g., surveillance camera, smart phone and light detection sensor etc.) is compromised, an adversary can then get access to a specific device and can damage daily behavior activity by altering the data and commands. In this scenario, a group of common instruction processes may get involved to generate deadlock. Therefore, an effective suitable security solution is required for smart home architecture. This paper proposes seamless distributed Scheme which fortifies low computational wireless devices for secure communication. Proposed scheme is based on lightweight key-session process to upheld cryptic-link for trajectory by recognizing of individual’s behavior activities pattern. Every device and service provider unit (low capacity sensors (LCS) and high capacity sensors (HCS)) uses an authentication token and originates a secure trajectory connection in network. Analysis of experiments is revealed that proposed scheme strengthens the devices against device seizure attack by recognizing daily behavior activities, minimum utilization memory space of LCS and avoids network from deadlock. Additionally, the results of a comparison with other schemes indicate that scheme manages efficiency in term of computation and communication.
Abstract: The north-eastern, Himalayan, and Eastern Ghats Belt
of India comprise of earthquake-prone, remote, and hilly terrains.
Earthquakes have caused enormous damages in these regions in the
past. A wireless sensor network based earthquake early warning
system (EEWS) is being developed to mitigate the damages caused
by earthquakes. It consists of sensor nodes, distributed over the
region, that perform majority voting of the output of the seismic
sensors in the vicinity, and relay a message to a base station to alert
the residents when an earthquake is detected. At the heart of the
EEWS is a low-power two-stage seismic sensor that continuously
tracks seismic events from incoming three-axis accelerometer signal
at the first-stage, and, in the presence of a seismic event, triggers
the second-stage P-wave detector that detects the onset of P-wave
in an earthquake event. The parameters of the P-wave detector have
been optimized for minimizing detection time and maximizing the
accuracy of detection.Working of the sensor scheme has been verified
with seven earthquakes data retrieved from IRIS. In all test cases, the
scheme detected the onset of P-wave accurately. Also, it has been
established that the P-wave onset detection time reduces linearly with
the sampling rate. It has been verified with test data; the detection
time for data sampled at 10Hz was around 2 seconds which reduced
to 0.3 second for the data sampled at 100Hz.
Abstract: In the current age of technology, information is the most precious asset of a company. Today, companies have a large amount of data. As the data become larger, access to data for some particular information is becoming slower day by day. Faster data processing to shape it in the form of information is the biggest issue. The major problems in distributed databases are the efficiency of data distribution and response time of data distribution. The security of data distribution is also a big issue. For these problems, we proposed a strategy that can maximize the efficiency of data distribution and also increase its response time. This technique gives better results for secure data distribution from multiple heterogeneous sources. The newly proposed technique facilitates the companies for secure data sharing efficiently and quickly.
Abstract: Industry accounts for one-third of global final energy demand. Crossover technologies (e.g. motors, pumps, process heat, and air conditioning) play an important role in improving energy efficiency. These technologies are used in many applications independent of the production branch. Especially electrical power is used by drives, pumps, compressors, and lightning. The paper demonstrates the algorithm of the energy analysis by some selected case studies for typical industrial processes. The energy analysis represents an essential part of energy management systems (EMS). Generally, process control system (PCS) can support EMS. They provide information about the production process, and they organize the maintenance actions. Combining these tools into an integrated process allows the development of an energy critical equipment strategy. Thus, asset and energy management can use the same common data to improve the energy efficiency.
Abstract: A very large percentage of bridge failures are attributed to scouring around bridge piers and this directly influences public safety. Experiments are carried out in a 12-m long rectangular open channel flume made of transparent tempered glass. A 300 mm thick bed made up of sand particles is leveled horizontally to create the test bed and a 50 mm hollow plastic cylinder is used as a model bridge pier. Tests are carried out with varying flow depths and velocities. Data points of various scour parameters such as scour depth, width, and length are collected based on different flow conditions and visual observations of changes in the stream bed downstream the bridge pier are also made as the scour progresses. Result shows that all three major flow characteristics (flow depth, Froude number and densimetric Froude number) have one way or other affect the scour profile.
Abstract: This paper is an attempt to develop an Integrated Mass Rapid Transit System (MRTS) for a smart city project in Western India. Integrated transportation is one of the enablers of smart transportation for providing a seamless intercity as well as regional level transportation experience. The success of a smart city project at the city level for transportation is providing proper integration to different mass rapid transit modes by way of integrating information, physical, network of routes fares, etc. The methodology adopted for this study was primary data research through questionnaire survey. The respondents of the questionnaire survey have responded on the issues about their perceptions on the ways and means to improve public transport services in urban cities. The respondents were also required to identify the factors and attributes which might motivate more people to shift towards the public mode. Also, the respondents were questioned about the factors which they feel might restrain the integration of various modes of MRTS. Furthermore, this study also focuses on developing a utility equation for respondents with the help of multiple linear regression analysis and its probability to shift to public transport for certain factors listed in the questionnaire. It has been observed that for shifting to public transport, the most important factors that need to be considered were travel time saving and comfort rating. Also, an Integrated MRTS can be obtained by combining metro rail with BRTS, metro rail with monorail, monorail with BRTS and metro rail with Indian railways. Providing a common smart card to transport users for accessing all the different available modes would be a pragmatic solution towards integration of the available modes of MRTS.
Abstract: The production and publication of scientific works have increased significantly in the last years, being the Internet the main factor of access and distribution of these works. Faced with this, there is a growing interest in understanding how scientific research has evolved, in order to explore this knowledge to encourage research groups to become more productive. Therefore, the objective of this work is to explore repositories containing data from scientific publications and to characterize keyword networks of these publications, in order to identify the most relevant keywords, and to highlight those that have the greatest impact on the network. To do this, each article in the study repository has its keywords extracted and in this way the network is characterized, after which several metrics for social network analysis are applied for the identification of the highlighted keywords.
Abstract: One of the main aims of current social robotic research
is to improve the robots’ abilities to interact with humans. In order
to achieve an interaction similar to that among humans, robots
should be able to communicate in an intuitive and natural way
and appropriately interpret human affects during social interactions.
Similarly to how humans are able to recognize emotions in other
humans, machines are capable of extracting information from the
various ways humans convey emotions—including facial expression,
speech, gesture or text—and using this information for improved
human computer interaction. This can be described as Affective
Computing, an interdisciplinary field that expands into otherwise
unrelated fields like psychology and cognitive science and involves
the research and development of systems that can recognize and
interpret human affects. To leverage these emotional capabilities
by embedding them in humanoid robots is the foundation of
the concept Affective Robots, which has the objective of making
robots capable of sensing the user’s current mood and personality
traits and adapt their behavior in the most appropriate manner
based on that. In this paper, the emotion recognition capabilities
of the humanoid robot Pepper are experimentally explored, based
on the facial expressions for the so-called basic emotions, as
well as how it performs in contrast to other state-of-the-art
approaches with both expression databases compiled in academic
environments and real subjects showing posed expressions as well
as spontaneous emotional reactions. The experiments’ results show
that the detection accuracy amongst the evaluated approaches differs
substantially. The introduced experiments offer a general structure
and approach for conducting such experimental evaluations. The
paper further suggests that the most meaningful results are obtained
by conducting experiments with real subjects expressing the emotions
as spontaneous reactions.
Abstract: Seabed instability around an offshore pipeline is one
of key factors that need to be considered in the design of offshore
infrastructures. Unlike previous investigations, a three-dimensional
numerical model for the wave-induced soil response around an
offshore pipeline is proposed in this paper. The numerical model was
first validated with 2-D experimental data available in the literature.
Then, a parametric study will be carried out to examine the effects of
wave, seabed characteristics and confirmation of pipeline. Numerical
examples demonstrate significant influence of wave obliquity on the
wave-induced pore pressures and the resultant seabed liquefaction
around the pipeline, which cannot be observed in 2-D numerical
simulation.
Abstract: The main objective of this work is to enhance the Pulsed Eddy Current (PEC) response from the aluminum structure using signal processing. Cracks and metal loss in different structures cause changes in PEC response measurements. In this paper, time-frequency analysis is used to represent PEC response, which generates a large quantity of data and reduce the noise due to measurement. Power Spectral Density (PSD) after Wavelet Decomposition (PSD-WD) is proposed for defect detection. The experimental results demonstrate that the cracks in the surface can be extracted satisfactorily by the proposed methods. The validity of the proposed method is discussed.
Abstract: In this study, a model, together with a software tool that implements it, has been developed to determine the performance ratings of employees in an organization operating in the information technology sector using the indicators obtained from employees' online study data. Weighted Sum (WS) Method and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method based on multidimensional decision making approach were used in the study. WS and TOPSIS methods provide multidimensional decision making (MDDM) methods that allow all dimensions to be evaluated together considering specific weights, allowing employees to objectively evaluate the problem of online performance tracking. The application of WS and TOPSIS mathematical methods, which can combine alternatives with a large number of dimensions and reach simultaneous solution, has been implemented through an online performance tracking software. In the application of WS and TOPSIS methods, objective dimension weights were calculated by using entropy information (EI) and standard deviation (SD) methods from the data obtained by employees' online performance tracking method, decision matrix was formed by using performance scores for each employee, and a single performance score was calculated for each employee. Based on the calculated performance score, employees were given a performance evaluation decision. The results of Pareto set evidence and comparative mathematical analysis validate that employees' performance preference rankings in WS and TOPSIS methods are closely related. This suggests the compatibility, applicability, and validity of the proposed method to the MDDM problems in which a large number of alternative and dimension types are taken into account. With this study, an objective, realistic, feasible and understandable mathematical method, together with a software tool that implements it has been demonstrated. This is considered to be preferable because of the subjectivity, limitations and high cost of the methods traditionally used in the measurement and performance appraisal in the information technology sector.
Abstract: Identification of customer requirements and their preferences are the starting points in the process of product design. Most of design methodologies focus on traditional requirements. But in the previous decade, the green products and the environment requirements have increasingly attracted the attention with the constant increase in the level of consumer awareness towards environmental problems (such as green-house effect, global warming, pollution and energy crisis, and waste management). Determining the importance weights for the customer requirements is an essential and crucial process. This paper used the analytic hierarchy process (AHP) approach to evaluate and rate the customer requirements for green products. With respect to the ultimate goal of customer satisfaction, surveys are conducted using a five-point scale analysis. With the help of this scale, one can derive the weight vectors. This approach can improve the imprecise ranking of customer requirements inherited from studies based on the conventional AHP. Furthermore, the AHP with extent analysis is simple and easy to implement to prioritize customer requirements. The research is based on collected data through a questionnaire survey conducted over a sample of 160 people belonging to different age, marital status, education and income groups in order to identify the customer preferences for green product requirements.
Abstract: Egypt suffers from a severe shortage of data and charts concerning the physical dimensions, measurements, qualities and consumer behavior. The shortage of needed information and appropriate methods has forced the Egyptian designer to use any other foreign standard when designing a product for the Egyptian consumer which has led to many problems. The urgently needed database concerning the physical specifications, measurements of the Egyptian consumers, as well as the need to support the Ergonomics given courses in many colleges and institutes with the latest technologies, is stated as the research problem. Descriptive analytical method relying on the compiling, comparing and analyzing of information and facts in order to get acceptable perceptions, ideas and considerations is the used methodology by the researcher. The research concludes that: 1. Good interaction relationship between users and products shows the success of that product. 2. An integration linkage between the most prominent fields of science specially Ergonomics, Interaction Design and Ethnography should be encouraged to provide an ultimately updated database concerning the nature, specifications and environment of the Egyptian consumer, in order to achieve a higher benefit for both user and product. 3. Chinese economic policy based on the study of market requirements long before any market activities should be emulated. 4. Using Ethnography supports the design activities creating new products or updating existent ones through measuring the compatibility of products with their environment and user expectations, While contracting a joint cooperation between military colleges, sports education institutes from one side, and design institutes from the other side to provide an ultimately updated (annually updated) database concerning some specifications about students of both sexes applying in those institutes (height, weight, etc.) to provide the Industrial designer with the needed information when creating a new product or updating an existing one concerning that category is recommended by the researcher.
Abstract: The brain’s functional connectivity while temporally non-stationary does express consistency at a macro spatial level. The study of stable resting state connectivity patterns hence provides opportunities for identification of diseases if such stability is severely perturbed. A mathematical model replicating the brain’s spatial connections will be useful for understanding brain’s representative geometry and complements the empirical model where it falls short. Empirical computations tend to involve large matrices and become infeasible with fine parcellation. However, the proposed analytical model has no such computational problems. To improve replicability, 92 subject data are obtained from two open sources. The proposed methodology, inspired by financial theory, uses multivariate regression to find relationships of every cortical region of interest (ROI) with some pre-identified hubs. These hubs acted as representatives for the entire cortical surface. A variance-covariance framework of all ROIs is then built based on these relationships to link up all the ROIs. The result is a high level of match between model and empirical correlations in the range of 0.59 to 0.66 after adjusting for sample size; an increase of almost forty percent. More significantly, the model framework provides an intuitive way to delineate between systemic drivers and idiosyncratic noise while reducing dimensions by more than 30 folds, hence, providing a way to conduct attribution analysis. Due to its analytical nature and simple structure, the model is useful as a standalone toolkit for network dependency analysis or as a module for other mathematical models.