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This paper aims to address the various issues of board‐level (off‐chip) interconnects testing. A new algorithm based on the boundary scan architecture is developed to test off‐chip interconnect faults. The proposed algorithm can easily diagnose which two interconnects are shorted.

The problems in board‐level interconnects testing are not simple. A new algorithm is developed to rectify some of the problems in existing algorithms. The proposed algorithm to test board‐level interconnect faults is implemented using Verilog on Modelsim software. The output response of each shorting between different wires of different nodes is different, which is the basis of fault detection by the proposed algorithm. The test vectors are generated by the test pattern generator and these test vectors are different for different nodes. This work implements built in self test using boundary scan technique.

The dominant‐1 (wired‐OR, denoted as WOR), dominant‐0 (wired‐AND, denoted as WAND) and stuck‐at faults are tested using the proposed algorithm. The proposed algorithm is also compared with the several algorithms in the literature, i.e. modified counting, walking one's algorithm and others. This paper's results are found to be better than the existing algorithms.

The limitation of the proposed algorithm is that, at any time, the faults on any seven nodes can be tested to avoid aliasing. So, the groups are formed out of total nodes, in a multiple of seven to carry out the testing of faults.

The proposed algorithm is free from the problems of syndromes and utilizes a smaller number of test vectors.

Various existing algorithms namely modified counting, walking one's algorithm and others are discussed. A new algorithm is developed which can easily detect board‐level dominant‐1 (WOR), dominant‐0 (WAND) and stuck‐at faults. The proposed algorithm is completely free from aliasing and confounding syndromes.

Guar Gum (GG) is used in Shale oil exploration. Excessive price increase in the Guar futures market had a spillover impact on Guar spot prices and affected Guar export from India as Shale oil producers started exploring alternate sources. In this paper, the role of excessive speculation in the futures market, and its adverse impact on the guar-based agri-business ecosystem have been empirically explored.

Volatility spillover dynamics between WTI crude oil and Guar futures have been explored using bivariate-Granger Causality, BEKK–GARCH models with Wavelet multi-resolution analysis. The wavelet-based models capture the multi-scale features of mean and volatility spillover to identify the effect of heterogenous investment behavior in the time and frequency domain.

The results provide evidence that excessive speculation in futures markets increases spot market volatility. The results also suggest that the excess presence of short-term investors can destabilize the futures market.

The purpose of the commodity futures market is to support price discovery and risk management. However, speculative practices can destabilize these purposes leading to the failure of the business ecosystem.

The novelty of this paper is twofold. First, it explores the economic linkages between the spot and futures market and tests whether the presence of heterogeneous traders affects the economic linkages. Second, it models the impact of short-term speculative investment on the destabilization of the spot market.

This chapter sheds light on the ‘country of origin’ concept. The author contends that this concept is composed of micro- and macro-components. He argues that the tourists’ hedonic and monetary gratifications are derived from the travel experiences. Therefore, the country-of-origin image (COI) can have an impact on the destination’s brand extension. In this light, this contribution examines the relationship among COI, overall brand equity and brand extension. The author implies that the hedonic and monetary values can have a moderating effect on the impact of COI and on destination brand extension.

The purpose of this paper is to explore the functioning of very‐large‐scale integration (VLSI) interconnects and modeling of interconnects and evaluate different approaches of testing interconnects.

In the past, on‐chip interconnect wires were not considered in circuit analysis except in high precision analysis. Wiring‐up of on‐chip devices takes place through various conductors produced during fabrication process. The shrinking size of metal‐oxide semiconductor field effect transistor devices is largely responsible for growth of VLSI circuits. With deep sub‐micron (DSM) technology, the interconnect geometry is scaled down for high wiring density. The complex geometry of interconnects and high operational frequency introduce wire parasitics and inter‐wire parasitics. These parasitics causes delay, power dissipation, and crosstalk that may affect the signal integrity in VLSI system. Accurate analysis, sophisticated design, and effective test methods are the requirement to ensure the proper functionality and reliability of VLSI circuits. The testing of interconnect is becoming important and a challenge in the current technology.

The effects of interconnect on signal integrity, power dissipation, and delay emerges significantly in DSM technology. For proper performance of the circuit, testing of interconnect is important and emerging challenge in the nanotechnology era. Although some work has been done for testing of interconnect, however, it is still an open area to test the parasitics effects of VLSI/ultra‐large‐scale integration interconnects. Efforts are required to analyze and to develop test methods for crosstalk, delay and power dissipation in current technology with solutions to minimize this effect.

This paper reviews the functioning of VLSI interconnects from micrometer to nanometer technology. The development of various interconnect models from simple short circuit to latest resistance inductance capacitance transmission line model are discussed. Furthermore, various methodologies such as built‐in self test and other techniques for testing interconnect for crosstalk and delay are discussed.

This chapter analyzes the link between the digital divide, infrastructure regulation, and disaster planning and relief through a case study of the flood in San Jose, California triggered by the Anderson dam’s overtopping in February 2017 and an examination of communication failures during the 2018 wildfire in Paradise, California. This chapter theorizes that regulatory decisions construct social and disaster vulnerability. Rooted in the Whole Community approach to disaster planning and relief espoused by the United Nations and the Federal Emergency Management Agency, this chapter calls for leadership to end the digital divide. It highlights the imperative of understanding community information needs and argues for linking strategies to close the digital divide with infrastructure and emergency planning. As the Internet’s integration into society increases, the digital divide diminishes access to societal resources including disaster aid, and exacerbates wildfire, flood, pandemic, and other risks. To mitigate climate change, climate-induced disaster, protect access to social services and the economy, and safeguard democracy, it argues for digital inclusion strategies as a centerpiece of community-centered infrastructure regulation and disaster relief.

Introduction: Big data in the insurance industry can be defined as structured or unstructured data that can affect the rating, marketing, pricing, or underwriting. The five Vs of big data provide insurers with a valuable framework for converting their raw data into actionable information. These five Vs are specifically: (1) Volume: The need to look at the type of data and the internal systems; (2) Velocity: The speed at which big data is generated, collected, and refreshed; (3) Variety: Refers to both the structured and unstructured data; (4) Veracity: Refers to trustworthiness and confidence in data; and (5) Value: Refers to whether the data collected are good or bad.

Purpose: Insurance companies face many data challenges. However, the administration of big data has allowed insurers to acknowledge the demand of their customers and develop more personalised products. In addition, it can be used to make correct decisions about insurance operations such as risk selection and pricing.

Methodology: We do this by conducting a systematic literature review on big data. Our emphasis is on gathering information on the five Vs of the big data and the insurance market. Specifically, how big data can help in data-driven decisions.

Findings: Big data technology has created an endless series of opportunities, which have ensured a surge in its usage. It has helped businesses make the process more systematic, cost-effective, and helped in the reduction in fraud and risk prediction.

This paper develops a decision-analysis model to prioritize and select the site to establish a new hospital over different indicators such as cost, market conditions, environmental factors, government factors, locations and demographics. In this way, an integrated model is proposed under the intuitionistic fuzzy information (IFI), the standard deviation (SD), the rank-sum (RS) and the measurement of alternatives and ranking using the compromise solution (MARCOS) approach for ranking hospital sites (HSs).

The IF-SD-RS model is presented to obtain the combined weight with the objective and subjective weights of diverse sub-criteria and indicators for ranking sites to establish the hospital. The IF-MARCOS model is discussed to prioritize the various sites to establish the hospital over several crucial indicators and sub-criteria.

The authors implement the developed model on a case study of HSs assessment for the construction of new hospital. In this regard, inclusive set of 6 key indicators and 18 sub-criteria are considered for the evaluation of HSs. This study distinguished that HS (h₂) with combined utility function 0.737 achieves highest rank compared to the other three sites for the given information. Sensitivity analysis is discussed with different parameter values of sub-criteria to examine how changes in weight parameter ratings of the sub-criteria affect the prioritization of the options. Finally, comparative discussion is made with the diverse extant models to show the reasonability of the developed method.

This study aims to develop an original hybrid weighting tool called the IF-SD-RS model with the integration of IF-SD and IF-RS approaches to find the indicators' weights for prioritizing HSs. The developed integrated weighting model provides objective weight by IF-SD and subjective weight with the IF-RS model. The model presented in the paper deals with a consistent multi-attribute decision analysis (MADA) concerning the relations between indicators and sub-criteria for choosing the appropriate options using the developed IF-SD-RS-MARCOS model.

This paper aims to design a most demanding low profile and compact ultra-wide band (UWB) antenna system for various wireless applications. The performance (in terms of data rate) of UWB system is improved by using multiple-input-multiple-output (MIMO) technology with it. Owing to the overlap of other existing licensed bands with that of UWB, electromagnetic signals can interfere. So, notched band UWB MIMO antenna system reported here which is highly compact, bandwidth efficient, superior data rate and high inter-element isolation comparatively to other reported designs.

A 49 × 49 × 1.6 mm³ quad-port UWB MIMO antenna with specific bandwidth elimination property is designed. The proposed planar MIMO configuration comprises unique four identical “Cordate-shaped” monopole radiators fed by 2.3-mm thick microstrip-lines. The radiators are located right-angled to each other to enhance inter-element isolation. Further, a different approach of slitted-substrate is applied to minimize the overall size and mutual coupling of the MIMO antenna, as a substitute of decoupling and matching structures. The defected ground structure is used to obtain −10 dB impedance bandwidth in entire UWB band, without compromising with the lower cut-off frequency response. Further, to eliminate the undesired resonant band (WLAN at 5.5 GHz) from UWB, a rounded split ring resonator is introduced in monopole patch.

In the entire operating band of 2.8 to 11 GHz, isolation among elements is more than 24 dB, envelope correlation coefficient less than 0.002, diversity gain greater than 9.99 dB and TARC less than −7 dB are obtained at all 4-ports.

The measured parameters of the fabricated prototype antenna on FR4 substrate are found in good agreement with the simulated results. The small variation in software results and hardware results are observed due to hardware design limitations.

The proposed design may be used for any wireless application following in the range of UWB.

It can be shown from graphs of measured parameters of the fabricated prototype antenna. They found to be in good agreement with the simulated results.

The transient thermal behaviour, based on a rigorous transient thermodynamic treatment, of a power VDMOS transistor during turn‐off is presented. The time variation of the interior lattice temperature within the device is calculated by self‐consistently solving the fully coupled Poisson's equation and transient electron continuity equation together with the transient heat flow equation. The simulation takes account of temperature dependent heat conduction and capacity and includes thermoelectric currents due to temperature gradient. To make the transient thermal simulation more robust, a new analytical expression for heat capacity is used.

The purpose of this study is to assess the quality of honey from different agro-climatic zones of Himachal Pradesh in terms of physicochemical characteristics and mineral status.

Three honey-producing locations were selected within each agro-climatic zone, honey sampled from four separate apiaries within each location and analyzed for physicochemical characteristics and mineral status using standard methodologies. The data were analyzed using one-way analysis of variance with one-way classification, after appropriate transformation through online OP-STAT software and MS Excel. The correlation coefficient (r) was also calculated. Principal component analysis was done using XL-STAT software.

The honey of Zone 4 had highest fructose (36.62%), F:G ratio (1.55), acidity (46.07 meq/kg), vitamin C (25.04 mg/100 g) and diastase (19.22 DN), whereas the pollen density (76,666.67 pollen grains per 10 g), pH (5.94), sucrose (6.94%), hydroxy methyl furfuraldehyde (70.20 mg/kg), amino acid (103.83 mg/100 g), phenols (77.39 mg/100 g), Ca (81.04 mg/kg) and K (354.17 mg/kg) were highest for Zone 2. Highest electrical conductivity (0.24 mS/cm), moisture (16.50 %), glucose (34.20%) and P content (62.93 mg/kg) were recorded for Zone 1. Correlation studies indicated a significant positive correlation between pH and EC; EC and moisture; colour and pollen density. Examining the graphical distribution of the honey samples, a natural separation between honeys of four different agro-climatic zones was obtained.

The impact of geographical/agro-climatic variations in physicochemical characteristics of honey has not been worked out under the present scenario in Himachal Pradesh.