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Supply Chain Management (SCM) consists of handling and optimizing all the facets of the supply chain process of goods and services. Modern SCM is reaping the benefits from the emerging and growing Internet of Things (IoT) field. IoT technology can automate and digitalize the supply chain processes to get maximum operational efficiencies by reducing operating costs. The mass proliferation of IoT devices has revolutionized supply chains. IoT devices in the supply chain process track and trace shipments using the latest real-time monitoring technologies, including GPS. IoT devices are also used for asset management using NFC technology and RFID tags. Overall, IoT devices are used in almost every stage of the supply chain process. Research on IoT-based SCM is still in the growing phase. A lot of technical work is currently being published on IoT-based SCM, but a few Systematic Literature Reviews (SLRs) have been found for IoT-based SCM. The holistic view of IoT-based SCM with detailed analysis is still not reported in any review. This paper addresses this knowledge gap by presenting an SLR on IoT-based SCM with a detailed analysis of IoT-based SCM from 2018 to 2022. This review covers the aspects of IoT-based SCM, such as application domains, technologies, sensors, and devices used to implement IoT-based SCM systems. The SLR findings will assist future researchers and practitioners interested in IoT-based SCM by offering an in-depth study of the literature on IoT-based SCM, including helpful insights on challenges, benefits, and economic and business implications.

Neonatal hemochromatosis (NH) due to Gestational alloimmune liver disease (GALD) is a rare form of fulminant liver disease of unknown cause characterized by diffuse deposition of iron in the liver and extra hepatic sites without any evidence of increased iron intake. Neonatal cholestasis is characterized by persistent elevation of conjugated bilirubin. It can be caused by infections, biliary atresia, by toxins or by metabolic disorders of the liver. GALD is rarely reported as a cause of fulminant neonatal cholestasis. We present three cases of infants who presented with neonatal cholestasis and were found to have NH as well.

Antiphospholipid syndrome (APS) presenting with chronic thrombosis is rare in children. We present a 2-year-old child with APS who had chronic thrombosis of portovenous system with extra hepatic portal hypertension (EHPHT) and had multiple episodes of melena and hematemesis contraindicating use of anticoagulation.

peer-reviewed, Background: Elevated pre-operative neutrophil: lymphocyte ratio (NLR) has been identified as a predictor of survival in patients with hepatocellular and colorectal cancer. The aim of this study was to examine the prognostic value of an elevated preoperative NLR following resection for oesophageal cancer. Methods: Patients who underwent resection for oesophageal carcinoma from June 1997 to September 2007 were identified from a local cancer database. Data on demographics, conventional prognostic markers, laboratory analyses including blood count results, and histopathology were collected and analysed. Results: A total of 294 patients were identified with a median age at diagnosis of 65.2 (IQR 59-72) years. The median pre-operative time of blood sample collection was three days (IQR 1-8). The median neutrophil count was 64.2 × 10-9/litre, median lymphocyte count 23.9 × 10-9/litre, whilst the NLR was 2.69 (IQR 1.95-4.02). NLR did not prove to be a significant predictor of number of involved lymph nodes (Cox regression, p = 0.754), disease recurrence (p = 0.288) or death (Cox regression, p = 0.374). Furthermore, survival time was not significantly different between patients with high (≥ 3.5) or low (< 3.5) NLR (p = 0.49). Conclusion: Preoperative NLR does not appear to offer useful predictive ability for outcome, disease-free and overall survival following oesophageal cancer resection., PUBLISHED, peer-reviewed

Machine learning with its high precision algorithms, Precision agriculture (PA) is a new emerging concept nowadays. Many researchers have worked on the quality and quantity of PA by using sensors, networking, machine learning (ML) techniques, and big data. However, there has been no attempt to work on trends of artificial intelligence (AI) techniques, dataset and crop type on precision agriculture using internet of things (IoT). This research aims to systematically analyze the domains of AI techniques and datasets that have been used in IoT based prediction in the area of PA. A systematic literature review is performed on AI based techniques and datasets for crop management, weather, irrigation, plant, soil and pest prediction. We took the papers on precision agriculture published in the last six years (2013-2019). We considered 42 primary studies related to the research objectives. After critical analysis of the studies, we found that crop management; soil and temperature areas of PA have been commonly used with the help of IoT devices and AI techniques. Moreover, different artificial intelligence techniques like ANN, CNN, SVM, Decision Tree, RF, etc. have been utilized in different fields of Precision agriculture. Image processing with supervised and unsupervised learning practice for prediction and monitoring the PA are also used. In addition, most of the studies are forfaiting sensory dataset to measure different properties of soil, weather, irrigation and crop. To this end, at the end, we provide future directions for researchers and guidelines for practitioners based on the findings of this review

Recently, cyber-attacks have been extensively seen due to the everlasting increase of malware in the cyber world. These attacks cause irreversible damage not only to end-users but also to corporate computer systems. Ransomware attacks such as WannaCry and Petya specifically targets to make critical infrastructures such as airports and rendered operational processes inoperable. Hence, it has attracted increasing attention in terms of volume, versatility, and intricacy. The most important feature of this type of malware is that they change shape as they propagate from one computer to another. Since standard signature-based detection software fails to identify this type of malware because they have different characteristics on each contaminated computer. This paper aims at providing an image augmentation enhanced deep convolutional neural network (CNN) models for the detection of malware families in a metamorphic malware environment. The main contributions of the paper's model structure consist of three components, including image generation from malware samples, image augmentation, and the last one is classifying the malware families by using a convolutional neural network model. In the first component, the collected malware samples are converted binary representation to 3-channel images using windowing technique. The second component of the system create the augmented version of the images, and the last component builds a classification model. In this study, five different deep convolutional neural network model for malware family detection is used., Comment: 18 pages

Purpose: Identity fraud is a growing issue for online retail organisations. The literature on this issue is scattered, and none of the studies presents a holistic view of identity fraud management practices in online retail context. Therefore, this study aims at investigating the identity fraud management practices and presents a comprehensive set of practices for e-tail sector. Methodology: A systematic literature review approach was adopted, and the articles were selected through pre-set inclusion criteria. We synthesised existing literature to investigate identity fraud management in e-tail sector. Findings: The research finds that literature on practices for identity fraud management is scattered. Findings also reveal that firms assume identity fraud issues as a technological challenge, which is one of the major reasons for a gap in effective management of identity frauds. This research suggests e-tailers to deal this issue as a management challenge and counter strategies should be developed in technological, human and organisational aspects. Research limitations: This study is limited to the published sources of data. Studies, based on empirical data, will be helpful to support the argument of this study, additionally future studies are recommended to include a wide number of databases. Originality: This research makes unique contributions by synthesising existing literature at each stage of fraud management and encompasses social, organisational and technological aspects. It will also help academicians understanding a holistic view of available research and opens new lines for future research. Practical implications: This research will help e-tail organisations to understand the whole of identity fraud management and help them develop and implement a comprehensive set of practices at each stage, for effective management identity frauds.

Effective and efficient staff scheduling has always been a challenging issue, especially in health service organisations. Both the extremes of staff shortage and overage have an adverse impact on the performance of healthcare organisations. In this case, an electronic and systematic staff scheduling (e-rostering) system is the often seen as the best solution. Unless an organisation has an effective implementation of such a system, possible cost savings, efficiency, and benefits could be minimal. This study is aimed to research key success factors for the successful effective implementation of an electronic rostering system, especially at healthcare organisations. A case study research method was used to evaluate critical success factors for effectively implementing an e-rostering system. The data were collected through interviews and observations. The findings indicate that technical support, an effective policy, leadership, clear goals and objectives, gradual change, evidence of the advantages of the new system, senior management support, and effective communication are the critical success factors in implementing an e-rostering system in healthcare organisations. Prior to this study, no such factors were grounded in the current context, so this research would help in bridging the gap towards effective implementation of an e-rostering system in the healthcare sector. This research also suggests future studies in different cultures and contexts.

This paper means to inspect the regression between the Price to Book ratio as a proxy for earning management and payout proportion as a proxy to dividend policy. This paper utilizes multivariate analysis to examine the relationship between the price to book ratio and dividend policy. Using 11 years’ annual data from 2006-2016, this paper delivers new confirmation demonstrating that timely payment of dividend has a positive impact on the reputation of the company in the market. Dividend payment boosts up investors’ confidence to invest in the company. This study helps the corporate superintendents and stock financial experts to focus on the relationship of the dividend. No past review has handled the issue of the contingent relationship between the price to book ratio and payout proportion in Pakistani Industry and specifically on cement, food and oil and gas sectors.Abstrak dalam Bahasa Indonesia : Tulisan ini bermaksud untuk meneliti regresi antara Price to Book Ratio sebagai proksi untuk manajemen penghasilan dan proporsi pembayaran sebagai proksi untuk kebijakan dividen.Penelitian ini menggunakan analisis multivariat untuk menguji hubungan antara Price to Book Ratio dan kebijakan dividen. Dengan menggunakan data tahunan selama 11 tahun dari 2006-2016, artikel ini memunculkan suatu konfirmasi yang menunjukkan bahwa pembayaran dividen tepat waktu memiliki dampak positif pada reputasi perusahaan di pasar. Pembayaran dividen meningkatkan kepercayaan investor untuk berinvestasi di perusahaan. Studi ini membantu pengawas perusahaan dan ahli keuangan saham untuk fokus pada hubungan dividen. Belum ada penelitian sebelumnya yang menangani masalah hubungan kontingen antara Price to Book Ratio dan proporsi pembayaran dalam Industri di Pakistan dan khususnya pada sektor semen, pangan dan minyak dan gas.

In this dissertation, I analyze behavior of two types of financial intermediaries that play critical roles in capital allocation: ratings agencies and merger advisors. Each type of intermediary survives due to (assumed) informational advantages relative to firms and investors. In the following chapters, I analyze how differences in information between market participants and intermediaries lead to signaling behavior related to privately-observed quality. My results explain some seemingly-anomalous aspects of financial markets, and provide a framework for assessing the impact intermediaries can have on efficient capital allocation.In the first chapter, I examine whether rating agencies strategically manipulate the informativeness of bond ratings in response to competition from private lenders. I model a monopolistic rating agency that caters to a low-quality marginal customer with uninformative ratings. High-quality customers prefer informative ratings but are captive customers of the rating agency in the absence of competition from private lenders. With competition from private lenders, the rating agency uses informative ratings to keep high-quality customers in public markets. The model also suggests that the ratings sector dampens the impact of capital supply shocks, and offers a strategic pricing rationale for the controversial practice of issuing unsolicited credit ratings. In the second chapter, I test predictions of the model using a measure of informativeness based on the impact of unexpected ratings on a debt issuer's borrowing cost. I analyze two events that increased the relative supply of private vs.\ public lending: the temporary shutdown of the high-yield market in 1989 and legislation in 1994 that reduced barriers to interstate bank lending. After each event, I find that the informativeness of ratings increased for issuers whose relative supply of private vs.\ public capital increased most. In the third chapter, I analyze how acquiring firms select and

Aim: The aim of this study was to investigate how national culture influence internal communication of university. Methodology: A qualitative approach was chosen to conduct this research. Semi structured interview were taken. Interviews were taken by face to face, skype and phone call. Ethical approach was considered while interpreting the data. Findings: Our study showed that high power distance has negative impact on internal communication. We found that high power distance creates block between supervisors and subordinates to share information. Thus it creates barriers for effective communication flow and hinders organizations development. Our study also found that power distance is available in both countries but the degree of power distance is varied from one to another. In our study we also found that Individualism and collectivism has effect on internal communication. Our study showed that Individualistic or collectivistic decision making process of university effect internal communication of university in both countries. Previous study suggests that high power distance country tends to be a collectivistic country. Though the result is not always true. However, we found that true in our study. Contribution: The study adopts employee centric approach to explore the effects of culture on internal communication. This is an important contribution to previous researches that focused on internal communication from different perspectives, inclusion of cultural differences on internal communication has added value to the research field. Moreover, this paper contributes insights in cultural differences as well as employee perspective and by doing so it suggests theorist and practitioners that how internal communication can relate to employee’s engagement in different cultural perspectives. Limitations: The major limitation of this study was that this study only focused on Hofstede’s power distance and individualism as cultural dimensions. Other dimensions were

Online Social Networks (OSNs) have become an important part of daily digital interactions for more than half billion users around the world. Online social networks exhibit many of the characteristics of human societies in terms of forming relationships and sharing personal information. However, current OSNs mainly assume binary, static, and symmetric relationship of equal value between the connected users. In human societies, social relationships are of varying tie strength, dynamic, and asymmetric in nature. The lack of an effective mechanism to represent diversity in social relationships leads to undesirable consequences of users personal information leakage to the unwanted audience and raises privacy concerns. The issue of privacy has received significant attention in both the research literature and the mainstream media. In this dissertation, we conduct a user study to analyze users' attitude towards personal information disclosure in online social networks. The findings reveal that personal information disclosure depends on the quality of relationship among the users and it can be easily inferred from user interaction pattern in online social networks. We propose a theoretical framework that addresses the aforementioned issue from a social science perspective and exploits existing social theories of Goffman, Granovetter, and Nissenbaum to model social privacy for OSNs users. Based on this theoretical framework, we developed SOCPRI (SOCial PRIvacy) ontology to represent diversity in social relationships in online social networks. This model regulates personal information disclosure on the basis of the social role and the relationship quality between the OSNs users. The model is evaluated by translating competency questions into description logic (DL) queries to demonstrate the applicability of our approach. The results of ontology evaluation demonstrate the appropriateness of our ontology against proposed requirements.

Online Social Networks (OSNs) have become an important part of daily digital interactions for more than half billion users around the world. Unconstrained by physical spaces, OSNs offer to social web users new means to communicate, interact, and socialize. Online social networks exhibit many of the characteristics of human societies in terms of forming relationships and sharing personal information. However, current OSNs mainly assume binary, static, and symmetric relationship of equal value between the connected users. In human societies, social relationships are of varying tie strength, dynamic, and asymmetric in nature. The lack of an effective mechanism to represent diversity in social relationships leads to undesirable consequences of users personal information leakage to the unwanted audience and raises privacy concerns. The issue of privacy has received significant attention in both the research literature and the mainstream media. In this dissertation, we conduct a user study to analyze users' attitude towards personal information disclosure in online social networks. The study gives insight into user's information sharing behavior and interaction patterns in online social networks. The findings reveal that personal information disclosure depends on the quality of relationship among the users and it can be easily inferred from user interaction pattern in online social networks. We propose a theoretical framework that addresses the aforementioned issue from a social science perspective and exploits existing social theories of Goffman, Granovetter, and Nissenbaum to model social privacy for OSNs users. Based on this theoretical framework, we developed SOCPRI (SOCial PRIvacy) ontology to represent diversity in social relationships in online social networks. This model regulates personal information disclosure on the basis of the social role and the relationship quality between the OSNs users. The model is evaluated by translating competency questions into descr

Information technology has dramatically increased online business opportunities; however these opportunities have also created serious risks in relation to information security. Previously, information security issues were studied in a technological context, but growing security needs have extended researchers' attention to explore the management role in information security management. Various studies have explored different management roles and activities, but none has given a comprehensive picture of these roles and activities to manage information security effectively. So it is necessary to accumulate knowledge about various managerial roles and activities from literature to enable managers to adopt these for a more holistic approach to information security management. In this paper, using a systematic literature review approach, we synthesised literature related to management's roles in information security to explore specific managerial activities to enhance information security management. We found that numerous activities of management, particularly development and execution of information security policy, awareness, compliance training, development of effective enterprise information architecture, IT infrastructure management, business and IT alignment and human resources management, had a significant impact on the quality of management of information security. Thus, this research makes a novel contribution by arguing that a more holistic approach to information security is needed and we suggest the ways in which managers can play an effective role in information security. This research also opens up many new avenues for further research in this area.

Online social networking is the latest craze that has captured the attention of masses, people use these sites to communicate with their friends and family. These sites o er attractive means of social interac- tions and communications, but also raise privacy concerns. This paper examines user's abilities to control access to their personal information posted in online social networks. Online social networks lack common mechanism used by individuals in their real life to manage their privacy. The lack of such mechanism signi cantly a ects the level of user control over their self presentation in online social networks. In this paper, we present social interaction based audience segregation model for online so- cial networks. This model mimics real life interaction patterns and makes online social networks more privacy friendly. Our model uses type, fre- quency, and initiation factor of social interactions to calculate friendship strength. The main contribution of the model is that it considers set of all possible interactions among friends and assigns a numerical weight to each type of interaction in order to increase or decrease its contribu- tion in calculation of friendship strength based on its importance in the development of relationship ties.

The classical Clarke model of mobile radio reception assumes a constant mobile velocity. We, in this paper, relax the assumption of constant mobile velocity to allow the mobile to have constant acceleration and derive expression for the non-stationary autocorrelation function of the channel process in general 2-dimensional (2D) scattering environments. Under suitable assumptions, an expression for Wigner-Ville spectrum is obtained in isotropic scattering environment which suggests that the Wigner-Ville spectrum is a natural generalization of the Clarke's model to constant mobile acceleration scenario.