Selection Logic Research Articles

There and Back Again: The Selectivity of Recidivism in Belgian Prisons

AbstractThe “panoptic” powers characteristic of nineteenth-century criminal justice systems created prison sources that are increasingly used to study past populations. Each step of the criminal process has its own selection logic, leading to a predominance of unskilled and low-skilled men and women in prison samples. There are also crucial differences between the profiles of single and repeat offenders. This article employs a sample of more than 27,000 individual admissions to Belgian prisons in the nineteenth century to explore these trends in greater depth. Recidivists form a specific subset of the prison population. Detailed comparisons of recidivists and nonrecidivists are therefore useful as they help to understand the selection mechanisms inherent in prison data. Male recidivists were predominately low-waged workers incarcerated for minor acts of violence or misconduct classified as disturbances of the peace. Female recidivists were disproportionately low-skilled workers arrested for beggary and sex work. Recidivists also differed in their stature. Male recidivists in Belgian prisons were shorter than the average prisoner. By contrast, female recidivists were taller than one-time offenders. These height differences have important implications for our understanding of well-being in the past.

Ultrasound Molecular Imaging of Cancer: Design and Formulation Strategies of Targeted Contrast Agents.

Gas-filled particles (microbubbles) can be prepared and stabilized for intravascular use as contrast agents in ultrasound imaging. Microbubbles are used in clinics as blood pool contrast materials for the past two decades. Shell of these bubbles is made of biocompatible and biodegradable lipids, proteins, and/or polymers. Gas core is air, or, lately, a perfluorinated gas, poorly soluble in water and blood. Making them useful for molecular targeting and molecular imaging in oncology is accomplished by decorating the shell of these particles with targeting ligands, that will selectively bind to the specific markers of tumor vasculature. In this review we discuss the formulation strategy for microbubble preparation, the logic of bubble shell selection, coupling tools that are used for the attachment of targeting ligands, and examples of the application of gas-filled bubbles for molecular imaging in oncology.

Service-aware objective function with QoS for RPL routing

The routing protocol for low power and lossy network (RPL), constructed according to the objective function (OF), is the standard for routing selection in low power and lossy networks (LLNs). Most schemes utilise the expected transmission count (ETX) as the routing metric for the next hop. Designing effective and efficient routing protocols in LLNs require the mechanism to meet the criteria of different applications or services. In this paper, we propose a service-aware OF with quality of service (SOF-QoS) mechanism which integrates received signal strength indicator (RSSI), energy consumption, and hop count metrics into RPL OF for path selection according to different services, such as normal data, video packets and emergency messages transmission in LLNs. The proposed SOF-QoS mechanism defines various weights with fuzzy logic for the next routing selection in response to each service. We conduct the simulation under different network topologies with static and mobile scenarios to analyse the performance of the proposed SOF-QoS mechanism and compare them with the traditional RPL schemes. The simulation result shows that our proposed SOF-QoS mechanism provides relatively better or superior performance with reliability than traditional ones for different services.

Service-aware objective function with QoS for RPL routing

The routing protocol for low power and lossy network (RPL), constructed according to the objective function (OF), is the standard for routing selection in low power and lossy networks (LLNs). Most schemes utilise the expected transmission count (ETX) as the routing metric for the next hop. Designing effective and efficient routing protocols in LLNs require the mechanism to meet the criteria of different applications or services. In this paper, we propose a service-aware OF with quality of service (SOF-QoS) mechanism which integrates received signal strength indicator (RSSI), energy consumption, and hop count metrics into RPL OF for path selection according to different services, such as normal data, video packets and emergency messages transmission in LLNs. The proposed SOF-QoS mechanism defines various weights with fuzzy logic for the next routing selection in response to each service. We conduct the simulation under different network topologies with static and mobile scenarios to analyse the performance of the proposed SOF-QoS mechanism and compare them with the traditional RPL schemes. The simulation result shows that our proposed SOF-QoS mechanism provides relatively better or superior performance with reliability than traditional ones for different services.

Integrating Blockchain and Broad Learning for Smart Energy Innovation: Design and Experiment

With the rapid development in recent years, the architecture and data sources of energy internet (EI) becomes increasingly complicated. It is a good opportunity and trend to combine energy equipment and information based on blockchain technology. However, high computational complexity inherently due to the blockchain must be addressed to achieve rapidly user electricity prediction. In this paper, an algorithm model of a blockchain technology combined with a broad learning data fusion algorithm is proposed. A novel and detailed combination model is introduced, mainly including CNN and LSTM model. Combination model considers energy data and blockchain data as parameter, and defines selection logic to guarantee user electricity forecast accuracy. Our proposed solution takes the advantage of CNN model in prediction accuracy and computation complexity, and advantage of LSTM model in long term memory. Further experiments illustrate that our solution achieves higher prediction accuracy of 94.1% (without considering the influence of real-time data), with the best result achieved ever. The experimental prediction results provide underlying insights to guide the direction of system resource planning.

Real-time watermark reconstruction for the identification of source information based on deep neural network

A novel deep neural network-based image watermarking method is presented to identify the source of digital data that is shared/forwarded on the internet using various messenger apps. The app that is used to share/communicate the image at the very first time is also identified in the proposed method. The ten-digit mobile number of the source (user) and identification data of particular messenger app (i.e. WhatsApp, Snapchat, Kik, Facebook messenger, etc.) is combined to get the text watermark signal. The part of the watermark signal representing specific mobile-based messenger application is obtained by randomizing the Walsh orthogonal codes using secret keys. To embed the watermark, the host image (shared/forwarded) is divided into blocks of equal size and then, slantlet transform is applied on each block. To get high reliability, three copies of the source information (user and app) are embedded during watermark embedding. Watermark extraction is performed using trained multilayer deep neural network. Furthermore, an optimal block selection logic is used to get improved results for real-time applications. The method is examined against various signal-processing attacks and high robustness with significant imperceptibility is attained. The method is also found to be fast enough for real-time applications. The prime objective of identifying the first user (source) and the shared/forwarded status (app detection) is successfully accomplished.

Application of Fuzzy Logic for Selection of Actor Nodes in WSANs -Implementation of Two Fuzzy-Based Systems and a Testbed.

The development of sensor networks and the importance of smart devices in the physical world has brought attention to Wireless Sensor and Actor Networks (WSANs). They consist of a large number of static sensors and also a few other smart devices, such as different types of robots. Sensor nodes have responsibility for sensing and sending information towards an actor node any time there is an event that needs immediate intervention such as natural disasters or malicious attacks in the network. The actor node is responsible for processing and taking prompt action accordingly. But in order to select an appropriate actor to do one task, we need to consider different parameters, which make the problem NP-hard. For this reason, we consider Fuzzy Logic and propose two Fuzzy Based Simulation Systems (FBSS). FBSS1 has three input parameters such as Number of Sensors per Actor (NSA), Remaining Energy (RE) and Distance to Event (DE). On the other hand, FBSS2 has one new parameter—Transmission Range (TR)—and for this reason it is more complex. We will explain in detail the differences between these two systems. We also implement a testbed and compare simulation results with experimental results.

Inframarginal Model Analysis of the Evolution of Agricultural Division of Labor

Division of labor plays a critical role in many parts of agriculture. For example, a specialized division of labor can lead to the improvement of labor productivity, the reduction of production costs, and the innovation of production technology and organization. At the heart of agricultural management is how the comparative advantages of farmers impact their production decision-making behavior, and, consequently, influence the division of labor structure. In this paper, we apply an infra-marginal model to interpret the selection logic of heterogeneous farmers’ specialized production with exogenous comparative technical advantages and transaction costs. Solving the nonlinear programming problem of the utility function within each respective labor structure leads to a corner equilibrium. Under reasonable assumptions of the model, we reduced the number of possible production–consumption decision modes from the maximum of 64 to an optimal of 3. Through this analysis, we discovered the ranges for transaction efficiency coefficients and preference parameter under which each structure can achieve general equilibrium. Our theoretical model thereby explains the structural evolution of agricultural division of labor.

A 12 Gb/s 1.59 mW/Gb/s Input-Data-Jitter-Tolerant Injection-Type CDR With Super-Harmonic Injection-Locking in 65-nm CMOS

This brief presents an input-data-jitter-tolerant injection-type clock and data recovery (CDR) circuit with a super-harmonic injection-locked ring oscillator (SH-ILRO). Unlike prior injection-type CDRs that utilize a power-hungry CML-type data injection path or for which the data rate is limited to the process-defined CMOS logic bandwidth, the proposed injection-type CDR achieves energy-efficient data edge injection. The proposed wide-bandwidth source follower-based edge detector extracts the input data edge energy efficiently. The proposed SH-ILRO enables quarter-rate injection-locking without high-speed injection selection logic. Fabricated in 65-nm CMOS, the prototype injection-type CDR consumes 19.08 mW at 12 Gb/s with 87-MHz jitter transfer bandwidth and more than 1.0 UIpp jitter tolerance at 20 MHz.

Necessities in the Processing of DNA Double Strand Breaks and Their Effects on Genomic Instability and Cancer.

Double strand breaks (DSBs) are induced in the DNA following exposure of cells to ionizing radiation (IR) and are highly consequential for genome integrity, requiring highly specialized modes of processing. Erroneous processing of DSBs is a cause of cell death or its transformation to a cancer cell. Four mechanistically distinct pathways have evolved in cells of higher eukaryotes to process DSBs, providing thus multiple options for the damaged cells. The homologous recombination repair (HRR) dependent subway of gene conversion (GC) removes IR-induced DSBs from the genome in an error-free manner. Classical non-homologous end joining (c-NHEJ) removes DSBs with very high speed but is unable to restore the sequence at the generated junction and can catalyze the formation of translocations. Alternative end-joining (alt-EJ) operates on similar principles as c-NHEJ but is slower and more error-prone regarding both sequence preservation and translocation formation. Finally, single strand annealing (SSA) is associated with large deletions and may also form translocations. Thus, the four pathways available for the processing of DSBs are not alternative options producing equivalent outcomes. We discuss the rationale for the evolution of pathways with such divergent properties and fidelities and outline the logic and necessities that govern their engagement. We reason that cells are not free to choose one specific pathway for the processing of a DSB but rather that they engage a pathway by applying the logic of highest fidelity selection, adapted to necessities imposed by the character of the DSB being processed. We introduce DSB clusters as a particularly consequential form of chromatin breakage and review findings suggesting that this form of damage underpins the increased efficacy of high linear energy transfer (LET) radiation modalities. The concepts developed have implications for the protection of humans from radon-induced cancer, as well as the treatment of cancer with radiations of high LET.

Online Boundary Computation Using Sampled Voltage Reference for Bus Clamping PWM-Based Hysteresis-Controlled VSI-Fed IM Drive

A current error space phasor based hysteresis current controller (HCC) with online computation of the current error boundaries using estimated sampled voltage references (SVR) for a two-level voltage source inverter (VSI) fed induction motor (IM) drive is proposed in this article. The space vector based current error of a two-level VSI-fed IM is monitored to keep the current error within the precalculated boundaries. The boundaries are computed knowing voltage error vector estimated from the current error information along α and β axes of IM. Vector selection logic is deduced to extract the features of voltage-controlled (VC) –30° and 60° bus clamping (BC) space vector pulsewidth modulation (SVPWM) based VSI-fed IM drive. The proposed HCC produces phase voltage harmonic spectrum and current error trajectories similar to that of a constant switching frequency—VC-BCSVPWM drive. It ensures adjacent voltage vector switching and retains all inherent advantages of a conventional HCC such as fast current control and has got a simpler controller implementation. A simulation model using MATLAB/Simulink is developed and analyzed over a wide speed range and experimentally validated using a dSPACE controller board on a 2.2 kW, 415 V, 3ϕ IM drive.

Tenure trumps title: Assessing the logic of informant selection in inter-organizational network research

AbstractResearchers collecting survey data on inter-organizational networks typically choose a single informant with the most senior job title in each organization from whom to obtain a report of the organization’s inter-organizational ties. This approach to informant selection is based on the logic that greater seniority confers greater knowledge of inter-organizational relationships. The present study investigated the wisdom of this logic, using data in which multiple informants’ reports of inter-organizational network ties were collected for each organization. We calculated the degree of agreement in network reports between the informant with the most senior job title and a second informant in the organization. To determine if alternative criteria to seniority serve as better approaches to informant selection, we assessed other potential predictors of agreement in informants’ reports. Results indicated that (1) informants’ perceptions of the network differed significantly according to job title, suggesting little agreement between senior informants and their more junior colleagues; and (2) greater informant tenure in the network and industry were associated with greater agreement among informants. These results call a common data collection practice into question and suggest that tenure may trump title as a criterion for informant selection in inter-organizational network research.

Polarization, Participation, and Premiums: How Political Behavior Helps Explain Where the ACA Works, and Where It Doesn't.

Political partisanship can influence whether individuals enroll in government programs. In particular, Republicans, ceteris paribus, are less likely to enroll in Affordable Care Act (ACA) individual marketplace insurance than Democrats. The logic of adverse selection suggests low uptake among Republicans would generally put upward pressure on marketplace premiums, especially in geographic areas with more Republican partisans. Using data from Healthcare.gov at the rating area level, this article examines the association between Republican vote share and growth in ACA marketplace premiums, being careful to account for potential confounding variables. Insurers have increased marketplace premiums at higher rates in areas with more Republican voters. In the preferred model specification, a 10-percentage-point difference in Republican vote share is associated with a 3.2-percentage-point increase in average premium growth for a standard plan. A variety of robustness and placebo checks suggest the relationship is driven by partisanship. Partisan polarization can threaten the successful implementation of policies that rely on high levels of citizen participation.

Internationally Comparative Research Designs in the Social Sciences: Fundamental Issues, Case Selection Logics, and Research Limitations

This paper synthesizes methodological knowledge derived from comparative survey research and comparative politics and aims to enable researches to make prudent research decisions. Starting from the data structure that can occur in international comparisons at different levels, it suggests basic definitions for cases and contexts, i. e. the main ingredients of international comparison. The paper then goes on to discuss the full variety of case selection strategies in order to highlight their relative advantages and disadvantages. Finally, it presents the limitations of internationally comparative social science research. Overall, the paper suggests that comparative research designs must be crafted cautiously, with careful regard to a variety of issues, and emphasizes the idea that there can be no one-fits-all solution.

Clustering based interest prediction in social networks

Efficient interest prediction for social networks is critical for both users and service providers for behavior analysis and a series of extension services. However, most existing approaches are inefficient, incomplete or isolated. In this paper, we propose combination of Gaussian and Markov approaches (namely, GAM) as typical soft computing technology for interest prediction of social intelligent multimedia systems. GAM model considers “the number of posted messages” as the only parameter, and defines selection logic to implement either Gaussian or Markov based approaches. Our proposed solution takes the advantage of Gaussian model in prediction accuracy and computation complexity, and advantage of Markov model in high availability. Further experiments illustrate that our solution achieves higher prediction accuracy of 94.3% (without considering the influence of swing users), with the best result achieved ever.

Model Checking Techniques Applied to Satellite Operational Mode Management

Satellites are nowadays complex systems and can be considered as components of larger mission-level systems of systems. The increasing complexity of space mission objectives is actually complicating the requirement engineering process. It is generally understood that space system engineers should translate system-level requirements (elaborated in natural language) into verifiable models, which can expose the design issues before the satellite manufacturing phase. This paper shows how the verification of complex system requirements can be performed via model checking. More specifically, a methodology is proposed which exploits the flexibility provided by the calculus of communicating systems to model complex system concurrent parts and their mutual interactions for verifying analytically their correctness, completeness, and consistency as prescribed by the system requirements. The proposed methodology is applied to the verification of a real satellite operational mode management specification. An abstraction reduction technique based on the selective mu-calculus logic is used to address the computational issues in model checking. It allows capturing and analyzing the parts of a satellite involved in the verification of a specific set of its system-level properties.

Application of Fuzzy Logic in Selection of Remanufacturing Technology

Abstract Fuzzy approach is frequently used for selection of manufacturing technology. However, the application of the fuzzy tool for choosing the appropriate remanufacturing technology is seldom applied. This study applies the fuzzy logic approach for the selection of technology in order to minimize vagueness in decision making, thereby making results more similar to experts’ thinking. Through elicitation of experts’ inputs, six cleaning technologies were evaluated and ranked appropriately, using criteria of technology cost, operating cost, and disposal effect. Moreover, the technology selection was computed through experts’ opinion using the fuzzy logic inference system. The results show that when technical function of the technology is at the low level of 20%, the technology quality is as low as 15%, and the technology flexibility is rated as low at 25%; then the technical adequacy of the assessed technology will be as low as 10%. The fuzzy approach shows that technology performance is largely impacted by criteria far beyond the technology itself, including purchasing cost, disposal cost, operating cost, and other support functions to compliment experience of experts. Despite the fact that decision makers are appropriately selecting technology, the application of the fuzzy logic tool helps to accommodate vagueness, ambiguity, and subjective views of experts. Notwithstanding the robustness of the approach, application of software to help selection of technology is more reliable and accurate, reduce time of decision, and can be accessed worldwide.

Aid application multicriteria the decision based on AHP Method and Fuzzy Logic in commercial land selection

Abstract The objective of this article is to select land for commercial buildings in Rio de Janeiro city using multiple criteria decision-making techniques. The techniques used were based on the Analytic Hierarchy Process (AHP) and Fuzzy Logic methods. These methods were chosen because of functionality, flexibility and great application in engineering problems for decision making involving multiple criteria. Its application was made through an opinion survey with expert builders, where 6 (six) factors for evaluation were selected in 10 (ten) commercial land alternatives. For the analytical operation of the methods, the software used were: Super Decisions and MATLAB®, respectively for each method, presenting the factors classified, in order of priority, in the selection of land, and ranking of the alternatives according to the defined scenario, facilitating in this way the process of selection of land for buildings, establishing a scientific way for the decision process.

A highly selective turn-on luminescent logic gates probe based on post-synthetic MOF for aspartic acid detection

We herein design an innovative strategy for the detection of aspartic acid (Asp) based on a post-modification metal-organic framework Cu/Tb@Zn-MOF (3), which is synthesized by successively encapsulating Tb3+ and Cu2+ ions into Zn-MOF (1). Subsequently, the luminescence-quenched composite 3 is developed as a fluorescence “turn-on” probe for Asp, demonstrating excellent selectivity and low detection limit (0.54 ppm). In addition, this On–Off–On pattern is further to construct an advanced analytical model based on IMPLICATION-type logic gate. More remarkable, the high selectivity and sensitivity for Asp are unparalleled among sensor type, with which lanthanide fluorescence is enhancing by MOFs.

Uniform and nonuniform precession of a nanoparticle with finite anisotropy in a liquid: Opportunities and limitations for magnetic fluid hyperthermia

We focus on an in-depth study of the forced dynamics of a ferromagnetic single-domain uniaxial nanoparticle placed in a viscous fluid and driven by an external rotating magnetic field. The process of conversion of magnetic and mechanical energies into heat is a physical basis for magnetic fluid hyperthermia that is very promising for cancer treatment. The dynamical approximation allows us to establish the limits of the heating rate and understand the logic of selection of the system parameters to optimize the therapy. Based on the developed analytical and numerical tools, we analyze from a single viewpoint the synchronous and asynchronous rotation of the nanoparticle or/and its magnetization in the following three cases. For the beginning, we actualize the features of the internal magnetic dynamics, when the nanoparticle body is supposed to be fixed. Then, we study the rotation of the whole nanoparticle, when its magnetization is supposed to be locked to the crystal lattice. And, finally, we realize the analysis of the coupled motion, when the internal magnetic dynamics is performed in the rotated nanoparticle body. In all these cases, we describe analytically the uniform mode, or synchronous rotation along with an external field, while the nonuniform mode, or asynchronous rotation, is investigated numerically.