Congestion-Aware Routing and Fuzzy-based Rate Controller for Wireless Sensor Networks

In this paper, congestion-aware routing and fuzzy-based rate controller for wireless sensor networks (WSNs) is proposed. The proposed method tries to make a distinction between locally generated data and transit data by using a priority-based mechanism which provides a novel queueing model. Furthermore, a novel congestion-aware routing using greedy approach is proposed. The proposed congestion-aware routing tries to find more affordable routes. Moreover, a fuzzy rate controller is utilized for rate controlling which uses two criteria as its inputs, including congestion score and buffer occupancy. These two parameters are based on total packet input rate, packet forwarding rate at MAC layer, number of packets in the queue buffer, and total buffer size at each node. As soon as the congestion is detected, the notification signal is sent to offspring nodes. As a result, they are able to adjust their data transmission rate. Simulation results clearly show that the implementation of the proposed method using a greedy approach and fuzzy logic has done significant reduction in terms of packet loss rate, end-to-end delay and average energy consumption

Aseptic Meningitis in Pediatrics: Epidemiologic Evaluation and Cerebrospinal Fluid Changes

ObjectiveThis study aimed at investigating seasonal variation, clinical symptoms, and cerebrospinal fluid (CSF) changes in patients with aseptic meningitis admitted in Mofid hospital between 1995 and 1996.Materials & MethodsA total of 63 children with aseptic meningitis were enrolled in the study. Their age, gender, season of the disease, etiology, clinical symptoms, CSF changes, and treatment were evaluated and  documented. Data were analyzed using SPSS 11.5.ResultsThe male to female ratio of the patients was 2.5 to 1, mean age being 6.5 years. The disease occurrence was most common in spring and summer, and the most common symptoms observed were fever (92.6%), followed by nausea and vomiting (88.88% and 68.25%), neck stiffness, neck stiffness (54%), seizure (19%), kernig sign (14.28%), Brudzinski's sign (11.11%), and 1.58% of the patients had history of head injury. Mean white blood cell count for CSF was 165/mm3 (range, 6 to 850/mm3), the common cells being mononuclear cells; mean red blood cell count was 538 (range, 0 to 8100/mm3); protein and glucose levels were within the normal ranges. Blood and CSF culture and CSF smear were negative. Prognosis was excellent and mean duration of recovery was 5 days (range, 2 to 18 days).ConclusionAlthough the clinical symptoms of aseptic meningitis are similar to those of bacterial meningitis, its prognosis is excellent. The CSF features can be used to diagnose the disease.

Engineering Privacy in Smartphone Apps: A Technical Guideline Catalog for App Developers

With the rapid growth of technology in recent years, we are surrounded by or even dependent on the use of technological devices such as smartphones as they are now an indispensable part of our life. Smartphone applications (apps) provide a wide range of utilities such as navigation, entertainment, fitness, etc. To provide such context-sensitive services to users, apps need to access users' data including sensitive ones, which in turn, can potentially lead to privacy invasions. To protect users against potential privacy invasions in such a vulnerable ecosystem, legislation such as the European Union General Data Protection Regulation (EU GDPR) demands best privacy practices. Therefore, app developers are required to make their apps compatible with legal privacy principles enforced by law. However, this is not an easy task for app developers to comprehend purely legal principles to understand what needs to be implemented. Similarly, bridging the gap between legal principles and technical implementations to understand how legal principles need to be implemented is another barrier to develop privacy-friendly apps. To this end, this paper proposes a privacy and security design guide catalog for app developers to assist them in understanding and adopting the most relevant privacy and security principles in the context of smartphone apps. The presented catalog is aimed at mapping the identified legal principles to practical privacy and security solutions that can be implemented by developers to ensure enhanced privacy aligned with existing legislation. Through conducting a case study, it is confirmed that there is a significant gap between what developers are doing in reality and what they promise to do. This paper provides researchers and developers of privacy-related technicalities an overview of the characteristics of existing privacy requirements needed to be implemented in smartphone ecosystems, on which they can base their work

Engineering Privacy in Smartphone Apps: A Technical Guideline Catalog for App Developers

With the rapid growth of technology in recent years, we are surrounded by or even dependent on the use of technological devices such as smartphones as they are now an indispensable part of our life. Smartphone applications (apps) provide a wide range of utilities such as navigation, entertainment, fitness, etc. To provide such context-sensitive services to users, apps need to access users' data including sensitive ones, which in turn, can potentially lead to privacy invasions. To protect users against potential privacy invasions in such a vulnerable ecosystem, legislation such as the European Union General Data Protection Regulation (EU GDPR) demands best privacy practices. Therefore, app developers are required to make their apps compatible with legal privacy principles enforced by law. However, this is not an easy task for app developers to comprehend purely legal principles to understand what needs to be implemented. Similarly, bridging the gap between legal principles and technical implementations to understand how legal principles need to be implemented is another barrier to develop privacy-friendly apps. To this end, this paper proposes a privacy and security design guide catalog for app developers to assist them in understanding and adopting the most relevant privacy and security principles in the context of smartphone apps. The presented catalog is aimed at mapping the identified legal principles to practical privacy and security solutions that can be implemented by developers to ensure enhanced privacy aligned with existing legislation. Through conducting a case study, it is confirmed that there is a significant gap between what developers are doing in reality and what they promise to do. This paper provides researchers and developers of privacy-related technicalities an overview of the characteristics of existing privacy requirements needed to be implemented in smartphone ecosystems, on which they can base their work

“It’s Shocking!": Analysing the Impact and Reactions to the A3: Android Apps Behaviour Analyser

The lack of privacy awareness in smartphone ecosystems prevents users from being able to compare apps in terms of privacy and from making informed privacy decisions. In this paper we analysed smartphone users' privacy perceptions and concerns based on a novel privacy enhancing tool called Android Apps Behaviour Analyser (A3). The A3 tool enables user to behaviourally analyse the privacy aspects of their installed apps and notifies about potential privacy invasive activities. To examine the capabilities of A3 we designed a user study. We captured and contrasted privacy concern and perception of 52 participants, before and after using our tool. The results showed that A3 enables users to easily detect their smartphone app's privacy violation activities. Further, we found that there is a significant difference between users' privacy concern and expectation before and after using A3 and the majority of them were surprised to learn how often their installed apps access personal resources. Overall, we observed that the A3 tool was capable the influence the participants' attitude towards protecting their privacy

Location-aware green energy availability forecasting for multiple time frames in smart buildings: The case of Estonia

Renewable Energies (RE) have gained more attention in recent years since they offer clean and sustainable energy. One of the major sustainable development goals (SDG-7) set by the United Nations (UN) is to achieve affordable and clean energy for everyone. Among the world's all renewable resources, solar energy is considered as the most abundant and can certainly fulfill the target of SDGs. Solar energy is converted into electrical energy through Photovoltaic (PV) panels with no greenhouse gas emissions. However, power generated by PV panels is highly dependent on solar radiation received at a particular location over a given time period. Therefore, it is challenging to forecast the amount of PV output power. Predicting the output power of PV systems is essential since several public or private institutes generate such green energy, and need to maintain the balance between demand and supply. This research aims to forecast PV system output power based on weather and derived features using different machine learning models. The objective is to obtain the best-fitting model to precisely predict output power by inspecting the data. Moreover, different performance metrics are used to compare and evaluate the accuracy under different machine learning models such as random forest, XGBoost, KNN, etc.Comment: The current version is submitted to Elsevier Solar Energy and is under consideration for future publicatio

Comparison between Diazepam and Phenobarbital in Prevention of Febrile Seizure: Clinical Trial

AbstractObjectiveFebrile convulsions (FC) are the most common convulsive events in childhood, occurring in 2-5% of children. About one third of these children will have  a recurrence during a subsequent febrile infection. This sudden neurologic problem is extremely frightening and emotionally traumatic for parents so some physicians try to prevent recurrence of FC by prescribing different drugs.Materials and MethodsThis is a randomized clinical trial in 85 healthy children, aged 6 months to 5 years, who were not treated before. These children received randomly either oral diazepam (0.33 mg/kg/TDS for two days during febrile illness) or continuous oral Phenobarbital (3-5mg/kg /24 h).ResultsUltimately 64 patients completed the study and were followed up for an average of 13 months (12-18 months). The rate of recurrence of febrile seizure was 18.2% in diazepam group and 32.3% in Phenobarbital group; the difference is not statistically significant (p=0.16).ConclusionThere was no significant difference between intermittent oral diazepam and continuous oral Phenobarbital for FC prevention