Miracle-dz/UniFAR-FTUs huggingface dataset:
PROFITABILITAS, LEVERAGE, KOMPOSISI DEWAN KOMISARIS, KOMITE AUDIT, DAN KOMPENSASI RUGI FISKAL TERHADAP PENGHINDARAN PAJAK PADA PERUSAHAAN PERBANKAN

Tax avoidance has been a main concern of almost in the world. It is mostly done by tax payer due to its legality. This study aims to analyze factors affecting tax avoidance (i.e, profitability, leverage, independent bord, audit committee, and fiscal loss compensation) with firm size as a control variable. Implementing purposive sampling approach, this study ended-up with 30 companies for 2011-2015 period (i.e., 150 observations). By using OLS regression, the findings shows that profitability influences positively on tax avoidance, meanwhile, leverage and fiscal loss compensation affect negatively on tax avoidance. Moreover, corporate governace mechanisms (i.e., independent board and audit committee) and firm size as a control variable do not have a significant influence on tax avoidance. Therefore, this study contribute to providing empirical evidence on factors affecting tax avoidance in Indonesian banking companies.
Boosting Political Trust with Direct Democracy? The Case of the Finnish Citizens’ Initiative

Complementing representative democracy with direct-democratic instruments is perceived to boost levels of political trust. This was why Finland in 2012 introduced an agenda initiative, which gives citizens the right to propose legislation and thereby provides citizens a say between elections. However, it remains unclear whether involvement in such mechanisms helps restore political trust and what factors shape developments in political trust during involvement. This article contributes to this research agenda by examining how using the Finnish agenda initiative affected developments in political trust. The study uses two surveys to determine developments in political trust: a four-wave panel survey (n = 809 - 1419) and a cross-sectional survey (n = 481) where the perceived change method is used. The results suggest that using the citizens’ initiative did not necessarily cause positive developments in political trust. Nevertheless, positive developments in political trust occurred when users achieved their intended aim and/or the process was seen as fair, which shows that direct-democratic instruments can increase levels of political trust under some circumstances.
Improving a Hybrid Method of Indoor Propagation Modeling for Wireless Communications Systems

Propagation prediction is very important in the design of wireless communication systems. A combined ray tracing and Finite Difference Time Domain (FDTD) method is improved on modeling the indoor radio propagation by applying Perfectly Matched Layer (PML) Absorbing Boundary Conditions (ABCs) to FDTD grid. Thus, more accurate propagation prediction can be obtained.
Improving Software Defined Cognitive and Secure Networking

Traditional communication networks consist of large sets of vendor-specific manually configurable devices. These devices are hardwired with specific control logic or algorithms used for different network functions. The resulting networks comprise distributed control plane architectures that are complex in nature, difficult to integrate and operate, and are least efficient in terms of resource usage. However, the rapid increase in data traffic requires the integrated use of diverse access technologies and autonomic network operations with increased resource efficiency. Therefore, the concepts of Software Defined Networking (SDN) are proposed that decouple the network control plane from the dataforwarding plane and logically centralize the control plane. The SDN control plane can integrate a diverse set of devices, and tune them at run-time through vendor-agnostic programmable Application Programming Interfaces (APIs). This thesis proposes software defined cognitive networking to enable intelligent use of network resources. Different radio access technologies, including cognitive radios, are integrated through a common control platform to increase the overall network performance. The architectural framework of software defined cognitive networking is presented alongside the experimental performance evaluation. Since SDN enables applications to change the network behavior and centralizes the network control plane to oversee the whole network, it is highly important to investigate SDN in terms of security. Therefore, this thesis finds the potential security vulnerabilities in SDN, studies the proposed security platforms and architectures for those vulnerabilities, and presents future directions for unresolved security vulnerabilities. Furthermore, this thesis also investigates the potential security challenges and their solutions for the enabling technologies of 5G, such as SDN, cloud technologies, and virtual network functions, and provides key insights into increasing the security of 5G networks.
Synthetic signature generation for automatic signature verification

Learning to write is complex and usually starts with lines and scribbles. Before reaching a mature handwriting, children start to know the letters’ shapes and their sequence, although the children’s motor control is not yet accurate. Modeling this behavior in a mathematically way would allow to understand the mechanical processes from the initial thought of signing to its complete fulfillment. For instance, statistical models of a particular muscle could gain a better understanding of its general behavior when a stimulus is applied. The kinematical response of an executed movement is also a source of information about the human reaction. Indeed, these characteristics could be mathematically modeled according to the literature in order to design synthetically human movements. On the other hand, handwriting signature is used as a biometric trait to authenticate the user identity. However, the signature-based biometric systems are not used in practical applications due to their lower performance compared to other biometric technologies. Therefore, it is often preferred to use other traits such as iris, fingerprint or face. As a bridge between synthesis of biometric data and human modeling, innovative methods are addressed in this dissertation to generate synthetic handwriting signatures following the insights learnt from the motor equivalence theory. As such, in this Thesis several procedures are proposed to generate i) fully synthetic signature databases and ii) duplicated signatures from a single real specimen. The goal of the proposed methods is to verify whether the generated signatures are able to introduce realistic intra and inter-personal variability in signature-based biometric systems as well as to certify their human-like appearance. For these purposes, machine-oriented and human-oriented evaluations are discussed in the frameworks used in this document.
Built environment exposures of adults in the moving to opportunity experiment

Abstract This article describes environmental exposures of adult participants in the Moving to Opportunity (MTO) for Fair Housing experiment over a four to seven year period from baseline to the interim evaluation. The MTO experiment randomized participants living in public housing or private assisted housing at baseline into experimental and control groups and provided a housing voucher for experimental group participants to move to neighbourhoods with less than 10% of the population below the poverty line. However, few studies have examined how this move affected exposures to health promoting environments. We used data on residential locations of MTO participants and archival data on the built and food environment to construct environmental exposure variables. MTO participants in the experimental and Section 8 groups lived in neighbourhoods with higher food prices, less high intensity development and more open space relative to the control group. The findings suggest that housing policies can have potential health consequences by altering health-related environmental exposures.
From concurrent state machines to reliable multi-threaded Java code

• A submitted manuscript is the author's version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers.
Prescriptive Safety-Checks through Automated Proofs for Control-Flow Integrity

Embedded software today is pervasive: they can be found everywhere, from coffee makers and medical devices, to cars and aircraft. Embedded software today is also open and connected to the Internet, exposing them to external attacks that can cause its Control-Flow Integrity (CFI) to be violated. Control-Flow Integrity is an important safety property of software, which ensures that the behavior of the software is not inadvertently changed. The violation of CFI in software can cause unintended behaviors, and can even lead to catastrophic incidents in safety-critical systems. This dissertation develops a two-part approach for CFI: (i) prescribing source-code safetychecks, that prevent the root-causes of CFI, that programmers can insert themselves, and (ii) formally proving CFI for the machine-code of programs with source-code safety-checks. First, our prescribed safety-checks, when applied, prevent the root-causes of CFI, thereby enabling software to recover from CFI violations in a customizable way. In addition, our prescribed safety-checks are visible to programmers, empowering them to ensure that the behavior of their software is not inadvertently changed by the prescribed safety-checks. However, programmer-inserted safety-checks may be incomplete. Thus, current techniques for proving CFI, which assume that safety-checks are complete, may not work. Second, this dissertation develops a logic approach that automates formal proofs of CFI for the machine-code of software containing both source-code CFI safety-checks and system calls. We extend an existing trustworthy Hoare logic with new proof rules, proof tactics, and a novel proof-search algorithm, which exploit the principle of local reasoning for safety properties to automatically generate CFI proofs for the machine-code of programs compiled with our prescribed source-code safety-checks. To the best of our knowledge, our approach to CFI is the first to combine programmer-visible source-code enforcement mechanisms for CFI–enabling programmers to customize them and observe that their software is not inadvertently changed–with machine-code proofs of CFI that can be automated, and that does not require a trusted or verified compiler to ensure its proven properties hold in machine-code.
Bayesian networks for the analysis of inpatient admissions

A care pathway is defined as a complex intervention for the organisation of care processes for a specific group of patients during a specific period. Although the analysis of care pathways has been shown its benefits in clinical practices, little attention has been devoted to study how it can contribute to the optimization of the use of resources. In particular here we focus on the analysis of the history of a large number of patients’ admissions, i.e. of data that belong to the routine flow of information that all hospital provide to the Local Healthcare Agency. One goal is the identification of the most likely sequence of wards/clinics for a patient; in fact, knowing which wards/clinics are more interrelated can be useful for a better hospital organization. Moreover we suggest the use of Bayesian Networks to predict the care pathway that each patient will undertake, given his/her history.
ADVANCED AND RAPID DEVELOPMENT OF DYNAMIC ANALYSIS TOOLS FOR JAVA

Low-level bytecode instrumentation techniques are widely used in many software-engineering tools for the Java Virtual Machine (JVM), that perform some form of dynamic program analysis, such as profilers or debuggers. While program manipulation at the bytecode level is very flexible, because the possible bytecode transformations are not restricted, tool development based on this technique is tedious and error-prone. As a promising alternative, the specification of bytecode instrumentation at a higher level using aspect-oriented programming (AOP) can reduce tool development time and cost. Unfortunately, prevailing AOP frameworks lack some features that are essential for certain dynamic analyses. In this article, we focus on three common shortcomings in AOP frameworks with respect to the development of aspect-based tools - (1) the lack of mechanisms for passing data between woven advices in local variables, (2) the support for user-defined static analyses at weaving time, and (3) the absence of pointcuts at the level of individual basic blocks of code. We propose @J, an annotation-based AOP language and weaver that integrates support for these three features. The benefits of the proposed features are illustrated with concrete examples.
PELAKSANAAN EKSEKUSI SERTIPIKAT HAK TANGGUNGAN DALAM UPAYA PENYELESAIAN KREDIT MACET DI PENGADILAN NEGERI

Dalam lingkungan perbankan suatu kredit digolongkan sebagai kredit macet adalah semenjak tidak ditepatinya atau dipenuhinya ketentuan yang tercantum dalam perjanjian kredit, yaitu apabila debitur selama tiga kali berturut-turut tidak membayar angsuran dan bunganya. Salah satu cara untuk mengatasi adanya kredit macet tersebut, maka jalan yang paling efektif ditempuh oleh pihak bank dalam rangka mengembalikan uang yang di pinjamnya adalah dengan cara melalui eksekusi terhadap sertipikat hak tanggungan sebagai mana di atur dalam undang-undang No 4 tahun 1996. Bentuk eksekusi adalah parate executie, bahwa pelaksanaan parate executie merupakan cara termudah dan sederhana bagi kreditor untuk memperoleh kembali piutangnnya, manakala debitor cidera janji dibandingkan dengan eksekusi yang melalui bantuan atau campur tangan Pengadian Negeri. Tujuan penulisan tesis ini adalah: (1) Untuk menganalisa Pengadilan Negeri dalam menjalankan eksekusi hak tanggungan. (2) Untuk menganalisa akibat hukum yang timbul sebagai konsekuensi dari tugas Pengadilan Negeri dalam menjalankan eksekusi jaminan Hak Tanggungan untuk menyelesaikan kredit macet. Jenis penelitian yang digunakan dalam tesis ini adalah yuridis normatif. Dalam penelitian ini juga digunakan pendekatan perundang-undangan (Statute Approach) dan pendekatan konsep (conceptual approach) yaitu penulis ingin menganalisa tentang pelaksanaan eksekusi sertifikat hak tanggungan dalam upaya penyelesaian kredit macet di pengadilan Negeri kemudian seluruh data yang ada dianalisa secara deskriptif kualitatif sehingga mendapat jawaban kesimpulan akhir dari rumusan masalah penelitian yang diteliti. Hasil penelitian dalam tesis ini adalah: (1) Pengadilan Negeri dalam menjalankan eksekusi sertifikat hak tanggungan tidak saja meliputi sebagaimana ketentuan yang diamanatkan dalam Pasal 6 Undang-Undang Hak Tanggungan, Pasal 224 HIR/258 RBg, juga mamberikan pertimbangan hukum terhadap kreditor dan debitor. Kemudian dalam menyikapi permasalahan mengenai eksekusi Hak Tanggungan tersebut dengan berlandaskan pada ketentuan Pasal 218 (2) RBg maka dalam hal debitor/ termohon lelang tidak bersedia keluar dari obyek Hak Tanggungan atau jaminan atau barang yang dilelang maka cukup mengajukan permohonan kepada Ketua Pengadilan Negeri untuk dilakukan eksekusi pengosongan dan hal ini dalam beberapa kesempatan telah dilaksanakan dan berjalan dengan baik, sekalipun dalam proses atau pelaksanaan eksekusi Hak Tanggungan tersebut salah satunya dilakukan dengan bantuan kekuatan hukum. (3) Akibat hukum yang timbul sebagai konsekuensi dari tugas Pengadilan Negeri dalam menjalankan eksekusi jaminan Hak Tanggungan untuk menyelesaikan kredit macet adalah debitor harus patuh untuk melunasi hutangnya, bila tidak patuh maka dipaksa melalui lelang, cekal dan atau paksa badan dan kalau keberatan terhadap eksekusi dapat mengajukan gugatan, sedangkan terhadap kreditor/bank yang tidak puas atas pengurusan hah tanggungan dapat mengurus sendiri piutangnya, serta terhadap Pihak Ketiga yang keberatan dapat mengajukan perlawanan (derdenverzet).
How an unequal intra-firm resources distribution affect market share

Purpose The purpose of this paper is to address how marketing assets and resources of the firm perform under different product (brand) innovation conditions using the dynamic marketing capabilities (DMC) research perspective. The study contributes to the DMC research stream showing the effects and performance of heterogeneous firm drivers and resources. Academic research to date has paid a little attention to the interrelationship between market share as a performance metric, dynamic capabilities and product (brand) innovation. The current study bridges this knowledge gap by empirically validating the effects of DMC on market share performance output using panel data for 753 retail food brands. Design/methodology/approach The model was initially fitted with the β regression analysis and cluster analysis in the second step of the estimation procedure. The results of simulation by Monte Carlo experimentation are discussed. Findings The findings show that firms leverage their marketing capabilities unequally in the multi-brand portfolios, which leads to an unequal intra-firm distribution of assets and resources. The research contributes to the understanding of the brand competitive dynamics and appropriate deployment of assets and resources for improved firm performance. Originality/value These findings are useful for both academics and practitioners because they address new and future research. In doing so, the authors advance the firm performance and branding literature with extension in the DMC literature.
Implementing ChatBots using Neural Machine Translation techniques

Conversational agents or chatbots (short for chat robot) are a branch of Natural Language Processing (NLP) that has arisen a lot of interest nowadays due to the extent number of applications in company services such as customer support or automatized FAQS and personal asistent services, for instance Siri or Cortana. There are three types: rule-based models, retrieval-based models and generative-based models. The difference between them is the freedom they have at the time of generating an answer given a question. The chatbot models usually used in public services are rule-based or retrieval-based given the need to guarantee quality and adecuate answers to users. But these models can handle only conversations aligned with their previous written answers and, therefore, conversations can sometimes sound artificial if it goes out of the topic. Generative-based models can handle better an open conversation which makes them a more generalizable approach. Promising results have been achieved in generative-based models by applying neural machine translation techniques with the recurrent encoder/decoder architecture. In this project is implemented, compared and analyzed two generative models that constitute the state of the art in neural machine translation applied to chatbots. One model is based on recurrence with attention and the other is based exclusively in attention. Additionally, the model based exclusively on recurrence has been used as a reference. Experiments show that, as in translation, an architecture based only in attention mechanisms obtains better results than the recurrence based models.
Talent management: a Delphi study of assessing and developing GenZ hospitality leaders

This study aims to examine how hospitality human resource (HR) professionals assess talent when recruiting college students, how MIT programs are structured and how recruiters perceive GenZ compared to Millennials. ,A Delphi approach was used to collect the opinions of experts in the area of hospitality recruiting and talent development. ,Results showed integrity and strong work ethic are top descriptors to define talent, and prior performance and soft skills are top items assessed when hiring talent. The participants view GenZ as desiring work-life balance, tech savvy, interested in social responsibility, more accepting of differences, wanting higher salaries and more tech savvy than Millennials. ,Recruiters highly value prior work experience so students should be encouraged to pursue internships with companies they are interested in working for upon graduation. Providing mock interviews and networking events can help students better their soft skills. Organizations using MIT programs should use realistic job previews in the selection process and make regular coaching and mentoring a key part of the program. Hospitality organizations should place emphasis on GenZ’s quest for work-life balance and find ways to take advantage of their technology savviness. ,This study is one of the first to understand how hospitality organizations’ MIT programs are structured. It is one of the few to examine how talent is defined and assessed by hospitality HR professionals and compare HR professionals’ perceptions of GenZ versus Millennials.
Are executive stock option exercises driven by private information

In this study, we investigate the extent to which exercise of executive stock options is based upon private information. Contrary to popular belief, we find that shares are held more than 30 days following over a quarter of options exercised. Partitioning the data, we find weak evidence that decisions to exercise and sell immediately are prompted by bad news and stronger evidence that decisions to exercise and hold for at least 30 days are prompted by good news. Enhancing the power of our tests by considering several factors important to exercise decisions, we find that the higher the opportunity costs of early exercise as measured by the time-value of options, the greater the trading profits to executives. We also find that the greater the disguise provided by incentives to diversify and consume as measured by the depth of options in the money, the greater the trading profits to executives who exercise and sell. Turning to non-exercise decisions, we find that a strategy of holding options rather than shares to exploit good news yields positive abnormal returns consistent with theoretical predictions in the absence of dividends.
Cassandra's Twin: What Does the Data Predict?

This paper examines what type of insights can be extracted from a given dataset. This analysis is intended to encourage those collecting data to engineer their collection processes with data usability in mind. It is also meant to caution researchers against the pitfalls of trying to squeeze out more information from data than the data actually warrants. The ideas presented are illustrated through a concrete example of using CDC’s Behavioral Risk Factor Surveillance System (BRFSS) dataset to identify risk factors associated with hypertension. A complete end-to-end predictive modeling process is described in detail from data conversion and pre-processing, to model building, and interpretation of results. Python code to process the data as well as Matlab code to build, train, and evaluate the models are included in full and are sufficiently general in nature to be used for other analyses beyond hypertension.