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Inherent error resilience in neuromorphic computing allows remarkable power and energy savings by exploiting approximate computing. This paper presents approximate digital leaky integrate-and-fire (LIF) neurons that leverage the approximate adders for energy efficient spiking neural networks (SNNs). Various approximate adder architectures were assessed and adopted in designing a digital LIF neuron. To demonstrate the performance of the approximate LIF neurons, a two-layer SNN with more than 1,000 digital neurons were used with the approximate adders. The results showed that the approximation errors of the lower-part OR adder (LOA) and optimized lower-part constant OR adder (OLOCA) do not affect the neuron’s spiking activities of the network significantly. In addition, they showed good power and energy efficiency. The results suggest that the LOA and OLOCA are more suitable for SNNs to achieve power- and energyefficient neuromorphic computing than the other approximate adders.

Neuromorphic computing has been studied to implement functions inspired by the human brain such as low power, fine-grained parallel processing, and real-time learning beyond the limitations seen by a standard von Neumann processor. In this paper, Intel's Loihi neuromorphic research chip and its hardware systems are introduced and find out how they are applied and used in actual research fields.

Networks-on-chips (NoCs) are gaining in popularity as replacement for shared medium interconnects in chip-multiprocessors (CMPs) and multiprocessor systems-on-chips, and their performance becoming essential to system performance. There have been emerging studies to achieve better power/energy efficiency without performance degradation on NoCs. However, there are still non-negligible latency issues caused by the mechanism of power efficient approaches. To alleviate the latency problem and to transfer data efficiently with the high utilization of interconnect resources, we propose an on-chip network architecture that improves latency and bandwidth. Increasing the data/link widths across the network may considerably resolve this problem but is a costly proposition both in terms of device area and of power. Alternatively, we propose a dual-path router architecture that efficiently exploits path diversity to attain low latency without significant hardware overhead. By: 1) doubling the number of injection and ejection ports; 2) splitting packets into two halves; 3) recomposing routing policy to support path diversity; and 4) provisioning the network hardware design, we can considerably enhance network resource utilization to achieve much higher performance in latency. The proposed simultaneous dual-path routing (SDPR) scheme outperformed the conventional dimension order routing (DOR) technique across synthetic workloads by 31%–40% in average latency and up to a 100% improvement in throughput performance running on a 49-core CMP. Our synthesizable model for the SDPR router and network provides accurate power and area reports. According to the synthesis reports, SDPR incurs insignificant overhead compared to the baseline XY DOR router.

Loihi is a 60-mm2 chip fabricated in Intels 14-nm process that advances the state-of-the-art modeling of spiking neural networks in silicon. It integrates a wide range of novel features for the field, such as hierarchical connectivity, dendritic compartments, synaptic delays, and, most importantly, programmable synaptic learning rules. Running a spiking convolutional form of the Locally Competitive Algorithm, Loihi can solve LASSO optimization problems with over three orders of magnitude superior energy-delay-product compared to conventional solvers running on a CPU iso-process/voltage/area. This provides an unambiguous example of spike-based computation, outperforming all known conventional solutions.

The aim of the study was to evaluate the clinical and histopathological characteristics of patients with post burn pruritus. The authors took skin samples from 62 burn patients with or without pruritus. The measured skin condition includes thickness and paresthesia. Various clinical features were rated on patient assessment scale (PSAS) and observer scar assessment scale. The samples were stained with hematoxylin & eosin, Masson's trichrome, Verhoeff's elastic, and toluidine blue stain. The stained samples were analyzed in terms of epidermal thickness, mononuclear cell infiltration, collagen bundles, elastic fibers, and mast cell distribution. A total of 62 patients were divided into group A (43 patients with pruritus) and group B (19 patients without). The mean (±SD) intensity of itch in group A patients was 4.58 (±3.24). Group A patients had thickened epidermises and higher scores on the PSAS and observer scar assessment scale, especially on the PSAS score. Sensations, including stinging and electric shock sensations, were more frequent in group A than in group B. Histological analysis revealed that group A patients had thinner collagen bundles and more increased mast cell counts, while others did not. Patients suffering from post burn pruritus had distinctive clinical and histopathological features, such as prominent mast cell deposition and thin collagen bundles, compared with group B patients. These results may help better understand post burn pruritus.

This paper presents an energy-efficient approximate adder with a novel hybrid error reduction scheme to significantly improve the computation accuracy at the cost of extremely low additional power and area overheads. The proposed hybrid error reduction scheme utilizes only two input bits and adjusts the approximate outputs to reduce the error distance, which leads to an overall improvement in accuracy. The proposed design, when implemented in 65-nm CMOS technology, has 3, 2, and 2 times greater energy, power, and area efficiencies, respectively, than conventional accurate adders. In terms of the accuracy, the proposed hybrid error reduction scheme allows that the error rate of the proposed adder decreases to 50% whereas those of the lower-part OR adder and optimized lower-part OR constant adder reach 68% and 85%, respectively. Furthermore, the proposed adder has up to 2.24, 2.24, and 1.16 times better performance with respect to the mean error distance, normalized mean error distance (NMED), and mean relative error distance, respectively, than the other approximate adder considered in this paper. Importantly, because of an excellent design tradeoff among delay, power, energy, and accuracy, the proposed adder is found to be the most competitive approximate adder when jointly analyzed in terms of the hardware cost and computation accuracy. Specifically, our proposed adder achieves 51%, 49%, and 47% reductions of the power-, energy-, and error-delay-product-NMED products, respectively, compared to the other considered approximate adders.

Recent studies have given ample evidence that atopy is associated with a T-cell deficiency. This deficiency appears to be primary and not merely a consequence of disease manifestations. Several studies have indicated that the T-cell defect displays a certain selectivity, resulting in imbalance between helper and suppressor T-cell in atopics. Suppressor cells, carrying Fc IgG marker (T gamma cells) or being inducible by concanavalin A, have been found to be deficient, and recent data suggest that there is an imbalance between T8+ (cytotoxic/suppressor) and T4+ (inducer/helper) T-cells in individuals with severe atopic disease. There appears to be a negative correlation between suppressor cell activity and serum IgE levels. These findings suggest that there is a causal relationship between the T-cell deficiency and hyperproduction of IgE in atopy. The immunological abnormalities in atopy cannot be easily explained by the beta-adrenergic blockade which is associated with the disease. Further immunopharmacological studies may help to elucidate the pathogenesis of atopic disease.

WaveSync is a network-on-chip architecture for a globally asynchronous locally-synchronous (GALS) design. The WaveSync design facilitates low-latency communication leveraging the source-synchronous clock sent along with the data to time components in the datapath of a downstream router, reducing the number of synchronizations needed. WaveSync accomplishes this by partitioning the router components at each node into different clock domains, each synchronized with one of the orthogonal incoming source-synchronous clocks in a GALS 2D mesh network. The data and clock subsequently propagate through each node/router synchronously until the destination is reached, regardless of the number of hops this may take. As long as the data travels in the path of clock propagation and no congestion is encountered, it will be propagated without latching as if in a long combinatorial path, with both the clock and the data accruing delay at the same rate. The result is that the need for synchronization between the mesochronous nodes and/or the asynchronous control associated with the typical GALS network is completely eliminated. To further reduce the latency overhead of synchronization, for those occasions when synchronization is still required (when a flit takes a turn or arrives at the destination), we propose a novel less-than-one-cycle synchronizer. The proposed WaveSync network outperforms conventional GALS networks by 87--90% in average latency, synthesized using a 45nm CMOS library.

This article presents a low-power decoder design for joint source-channel decoding (JSCD) based on a novel unequal error protection (UEP) scheme over additive white gaussian noise (AWGN) channels. Conventional JSCD schemes, adopting low-density parity check (LDPC) codes for multimedia devices, typically operate at a fixed-time decoding loop, regardless of the quality of data received. We present a JSCD scheme that achieves reduction in power through minimum energy decoding and dynamic voltage and frequency scaling (DVFS). Consequently, up to 39% power reduction is achieved in Foreman, Akiyo, and Mobile video streams without performance degradation in reconstructed video quality.

This 4study proposed a novel energy harvesting from food waste by inoculation of vermicomposted organic matter into MFC in order to produce electricity while decomposing organic waste by catalytic activity of geobacter species which already live in the compost. We designed and implemented a prototype of vermicomposting MFC energy harvester and measured its output voltage for 4 weeks. The voltage-time profile and current-voltage (CV) characteristic showed a maximum open-circuit voltage of 0.75 volts and maximum power of 0.41mW. The proposed energy harvester can contribute to recycle of food waste as well as providing sustainable electricity. Further study will focus on its applications which are energy self-sustainable so that it may encourage more installation and utilization of the proposed food waste energy harvester.

A reliable, energy-efficient on-chip interconnection network employing low-swing signaling can be designed by incorporating error-correcting code. Orthogonal Latin Square Code (OLSC) can protect the interconnection against transient errors, while also lowering energy consumption. When applied to a 64-bit link using a 45-nm CMOS technology with low-swing signaling, OLSC provided up to 55% energy reduction, with only a small area overhead and no loss in reliability.

Chemoresistive responses of four different carbon black-polymer composite sensors were measured with varying a sensor temperature upon exposure to volatile organic compounds (VOCs). A new thermodynamic response was extracted from the temperature dependence of the chemoresistive responses. The thermodynamic parameter was determined by the standard enthalpy energy change during the sensing processes. It mainly reflected non-specific physical interactions between the composite materials and the analyte vapors rather than analyte-specific interactions. In order to prove its capability as a feature parameter in pattern recognition programs, principal component analyses were performed by using both the chemoresistive and the thermodynamic responses simultaneously. The resultant outcome clearly demonstrated that the use of the additional thermodynamic feature improved the classification capability between VOC classes due to the correction of the deteriorations originated from the temperature-dependent response variations.

A small electronic nose (E-Nose) system has been developed using an 8-channel vapor detection array and personal digital assistant (PDA). The sensor array chip, integrated on a single microheater-embedded polyimide substrate, was made of carbon black-polymer composites with different kinds of polymers and plasticizers. We have successfully classified various volatile organic compounds such as methanol, ethanol, i-propanol, benzene, toluene, n-hexane, n-heptane, and c-hexane with the aid of the sensor array chip, and have evaluated the resolution factors among them, quantitatively. To achieve a PDA-based E-Nose system, we have also elaborated small sensor-interrogating circuits, simple vapor delivery components, and data acquisition and processing programs. As preliminary results show, the miniaturized E-Nose system has demonstrated the identification of essential oils extracted from mint, lavender, and eucalyptus plants.

A portable electronic nose system based on personal digital apparatus has been developed by using the vapor detection array made of carbon black–polymer composites and the user software, such as data acquisition and pattern recognition. The gas sensor array is possible to have maximum 16 sensing elements integrated on the same silicon substrate. The individual element has a Si bulk-micromachined well which allows the polymer-carbon black composite solution to be placed reproducibly in a specific and well-constrained area during the drop-coating process. Preliminary results show that our portable electronic nose system has successfully classified simple volatile organic compounds, and the complex liquor samples of brandy and whiskey.

A series of mixed-ligand gold nanoparticles were synthesized, characterized and used to form transducer films to investigate and enhance vapor-sensing properties. Chlorobenzenemethanethiol (CBMT) nanoparticle, prepared using a two-phase method, was used for place-exchange reactions with a varying amount of n-octanethiol (OT) to produce a series of mixed-ligand gold nanoparticles (Au_CBMT-OT-1, Au_CBMT-OT-2, and Au_CBMT-OT-3). The nanoclusters were characterized by 1 H NMR spectroscopy, thermal gravimetric analysis (TGA), and transmission electron microscopy (TEM). Thin film transducers of the monolayer-protected nanoparticles were formed through a dip-coating procedure on glass substrates mounted with interdigitated gold electrodes. SEM analysis indicated that mostly the surfaces of the sensors films were smooth. Nanoparticle sensors experienced repeated cycles of analyte vapors and blank air gas as the analyte concentrations were varied. Mostly the nanoparticle sensors produced rapid and reversible responses toward the vapors of 1-propanol, acetone and cyclohexane. Linear relationship between maximum resistance changes and vapor concentrations were observed. Above all the variations in compositions of the ligand molecules (CBMT and OT) resulted in differences in signal amplitudes.

The vapor recognition performance of electronic nose (E-nose) system can be improved by manipulating the sensor array responses of vapors in profile forms. The sensor array composed of various carbon-black (CB) polymer composites shows featured response profile patterns, varied from vapors to vapors due to different chemical interactions between the arrayed materials and the vapors. These multidimensional sensory data gives more information than collection of the piecemeal signal features, i.e., maximum sensitivity, signal slopes, rising-time. To use them in vapor recognition task, we proposed a novel matched-profile method was proposed, which is based on the typical digital image pattern matching. The degrees of matching between eight different vapors were evaluated by using the proposed method. The vapor responses are measured by the silicon-based gas sensor array with 16 CB polymer composites installed in membrane structure. The results showed higher contrast between matching and non-matching vapors than conventional method. This implies reliable vapor recognition in E-nose system.

The electronic nose (e-nose) has been used in food industry and quality controls in plastic packaging. Recently it finds its applications in medical diagnosis, specifically on detection of diabetes, pulmonary or gastrointestinal problem, or infections by examining odors in the breath or tissues with its odor characterizing ability. Moreover, the use of portable e-nose enables the on-site measurements and analysis of vapors without extra gas-sampling units. This is expected to widen the application of the e-nose in various fields including point-of-care-test or e-health. In this study, a PDA-based portable e-nose was developed using micro-machined gas sensor array and miniaturized electronic interfaces. The rich capacities of the PDA in its computing power and various interfaces are expected to provide the rapid and application specific development of the diagnostic devices, and easy connection to other facilities through information technology (IT) infra. For performance verification of the developed portable e-nose system, Six different vapors were measured using the system. Seven different carbon-black polymer composites were used for the sensor array. The results showed the reproducibility of the measured data and the distinguishable patterns between the vapor species. Additionally, the application of two typical pattern recognition algorithms verified the possibility of the automatic vapor recognition from the portable measurements. These validated the portable e-nose based on PDA developed in this study.

This paper reports a new fabrication method and a performance of miniaturized and temperature-controllable gas sensor array constructed on 5 in. double side polished (1 0 0) silicon wafer. The films of polymer-carbon black composite were used as gas sensors. Both silicon process and bulk micromachining technology were employed to fabricate sensor array equipped with an interdigitated electrode pair, microheater, and micromachined well of an area of 2 mm ×2 mm. During dispensing a polymer composite–solvent solution on the electrode, micromachined well helped the sensor film be placed in a constrained area and be formed reproducibly from a constant volume of the polymer composite–solvent solution. The dimension of a sensor array chip consisting of 16 separate sensors is 30 mm ×14 mm. The sensors of polymer-carbon black composite responded diversely when they were dispensed in micromachined wells and exposed to various chemical vapors. Principal component analysis (PCA) clearly demonstrated that the gas sensor array could identify various chemical vapors. Pt microheater consumed 7 mW to heat sensor film at the operating temperature of 40 °C, and temperature reached a steady maximum value promptly because of its small heat capacity and effective thermal isolation. The electrical resistance of polymer composite sensor and the partition coefficients for sensor–vapor interactions showed to be considerably affected by the substrate temperature.

The porous Ti-45at.%Al-1.6at.%Mn intermetallic alloys were fabricated by reactive sintering process using warm extruded mixtures consisting of elemental titanium and aluminum alloy powders and subsequent heat treatment. At the extrusion stage, three different extrusion ratios were tried in order to provide the various types of porous structure in the microstructure. It was clearly found that the shape of pore and porosity are largely dependent on extrusion ratio. With increasing extrusion ratio the porosity decreased, on the other hand, aspect ratio of porous structure increased. The porosity measured was in the range from 35% to 45%. The maximum porosity of 45% can be obtained when the specimen was reactively sintered with the extrusion ratio of 1. A directionality of pores oriented parallel to the extrusion direction was found when the extrusion ratio of powder mixtures is 6 and above.

Recent studies reporting trans-differentiation of mononucleated cells derived from human umbilical cord blood into neuronal cells aroused interest among investigators for their clinical implication and significance in regenerative medicine. In the present study, purified populations of hematopoietic stem cells were isolated via magnetic bead sorting and fluorescence-activated cell sorter (FACS) using a specific CD133 antibody, a cell type-specific marker for hematopoietic stem cells, and grown in culture in the presence of retinoic acid (RA). CD133+ hematopoietic stem cells expressed neuronal and glial phenotypes after RA treatment. RT-PCR analysis indicated that the RA treated CD133+ cells expressed mRNA transcripts for ATP-binding cassettes transporter ABCG2 (a universal stem cell marker), nestin (a specific cell type marker for neural stem cells), Musashi1 (a specific marker for neural stem cells) and RA receptors (RAR) including RAR-alpha, RAR-beta, and retinoid X receptor (RXR)-gamma. RA-treated CD133+ cells expressed mRNA transcripts for neuron-specific markers neurofilament proteins (NF-L, -M, -H) and synaptophysin as determined by RT-PCR, structural proteins characteristic of neurons including tubulin beta III and neuron specific enolase (NSE) by Western blot, and neuron-specific markers NeuN and microtubule-associated protein-2 (MAP2) by immunocytochemistry. RA-treated CD133+ cells also expressed the astrocyte-specific marker glial fibrillary acidic protein (GFAP), as demonstrated by RT-PCR, Western blot, and immunocytochemistry. In addition, RA-treated CD133+ cells expressed cell type-specific markers for oligodendrocytes including myelin basic protein (MBP) as shown by RT-PCR, proteolipid protein (PLP) by Western blot analysis, and cyclic nucleotide phosphodiesterase (CNPase) by immunostaining. Upregulated expression of several basic helix-loop-helix (bHLH) transcription factors important for early neurogenesis, including Otx2, Pax6, Wnt1, Olig2, Hash1 and NeuroD1, was also demonstrated in CD133+ cells after RA treatment. These results indicate that human cord blood-derived CD133+ hematopoietic stem cells could trans-differentiate into neural cell types of neuron-like cells, astrocytes, and oligodendrocytes by RA treatment.

In order to automate routine fecal examination for parasitic diseases, the authors propose in this study a computer processing algorithm using digital image processing techniques and an artificial neural network (ANN) classifier The morphometric characteristics of eggs of human parasites in fecal specimens were extracted from microscopic images through digital image processing. An ANN then identified the parasite species based on those characteristics. The authors selected four morphometric features based on three morphological characteristics representing shape, shell smoothness, and size. A total of 82 microscopic images containing seven common human helminth eggs were used. The first stage (ANN-1) of the proposed ANN classification system isolated eggs from confusing artifacts. The second stage (ANN-2) classified eggs by species. The performance of ANN was evaluated by the tenfold cross-validation method to obviate the dependency on the selection of training samples. Cross-validation results showed 86.1% average correct classification ratio for ANN-1 and 90.3% for ANN-2 with small variances of 46.0 and 39.0, respectively. The algorithm developed will be an essential part of a completely automated fecal examination system.

Background The Atopic Dermatitis Antecubital Severity (ADAS) score is a new objective scale for the assessment of the severity of atopic dermatitis (AD). It is calculated by multiplying the intensity of inflammatory signs by the size of an antecubital eczema lesion. Aim To test the validity, reliability, and sensitivity to changes of the ADAS score compared with those of the Eczema Area and Severity Index (EASI) score. Methods Forty patients with AD were enrolled and treated with a moisturizer. At baseline, and in weeks 1 and 2, two independent evaluators measured the ADAS score, the EASI score, and the investigator's global assessment score rated on a six-point scale. Results The ADAS score showed a higher validity than the EASI score. The superiority of the ADAS to the EASI was prominent in mild AD. Inter-evaluator reliability was excellent in both the ADAS score and the EASI. The sensitivity to changes was higher in the ADAS score than in the EASI score. Conclusions The ADAS score may be used as a simple scoring system with good validity, reliability, and sensitivity to changes, especially in patients with mild-to-moderate AD.

This paper presents a data processing and control logic design for a new radiation detection sensor system that can process data at or above peta-bits-per-second level. We propose a novel data compression method and operation strategy for a radiation sensor array including low power and network-on-wafer solutions. The design goal is to achieve a subtle data compression before the information is ferried to the network, minimizing the loss of information. The result is a radiation detection system that can operate at scan-rate of billion frames per second. The implementation result of the data processing system shows that the intended clock rate is achieved within the power target of less than 200mW.

Background Atopic dermatitis (AD) is characterized by itching and eczema-like skin lesions, and its symptoms alleviate with age. Recently, the prevalence of AD has increased among adolescents and adults. The increasing prevalence of AD seems to be related to westernized lifestyles and dietary patterns. Objective The aim of this study was to evaluate the dietary patterns and nutrient intake of patients with AD. Methods The study population consisted of 50 children with AD who visited the Department of Dermatology at Kangnam Sacred Heart Hospital, Seoul, Korea from May 2008 to May 2009. Physical condition and calorie intake were evaluated using the Eczema Area and Severity Index score and Food Record Questionnaire completed by the subjects, and the data were analyzed using the Nutritional Assessment Program Can-pro 3.0 (The Korean Nutrition Society, 2005) program to determine the gap between the actual ingestion and average requirements of 3 major nutrients (i.e. carbohydrates, proteins, and lipids), vitamins (i.e. A, B, C, and E), niacin, folic acid, calcium, iron, phosphorus, and zinc in all subjects. Results The intake rate of proteins was 18.02% (recommended dietary allowance [RDA], 7%~20%), of carbohydrates was 67.7% (RDA, 55%~70%), and of lipids was 14.24% (RDA, 15%~30%). Thirty-one subjects (62%) showed deficiency of folic acid, and 21 subjects (42%), of iron supplements. Conclusion Essential nutrient intake tends to be lower in AD patients than in healthy subjects, and this low intake is closely related to the severity of AD.