142 research outputs found

    Authoritarianism in Russian Politics: State Reformation at Stake?

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    Russia’s political development has been mixed since the fall of Soviet Union in 1991. An optimistic burst of activity in the early 1990s pushed the country from Soviet rule toward a greater emphasis on individual rights, but the country is now widely considered to be under authoritarian rule, or at least to be moving decisively toward centralization. At best, Russia can be seen as a "hybrid regime" or "competitive authoritarianism" that blends in some elements of electoral democracy. Russia’s trajectory since 1991 is one in which a democratizing moment has been followed by a return to more centralized power and decision making by a closed set of economic and political elites (Dickovick and Eastwood, 2015: 533). However, the central argument of this study is that the current Russian order is not participatory, democratic, and liberal enough due to personalization and centralization of political and economic powers by the executive body. As a result, the Russian political culture is struggling to construct a democratic fabric for the citizens based on equality, justice, rule of law, freedom, separation of powers, and egalitarian distribution. Institutional reform or re-design in the executive body, especially in the chief executive, would be a great initiative in order to visualize as well as build a democratic and liberal Russian order

    Bangladesh's Space Age: A Strategic Turnover?

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    Bangladesh’s space age has begun with the successful launch of the Bangabandhu-1 satellite by SpaceX into orbit on 11 May, providing Bangladesh the status of one of the 57 nations having own satellite. As the country is developing in terms of economic development, growth, GDP, women empowerment, human resource development, expanding connectivity, improving communications as well as technological advancement but the future space-based Bangladesh might be going to face some sort of mixed experiences. Obviously, the satellite is going to construct our dreamt ‘Digital Bangladesh’ providing huge prospects for the nation but several internal, external, and strategic challenges cannot be ignored

    Data analytics on key indicators for the city's urban services and dashboards for leadership and decision-making

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    Cities are continuously evolving human settlements. Our cities are under strain in an increasingly urbanized world, and planners, decision-makers, and communities must be ready to adapt. Data is an important resource for municipal administration. Some technologies aid in the collection, processing, and visualization of urban data, assisting in the interpretation and comprehension of how urban systems operate. The relationship between data analytics and smart cities has come to light in recent years as interest in both has grown. A sophisticated network of interconnected systems, including planners and inhabitants, is what is known as a smart city. Data analysis has the potential to support data-driven decision-making in the context of smart cities. Both urban managers and residents are becoming more interested in city dashboards. Dashboards may collect, display, analyze, and provide information on regional performance to help smart cities development having sustainability. In order to assist decision-making processes and enhance the performance of cities, we examine how dashboards might be used to acquire accurate and representative information regarding urban challenges. This chapter culminates Data Analytics on key indicators for the city's urban services and dashboards for leadership and decision-making. A single web page with consolidated information, real-time data streams pertinent to planners and decision-makers as well as residents' everyday lives, and site analytics as a method to assess user interactions and preferences are among the proposals for urban dashboards. Keywords: -Dashboard, data analytics, smart city, sustainability

    Enhancing Prediction and Analysis of UK Road Traffic Accident Severity Using AI: Integration of Machine Learning, Econometric Techniques, and Time Series Forecasting in Public Health Research

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    This research investigates road traffic accident severity in the UK, using a combination of machine learning, econometric, and statistical methods on historical data. We employed various techniques, including correlation analysis, regression models, GMM for error term issues, and time-series forecasting with VAR and ARIMA models. Our approach outperforms naive forecasting with an MASE of 0.800 and ME of -73.80. We also built a random forest classifier with 73% precision, 78% recall, and a 73% F1-score. Optimizing with H2O AutoML led to an XGBoost model with an RMSE of 0.176 and MAE of 0.087. Factor Analysis identified key variables, and we used SHAP for Explainable AI, highlighting influential factors like Driver_Home_Area_Type and Road_Type. Our study enhances understanding of accident severity and offers insights for evidence-based road safety policies.Comment: 3

    Laluan pengembangan pelaburan di Malaysia 1970-1998

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    Ide Laluan Pengembangan Pelaburan [LDP] telah diperkenalkan oleh Dunning pada talum 1979. Hipofesis IDP menyatakan bahawa terdapat hubungan Glllara tingkat pembcUlgunan sesebuah negara (diproksikan oleh Keluaran Negara Kasar per kapita) dengan kedudukan pelaburan antarabangsanya (stok pelaburan langsung asing (PDf) bersih, iaitu FDI keillar dito/ak FDI l1lasuk). Artikel ini adalah bertujuan untuk menguji ide IDP ini bagi kes Malaysia. Hllbrmgan antara pelaburan dengan pembangunan ini akan dilihat berasaskan kajian empirikal bagi tempoh 1970-1998. Tujuannya ialah untuk menentukan sama ada PDf di Malaysia menepati jangkaan seperti apa yang disarankan dalam teorem IDP. Analisis regresi menunjukkan bahawa FDI di Malaysia memasuki tahap I dan tahap 2 daripada 5 tahap paradigma IDP dan dapatan ini menyokong paradigma IDP di Malaysia

    Pulangan,risiko dan kemeruapan sektor sekuriti diluluskan syariah : Pendekatan GARCH dan CAPM bersyarat

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    Bagi menunjukkan sistem kewangan Islam adalah satu alternatif yang terbaik, maka prestasi saham syariah perlu dikaji dun membandingkannya dengan saham konvensional. Pulangan yang tinggi akan menarik pelabur membuat pelaburan dalam sekuriti tersebut.Ini kerana pulangan kepada syarikat seterusnya dibahagikan kepada para pemegang saham dalam bentuk keuntungan dan dividen Walau bagaimanapun, pelabur juga mengetahui bahawa pelaburan yang berisiko tinggi akan menjamin pulangan yang tinggi (high risk high return).Oleh itu, kajian ini adalah satu usaha untuk mendalami pengetahuan tentang prestasi pulangan sekuriti lulus Syariah. Salah satu kajian yang perlu dilakukan ialah melihat hubungan di antara pulangan dan beta (pengukur risiko) dan peranan beta dan CAPM dalam menerangkan perbezaan keratan rentas pulangan sekuriti lulus Syariah. Kajian ini menumpukan kepada 456 sekuriti lulus Syariah yang tersenarai di Papan Utama dengan melihat hubungan bersyarat purata pulangan dan beta bagi sekuriti-sekuriti yang diluluskan oleh Majlis Penasihat Syariah. Sementara itu kemeruapan pulangan saham ditakrifkan sebagai serakan terhadap purata pulangan saham atau lebih dikenali sebagai varians. Maklumat dan pengetahuan mengenai gelagat kemeruapan pulangan saham begitu penting kepada ahli ekonomi dan para penganalisis kewangan dalam menyelesaikan beberapa masalah ekonomi yang berkaitan. Poterba dan Summers (1986) telah mengaitkan pengaruh keberterusan pulangan terhadap hubungan antara perubahan kemeruapan dengan harga saham manakala Bollerslev et. al. (1992) pula menyatakan bahawa terdapat tiga sifat yang mempengaruhi kemeruapan pulangan saham iaitu sifat keberterusan pulangan, sifat min-varians, dan sifat hubungan tidak simetri. Kajian ini menggunakan model-model keluarga ARCH untuk menganalisis gelagat kemeruapan pulangan saham lulus syariah di Bursa Saham Kuala Lumpur, Malaysia. Penganggar empirikal ini menggunakan data mengenai harga saham lulus syariah untuk setiap hunter, volume dagangan, Indeks industri Dow Jones (IZDJ), Indeks Syariah, Indeks Komposit, Kadar Faedah Antara Bank dun Kadar Faedah Antara Bank Islam. Analisis seterusnya adalah membandingkan dapatan untuk melihat hubungan antara risiko,pulangan dan kemeruapan

    EFL Learners’ Participation in Primary Schools of Coastal Areas in Bangladesh

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    Despite numerous initiatives by both governmental and non-governmental organizations, primary level students’ skills in English language are still below the expected level in Bangladesh (Hamid & Honan, 2012; Sultana, 2010). Our study examined reasons behind the limited participation of EFL (English as a Foreign Language) learners in primary level classrooms in the coastal areas of Bangladesh. To conduct the research, we followed an explanatory sequential mixed methods design (Creswell, 2014; Creswell & Creswell, 2018; Ivankova & Stick, 2007). We collected data from 37 male and 23 female students in grades four and five through questionnaire surveys and three focus group discussions (FGDs). We also collected data from five teachers through interviews and three class observations. We found that teachers had less motivation to create an interactive learning environment for the students due to heavy teaching loads and administrative assignments. Many of the students had low academic expectations and motivation, lived in poor socio-economic conditions that required them to work, and were impacted by frequent natural disasters that interrupted their regular classes. The results of our research provide insights for educationists and policymakers related to primary education in disaster-prone coastal areas as well as other rural parts of the country

    Vision-based Human Fall Detection Systems using Deep Learning: A Review

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    Human fall is one of the very critical health issues, especially for elders and disabled people living alone. The number of elder populations is increasing steadily worldwide. Therefore, human fall detection is becoming an effective technique for assistive living for those people. For assistive living, deep learning and computer vision have been used largely. In this review article, we discuss deep learning (DL)-based state-of-the-art non-intrusive (vision-based) fall detection techniques. We also present a survey on fall detection benchmark datasets. For a clear understanding, we briefly discuss different metrics which are used to evaluate the performance of the fall detection systems. This article also gives a future direction on vision-based human fall detection techniques
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