Miracle-dz/UniFAR-FTUs huggingface dataset:
URBAN AND PERI-URBAN DAIRY FARM HOUSEHOLD WILLINGNESS TO PAY FOR DAIRY COWS INSURANCE

Studying willingness to pay for dairy cows insurance gives an opportunity for the assessment of insurance markets. This is particularly essential in developing countries where livestock insurance markets are either non-existent or weak because of uncertainties about the insurance product and risk behavior of potential clients. In this paper, based on survey data collected from urban and peri-urban dairy-farm households in northern Ethiopia, we investigate the way willingness to pay for dairy cattle insurance is correlated with various factors. After performing robustness checks for competing models, results from the preferred Hurdle-count model are presented and discussed. Dairy cattle insurance adoption was found to be positively correlated with household income, dairy cattle price and dairy farm area. Some of these key factors such as income and farm area may create opportunities for economies of scale in dairy cattle farming. While higher income explains the purchase of more of a ‘luxury good’, i.e., insurance premium, spacious dairy farm allows expansion that eventually induces economies of scale. The positive correlation of price with willingness to pay for higher premiums may be related to the behavior of risk-averting farmers paying higher insurance premiums for their high value (higher price) dairy cattle. Improved and better access to credit that eases liquidity constraints was also found to be positively associated with the number of dairy cattle farm households would want to insure. Dairy cattle farm households’ willingness to pay can provide valuable insight into their risk behavior, adoption of insurance and risk premiums and the promotion of dairy insurance schemes.
Rational hierarchical planning and coordination in multi-agent systems.

Multi-agent planning involves agents planning to achieve a set of common goals. In dynamic environments, agents are required to make autonomous decisions at execution time. Coordination is necessary to manage the interdependencies between activities performed by all agents and to achieve intended goals. This thesis uses a framework that incorporates notions from game theory and Hierarchical Task Network planning to achieve a degree of coordination and ensure that the agents exhibit som e form of rational behavior. The utility-based approach incorporates spatiotemporal factors in assessing the utility of various desired goals, and in selecting the appropriate intentions. To test the proposed approach, a multi-agent urban disaster simulation environment is used where rescue agents cooperate to extinguish fires, save injured agents, and clear blocked roads. These tests show that in many cases, the proposed approach has outperformed other approaches that rely on different heuristics in planning and coordination.
Circuit Techniques for Low-Power and Secure Internet-of-Things Systems

The coming of Internet of Things (IoT) is expected to connect the physical world to the cyber world through ubiquitous sensors, actuators and computers. The nature of these applications demand long battery life and strong data security. To connect billions of things in the world, the hardware platform for IoT systems must be optimized towards low power consumption, high energy efficiency and low cost. With these constraints, the security of IoT systems become a even more difficult problem compared to that of computer systems. A new holistic system design considering both hardware and software implementations is demanded to face these new challenges. In this work, highly robust and low-cost true random number generators (TRNGs) and physically unclonable functions (PUFs) are designed and implemented as security primitives for secret key management in IoT systems. They provide three critical functions for cryptographic systems including runtime secret key generation, secure key storage and lightweight device authentication. To achieve robustness and simplicity, the concept of frequency collapse in multi-mode oscillator is proposed, which can effectively amplify the desired random variable in CMOS devices (i.e. process variation or noise) and provide a runtime monitor of the output quality. A TRNG with self-tuning loop to achieve robust operation across -40 to 120 degree Celsius and 0.6 to 1V variations, a TRNG that can be fully synthesized with only standard cells and commercial placement and routing tools, and a PUF with runtime filtering to achieve robust authentication, are designed based upon this concept and verified in several CMOS technology nodes. In addition, a 2-transistor sub-threshold amplifier based ”weak” PUF is also presented for chip identification and key storage. This PUF achieves state-of-the-art 1.65% native unstable bit, 1.5fJ per bit energy efficiency, and 3.16% flipping bits across -40 to 120 degree Celsius range at the same time, while occupying only 553 feature size square area in 180nm CMOS. Secondly, the potential security threats of hardware Trojan is investigated and a new Trojan
AN INNOVATIVE DATA QUERY SYSTEM FOR COMMON INTERESTS OF NEIGHBOURS

Internet recognition bakes an essential motivation towards peer to determine file talking about. For understanding the peer to determine file talking about system, an important qualifying qualifying criterion to is efficiency of file location. Inside our work we submit a peer to determine file talking about system that's closeness-aware additionally to Interest-clustered based on structured peer to determine system. It forms close nodes to cluster after which groups general interest nodes into sub-cluster that is founded on hierarchical topology and apply a wise file replication to boost file query effectiveness. The forecasted system can keep each and every advantage of distributed hash tables above unstructured peer to determine systems. It's closeness-aware additionally to Interest-clustered utilizes an intellectual file replication to boost file research competence and places files sticking with the same interests with one another which makes them available through routing function. The device will progress intra-sub-cluster file searching completely through several approaches. It evolves an overlay for every group that bond lesser capacity nodes towards advanced capacity nodes for spread file querying during remaining from of node overload. Recommended system utilizes range of positive file data to make sure that file requester can recognize whether requested for file reaches its close by nodes.
Sorting Effects of Broad-Based Equity Compensation

We examine the sorting role of broad-based equity pay using detailed employee-level data. We propose trust in management as an important characteristic over which equity pay sorts employees, as such pay typically leaves employees with concentrated positions in employer stock and therefore more exposed to the outcomes of management’s actions. Consistent with this conjecture, we find that the relation between employees’ perceptions of management’s credibility and voluntary turnover intentions is significantly stronger in the presence of a broad-based equity plan. Our findings provide insight into how broad-based equity pay can improve firm performance despite theoretical challenges regarding its incentive effects. This paper was accepted by Suraj Srinivasan, accounting.
Stress Recognition from Heterogeneous Data

In modern society, the stress of an individual has been found to be a common problem. Continuous stress can lead to various mental and physical problems and especially for the people who always face emergency situations (e.g., fireman): it may alter their actions and put them in danger. Therefore, it is meaningful to provide the assessment of the stress of an individual. Based on this idea, the Psypocket project is proposed which is aimed at making a portable system able to analyze accurately the stress state of an individual based on his physiological, psychological and behavioural modifications. It should then offer solutions for feedback to regulate this state.The research of this thesis is an essential part of the Psypocket project. In this thesis, we discuss the feasibility and the interest of stress recognition from heterogeneous data. Not only physiological signals, such as Electrocardiography (ECG), Electromyography (EMG) and Electrodermal activity (EDA), but also reaction time (RT) are adopted to recognize different stress states of an individual. For the stress recognition, we propose an approach based on a SVM classifier (Support Vector Machine). The results obtained show that the reaction time can be used to estimate the level of stress of an individual in addition or not to the physiological signals. Besides, we discuss the feasibility of an embedded system which would realize the complete data processing. Therefore, the study of this thesis can contribute to make a portable system to recognize the stress of an individual in real time by adopting heterogeneous data like physiological signals and RT
The Extended Friday the 13th Effect in the US Stock Returns

The classical Friday the 13th Effect refers to a calendar anomaly of financial markets which is generated by the fear of bad luck shared by the superstitious investors. As a result of their behavior, the returns from the supposed unlucky day of Friday the 13th are significant lower than those from the other Fridays. The superstition could also affect the returns from the trading days there are adjacent to Friday the 13th. In order to avoid the bad luck, some investors sell their stocks a trading day before and their transactions lead to a fall of the prices. Those who are reluctant to buy stocks on Friday the 13th delay such transactions to the next trading day causing prices to rise. In time, the knowledge about this pattern could induce significant changes in investors’ behavior, even to those that are not superstitious. Once become aware that one trading day before Friday the 13th the stock prices are usually low, many investors would prefer to sell two or three trading days before. There also were investors that would buy stocks not one trading day after Friday the 13th, when the prices are expected to be high, but two or three trading days after. Other investors could exploit the opportunities to buy cheap on Friday the 13th or one trading day before or to sell high one trading day after and their transactions could attenuate the abnormal returns from these days. In such ways the classical form of Friday the 13th Effect could be replaced by an extended form which consists in abnormal returns for a specific time interval that starts some trading days before the supposed unlucky day and ends some trading days after. This paper explores the behavior of the stock returns of 42 companies, from seven sectors of the United States economy, in the period January 2010 – March 2019, for a time interval that starts three trading days before Friday the 13th and ends three trading days after. The results indicate, for many of them, significant low returns in some trading days before Friday the 13th and/or significant high returns some trading days after. We also found some particularities of the extended Friday the 13th Effect among the seven sectors.
Computer-Aided Design of a Switchable True Time Delay (TTD) Line With Shunt Open-Stubs

This paper presents a new technique to design switchable true time delay (TTD) lines using periodic shunt open-stubs, shorter than a quarter wavelength at the highest frequency of interest. Structural parameters are obtained by minimizing the group delay variation and maximizing the return loss over the operating band. Advantages of the proposed design are low insertion loss, higher 1 dB compression point, and less number of switches compared to the conventional designs. To verify the proposed technique, 2-states and 8-states TTD lines are fabricated for L- and S-band applications. For the 8-states delay networks, measured insertion losses are smaller than 1.9 dB at 3 GHz. Return losses are more than 10 dB over 1–4 GHz band. Measured maximum time delay is 84 ps for the 8-states delay lines with a step size of 10 ps. All the TTDs operate as linear device at least up to 23 dBm.
Détection et suivi de personnes par vision omnidirectionnelle : approche 2D et 3D

Dans cette these, nous traiterons du probleme de la detection et du suivi 3D de personnes dans des sequences d'images omnidirectionnelles, dans le but de realiser des applications permettant l'estimation de pose 3D. Ceci necessite, la mise en place d'un suivi stable et precis de la personne dans un environnement reel. Dans le cadre de cette etude, on utilisera une camera catadioptrique composee d'un miroir spherique et d'une camera perspective. Ce type de capteur est couramment utilise dans la vision par ordinateur et la robotique. Son principal avantage est son large champ de vision qui lui permet d'acquerir une vue a 360 degres de la scene avec un seul capteur et en une seule image. Cependant, ce capteur va engendrer des distorsions importantes dans les images, ne permettant pas une application directe des methodes classiquement utilisees en vision perspective. Cette these traite de deux approches de suivi developpees durant cette these, qui permettent de tenir compte de ces distorsions. Elles illustrent le cheminement suivi par nos travaux, nous permettant de passer de la detection de personne a l'estimation 3D de sa pose. La premiere etape de nos travaux a consiste a mettre en place un algorithme de detection de personnes dans les images omnidirectionnelles. Nous avons propose d'etendre l'approche conventionnelle pour la detection humaine en image perspective, basee sur l'Histogramme Orientes du Gradient (HOG), pour l'adapter a des images spheriques. Notre approche utilise les varietes riemanniennes afin d'adapter le calcul du gradient dans le cas des images omnidirectionnelles. Elle utilise aussi le gradient spherique pour le cas les images spheriques afin de generer notre descripteur d'image omnidirectionnelle. Par la suite, nous nous sommes concentres sur la mise en place d'un systeme de suivi 3D de personnes avec des cameras omnidirectionnelles. Nous avons fait le choix de faire du suivi 3D base sur un modele de la personne avec 30 degres de liberte car nous nous sommes imposes comme contrainte l'utilisation d'une seule camera catadioptrique.
Slow Philosophy in Tourism Development in Latvia: The Supply Side Perspective

ABSTRACT Slow philosophy, which has gained popularity in recent years, is used to inform tourism development. Yet, its actual implementation is limited mostly to Cittáslow (Slow Cities) and Slow Food related projects. Therefore, it is questionable whether the ideas of slow philosophy are viable in tourism development outside the Cittáslow and Slow Food contexts. This article attempts to identify opportunities and challenges for using slow philosophy in tourism development in Latvia focusing on the supply side perspective. This article contributes to the tourism destination development literature and gives practical insights for tourism destination managers.
Design, Engineering and Optimization of a Grid-Tie Multicell Inverter for Energy Storage Applications

Multilevel converters have found many applications within renewable energy systems thanks to their unique capability of generating multiple voltage levels. However, these converters need multiple DC sources and the voltage balancing over capacitors for these systems is cumbersome. In this work, a new grid-tie multicell inverter with high level of safety has been designed, engineered and optimized for integrating energy storage devices to the electric grid. The multilevel converter proposed in this work is capable of maintaining the flying capacitors voltage in the desired value. The solar cells are the primary energy sources for proposed inverter where the maximum power density is obtained. Finally, the performance of the inverter and its control method simulated using PSCAD/EMTDC software package and good agreement achieved with experimental data.
TRUTHFUL DETECTION OF PACKET DROPPING ATTACK IN MANET

: Mobility and portable nature of Mobile Ad hoc Networks (MANET) has increased its popularity by two fold. MANETs have become a commonly used network for various applications. But this advantage suffers with serious security concerns, mainly a wireless transmission medium perspective where such networks may be subject to packet dropping. Mobility and portable nature of Mobile Ad hoc Network may also lead to link failure. During packet forward, valuable packets may be dropped by malicious nodes present in the network. Link error and malicious packet dropping are the two sources for packet losses in MANET. A node can act maliciously and could harm the packet sending process. Ad hoc on demand distance vector (AODV) is a popular routing protocol but is exposed to well known packet dropping attack. Proposed system introduces a new protocol named secured Ad hoc on demand distance vector (SAODV), which can truthfully detect packet dropping attack in MANET. SAODV can detect malicious nodes by identifying dropping of routing and data packet. Packet dropping due to both link error and presence of malicious nodes can detect by SAODV. It also provides importance to preserve privacy of data.
Using Hidden Markov Models and Rule-based Sensor Mediation on Wearable eHealth Devices

Improvements in sensor miniaturization allow wearable devices to provide more functionality while also being more comfortable for users to wear. The Samsung Simband©, for example, has 6 different sensors Electrocardiogram (ECG), Photoplethysmogram (PPG), Galvanic Skin Response (GSR), BioImpedance (Bio-Z), Accelerometer and a thermometer as well as a modular sensor hub to easily add additional ones. This increased number of sensors for wearable devices opens new possibilities for a more precise monitoring of patients by integrating the data from the different sensors. This integration can be influenced by failing or malfunctioning sensors and noise. In this paper, we propose an approach that uses Hidden Markov Models (HMM) in combination with a rule-based engine to mediate among the different sensors’ data in order to allow the eHealth system to compute a diagnosis on the basis of the selected reliable sensors. We also show some preliminary results about the accuracy of the first stage of the proposed model. Keywords–Wearable devices; Conflict handling; Hidden Markov Model; Autonomic Computing; Rule-based Systems; Sensor Mediation.
Product and Service Bundling Decisions and their Effects on Purchase Intention

Examines the effects of four factors (the bundle: pure or mixed, the price discount, the functional complementarity of bundle components, and the number of bundle components) on consumers’ intentions to purchase product and service bundles. The findings were relatively consistent across product (automobile) and service (automotive service) contexts, and illustrate that pure bundles are preferred to mixed bundles, and a greater price discount is preferred to a lesser one. The results also indicate that five component bundles generate greater purchase intention than either three or seven component bundles, and that “very related” bundle components result in greater purchase intention than either moderately or not related components. Additionally, several interactions are present.
Cryptography meets voting

We survey the contributions of the entire the- oretical computer science/cryptography community dur- ing 1975-2002 that impact the question of how to run ver- ifiable elections with secret ballots. The approach based on homomorphic encryptions is the most successful; one such scheme is sketched in detail and argued to be fea- sible to implement. It is explained precisely what these ideas accomplish but also what they do not accomplish, and a short history of election fraud throughout history is included.
Constrained encoding in hypercubes: algorithms and applications tological synthesis

PLA optimization aims at minimizing the area occupied by the PLA and the delay through it (proportional to the number of product-terms, to a first order approxima tion). PLA-based FSM optimum state assignment looks for the assignment corresponding to a PLA implementation of minimum area. State assignment by means of symbolic (multiple-valued) logic minimization requires solving the problem of CONSTRAINED CUBICAL EMBEDDING : assigning subsets of states to subcubes of a boolean ft-cube, for a minimum ft. Combinatorial theoretical models of CON STRAINED CUBICAL EMBEDDING are examined. A review of previous techniques of embedding graphs into hypercubes is presented. A new model in terms of poset embedding is given and new optimization problems are defined : SUBPOSET DIMEN SION and SUBPOSET EQUIVALENCE (the recognition version of the first one). The latter is shown to be NP-complete and the former is shown to be NP-hard. An algorithm to solve exactly SUBPOSET DIMENSION is described . It has been developed, beside intrinsic combinatorial interest, as a tool to make real progress with approximate solutions to CONSTRAINED CUBICAL EMBEDDING based on heuristics. An approximate algorithm. NOVA, that tries heuristically to satisfy all it can with minimum code length (log of cardinality of the state set) is also described. Results of an extensive testing are reported, showing that NOVA outperforms KISS in terms of area efficiency and that it can handle also large examples on which KISS is unable to complete successfully. A table is reported with the results of the exact encoding algo rithm applied to the optimal encoding of some FSMs . Compared to KISS, the exact algorithm achieves almost always a smaller number of product terms and a shorter code-length, but NOVA is almost always winner in terms of area .
Corporate Social Responsibility and Earnings Management: The Moderating
Role of Family Ownership

This study aims to explore the impact of family ownership on the relationship among corporate social responsibility (CSR) and earning management (EM) in Pakistan. Data is collected from nonfinancial listed firms on Pakistan Stock Exchange (PSE) for the period 2009-2017. Our results of pooled ordinary least square regression indicate that CSR has significant negative impact on EM. Furthermore, results also indicate that association between CSR and EM is moderated by family ownership. Family firms which perform CSR activities are less involved in EM as compare to nonfamily firms perform CSR activities. This variation in behavior of EM in family and non-family firms can possibly be explained by socioemotional wealth theory. Keywords: Corporate Social Responsibility, Earnings Management, Family Ownership
Auditing the Auditors and Stock Crashes: International Evidence

We investigate the impact of the initiations of national audit inspection programs on firm-specific stock crash risk in 38 countries worldwide. The staggered commencement of the inspection regimes in different countries allows us to identify the causal effect of audit quality on crash risk. We find a significant decrease (32.39%) in a firm’s crash risk subsequent to the initiations of audit inspections. This negative effect is stronger for auditors with smaller size, limited industry expertise, and longer tenure. We further explore the mechanisms through which audit inspections affect crash risk. We find that the effect of inspection programs on crash risk is driven by client firms facing higher ex ante inspection risk, as well as client firms in which auditors play an important role in monitoring managers.