1,362,908 research outputs found
Interview with Sadiq Khan: “London must have a seat at the table during the negotiations to leave the EU”
Get PDFWhat will Brexit mean for the city of London? In an interview with EUROPP’s editor Stuart Brown, the Mayor of London, Sadiq Khan, discusses his new ‘London is Open’ campaign, the effect of Brexit on Londoners, and whether there is a case for London having more say over how the money it generates in tax revenue is spent
YPFS Lessons Learned Oral History Project: An Interview with Sadiq Malik
Get PDFSuggested Citation Form: Malik, Sadiq, 2020. “Lessons Learned Interview. Interview by Maryanne Lynch. Yale Program on Financial Stability Lessons Learned Oral History Project. November 11, 2020. Transcript. https://ypfs.som.yale.edu/library/ypfs-lesson-learned-oral-history-project-interview-malik-sadi
Sayyid Sadiq interview, 13 August 2016
No full textSayyid Sadiq was born in northern Lebanon in the area of Batron where family worked in agriculture. He has three brothers and one sister. He owns a gas station in Berea. His grandfather was a brick layer in Cleveland. He came first to the US (Mississippi) in 1977 because of the Civil War in Lebanon. After graduation from the University of Mississippi with a BS degree, he worked for a while in Chicago in steel. Sayyid went back to Lebanon and then to Saudi Arabia. He came back to US in 1989 to Cleveland where he has relatives in Berea. He met his wife, who used to live Detroit, in Cleveland and got married in 1989. They have two sons that graduated from universities and left Cleveland. He thinks that the story of the Arabs in Cleveland a story of success
Sayyid Sadiq interview, 13 August 2016
No full textSayyid Sadiq was born in northern Lebanon in the area of Batron where family worked in agriculture. He has three brothers and one sister. He owns a gas station in Berea. His grandfather was a brick layer in Cleveland. He came first to the US (Mississippi) in 1977 because of the Civil War in Lebanon. After graduation from the University of Mississippi with a BS degree, he worked for a while in Chicago in steel. Sayyid went back to Lebanon and then to Saudi Arabia. He came back to US in 1989 to Cleveland where he has relatives in Berea. He met his wife, who used to live Detroit, in Cleveland and got married in 1989. They have two sons that graduated from universities and left Cleveland. He thinks that the story of the Arabs in Cleveland a story of success
Trust aware crowd associated network-based approach for optimal waste management in smart cities
Get PDFThis is an accepted manuscript of an article published by CRC Press (Taylor & Francis) in Security and Organization within IoT and Smart Cities (in press), available online: https://www.routledge.com/Security-and-Organization-within-IoT-and-Smart-Cities/Ghafoor-Curran-Kong-Sadiq/p/book/9780367893330
The accepted version of the publication may differ from the final published version.Waste management has been a serious issue in urban areas due to the population growth. An appropriate solid waste management system is needed to improve the cleanliness of the environment. On the other hand, the rapid growth of the wide adoption of the Internet of Things (IoT) within the context of smart cities has motivated numerous number of studies investigating new solutions that could be helpful in mitigating and solving the waste management issue. Despite the existence of such methods have been introduced and used in managing waste’s location, volume and the optimal path for collection, yet these IoT based technologies are vulnerable to misinformation kinds of cyber attack. Consequently these types of attacks will yield crucial impact on the decided collection path and the frequency of garbage trucks visiting the fake reported waste points, which obviously costs money and time. Hence, this chapter proposes a trusted crowd associated network architecture that uses a group of components to monitor waste and provide optimum collection route for the garbage truck. Netlogo a multi-agent platform has been used to simulate a real time monitoring on waste management as a proof of concept. Our proposed approach measures the waste level data then updates and records them continuously. An optimal route will then be provided to the garbage truck for the optimal waste’s collection once a certain number of bins have reached a predefined threshold (combination of weight and height values). Three simulation scenarios are defined, implemented, and their results have been validated. The performance measure shows that our proposed solution could provide an aid waste management companies in reducing cost and time in the waste collection process, which supports the integration plans of IoT technology within smart cities
Revitalising the Australian Shipping Industry through Tax Reform: Alchemy or Piracy?
No full textThe Australian Federal Government has recently passed reforms to the shipping industry. These reforms are aimed at removing barriers to investment in Australian shipping, fostering global competitiveness and securing a stable maritime skills base. The shipping reform package adopts a two pronged approach designed to achieve its stated goals by providing both a ‘stick’ and ‘carrot’ to industry participants. First, the ‘stick’ is delivered via the provision of tighter regulation of coastal trading operations through a new licencing system, along with the introduction of a civil penalty regime and an increase in existing penalties. Second, the ‘carrot’ is delivered via taxation incentives available to vessels registered in Australia where the registrant meets certain specified criteria. These incentives, introduced through amendments to the Income Tax Assessment Act 1997 and the Income Tax Assessment Act 1936 and contained in the Tax Laws Amendment (Shipping Reform) Act 2012, provide five key tax incentives to the shipping industry. From 1 July 2012, amendments give effect to an income tax exemption for qualifying ship operators, accelerated depreciation of vessels, roll-over relief from income tax on the sale of a vessel, an employer refundable tax offset, and an exemption from royalty withholding tax for payments made for the lease of certain shipping vessels
Adapting authoritarianism: institutions and co-optation in Egypt and Syria
No full textThis PhD thesis compares Egypt and Syria’s authoritarian political systems. While the tendency in social science political research treats Egypt and Syria as similarly authoritarian, this research emphasizes differences between the two systems with special reference to institutions and co-optation. Rather than reducibly understanding Egypt and Syria as sharing similar histories, institutional arrangements, or ascribing to the oft-repeated convention that “Syria is Egypt but 10 years behind,” this thesis focuses on how events and individual histories shaped each states current institutional strengthens and weaknesses. Specifically, it explains the how varying institutional politicization or de-politicization affects each state’s capabilities for co-opting elite and non-elite individuals.
Beginning with a theoretical framework that considers the limited utility of democratization and transition theoretical approaches, the work underscores the persistence and durability of authoritarianism. Chapter two details the politicized institutional divergence between Egypt and Syria that began in the 1970s. Chapter three and four examines how institutional politicization or de-politicization affects elite and non-elite individual co-optation in Egypt and Syria. Chapter five discusses the study’s general conclusions and theoretical implications.
This thesis’s argument is that Egypt and Syria co-opt elites and non-elites differently because of the varying degrees of institutional politicization in each governance system. Rather than view one country as more politically developed than the other, this work argues that Syria’s political institutions are more politicized than their Egyptian counterparts. Syria’s political arena is, thus, described as politicized-patrimonialism. Syria’s politicized-patrimonial arena produces uneven co-optation of elites and non-elites as they are diffused through competing institutions. Conversely, the Egyptian political arena remains highly personalized as weak institutions and individuals are manipulated and molded according to the president’s ruling clique. This is referred to as personalized-patrimonialism. As a consequence, Egypt’s political establishment demonstrates more flexibility in ad hoc altering and adapting its arena depending on the emergence of crises.
This study’s theoretical implications suggest that, contrary to modernization and democratization theory’s adage that institutions lead to a political development, politicized institutions within a patrimonial order actually hinder regime adaptation because consensus is harder to achieve and maintain. It is within this context that Egypt’s de-politicized institutional framework advantages its top political elite. In this reading of Egyptian and Syrian politics, Egypt’s personalized political arena is more adaptable than Syria’s. These conclusions do not indicate that political reform is a process underway in either state
Application of remote sensing methods for discrimination of surficial sand types in Qatar oeninsula, the Arabian Gulf
No full textThe main objective of this work was to investigate the effectiveness of digital processing of Landsat-5 TM data in producing high-quality images for mapping various surficial sand types based on their spectral signatures. To achieve this objective, Landsat-5 TM imagery data were acquired from two dates, one in February 1987 and the other in June 1990. These data were processed on a SUN 4/260 workstation using ERDAS 7.5 software. The applied image processing techniques include preprocessing for radiometric and geometric correction, various enhancement methods, classification and accuracy assessment. A Geographic Information System (GIS) was used to compile data captured and reduced from Landsat TM imagery analysis, together with data from other sources. Spectral measurement of selected surficial sand types was carried out in four different areas of Qatar. These are the western area, the northern tip, the northeastern coast and the southeastern coast. One hundred and forty measurements of spectral reflectances were recorded in the field for various sediment exposures representing the main sand types in the four study areas. From these sand types 53 representative samples were collected for laboratory investigations. These samples were subjected to grain size analyses, X-ray diffraction and laboratory measurement of spectral reflectances. Successful, accurate and detailed geological mapping of these Quaternary sands was achieved by use of a set of diverse false-color composite (FCC) images and by principal component (PC) analysis and image classification. The use of a three-band combination of six non-thermal TM bands indicates that the combination of a visible band (1 or 3), near and mid-infrared bands provides the best discrimination of sand classes. The outcrop of ancient rock types is also revealed. Thus, the results of the remote sensing studies are interpreted in the light of the geologic and tectonic setting of Qatar Peninsula. The work revealed that the surficial aeolian sands can be categorized into three main types, namely-(i) sabkha-derived, salt-rich quartz sands, (ii) beach-derived, calcareous sand and (iii) quartz-rich dune sands. Each of these types has a specific spectral signature affected by the mineralogical composition, grain size, erosional maturity and the mode of occurrence. Such results could be useful to discriminate other surficial deposits in similar environmental conditions prevailing in and lands.</p
Enhancement performance of random forest algorithm via one hot encoding for IoT IDS
Get PDFThe random forest algorithm is one of important supervised machine learning (ML) algorithms. In the present paper, the accuracy of the results of the random forest (RF) algorithm has been improved by the use of the One Hot Encoding method. The Intrusion Detection System (IDS) can be defined as a system that can predict security vulnerabilities within network traffic and is located out of range on a network infrastructure. It does not affect the efficiency of the built-in network because it analyzes a copy of the built-in traffic flow and reports results to the administrator by giving alerts. However, since IDS is a listening system only, it cannot take automatic action to prevent an attack or security vulnerability detected from infecting the system, it provides information about the source address to start the break-in, the address of the target and the type of suspected attack. The IoTID20 dataset is used to verify the improved algorithm, where this dataset is having three targets, the proposed system is compared with the state-of-art approaches and shows superiority over them
IoT Intrusion Detection Using Modified Random Forest Based on Double Feature Selection Methods
No full textOne of the fast-expanding technology today is the Internet of Things (IoT). It is very necessary, to protect these machines from adversaries and unwanted entry and alteration. Intrusion Detection Systems (IDS) are techniques that can be used in information systems to monitor identified threats or anomalies. The challenge that arises is that the IDS should detect attacks on time in high-speed network traffic data. This paper proposed a modified IDS in IoT environments based on hybrid feature selection techniques for the random forest that can be used to detect intrusions with high speed and good accuracy. IoTID20 dataset is used which has three target classes which are the binary class as normal or abnormal and the classes of categories and sub-categories for the binary class. The highest-ranked attributes in the dataset are selected and the others are reduced, to minimize execution time and improve accuracy, the number of trees in the random forest classifier is reduced to 20, 25, and 20 for binary, category, and sub-category respectively. The trained classifier is then tested and achieved accuracy approaches 100% for the binary target prediction, 98.7% for category and accuracy ranges from 78.1% to 95.2% for the sub-category target prediction. The proposed system is evaluated and compared with previous ones and showed its performance
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