A Knapsack Problem Approach For Achieving Efficient Energy Consumption in Smart Grid for Endusers’ Life Style

In order to achieve an efficient energy consumption level in the residential sector of a smart grid, the end-users are equipped with various smart home energy controller technologies. The devices are provided to inform the consumers about their consumption pattern by showing or sending different kinds of consumptional information to them. This kind of information is provided to assist them in making decisions about altering their consumption behaviour or to urge them to modify their life style during peak hours. We propose that the energy home controllers should offer preferred and optimal scenarios to support end-users when making a decision about their consumption. Effective scenarios should emerge from consumer's life style and preferences. In this paper, we will apply AHP methodology to quantify the consumer's preferences for using appliances during peak periods when the price has increased, and use the Knapsack problem approach to achieve the optimal solution for managing the appliances. With this approach, not only will the cost of electricity not escalate during peak hours, but also user preferences, satisfaction and minimum change to current life style will be considered

Subjective Quality Assessments in Virtual Environments

Being able to make objective Quality of Service (QoS) judgments or assessments is a challenging and crucial activity. The process of making these assessments is compounded when the environment in which the assessments have to be made are virtual; in the sense the interacting parties might not have necessarily metwith each other physically. In a broad sense Quality of Service assessments could be broadly categorized into two areas, namely objective assessments and subjective assessments. In this paper, we propose a suite of metrics to carry out subjective quality assessment in a virtual environment

The Role of Antiepileptic Treatment in the Recurrence Rate of Seizures After First Attack: A Randomized Clinical Trial

How to Cite This Article: Assarzadegan F, Tabesh H, Hesami O, Derakhshanfar H, Beladi Moghadam N, Shoghli A, Beale A.D, Hosseini-Zijoud S.M. The Role of Antiepileptic Treatment in the Recurrence Rate of Seizures After First Attack: A Randomized Clinical Trial. Iran JChild Neurol. Spring 2015; 9(2):46-52.AbstractObjectiveEpilepsy is a serious, potentially life-shortening brain disorder that occurs in patients of all ages and races. A total of 2–4% of people have experienced seizures at least once in their lifetime. Although treatment usually begins after a seizure, it is an important question whether the first cases of seizure do need to be treated by antiepileptic drugs. In this manner, we compare the recurrence rates of epilepsy in first seizure patients treated with sodium valproic acid as an antiepileptic drug versus a placebo.Material & MethodsIn a randomized clinical trial study, 101 first seizure patients were randomly divided into two groups: one group was treated with antiepileptic drugs (sodium valproate 200mg, three times a day) and the other group was given a placebo.The recurrence rate of seizures was evaluated and compared between the groups after 6 months of follow up.ResultsEight recurrence cases were detected. All recurrence cases came from the placebo group, with four patients suffering an additional seizure after four months and between 4-6 month follow up. A comparison of recurrence rate detected a statistically significant difference between the drug group and placebo group.ConclusionOur data shows that the recurrences occurred only in the placebo group with the difference between the recurrence rates in the placebo versus drug-treated was significant. Our results suggest that drug therapy for people after their first seizure attack might reduce the probability of seizure recurrence

Intraoral mass presenting as maxillary sinus carcinoma: a case report.

Sinonasal undifferentiated carcinoma is an extremely rare malignancy of the paranasal sinuses and nasal cavity. It is of unknown etiology, and occurs more commonly in the elderly men, with a routinely shown aggressive behavior and poor prognosis for survival. Radiographically, it looks like severe osteomyelitis. Histopathologic study is essential to confirm diagnosis, and the undifferentiated histologic appearance often necessitates immunohistochemical studies for differentiation from other high-grade neoplasms. We present an 83-year-old man complaining of pain and unilateral swelling on the left side of the face due to a rare malignant tumor of maxillary sinus origin, a sinonasal undifferentiated carcinoma. He underwent hemimaxillectomy and radiotherapy, but refused chemotherapy. Maxillary sinus malignancy may be presented with unspecific symptoms mimicking sinusitis or dental pain. Coming across such symptoms, the physician or dentist must consider malignancies as well, and carry out medical and dental workups

Intelligent Decision Support System for Including Consumers’Preferences in Residential Energy Consumption Management in Smart Grid

Smart Grid is a novel initiative the aim of which is to deliver energy to the users and also to achieve consumption efficiency by means of two-way communication. The Smart Grid architecture is a combination of various hardware devices, management and reporting software tools that are combined within an ICT infrastructure. This infrastructure is needed to make the smart grid sustainable, creative and intelligent. One of the main goals of Smart Grid is to achieve Demand Response(DR) by increasing the end users' participation in decision making and increasing the awareness that will lead them to manage their energy consumption in an efficient way. Approaches proposed in the literature achieve demand response at the different levels of the Smart Grid, but no approach focuses on the users' point of view at the home level on a continuous basis and in an intelligent way to achieve demand response. In this paper, we develop such an approach by which demand response can be achieved on a continuous basis at the home level. To achieve this, the dynamic notion of price will be utilized to develop an intelligent decision-making model that will assist the users in achieving demand response

Marginal Accuracy of Lithium Disilicate Full‐Coverage Single Crowns Made by Direct and Indirect Digital or Conventional Workflows: A Systematic Review and Meta‐Analysis

Purpose Several studies have compared digital intraoral scanners and conventional impressions. The accuracy of these two methods in terms of marginal accuracy of lithium disilicate crowns is not well-established, yet. The purpose of this study was to systematically review available publications on marginal fit of single-unit, full-coverage, tooth-supported lithium disilicate restorations. Methods Pubmed, Web of Science, Cochrane, EMBASE, and Scopus were electronically searched along with a manual search. After critical appraisal, data from selected studies were extracted and mean marginal difference with a 95% confidence interval was calculated. Meta-analysis of the collected data was conducted using STATA software. Results The meta-analysis revealed similar marginal gap values in intraoral scanners with conventional groups (p>0.05) and in intraoral scanners with extraoral canners (p>0.05). Conclusion No significant difference was seen between digital and conventional impressions or intra- and extraoral scanners for marginal accuracy of lithium disilicate crowns

Machine Learning Applications: The Past and Current Research Trend in Diverse Industries

Dramatic changes in the way we collect and process data has facilitated the emergence of a new era by providing customised services and products precisely based on the needs of clients according to processed big data. It is estimated that the number of connected devices to the internet will pass 35 billion by 2020. Further, there has also been a massive escalation in the amount of data collection tools as Internet of Things devices generate data which has big data characteristics known as five V (volume, velocity, variety, variability and value). This article reviews challenges, opportunities and research trends to address the issues related to the data era in three industries including smart cities, healthcare and transportation. All three of these industries could greatly benefit from machine learning and deep learning techniques on big data collected by the Internet of Things, which is named as the internet of everything to emphasise the role of connected devices for data collection. In the smart grid portion of this paper, the recently developed deep reinforcement learning techniques and their applications in Smart Cities are also presented and reviewed

Marginal adaptation of zirconia complete-coverage fixed dental restorations made from digital scans or conventional impressions: A systematic review and meta-analysis

Statement of problem: Intraoral scanners have been increasingly used in recent years. However, the accuracy of digital scans as it affects marginal adaptation is unclear. Purpose: The purpose of this systematic review and meta-analysis was to compare the marginal adaptation of single-unit zirconia crowns fabricated with digital scans or with conventional impressions. Material and methods: The electronic databases PubMed (MEDLINE), Cochrane Central Register of Controlled Trials (CENTRAL), Web of Science (ISI), Scopus, and EMBASE were searched and complemented by a manual search. Risks of bias were assessed by using a modified methodological index for nonrandomized studies (MINORS). Mean ±standard deviation (SD) values of marginal accuracy of studies were extracted for both methods. Mean marginal difference and 95% confidence interval (CI) were calculated to evaluate the marginal accuracy of each method. Pooled data were statistically analyzed by using a random-effect model. Results: Seventeen studies were used to perform the meta-analysis. Subgroup analysis was performed based on intraoral scanners. Standardized mean marginal difference and 95% CI of each subgroup were as follows: Lava: -0.85 μm (95% CI: -1.67, -0.03) (P=.043); CEREC: -1.32 μm (95% CI: -2.06, -0.59) (P<.001); iTero: -0.44 μm (95% CI: -1.35, 0.47) (P=.338); TRIOS: -1.26 μm (95% CI: -2.02, -0.51) (P=.001); unknown scanner: -0.21 μm (95% CI: -1.14, 0.72); all studies: -0.89 μm (95% CI: -1.24, -0.54) (P<.001). Conclusions: Digital scanning of prepared teeth for single-unit zirconia restorations resulted in better marginal accuracy than conventional techniques using elastomeric impression materials

Acceptability of COVID-19 vaccination in Herat, Afghanistan

Background: COVID-19 vaccine hesitancy is one of the major concerns in the roll out of vaccines in many countries. The aim of the study was to assess the level of COVID-19 vaccine acceptability among the population in Herat, Afghanistan, the third largest city in the country. Methods: This cross-sectional study was conducted between 15 April 2021 and 20 April 2021 among the general population of Herat City to examine the acceptability rate of COVID-19 vaccine. Sample size was calculated at 555. Different variables were collected using a questionnaire developed. Data were evaluated in IBM SPSS program. Results: Only 10.63% of the participants were willing to receive COVID-19 vaccine without having any concern and reservation. 45% were willing to receive the COVID-19 vaccine. 66.5% were concerned about the vaccine and its side effects and 29% were afraid of being infected by transmission of COVID-19 through the administration of vaccine on them. Conclusion: This research demonstrates that, concerns about the vaccine, myths and misinformation are widespread which will undermine the vaccination process. This study recommends the initiation of more health-related campaigns and awareness programs by the government for general population to enhance and expedite the roll out of COVID-19 vaccine