Aims: 
The purpose of the study was to seek a better insight into whether the online medium or the online activity was more important in relation to excessive online use. It is not clear whether those people who spend excessive amounts of time on the Internet are engaged in general Internet or whether excessive Internet use is linked to specific activities.
Methods:
Perceived changes in Internet use habits as function of hypothetical accessibility of favorite sites were investigated in young adults. University students (n = 130, mean age = 20.6 years) who had (on average) spent over 20 hours a week on the Internet for at least nine years completed a survey. The most favored online activities and expected quality of life without Internet access were also investigated.
Results:
Findings revealed that social networking was by far the most popular online activity, and that lack of access to their preferred online activities would drop by 65% (as measured by perceived Internet usage). Approximately one in six participants (16%) claimed they would not even switch on the computer if access to their favorite online activities were unavailable. In relation to a hypothetical question about the quality of life without Internet access, the responses were normally distributed (rather than skewed). Conclusions: These results show that time spent with Internet activity is not random and/or generalized, but appears more focused. Attraction or addiction on Internet to one or more specific behavior(s) may be a better way forward in the quest for better understanding excessive human behavior in the online environment.

Is excessive online usage a function of medium or activity? An empirical pilot study [forthcoming]

Membrane computing is a well-known research area in computer science inspired by the organization and behavior of live cells and tissues. Their computational devices, called P systems, work in parallel and distributed mode and the information is encoded by multisets in a localized manner. All these features make P systems appropriate for dealing with digital images. In this paper, some of the open research lines in the area are presented, focusing on segmentation problems, skeletonization and algebraic-topological aspects of the images. An extensive bibliography about the application of membrane computing to the study of digital images is also provided.

Membrane computing and image processing: a short survey

The purpose of this study is to identify the factors that can impact the adoption of mobile apps for teaching-learning process focusing on the girls’ school in rural India. The hypotheses were proposed and a conceptual model has been developed. There is a survey work conducted to collect the data from different respondents using a convenience sampling method. The model has been validated statistically through PLS-SEM analysis covering feedbacks of 271 effective respondents. The study highlights the impact of different antecedents of the behavioural intention of the students of using mobile applications for teaching-learning process. The results also show that among other issues, price value has insignificant influence on the intention of the girl students of the rural India. During survey feedbacks have been obtained from the 271 respondents, which is meagre compared to vastness of the population and school of rural India. Only few predictors have been considered leaving possibilities of inclusion of other boundary conditions to enhance the explanative power more than that has been achieved in the proposed model with the explanative power of 81%. The model has provided laudable inputs to the educational policy makers and technology enablers and administrators to understand the impact of the mobile applications on the rural girls’ school of India and facilitate the development of m-learning. Very few studies been conducted to explore the impact of mobile applications on the school education of rural India especially focusing on the girls’ schools.

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Adoption of mobile applications for teaching-learning process in rural girls’ schools in India: an empirical study

Bioeconomy has been presented as an alternative for sustainable development. Public policies and national bioeconomy programs have reserved an essential role for biorefineries. However, the misinterpretation of what a biorefinery might be can lead to the adoption of biased public policies, restricting its potential. Therefore, the concept of biorefinery requires a conceptual definition appropriate for the context of bioeconomy. This article aims to propose a contemporary concept for biorefinery, adjusted to the bioeconomy perspective. An epistemological review of the prefix “bio” and the base “refine” was carried out. The biorefinery concepts established in the literature were revisited and grouped by their focus on inputs, processes, or bioproducts. The required concept of biorefinery in the bioeconomy context is discussed. Our updated concept defines biorefinery as “a physical, chemical, or biological process which purifies, separates, refines, or transforms elements constituting biological assets from the kingdoms Monera, Protista, Plantae, Animalia, or Fungi, originating from the terrestrial or oceanic environment, in bioproducts for final use or that serve as raw material for other bioproducts.” Adopting this concept can promote appropriate public policies for a broader set of biorefineries and pave the way for the sociotechnical transition toward bioeconomy.

Biorefinery: A comprehensive concept for the sociotechnical transition toward bioeconomy

The samples, sand and pebble (Sediment River), were collected from their selling places in Sulaymaniyah city, Iraq Sand and pebble emanate each of 238U, 232Th, 40K, and radon naturally The radon concentration in the air (Co) and gamma-specific activity (As) of the samples were measured using passive detectors (CR-39) and gamma spectrum analyzer (3 × 3 NaI (Tl) connected to digital spectrum analyzer), respectively The mean value of the Co ± deviation of the investigated samples was 1765 ± 69 Bq/mᵌ, which is lower than the worldwide value of 300 Bq m− ᵌ reported by the IAEA However, an anomaly in Co value was found in Tanjaro (Sand) sample The mean value radon mass exhalation rate (EM) was 109 ± 05 μBq/kg/h The second part of the measuring is the gamma-specific activities (As) of each 226Ra, 232Th, and 40K The As values were ranged (43 ± 02–226 ± 02), (19 ± 01–42 ± 01), and (398 ± 02–860 ± 04) Bq/kg , respectively The mean calculated value of radium equivalent (Raeq) was 202±02 Bq/kg The annual effective dose rate of gamma (Hann) was 013 mSv/y Fortunately, the Hann value of the samples is lower than the world average value of 048 mSv/y

/pdf/natural-radioactivity-and-radon-exhalation-in-the-sediment-3lh21aa226.pdf

Natural Radioactivity and Radon Exhalation in the Sediment River Used in Sulaymaniyah Governorate, Iraq, Dwellings

Classification of Aedes aegypti (Linnaeus) and Aedes albopictus (Skuse) by humans remains challenging. We proposed a highly accessible method to develop a deep learning (DL) model and implement the model for mosquito image classification by using hardware that could regulate the development process. In particular, we constructed a dataset with 4120 images of Aedes mosquitoes that were older than 12 days old and had common morphological features that disappeared, and we illustrated how to set up supervised deep convolutional neural networks (DCNNs) with hyperparameter adjustment. The model application was first conducted by deploying the model externally in real time on three different generations of mosquitoes, and the accuracy was compared with human expert performance. Our results showed that both the learning rate and epochs significantly affected the accuracy, and the best-performing hyperparameters achieved an accuracy of more than 98% at classifying mosquitoes, which showed no significant difference from human-level performance. We demonstrated the feasibility of the method to construct a model with the DCNN when deployed externally on mosquitoes in real time.

/pdf/implementation-of-a-deep-learning-model-for-automated-ym1mnbqblq.pdf

Implementation of a deep learning model for automated classification of Aedes aegypti (Linnaeus) and Aedes albopictus (Skuse) in real time.

In todays Information Age, an application to be claimed being interoperable has many benefits and advantages. Our attempt is to propose transformation methods on spatial attributes so that interoperability between spatial data can be obtained. Interoperability state can only be obtained by equalizing two attributes utilized in identifying a location, which are coordinate of the location and LoD of the spatial data through transformation processes. We use GLOBALBASE & Google Maps as the case study to verify the proposed transformations. Through running some experiments we showed the utilizations of the proposed transformation.

Transformation of Spatial Data Format for Interoperability between GIS Applications

P system is a distributed and parallel computing model in membrane computing, processing multisets of symbol objects in a localized manner This computational model has proved to be a robust framework for modelling a variety of situations arising in very different areas, for instance, investigation of problems related to digital images In this paper, we develop a P system for handling region-based segmentation of two-dimensional hexagonal digital images motivated by a corresponding model for rectangular digital images and point out the utility of these P systems for segmenting groups of crowds

Region-based segmentation of Hexagonal digital images using membrane computing

Array P systems with permitting features

In the bio-inspired area of membrane computing, P system is a versatile model providing a rich framework for many computational problems. Array P system and its variant with parallel rewriting facilitate the study of picture languages within this area of membrane computing. Here another variant of array P system, called tabled parallel array P system (TPAP), is introduced, by endowing it with the features of parallel rewriting and tables of array-rewriting rules. The generative power of TPAP as well as the ability of this system in describing picture patterns are investigated.

Pradeep Isawasan

Papers

Implementation of a deep learning model for automated classification of Aedes aegypti (Linnaeus) and Aedes albopictus (Skuse) in real time.

Transformation of Spatial Data Format for Interoperability between GIS Applications

Region-based segmentation of Hexagonal digital images using membrane computing

Array P systems with permitting features

A Membrane Computing Model for Generation of Picture Arrays