Popularity of Tracking Device as an Anti-theft Measure and Impact of its sales on Sales of Auto Insurance Policies: Evidence from Karachi, Pakistan

In this paper attempt has been made to examine the popularity of tracking devices and its impact on the sales of automobiles insurance policies. Literature review revealed that people insure their vehicles to protect them from theft as well as from other perils such as fire, SRCC, accidental losses and third party liability. The coverage is mainly obtained to prevent theft, which has the major significance. Insurance companies have been trying since a long time to curtail the cost of theft, which is the major cause for higher premium rates. To achieve the objectives of this study Non Probability Technique known as Purposive Sampling is applied, based upon questionnaire survey from a representative sample of tracker and insurance service users. This research revealed that blending the motor insurance policies, with tracker devices, have successfully attracted the major chunk of market and have gained access to a larger segment of the market, offering packaged policies with discounted premium rates and hence the loss ratio has declined with the use of these devices, which ultimately affects the premium rates. The researchers tested the relationship between tracker sales and insurance policy sales. The research revealed significant insights into the relationship.Tracker Devices, Auto Insurance, Sales, Theft, Third Party Liability.

Performance Enhancement of Wearable Antenna Using High Impedance Surfaces

This paper presents a novel textile wearable antenna that has been designed to operate at Wi-Fi bands of 2.4GHz & 5.8GHz. Antenna performance in free space environment showed Gain of 1.8dBi at 2.4GHz and 4.5dBi at 5.8GHz. However, performance deteriorated when antenna was operated near human body which is lossy and complex in nature. For mitigating the human body effect on antenna performance, high impedance surface (HIS) was designed and integrated with this textile antenna. Due to shielding effect of HIS, antenna Gain increased to 8dBi at 2.4GHz and 9dBi at 5.8GHz. The SAR values were also reduced to 0.682W/Kg at 2.4GHz and 0.0692W/Kg at 5.8GHz for 10g tissue. The proposed antenna was also tested under bending and crumpling conditions. It was observed that antenna performance was not significantly deteriorated. The proposed textile antenna can have exciting applications in emerging wearable technologies

Characteristic Assessment of Advancement in Duties of Librarians and Function of Libraries in Data Science Era

Data sciences usually involve data management, its utilization, distribution as well as its re-utilization. All these components need to be focused while targeting data science. Thus data puts a significant burden on research institutes because it is the authority that decides the responsible for the whole course of the procedure. It is of prime importance for data science librarians serving in data-centric age to know regarding LIS principles, theories, and other related skills that are mandatory for management and support of data science. This paper sums up the reviews of researchers regarding the data science era. Moreover, this paper includes diagnostic assessment of data science environment concerning recent advancements in data science and progress in duties of librarians, presentation of detailed data, the function of data science libraries as well as librarians concerning data users. It is supposed to be an exciting era to work in a library as its role is expanding with specific new challenges. It is the need of the current period to educate librarians, library science researchers, and students regarding understanding, utility, and management of data to meet the requirements of data science librarians

Predictors of Acute Stent Thrombosis After Primary Percutaneous Coronary Intervention

OBJECTIVES To identify the specific predictors of acute stent thrombosis in patients after primary percutaneous coronary intervention.METHODOLOGY This retrospective study was carried out at the Department of Cardiology Hayatabad Medical Complex Peshawar from 1st January to 30th June 2022. All consecutive patients with an angiographically confirmed stent thrombosis were enrolled. Patients gave informed consent for the inclusion of data in this registry. Stent thrombosis was categorized according to the timing of the event as acute (occurrence within the first 24 hours after the index procedure).RESULTSA total of 400 patients were included in the study. Age ranged between 35-70 years, with a mean age of 52.5. There were 260(65%) males and 140(35%) females, with male to female ratio of 1.8:1. All patients underwent primary PCI with stent implantation. According to the elapsed time since stent implantation, 42(10.5%) patients presented with acute stent thrombosis after primary percutaneous coronary intervention. The mean time to develop acute stent thrombosis after primary PCI was ±4.5 hours (range 3-6 hours). In most STEMI patients, 340(85%) received a loading dose of clopidogrel at the time of the index PCI. In 23(54.7%) patients, acute stent thrombosis occurred within 6 hours, 10(23.8%) within 12 hours, 6(14.2%) within 18 hours and 3(7.1%) after clopidogrel loading.CONCLUSIONInadequate stent expansion or mal-opposition, diabetes mellitus, chronic kidney disease, and female gender were the strong predictors of acute stent thrombosis

Impact and Scope of Open Access Research Data: Perceptions of Library and Information Professionals

This study aims to prove that those scholarly articles belonging to subjects with changing proportions of open-access implementation have an incredible research impact if the research articles are openly accessible online than by paid access. This study also explores the impact of open access research data in Pakistan through the library and information science (LIS) professionals\u27 perception. The foundation of this study includes surveying the research method. The LIS professionals were surveyed to assess their perception towards the possibly better impact of open access research data than non-OA ones. This study indicates that free-access research data have a better research impact and scope than those that have not openly accessible. This study is part of a Ph.D. dissertation. This study\u27s respondents were library professionals working in public sector university libraries of Pakistan, so the library professionals are working in the libraries of colleges, schools, and private sector universities. Data should only be made open and placed online when there is a clear demand for it. Academic institutions should focus on releasing open data. Academic institutions should provide tools that make it easier for the researcher to look inside open datasets

Serious Games in Science Education. A Systematic Literature Review

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Deep Semisupervised Teacher-Student Model Based on Label Propagation for Sea Ice Classification

In this article, we propose a novelteacher–student-based label propagation deep semisupervised learning (TSLP-SSL) method for sea ice classification based on Sentinel-1 synthetic aperture radar data. For sea ice classification, labeling the data precisely is very time consuming and requires expert knowledge. Our method efficiently learns sea ice characteristics from a limited number of labeled samples and a relatively large number of unlabeled samples. Therefore, our method addresses the key challenge of using a limited number of precisely labeled samples to achieve generalization capability by discovering the underlying sea ice characteristics also from unlabeled data. We perform experimental analysis considering a standard dataset consisting of properly labeled sea ice data spanning over different time slots of the year. Both qualitative and quantitative results obtained on this dataset show that our proposed TSLP-SSL method outperforms deep supervised and semisupervised reference methods

Synovial sarcoma of cervicodorsal spine: A case report

Synovial sarcoma is a soft-tissue sarcoma. Its involvement of the spine is extremely rare. We report a 40 year old male who presented with shoulder pain and progressive weakness in all four limbs for six months with a visible, slowly growing bulge in his upper back. On examination he had quadriparesis and diffuse sensory deficit. MRI of the cervical spine showed a large soft tissue mass, iso to hypointense, extending into the neural canal, compressing the cord. The mass had a few internal areas of contrast enhancement with extension into the right paraspinal regions involving the vertebral bodies. Sub-periosteal spine dissection was done. Tumour was primarily extradural, involving and extending from paraspinal soft tissues to the posterior arches, laminae and spinous processes of the verteberae, with their destruction. Gross radical removal of the visible mass was done, followed by three cycles of radiation therapy. Excisional biopsy showed synovial sarcoma TYPE II. In conclusion, synovial sarcomas should be kept in the differentials of a mass arising in spinal axis

Efficient Fire Segmentation for Internet-of-Things-Assisted Intelligent Transportation Systems

[EN] Rapid developments in deep learning (DL) and the Internet-of-Things (IoT) have enabled vision-based systems to efficiently detect fires at their early stage and avoid massive disasters. Implementing such IoT-driven fire detection systems can significantly reduce the corresponding ecological, social, and economic destruction; they can also provide smart monitoring for intelligent transportation systems (ITSs). However, deploying these systems requires lightweight and cost-effective convolutional neural networks (CNNs) for real-time processing on artificial intelligence (AI)-assisted edge devices. Therefore, in this paper, we propose an efficient and lightweight CNN architecture for early fire detection and segmentation, focusing on IoT-enabled ITS environments. We effectively utilize depth-wise separable convolution, point-wise group convolution, and a channel shuffling strategy with an optimal number of convolution kernels per layer, significantly reducing the model size and computation costs. Extensive experiments on our newly developed and other benchmark fire segmentation datasets reveal the effectiveness and robustness of our approach against state-of-the-art fire segmentation methods. Further, the proposed method maintains a balanced trade-off between the model efficiency and accuracy, making our system more suitable for IoT-driven fire disaster management in ITSs.Muhammad, K.; Ullah, H.; Khan, S.; Hijji, M.; Lloret, J. (2023). Efficient Fire Segmentation for Internet-of-Things-Assisted Intelligent Transportation Systems. IEEE Transactions on Intelligent Transportation Systems. 24(11):13141-13150. https://doi.org/10.1109/TITS.2022.32038681314113150241